Lucio CIABATTONI

Pubblicazioni

Lucio CIABATTONI

 

100 pubblicazioni classificate nel seguente modo:

Nr. doc. Classificazioni
66 4 Contributo in Atti di Convegno (Proceeding)
21 1 Contributo su Rivista
12 2 Contributo in Volume
1 8 Tesi di dottorato
Anno
Risorse
2021
Cross-domain classification of physical activity intensity: An eda-based approach validated by wrist-measured acceleration and physiological data
ELECTRONICS
Autore/i: Poli, A.; Gabrielli, V.; Ciabattoni, L.; Spinsante, S.
Classificazione: 1 Contributo su Rivista
Abstract: Performing regular physical activity positively affects individuals’ quality of life in both the short-and long-term and also contributes to the prevention of chronic diseases. However, exerted effort is subjectively perceived from different individuals. Therefore, this work explores an out-of-laboratory approach using a wrist-worn device to classify the perceived intensity of physical effort based on quantitative measured data. First, the exerted intensity is classified by two machine learning algorithms, namely the Support Vector Machine and the Bagged Tree, fed with features computed on heart-related parameters, skin temperature, and wrist acceleration. Then, the outcomes of the classification are exploited to validate the use of the Electrodermal Activity signal alone to rate the perceived effort. The results show that the Support Vector Machine algorithm applied on physiological and acceleration data effectively predicted the relative physical activity intensities, while the Bagged Tree performed best when the Electrodermal Activity data were the only data used.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/294223 Collegamento a IRIS

2021
A novel open-source simulator of electric vehicles in a demand-side management scenario
ENERGIES
Autore/i: Ciabattoni, L.; Cardarelli, S.; Di Somma, M.; Graditi, G.; Comodi, G.
Classificazione: 1 Contributo su Rivista
Abstract: Recently, due to the growth of the electric vehicle (EV) market, the investigation of grid-to-vehicle and vehicle-to-grid strategies has become a priority in both the electric mobility and distribution grid research areas. However, there is still a lack of large-scale data sets to test and deploy energy management strategies. In this paper, a fully customizable EV population simulator is presented as an attempt to fill this gap. The proposed tool is designed as a web simulator as well as a Matlab/Simulink block, in order to facilitate its integration in different projects and applications. It provides individual and aggregated charge, discharge and plugin/out event data for a population of EVs, considering both home and public charging stations. The population is generated on the basis of statistical data (which can be fully customized) including commuting distances, vehicle models, traffic and social behavior of the owners. A peak-shaving case study is finally proposed to show the potential of the simulator.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/291854 Collegamento a IRIS

2021
Cognitive Buildings for Increasing Elderly Fire Safety in Public Buildings: Design and First Evaluation of a Low-Impact Dynamic Wayfinding System
Ambient Assisted Living. ForItAAL 2019
Autore/i: Bernardini, Gabriele; Ciabattoni, Lucio; Quagliarini, Enrico; D’Orazio, Marco
Editore: Springer
Luogo di pubblicazione: Cham
Classificazione: 2 Contributo in Volume
Abstract: The progressive population ageing increases the participation of autonomous Elderly to the community life and their presence in public buildings. Such complex spaces are generally characterized by high occupants’ density, with different users’ types (including elderly) that additionally own a scarce familiarity with the emergency layout. Emergency safety levels (i.e.: fire) are significantly affected by man-environment interactions, especially for the hosted autonomous Elderly. Here, they tend to choose well-known paths, while group behaviours can provoke overcrowding and, hence, an increasing of the evacuation time. Cognitive Buildings can solve this issue, because they can suggest to people how to behave in relation to the monitored surrounding conditions. This study proposes a Cognitive Wayfinding System (Co-WayS) to be applied in such scenarios, with a low impact level. Co-Ways is composed by: individuals’ badges for their wi-fi tracking; building components including wi-fi tracking system and electrically-illumined signs (to dynamically address correct paths to evacuees); central processing unit to solve a density-based guidance algorithm for sign activation. Co-WaysS addresses the egress paths depending on monitored queueing conditions. A first validation in a significant public building is performed through egress drills. When using Co-WayS, the evacuation time decreases (−28%) while correct path choices (+17%) and individuals’ sign confidence (+58%) increases, with respect to standard signage.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/289489 Collegamento a IRIS

2021
Human-in-the-Loop Approach to Safe Navigation of a Smart Wheelchair via Brain Computer Interface
Lecture Notes in Electrical Engineering
Autore/i: Ciabattoni, L.; Ferracuti, F.; Freddi, A.; Iarlori, S.; Longhi, S.; Monteriu', A.
Editore: Springer Science and Business Media Deutschland GmbH
Classificazione: 2 Contributo in Volume
Abstract: Assistive robots operate in complex environments and in presence of human beings, as such they are influenced by several factors which may lead to undesired outcomes: wrong sensor readings, unexpected environmental conditions or algorithmic errors represent just few examples. When the safety of the user must be guaranteed, a possible solution is to rely on a human-in-the-loop approach, e.g. to monitor if the robot performs a wrong action or environmental conditions affect safety during the interaction, and provide a feedback accordingly. The proposed work presents a human supervised smart wheelchair, i.e. an electric powered wheelchair with semiautonomous navigation capabilities of elaborating a path planning, whose user is equipped with a Brain Computer Interface (BCI) to provide safety feedbacks. During the wheelchair navigation towards a desired destination in an indoor scenario, possible problems (e.g. obstacles) along the trajectory cause the generation of error-related potentials signals (ErrPs) when noticed by the user. These signals are captured by the interface and are used to provide a feedback to the navigation task, in order to preserve safety and avoiding possible navigation issues modifying the trajectory planning.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/289263 Collegamento a IRIS

2021
Stress Detection in Computer Users from Keyboard and Mouse Dynamics
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
Autore/i: Pepa, L.; Sabatelli, A.; Ciabattoni, L.; Monteriu', A.; Lamberti, F.; Morra, L.
Classificazione: 1 Contributo su Rivista
Abstract: Detecting stress in computer users, while technically challenging, is of the utmost importance in the workplace, especially now that remote working scenarios are becoming ubiquitous. In this context, cost-effective, subject-independent systems are needed that can be embedded in consumer devices and classify users' stress in a reliable and unobtrusive fashion. Leveraging keyboard and mouse dynamics is particularly appealing in this context as it exploits readily available sensors. However, available studies are mostly performed in laboratory conditions, and there is a lack of on-field investigations in closer-to-real-world settings. In this study, keyboard and mouse data from 62 volunteers were experimentally collected in-the-wild using a purpose-built Web application, designed to induce stress by asking each subject to perform 8 computer tasks under different stressful conditions. The application of Multiple Instance Learning (MIL) to Random Forest (RF) classification allowed the devised system to successfully distinguish 3 stress-level classes from keyboard (76% accuracy) and mouse (63% accuracy) data. Classifiers were further evaluated via confusion matrix, precision, recall, and F1-score.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/301353 Collegamento a IRIS

2021
An Open Source Electric Vehicle Simulator with Battery Aging Modeling
IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Autore/i: Ciabattoni, L.; Ferracuti, F.; Marchegiani, E.; Monteriu, A.
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The ever growing incidence of electric vehicles in the transportation industry required the development of innovative strategies and tools to help engineers in the design of demand side management strategies and to solve grid issues. In this study, a battery aging model is integrated in an electric vehicle simulator in order to better reproduce the vehicle's life in a consumer perspective and for Vehicle-to-grid applications.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/299294 Collegamento a IRIS

2020
Managing plug-in electric vehicles in eco-environmental operation optimization of local multi-energy systems
SUSTAINABLE ENERGY, GRIDS AND NETWORKS
Autore/i: Di Somma, M.; Ciabattoni, L.; Comodi, G.; Graditi, G.
Classificazione: 1 Contributo su Rivista
Abstract: Local multi-energy systems (LMES) have been recently recognized as a promising alternative to centralized energy supply systems to meet local energy needs, since they promote efficient use of the available energy thanks to the coordination of heat and power technologies, storage, flexible demand and plug-in electric vehicles (PEVs). In this framework, PEVs represent loads to satisfy in the grid-to-vehicle (G2V) mode, while also serving as distributed storage when equipped with vehicle-to-grid (V2G) technology, and can provide both economic and environmental benefits if properly managed. The contribution of this paper is to present a comprehensive multi-objective optimization model for the energy management of an LMES in the presence of PEVs, with the aim to combine maximization of LMES operator's profit with the minimization of CO2 emissions. The LMES supplies electricity, heat and cooling to a building cluster with PEVs, which can operate in both G2V and V2G modes. The problem consists of dispatching technologies in the LMES and finding the optimized charging/discharging strategies of PEVs in order to maximize the operator's profit while also reducing CO2 emissions, and it is addressed by formulating a multi-objective linear programming problem with the detailed modeling of interdependencies among energy carriers. The weighted sum method is used to represent the eco-environmental optimization problem, and it is solved by using CPLEX solver and considering a cluster of office buildings located in Italy as end-user of the LMES with PEVs owned by the offices’ employees. Testing results demonstrate the effectiveness of the optimization framework to maximize the operator's profit while also reducing the CO2 emissions, thanks to the optimal coordination of the multiple energy carriers in the LMES and the effective management of the flexibility collected at both supply and demand sides. Moreover, it is found that through the optimized charging and discharging strategies, the PEVs, acting as distributed energy storage, allow the provision of demand response services by also complementing renewable power to improve energy efficiency. In detail, under the economic optimization, most of flexibility collected from PEVs is sold into the wholesale market in order to maximize the operator's profit, whereas, under the environmental optimization, the power discharged from PEVs is exploited for self-use in the LMES to minimize environmental impacts by using a carbon-free source.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/285157 Collegamento a IRIS

2020
Machine learning-as-a-service for consumer electronics fault diagnosis: A comparison between matlab and azure ML
Digest of Technical Papers - IEEE International Conference on Consumer Electronics
Autore/i: Prist, M.; Longhi, S.; Monteriu, A.; Freddi, A.; Pallotta, E.; Ciabattoni, L.; Cicconi, P.; Giuggioloni, F.; Caizer, E.; Verdini, C.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Today, the improvement of the product value in consumer goods, such as new services to increase the positive customer experience, is the subject of many research activities. In a context where the product complexity becomes ever greater and the product life-cycle is always shorter, the use of intelligent tools for supporting all phases of the product life-cycle is very important. One of the aspects that is taking interest is to support the consumer in fault management. This analysis are well-known practices in the industrial, automotive fields, etc. but less used for consumer electronics. This paper analizes a Cloud service based on a Machine Learning (ML) approach used to provide fault detection capabilities to household appliances equipped with electric motors and compare the results with on premise ML algorithms provided research tools. The purpose of this paper is to perform a preliminary comparison of ML algorithm performances provided by two software, namely Microsoft Azure (cloud solution) and MATLAB (on premise solution), on a study case. In detail, the vibration data of an asynchronous motor installed in an oven extractor hood for commercial restaurant kitchen have been analyzed. To this end, two classification algorithms have been selected to implement fault diagnosis techniques.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/276300 Collegamento a IRIS

2020
A New Hybrid Software Tool for the Simulation of Energy Usage in a Population of Electric Vehicles
Proceedings - 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2020
Autore/i: Ciabattoni, L.; Cardarelli, S.; Di Somma, M.; Graditi, G.; Comodi, G.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Recently, due to the increment of electric vehicles (EVs), the investigation of vehicle-to-grid paradigm strategies has become a key concern in both the electric mobility and distribution grid research areas. Indeed each EV can be seen as a distributed energy storage, thus giving to each customer a potential active role in the energy distribution scenario. However, there is still a lack of large scale data (often location dependant) to test and deploy energy management strategies for vehicle-to grid services. In this paper, a scalable EVs population simulator is presented as an attempt to fill this gap. The proposed tool provides individual and aggregated charge, discharge and plugin/-out events data of a custom geographically defined population of EVs, considering both home and public charging stations. The population is generated on the basis of statistical data (which can be obtained by data driven approaches or a priori assumptions) including commuting distances, vehicles models, traffic and social behavior of the owners.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/301829 Collegamento a IRIS

2020
AI-Powered Home Electrical Appliances as Enabler of Demand-Side Flexibility
IEEE CONSUMER ELECTRONICS MAGAZINE
Autore/i: Ciabattoni, L.; Comodi, G.; Ferracuti, F.; Foresi, G.
Classificazione: 1 Contributo su Rivista
Abstract: In the digitalization era, the increasing number of connected appliances and the rise of artificial intelligence (AI) enabled a new realm of possibilities in the residential energy sector, including the chance for a consumer to play an active role in flexibility programs. We talk about demand-side flexibility (DSF) when a consumer adapts his/her energy consumption behavior in response to variable energy prices or market incentives. The procedure depends on a two-way communication between an energy supplier and a customer, and his/her willingness to act on the electricity consumption. The success of the different DSF approaches is strongly related to the estimation of appliance usage patterns and AI techniques represent a viable solution.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/282479 Collegamento a IRIS

2020
A stress detection system based on multimedia input peripherals
Digest of Technical Papers - IEEE International Conference on Consumer Electronics
Autore/i: Ciabattoni, L.; Foresi, G.; Lamberti, F.; Monteriu, A.; Sabatelli, A.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper a Stress Detection System based on Machine Learning Algorithms (MLAs), keyboard and mouse data is presented. The development of this system is composed by three steps. Firstly, each user performs some tasks while a web application framework collects data from keyboard and mouse. At the end of each task, he/she communicates the stress level in order to create the stress class. Secondly, from collected data, features extraction and features selection procedures through a Neighborhood Component Analysis (NCA) are implemented. Lastly, three MLAs, trained with features as input and stress classes as output, are implemented to detect stress.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/279449 Collegamento a IRIS

2020
A Methodology to Enable Electric Boiler as a Storage for Residential Energy Management
2020 IEEE International Conference on Consumer Electronics (ICCE)
Autore/i: Ciabattoni, L; Comodi, G; Ferracuti, F; Foresi, G
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In an Energy Management (EM) scenario, photo-voltaic (PV) generation systems could lead to an important cost-saving and "shiftable loads" (e.g., dishwasher, washing machine, cooker hood) play an important role. Among all "shiftable loads", electric boiler has considerable importance since it can be considered as a thermal storage. In this perspective, it is crucial to know the typical usage patterns and the state of charge of this appliance. In this paper, a methodology to identify the electric boiler usage patterns and to estimate its state of charge is presented.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/289809 Collegamento a IRIS

2020
A fuzzy logic system for the home assessment of freezing of gait in subjects with Parkinsons disease
EXPERT SYSTEMS WITH APPLICATIONS
Autore/i: Pepa, Lucia; Capecci, Marianna; Andrenelli, Elisa; Ciabattoni, Lucio; Spalazzi, Luca; Ceravolo, Maria Gabriella
Classificazione: 1 Contributo su Rivista
Abstract: Gait dysfunctions are pathognomonic, progressive and, generally, continuous in Parkinson’s Disease (PD). The Freezing of Gait (FoG) is an episodic gait disorder involving up to 70% of people with PD, within 10 years of clinical onset, and associated with an increased risk for falls and immobility, which in turn, contributes to greater disability. Automatic and objective monitoring of FoG may help clinicians to understand and treat this phenomenon. In this work, a smartphone app for real-time FoG detection is presented and tested both in a laboratory setting and at patients’ home. The app implements a novel fuzzy logic algorithm that uses important spatio-temporal parameters of gait and is built according to clinical knowledge about FoG. The app includes a gait detection function and the evaluation of two important clinical statistics, i.e. FoG time and FoG number. The app FoG detection performance was assessed against clinicians evaluation and compared with the Moore-Bachlin FoG detection algorithm through ROC analysis, the calculation of confusion matrix, and FoG hit rate. The proposed algorithm achieved better results with respect to the Moore-Bachlin algorithm. Home reports were compared with respect to the FoG Questionnaire and laboratory reports; results indicated significant correlations for both FoG time and FoG number. The results confirm the reliability and accuracy of this app for FoG detection, supporting its wide use for diagnostic and therapeutic purposes.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/273262 Collegamento a IRIS

2019
Design and Implementation of a Real-Time Upper Limbs Dyskinesia Detection System
2019 IEEE International Conference on Consumer Electronics, ICCE 2019
Autore/i: Belgiovine, G.; Capecci, M.; Ciabattoni, L.; Fiorentino, M. C.; Foresi, G.; Monteriù, A.; Pepa, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper a Real-Time L-dopa-Induced Dyskinesia (LID) Detection System based on Machine Learning Algorithms (MLAs) and simple devices such as smartphone and smartwatch is presented. The implementation of this system was performed in three steps. Firstly, the data collection is carried out, where each patient wears the smartwatch and completes some tasks, while a smartphone application captures data. Secondly, features in time and frequency domain were extracted from smartwatch data and used as input for the training of different off-line MLAs. Lastly, the best algorithm found has been integrated into a mobile App in order to real-time monitor the smartwatch data and detect LID. © 2019 IEEE.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/265761 Collegamento a IRIS

2019
An Adaptive System to Manage Playlists and Lighting Scenarios Based on the User's Emotions
2019 IEEE International Conference on Consumer Electronics
Autore/i: Generosi, A.; Ciabattoni, L.; Altieri, A.; Ceccacci, S.; Mengoni, M.; Talipu, A.; Turri, G.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: This paper introduces a new system capable of adaptively managing multimedia contents (e.g. music, video clips, etc.) and lighting scenarios based on the detected user's emotional state. The system captures the emotion from the user's face expression mapping it into a 2D valence-arousal space where the multimedia content is mapped and matches them with lighting color. Results of preliminary tests suggest that the proposed system is able to detect the user's emotional state and manage proper music and light colors in a symbiotic way
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/266294 Collegamento a IRIS

2019
An Automated Procedure to Evaluate Usability of eHealth Platforms in the Wild
2019 Zooming Innovation in Consumer Technologies Conference, ZINC 2019
Autore/i: Ballarini, E.; Ciabattoni, L.; Domenichelli, D.; Domenichelli, Mauro; Foresi, G.; Monteriù, A.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Nowadays, one of the keys for the success of ICT technologies, in particular in the e-Health realm, is 'Usability'. Self-assessment questionnaires are the most diffuse procedure for its evaluation. However, this procedure presents various limitations (e.g., subjectivity, needs of expert supervisors, etc.). In this paper, a methodology based on emotion recognition, web analytics and gaze detection is developed in order to asses usability of e-Health web platforms objectively, automatically, remotely and in the wild.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/271324 Collegamento a IRIS

2019
ErrP Signals Detection for Safe Navigation of a Smart Wheelchair
2019 IEEE 23rd International Symposium on Consumer Technologies, ISCT 2019
Autore/i: Ciabattoni, L.; Ferracuti, F.; Freddi, A.; Iarlori, S.; Longhi, S.; Monteriu, A.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Assistive robots operate in complex environments and in presence of human beings, as such they are influenced by several factors which may lead to undesired outcomes: wrong sensor readings, unexpected environmental conditions or algorithmic errors represent just few examples. When the safety of the user must be guaranteed, a possible solution is to rely on a human-supervised approach. The proposed work presents a smart wheelchair, i.e. an electric powered wheelchair with semiautonomous navigation capabilities, whose user is equipped with a Brain Computer Interface. During the wheelchair navigation, possible problems (e.g. obstacles) along the trajectory cause the generation of error-related potentials signals when noticed by the user. These signals are captured by the interface and are used to provide a feedback to the navigation task, in order to preserve safety and avoiding possible navigation issues.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272749 Collegamento a IRIS

2019
Real time indoor localization integrating a model based pedestrian dead reckoning on smartphone and BLE beacons
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
Autore/i: Ciabattoni, Lucio; Foresi, Gabriele; Monteriù, Andrea; Pepa, Lucia; Proietti Pagnotta, Daniele; Spalazzi, Luca; Verdini, Federica
Classificazione: 1 Contributo su Rivista
Abstract: Mobile and pervasive computing enabled a new realm of possibilities into the indoor positioning domain. Although many candidate technologies have been proposed, no one can still adapt to every use case. A case centered design and the implementation of the solution within the specific domain is the current research trend. With the rise of Bluetooth Low Energy (BLE) Beacons, i.e., platforms used to interact digitally with the real world, more standard positioning solutions are emerging in different contexts. However the reachable positioning accuracy with this technology is still unacceptable for some real applications (e.g., in the healthcare sector or the emergency management). In this paper, an hybrid localization application coupling a real time model based Pedestrian Dead Reckoning (PDR) technique and the analysis of the Received Signal Strength Indicator (RSSI) of BLE beacons is proposed. In particular, the smartphone application is composed by three main real time threads: a model based step length estimation, heading determination and the fusion of beacon information to reset the position and the drift error of the PDR. In order to give soundness to our approach we firstly validated the step length smartphone app with a stereo-photogrammetric system. The whole proposed solution was then tested on fifteen healthy subjects.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250892 Collegamento a IRIS

2019
A machine-learning based emotion recognition system in patients with Parkinson's disease
IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Autore/i: Capecci, M.; Ciabattoni, L.; Foresi, G.; Monteriu, A.; Pepa, L.
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper, a Machine-Learning Based Emotion Recognition System in patients with Parkinson's disease is presented. The development of this system is composed of three steps. Firstly, each user is required to execute an experimental protocol while a simple device (i.e., smartwatch), worn on the wrist, collects data. During the experimental protocol, a nine-point clinical scale and a commercial emotion recognition software have been used to identify emotions. Secondly, from smartwatch data, features extraction is implemented. Lastly, a Machine Learning Algorithm (MLA) is trained with extracted features as input and emotion classes as output.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/277371 Collegamento a IRIS

2018
A smart home services demonstration: Monitoring, control and security services offered to the user
IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Autore/i: Botticelli, Martina; Ciabattoni, Lucio; Ferracuti, Francesco; Monteriu, Andrea; Pizzuti, Stefano; Romano, Sabrina
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The Italian Ministry of Economic Development and the Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) have entered into a Program Agreement for the execution of the research and development lines of General Interest for the national electricity system. In particular, as part of the "Development of an integrated model of the Urban Smart District" project, an experimental demonstration of a Smart Home network has been carried out in the Centocelle district of Rome, called "Centocelle Smart Home". This project aims to develop a replicable model of Smart Home able to monitor energy consumption, the degree of comfort and safety in residential buildings, transmitting them to a higher level technological platform where data are analyzed and aggregated to provide a series of feedbacks to the user and to the community. The objective is to reduce the final consumption of energy (electric and thermal) of domestic consumers through a path of growth of energy awareness, also providing additional services on security. This paper presents the architecture proposed in the ENEA project for monitoring the energy consumption and increasing the degrees of comfort and safety of domestic users. The proposed security service is presented here together with the developed "Out of Home" App.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/265763 Collegamento a IRIS

2018
Collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logic
IET COMPUTER VISION
Autore/i: Capecci, Marianna; Ciabattoni, L.; Ferracuti, Francesco; Monteriù, Andrea; Romeo, Luca; Verdini, Federica
Classificazione: 1 Contributo su Rivista
Abstract: In this paper we present a low cost telerehabilitation system made up of a commercial RGB-D camera and a web-based platform. Our goal is to monitor and assess subject movement providing acceptable and usable at-home remote rehabilitation ser- vices without the presence of a clinician. Clinical goals, defined by physiotherapists, are firstly translated into motion analysis features. A Takagi Sugeno Fuzzy Inference System (FIS) is then proposed to evaluate and combine these features into scores. In this stage the “collaborative design” paradigm is used in depth and complete manner: the contribution of the clinician is not limited only to the rules definition but enters in the core of the evaluation algorithm through the definition of the fuzzy rules. A case study on low back pain rehabilitation involving 40 subjects, 5 exercises and 4 physiotherapists is then presented to effectiveness of the proposed system. Results of the validation of the system aimed at the assessment of the reliability of the proposed approach show high correlations between clinician evaluation and FIS scores. In this scenario, due to the high correlation, each FIS could represent a virtual alter-ego of the physiotherapist which enable a real time and free second opinion.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/252419 Collegamento a IRIS

2018
First Approach to a Holistic Tool for Assessing RES Investment Feasibility
SUSTAINABILITY
Autore/i: Flores-Arias, José María; Ciabattoni, Lucio; Monteriù, Andrea; Bellido-Outeiriño, Francisco José; Escribano, Antonio; Palacios-Garcia, Emilio José
Classificazione: 1 Contributo su Rivista
Abstract: Combining availability, viability, sustainability, technical options, and environmental impact in an energy-planning project is a difficult job itself for the today’s engineers. This becomes harder if the potential investors also need to be persuaded. Moreover, the problem increases even more if various consumptions are considered, as their patterns depend to a large extent on the type of facility and the activity. It is therefore essential to develop tools to assess the balance between generation and demand in a given installation. In this paper, a valuable tool is developed for the seamless calculation of the integration possibilities of renewable energies and the assessment of derived technical, financial and environmental impacts. Furthermore, it also considers their interaction with the power grid or other networks, raising awareness of the polluting emissions responsible for global warming. Through a series of Structured Query Language databases and a dynamic data parameterization, the software is provided with sufficient information to encode, calculate, simulate and graphically display information on the generation and demand of electric, thermal and transport energy, all in a user-friendly environment, finally providing an evaluation and feasibility report.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/257244 Collegamento a IRIS

2018
A robust and self-tuning speed control for permanent magnet synchronous motors via meta-heuristic optimization
INTERNATIONAL JOURNAL, ADVANCED MANUFACTURING TECHNOLOGY
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Foresi, Gabriele; Freddi, Alessandro; Monteriù, Andrea; Pagnotta, Daniele Proietti
Classificazione: 1 Contributo su Rivista
Abstract: In a reconfigurable manufacturing scenario, control system design needs innovative approaches to face the rapid changes in hardware and software modules. The control system should be able to automatically tune its parameters to enhance machine performances and dynamically adapt to different control objectives (e.g., minimize control efforts or maximize tracking performances) while preserving at the same time stability and robustness properties. In this paper, a robust control system for permanent magnet synchronous motors (PMSMs), together with an online self-tuning method, is presented. In particular, a robust discrete-time variable structure control (VSC) has been designed. A heuristic bio-inspired approach has been then implemented on a digital signal processor (DSP) to find the VSC parameter set which minimizes a specific objective function each time a novel speed reference is provided. Experimental results on a PMSM motor show the effectiveness of the proposed controller and tuning method, with noticeable improvements with respect to the original manufacturer-designed controller.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/254574 Collegamento a IRIS

2018
Non Intrusive Load Identification for Smart Energy Management Systems
36th IEEE International Conference on Consumer Electronics (ICCE)
Autore/i: Chelli, Giacomo; Ciabattoni, L.; Flores-Arias, J. M.; Foresi, Gabriele; Monteriù, A.; PROIETTI PAGNOTTA, Daniele
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In an energy management (EM) perspective, an ob- jective function considering the balance of energy and resources needs to be optimized. To reach the goal, in a residential scenario, a number of tasks (typically appliances) can be managed (e.g. shifted). This paper proposes an unobtrusive cascade classifier approach to autonomously identify the different appliances and their priorities (shiftable, non interruptible, continuous loads) in EM algorithms based on smart plugs measures.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255088 Collegamento a IRIS

2018
Hear to see-See to hear: A smart home system user interface for visually or hearing-impaired people
IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Autore/i: Ciabattoni, L.; Ferracuti, F.; Foresi, G.; Monteriu, A.
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper, we introduce a novel approach to design a user interface for commercial Smart Home Systems (SHS), following the needs of visually or hearing impaired users. The interface is able to transform visual information and alarms into audio signals and vice versa by using a mobile application. The aim of the interface is to make a commercial SHS usable for visually or hearing-impaired people, while maintaining a high level of acceptability, due to the use of an inclusive device, i.e., the smartphone. © 2018 IEEE.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/265762 Collegamento a IRIS

2018
Dynamic surface fault tolerant control for underwater remotely operated vehicles
ISA TRANSACTIONS
Autore/i: Baldini, Alessandro; Ciabattoni, Lucio; Felicetti, Riccardo; Ferracuti, Francesco; Freddi, Alessandro; Monteriù, Andrea
Classificazione: 1 Contributo su Rivista
Abstract: In this paper, we present a two stages actuator Fault Tolerant Control (FTC) strategy for the trajectory tracking of a Remotely Operated Vehicle (ROV). Dynamic Surface Control (DSC) is used to generate the moment and forces required by the vehicle to perform the desired motion. In the second stage of the control system, a fault tolerant thruster allocation policy is employed to distribute moment and forces among the thrusters. Exhaustive simulations have been carried out in order to compare the performance of the proposed solution with respect to different control techniques (i.e., PID, backstepping and sliding mode approaches). Saturations, actuator dynamics, sensor noises and time discretization are considered, in fault-free and faulty conditions. Furthermore, in order to provide a fair and exhaustive comparison of the control techniques, the same meta-heuristic approach, namely Artificial Bee Colony algorithm (ABC), has been employed to tune the controllers parameters.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/254633 Collegamento a IRIS

2018
Statistical Spectral Analysis for Fault Diagnosis of Rotating Machines
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Freddi, Alessandro; Monteriu, Andrea
Classificazione: 1 Contributo su Rivista
Abstract: Condition-based monitoring of rotating machines requires robust features for accurate fault diagnosis, which is indeed directly linked to the quality of the features extracted from the signals. This is especially true for vibration data, whose quasi-stationary nature implies that the quality of frequency domain extracted features depends on the Signal-to-Noise Ratio (SNR) condition, operating condition variations and data segmentation. This paper presents a novel Statistical Spectral Analysis, which leads to highly robust fault diagnosis with poor SNR conditions, different time-window segmentation and different operating conditions. The amplitudes of spectral contents of the quasi-stationary time vibration signals are sorted and transformed into statistical spectral images. The sort operation leads to the knowledge of the Empirical Cumulative Distribution Function (ECDF) of the amplitudes of each frequency band. The ECDF provides a robust statistical information of the distribution of the amplitude under different SNR and operating conditions. Statistical metrics have been adopted for fault classification, by using the ECDFs obtained from the spectral images as fault features. By applying simple statistical metrics, it is possible to achieve fault diagnosis without classifier training, saving both time and computational costs. The proposed algorithm has been tested using a vibration data benchmark: comparison with state-of-the-art fault diagnosis algorithms shows promising results.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/252246 Collegamento a IRIS

2018
Complex Activity Recognition System Based on Cascade Classifiers and Wearable Device Data
36th IEEE International Conference on Consumer Electronics (ICCE)
Autore/i: Ciabattoni, Lucio; Foresi, Gabriele; Monteriù, Andrea; Proietti Pagnotta, Daniele; Romeo, Luca; Spalazzi, Luca; De Cesare, Alex
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: This paper proposes a system for recognizing hu- man complex activities by using unobtrusive sensors such as smartphone, smartwatch and bluetooth beacons. The method encapsulates two classification stages. The former is composed of two parallel processes: the Main Activity Detection (MAD) and the Room Detection (RD). The latter implements the Complex Activity Detection (CAD) process by exploiting the outputs of the first stage and the accelerometer data of the smartwatch. The cascade classification approach that combines the room detection with the main/complex activities recognition task constitutes the novelty of the work. Preliminary results demonstrate the reliability of the system in terms of accuracy and macro-F1 score.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255085 Collegamento a IRIS

2018
Fall Detection System by Using Ambient Intelligence and Mobile Robots
2018 Zooming Innovation in Consumer Technologies Conference, ZINC 2018
Autore/i: Ciabattoni, L.; Foresi, G.; Monteriu, A.; Pagnotta, D. Proietti; Tomaiuolo, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper a robust Fall Detection Algorithm by using a deep learning approach and a low-cost mobile robot equipped with an RGB camera is presented. This method consists of four steps. The first step is the user detection, achieved by a real-time video stream and a Deep Learning approach. Once the user is detected, then its position is estimated in the second step. In the third step, if a fall is detected, a photo is acquired and a pre-registered audio message asks the user how he is. In the last step the photo and the audio captured are sent to a Telegram Bot (TB) in order to alert family members or caregivers. Tests have been performed in a real scenario.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/262310 Collegamento a IRIS

2018
Reliability of a smartphone-based home monitoring of freezing of gait in subjects with Parkinson's disease
ANNALS OF PHYSICAL AND REHABILITATION MEDICINE
Autore/i: Pepa, Lucia; Andrenelli, Elisa; DI BIAGIO, Laura; Ciabattoni, Lucio; Spalazzi, Luca; Ceravolo, Maria Gabriella; Capecci, Marianna
Classificazione: 1 Contributo su Rivista
Abstract: Background and aims. Freezing of Gait (FOG) is a distressing gait disorder frequently related to Parkinson’s disease (PD) progression and severe disability. Detecting and quantifying FOG, in a clinical setting, is difficult given its episodic nature; hence, reliable tools are warranted for FOG monitoring in the daily life. A number of wearable sensors to detect FOG have been studied, but the majority of the available technology lacks ‘‘ecological’’ validation. The study is aimed at assessing the usability, at home, of the smartphone-based system for FOG detection, validated in the outpatient setting (Capecci et al,2016). Moreover, the correlation between data collected in the daily living scenario and those recorded in the laboratory has been sought. Method. 24 patients with PD-related resistant-FOG were studied. At baseline, the following measures were taken: UPDRS, New-FOG-Q, 6MWT, PDQ-39, GFQ and video-recorded TUG-test with and without dual-tasks while wearing the smartphone, in both OFF and ON medication conditions. Patients were instructed on how to use the FOG monitoring system at home, and were requested to wear it for three consecutive days. The system was customized to record the number of FOG events and FOG duration per minute walking. Results.23 out of 24 patients (95.83%) complied with the recommendations about system wearing, and used the system 263[185;461] minutes/day. Median[IQR] values recorded during the 3 days were:3[1.05;5.15] FOG/min and 5.1[1.52;9.47]sec/min of FOG duration. Both parameters were significantly related with the number and duration of FOG events recorded during the simple-TUG performed either in OFF or in ON medication conditions(p=.001), and with dual-task in ON condition(p=.003). They were also related with GFQ(p=.006) and NFOG scores(p=.03). Conclusions. A smartphone-based FOG monitoring system is usable and reliable, even in daily living situations. It could be of great help in assessing the efficacy of rehabilitation approaches to relieve FOG-related disability.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264010 Collegamento a IRIS

2018
Variable Structure Control via Coupled Surfaces for Control Effort Reduction in Remotely Operated Vehicles
Offshore Mechatronics Systems Engineering
Autore/i: Baldini, Alessandro; Ciabattoni, Lucio; Dyda, A. A.; Felicetti, Riccardo; Ferracuti, Francesco; Freddi, Alessandro; Monteriù, Andrea; Oskin, D.
Editore: Taylor & Francis Group
Classificazione: 2 Contributo in Volume
Abstract: In this chapter, a Variable Structure Control law is presented and applied to solve the tracking problem for a Remotely Operated Vehicle. Unlike the classical Sliding Mode Control, which is composed by a single sliding surface, the proposed control law presents two coupled sliding surfaces. It follows that the state space can be divided into two spaces, namely one between the surfaces and one outside them. In the region outside the surfaces, the controller is designed similarly as for the classical Sliding Mode Control, while, inside the area, the system is in free motion. It follows that the control effort is null for some time intervals, hence a reduction of control efforts is possible. In order to test the performances of the proposed technique, exhaustive simulations are made for a Remotely Operated Vehicle, and compared with classical Sliding Mode Control, where linear sliding surfaces are taken into consideration for both cases, combined with a bang-bang-type control logic. Simulation results show that, for the tracking problem, the proposed Variable Structure Control technique performs better both in terms of performances (estimated with the Integral of Absolute Error) and energy consumption (estimated with a related cost function).
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/263386 Collegamento a IRIS

2018
Upper Limbs Dyskinesia Detection and Classification for Patients with Parkinson's Disease based on Consumer Electronics Devices
2018 Zooming Innovation in Consumer Technologies Conference, ZINC 2018
Autore/i: Belgiovine, G.; Capecci, M.; Ciabattoni, L.; Fiorentino, M. C.; Monteriu, A.; Pepa, L.; Romeo, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: This paper presents a L-dopa-Induced Dyskinesia Detection and Classification System based on Machine Learning Algorithms, wearable device (smartwatch) data and a smart-phone, connected via Bluetooth. This system was developed in three steps. The first step is the data collection, where each patient wears the smartwatch and performs some tasks while the smart-phone App captures data. These performed tasks are of different nature (i.e., writing, walking, sitting and cognitive task). In the second phase, some features were extracted from acceleration and angular velocity signals and a Z-score normalization is applied. In the last step two Machine Learning Algorithms, trained with these features as input, are used in order to detect and classify dyskinesias.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/281663 Collegamento a IRIS

2018
rEMpy: a comprehensive software framework for residential energy management
ENERGY AND BUILDINGS
Autore/i: Fagiani, M.; Severini, M.; Valenti, M.; Ferracuti, F.; Ciabattoni, L.; Squartini, S.
Classificazione: 1 Contributo su Rivista
Abstract: In this paper a comprehensive residential Energy Management in python, rEMpy, is presented. The framework has a modular structure and the Optimal Scheduler, featuring a task scheduling logic and a configuration structure to represent different subsystems, is the core. A dynamic configuration of the system and data visualization is allowed by the Web Interface. The required forecasts are delegated to the Prediction module. Moreover, the real-time validation of the controlled systems and devices is supported thought the Fault Diagnosis and Overload Manager modules. The cooperation among the modules and the manager capabilities are validated by performing evaluations on both tasks scheduling and storage management on real-case data.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/258312 Collegamento a IRIS

2018
Upper and Lower Limbs Dyskinesia Detection for Patients with Parkinson's Disease
2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018
Autore/i: Belgiovine, G.; Capecci, M.; Ciabattoni, L.; Fiorentino, MARIA CHIARA; Foresi, G.; Monteriu, A.; Pepa, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper a L-dopa-Induced Dyskinesia Detection System based on Machine Learning Algorithms (MLAs), smartwatch data and a smartphone is presented. The development of this system was performed in three steps. In the first step each patient wears the smartwatch and fulfills some tasks while the smartphone Application captures data. The second phase is the features extraction from acceleration and angular velocity signals and the application of a Z-score normalization. In the last step two MLAs, trained with these features as input, are implemented in order to detect dyskinesias. © 2018 IEEE.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/265757 Collegamento a IRIS

2018
Predicting Motor and Cognitive Improvement Through Machine Learning Algorithm in Human Subject that Underwent a Rehabilitation Treatment in the Early Stage of Stroke
JOURNAL OF STROKE AND CEREBROVASCULAR DISEASES
Autore/i: Sale, P.; Ferriero, G.; Ciabattoni, L.; Cortese, A. M.; Ferracuti, F.; Romeo, L.; Piccione, F.; Masiero, S.
Classificazione: 1 Contributo su Rivista
Abstract: Background: The objective of this study was to investigate, in subject with stroke, the exact role as prognostic factor of common inflammatory biomarkers and other markers in predicting motor and/or cognitive improvement after rehabilitation treatment from early stage of stroke. Methods: In this longitudinal cohort study on stroke patients undergoing inpatient rehabilitation, data from 55 participants were analyzed. Functional and clinical data were collected after admission to the rehabilitation unit. Biochemical and hematological parameters were obtained from peripheral venous blood samples on all individuals who participated in the study within 24 hours from the admission at the rehabilitative treatment. Data regarding the health status were collected at the end of rehabilitative treatment. First, a feature selection has been performed to estimate the mutual dependence between input and output variables. More specifically, the so called Mutual Information criterion has been exploited. In the second stage of the analysis, the Support Vector Machines (SVMs), a non-probabilistic binary machine learning algorithm widely used for classification and regression, has been used to predict the output of the rehabilitation process. Performances of the linear SVM regression algorithm have been evaluated considering a different number of input features (ranging from 4 to 14). The performance evaluation of the model proposed has been investigated in terms of correlation, Root Mean Square Error (RMSE) and Mean Absolute Deviation Percentage (MADP). Results: Results on the test samples show a good correlation between all the predicted and measured outputs (i.e. T1 Barthel Index (BI), T1 Motor Functional Independence Measure (FIM), T1 Cognitive FIM and T1 Total FIM) ranging from 0.75 to 0.81. While the MADP is high (i.e., 83.96%) for T1 BI, the other predicted responses (i.e., T1 Motor FIM, T1 Cognitive FIM, T1 Total FIM) disclose a smaller MADP of 30%. Accordingly, the RMSE ranges from 4.28 for T1 Cognitive FIM to 22.6 for T1 BI. Conclusions: In conclusion, the authors developed a new predictive model using SVM regression starting from common inflammatory biomarkers and other ratio markers. The main efforts of our model have been accomplished in regard to the evidence that the type of stroke has not shown itself to be a critical input variable to predict the discharge data, furthermore, among the four selected indicators, Barthel at T1 is the less predictable (MADP > 80%), while it is possible to predict T1 Cognitive FIM with an MADP less than 18%.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/277705 Collegamento a IRIS

2017
Data-driven models for short-term thermal behaviour prediction in real buildings
APPLIED ENERGY
Autore/i: Ferracuti, Francesco; Fonti, Alessandro; Ciabattoni, Lucio; Pizzuti, Stefano; Arteconi, Alessia; Helsen, Lieve; Comodi, Gabriele
Classificazione: 1 Contributo su Rivista
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/265737 Collegamento a IRIS

2017
Human indoor localization for AAL applications: An RSSI based approach
Ambient Assisted Living: Italian Forum 2016
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Freddi, Alessandro; Ippoliti, Gianluca; Longhi, Sauro; Monteriu', Andrea; Pepa, Lucia
Editore: Filippo Cavallo, Vincenzo Marletta, Andrea Monteriù, Pietro Siciliano
Classificazione: 2 Contributo in Volume
Abstract: Ambient intelligence technologies have the objective to improve the quality of life of people in daily living, by providing user-oriented services and functionalities. Many of the services and functionalities provided in Ambient Assisted Living (AAL) require the user position and identity to be known, and thus user localization and identification are two prerequisites of utmost importance. In this work we focus our attention on human indoor localization. Our aim is to investigate how Received Signal Strength (RSS) based localization can be performed in an easy way by exploiting common Internet of Things (IoT) communication networks, which could easily integrate with custom networks for AAL purposes. We thus propose a plug and play solution where the Beacon Nodes (BNs) are represented by smart objects located in the house, while the Unknown Node (UN) can be any smart object held by the user. By using real data from different environments (i.e., with different disturbances), we provide a one-slope model and test localization performances of three different algorithms. © Springer International Publishing AG 2017.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/241029 Collegamento a IRIS

2017
Real-time fall detection system by using mobile robots in smart homes
IEEE 7th International Conference on Consumer Electronics - Berlin (ICCE-Berlin)
Autore/i: Ciabattoni, L.; Ferracuti, F.; Foresi, G.; Freddi, A.; Monteriu, A.; Pagnotta, D. Proietti
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: An unobtrusive method to realize human fall detection by using bluetooth beacons, a smartphone and a low cost mobile robot is presented. The method is composed by five steps. The first consists in extracting features from the smartphone acceleration data, which are then analysed online by the fall detection algorithm. Once the fall event is detected, then the location is determined by using the bluetooth signal received from beacons. Then, the mobile robot moves towards the user's location, and finally verifies if the detected fall event is a true positive or not, through a procedure based on voice interaction with the potentially fallen user. The method has been tested in laboratory, proving to be a viable solution to perform fall detection in smart homes via consumer devices.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/254640 Collegamento a IRIS

2017
Active fault tolerant control of remotely operated vehicles via control effort redistribution
Proceedings of the ASME Design Engineering Technical Conference
Autore/i: Baldini, A.; Ciabattoni, L.; Felicetti, R.; Ferracuti, F.; Monteriù, A.; Fasano, A.; Freddi, A.
Editore: American Society of Mechanical Engineers (ASME)
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: An active fault tolerant control technique for Underwater Remotely Operated Vehicles is proposed in this paper. The main objective is to develop a controller for the tracking problem, which is robust against possible actuator faults and failures. The main advantage of the proposed fault tolerant control scheme is to develop a unique controller, and thus a unique set of control parameters, regardless the presence of faults and failures. This is achieved through a redistribution of the control effort on the healthy actuators. Simulation results are provided to demonstrate the viability of the proposed fault accommodating technique.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255563 Collegamento a IRIS

2017
An unobtrusive expert system to detect freezing of gait during daily living in people with Parkinson's disease
2017 2nd International Multidisciplinary Conference on Computer and Energy Science, SpliTech 2017
Autore/i: Pepa, Lucia; Capecci, Marianna; Ciabattoni, Lucio; Spalazzi, Luca; Ceravolo, Maria Gabriella
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255499 Collegamento a IRIS

2017
Robust control of a photovoltaic battery system via fuzzy sliding mode approach
Studies in Computational Intelligence
Autore/i: Baldini, Alessandro; Ciabattoni, Lucio; Felicetti, Riccardo; Ferracuti, Francesco; Freddi, Alessandro; Monteriu', Andrea; Vaidyanathan, Sundarapandian
Editore: Springer Verlag
Classificazione: 2 Contributo in Volume
Abstract: Studies in Computational Intelligence Volume 709, 2017, Pages 115-142 Robust control of a photovoltaic battery system via fuzzy sliding mode approach (Book Chapter) Baldini, A.a , Ciabattoni, L.a , Felicetti, R.a , Ferracuti, F.a , Freddi, A.b , Monteriù, A.a , Vaidyanathan, S.c a Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Via Brecce Bianche, Ancona, Italy b SMARTEST Research Centre, Università degli Studi eCampus, Via Isimbardi 10, Novedrate, CO, Italy c Research and Development Centre, Vel Tech University, Chennai, Tamil Nadu, India View additional affiliations View references (43) Abstract In this chapter we propose a novel fuzzy sliding mode approach to manage the power flow of a Photovoltaic (PV) battery system. In particular, due to the inner stochastic nature and intermittency of the solar production and in order to face the irradiance rapid changes, a robust and fast controller is needed. Sliding Mode Control (SMC) is a well-known approach to control systems under heavy uncertain conditions. However, one of the major drawbacks of this control technique is the high frequency chattering generated by the switching control term. In the proposed solution, we introduce a fuzzy inference system to set the controller parameters (boundary layer and gains) according to the measured irradiance. A comparison of the designed Fuzzy Sliding Mode Control (FSMC) with two popular controllers (PI and Backstepping) is performed. In particular, FSMC shows better performances in terms of steady state chattering and transient response, as confirmed by IAE, ISE and ITAE performance indexes. © Springer International Publishing AG 2017.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/247236 Collegamento a IRIS

2017
Particle swarm optimization based sliding mode control design: Application to a quadrotor vehicle
Studies in Computational Intelligence
Autore/i: Baldini, Alessandro; Ciabattoni, Lucio; Felicetti, Riccardo; Ferracuti, Francesco; Freddi, Alessandro; Monteriu', Andrea; Vaidyanathan, Sundarapandian
Editore: Springer Verlag
Classificazione: 2 Contributo in Volume
Abstract: In this chapter, a design method for determining the optimal sliding mode controller parameters for a quadrotor dynamic model using the Particle Swarm Optimization algorithm is presented. In particular, due to the effort to determine optimal or near optimal sliding mode parameters, which depend on the nature of the considered dynamic model, a population based solution is proposed to tune the parameters. The proposed population based-method tunes the controller parameters (boundary layers and gains) according to a fitness function that measures the controller performances. A comparison of the designed sliding mode control with two popular controllers (PID and Backstepping) applied to a quadrotor dynamic model is proposed. In particular sliding mode control shows better performances in terms of steady state and transient response, as confirmed by performance indexes IAE, ISE, ITAE and ITSE. © Springer International Publishing AG 2017.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/247237 Collegamento a IRIS

2017
Nonlinear control of a photovoltaic battery system via ABC-tuned Dynamic Surface Controller
IEEE Congress on Evolutionary Computation 2017
Autore/i: Baldini, Alessandro; Ciabattoni, Lucio; Felicetti, Riccardo; Ferracuti, Francesco; Freddi, Alessandro; Monteriù, Andrea
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: This paper proposes a control methodology basedon Dynamic Surface Control (DSC) to manage the powerflow of a photovoltaic (PV) battery system. In particular, dueto the inner stochastic nature and intermittency of the solarproduction and in order to face the irradiance rapid changes,a robust and fast controller is needed. Dynamic Surface Controlis a modified version of Backstepping control that avoidsthe explosion of terms, which is a typical drawback of theBackstepping control and furthermore it is not affected bythe well known problem of chattering, which affects SlidingMode controllers. Dynamic Surface Control is compared to theconventional Proportional–Integral–Derivative controller (PID).In particular, DSC shows better performances in terms of steadystate chattering and transient response, as confirmed by theIntegral of the Absolute value of Error (IAE), Integral of theSquared Error (ISE) and Integral of Time multiplied by theAbsolute value of Error (ITAE) performance indexes.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250028 Collegamento a IRIS

2017
A new open-source Energy Management framework: Functional description and preliminary results
2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
Autore/i: Fagiani, Marco; Severini, Marco; Squartini, Stefano; Ciabattoni, Lucio; Ferracuti, Francesco; Fonti, Alessandro; Comodi, Gabriele
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper, a new open-source SW framework for energy management is presented. Its name is rEMpy, which stands for residential Energy Management in python. The framework has a modular structure and it is composed by an optimal scheduler, a user interface, a prediction module and the building thermal model. Unlike most of the EMs in literature, rEMpy is open-source, can be fully customized (in terms of tasks, modules and algorithms) and integrates in real-time a thermal modelling software. In this contribution, an overview of the rEMpy and its constitutive parts is given first, followed by a detailed description of the rEMpy modules and the communication system. The Computational Intelligence algorithms which perform forecasting, thermal modelling and optimal scheduling are also presented. The performance of rEMpy is finally evaluated in two case studies with different heating technologies and the results are reported and discussed.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/252453 Collegamento a IRIS

2017
Personal monitoring and health data acquisition in smart homes
Human Monitoring, Smart Health and Assisted Living: Techniques and technologies
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Freddi, Alessandro; Longhi, Sauro; Monteriù, Andrea
Editore: IET The Institution of Engineering and Technology
Luogo di pubblicazione: London
Classificazione: 2 Contributo in Volume
Abstract: The use of ambient assisted living technology, namely technology to improve the quality of life of people at home, is becoming a common trait of modern society. This technology, however, is difficult to be completely defined and classified, since it addresses many different human needs ranging from the physiological sphere to the psychological and social ones. In this chapter we focus on personal monitoring and data acquisition in smart homes, and propose the results of our research activities in the form of the description of three functional prototypes, each one addressing a specific need: an environmental monitoring system to measure the respiratory rate, a domotic architecture for both comfort assessment and user indoor localization, and a device for supporting mobility indoors. Each prototype description is followed by an experimental analysis and, finally, by considerations suggesting possible future developments in the very near future.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/249842 Collegamento a IRIS

2017
Multimedia experience enhancement through affective computing
2017 IEEE International Conference on Consumer Electronics, ICCE 2017
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Longhi, Sauro; Pepa, Lucia; Romeo, Luca; Verdini, Federica
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259871 Collegamento a IRIS

2017
A sensor fusion approach for measuring emotional customer experience in an intelligent retail environment
Consumer Electronics - Berlin (ICCE-Berlin), 2017 IEEE 7th International Conference on
Autore/i: Ciabattoni, Lucio; Frontoni, Emanuele; Liciotti, Daniele; Paolanti, Marina; Romeo, Luca
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/256689 Collegamento a IRIS

2017
A real-Time Fuzzy Logic algorithm for freezing of gait management on a smartphone
IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Autore/i: Pepa, Lucia; Capecci, Marianna; Ciabattoni, Lucio; Spalazzi, Luca; Ceravolo, Maria Gabriella
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/262386 Collegamento a IRIS

2017
Microgrid sizing via profit maximization: A population based optimization approach
IEEE International Conference on Industrial Informatics (INDIN)
Autore/i: Cavanini, Luca; Ciabattoni, Lucio; Ferracuti, Francesco; Ippoliti, Gianluca; Longhi, Sauro
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/247738 Collegamento a IRIS

2017
Real-time mental stress detection based on smartwatch
2017 IEEE International Conference on Consumer Electronics, ICCE 2017
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Longhi, Sauro; Pepa, Lucia; Romeo, Luca; Verdini, Federica
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259872 Collegamento a IRIS

2016
Serious gaming approach for physical activity monitoring: A visual feedback based on quantitative evaluation
2016 IEEE 6th International Conference on Consumer Electronics - Berlin (ICCE-Berlin)
Autore/i: Ciabattoni, L.; Ferracuti, F.; Lazzaro, G.; Romeo, L.; Verdini, F.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: This work presents the design of an exergaming interface and an assessment tool for the analysis of physical activities. Typically, exergaming aim to engage the user in physical or cognitive activities by qualitative goals that do not take into account the quantitative assessment of the exercise execution. In this work, authors propose an interactive interface which displays a human avatar and returns a real-time visual feedback highlighting where the user is mistaken. Moreover, the performance assessment is obtained by Dynamic Time Warping (DTW) algorithm based on quaternion-based pose distance. Differently from other approaches, a quantitative motion assessment is provided through the rotational constraint descriptors of physical exercises, chosen by specialists, allowing its implementation in eHealth context.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/282882 Collegamento a IRIS

2016
Real time step length estimation on smartphone
2016 IEEE International Conference on Consumer Electronics, ICCE 2016
Autore/i: Pepa, Lucia; Marangoni, Giacomo; DI NICOLA, Matteo; Ciabattoni, Lucio; Verdini, Federica; Spalazzi, Luca; Longhi, Sauro
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Smartphones are particularly suitable for health related applications during daily living, given their diffusion into society and computational capabilities. We proposed a smartphone application for real-time step length estimation, using inverted pendulum model. We tested the proposed solution on 5 healthy subjects, comparing the smartphone estimation with a stereophotogrammetric system. © 2016 IEEE.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/237323 Collegamento a IRIS

2016
A novel computer vision based e-rehabilitation system: From gaming to therapy support
2016 IEEE International Conference on Consumer Electronics, ICCE 2016
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Iarlori, Sabrina; Longhi, Sauro; Romeo, Luca
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: We propose a novel e-rehabilitation system based on a commercial RGB-D device. Differently from exergaming approaches, clinical objectives scores of each specific body part involved in the exercise are computed. Subjects performances are sent to the physiotherapists in order to support and improve decisions and therapies. © 2016 IEEE.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/237316 Collegamento a IRIS

2016
Artificial bee colonies based optimal sizing of microgrid components: A profit maximization approach
2016 IEEE Congress on Evolutionary Computation, CEC 2016
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Ippoliti, Gianluca; Longhi, Sauro
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/247752 Collegamento a IRIS

2016
A novel RSSI based approach for human indoor localization: The Fuzzy Discrete Multilateration
IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Autore/i: Baldini, A.; Ciabattoni, Lucio; Felicetti, R.; Ferracuti, Francesco; Longhi, Sauro; Monteriu', Andrea; Freddi, Alessandro
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper a new algorithm for indoor localization, namely Fuzzy Discrete Multilateration (FDM), is proposed. As the name suggests, it elaborates data from any number of transmitters (anchor nodes), and returns the estimated position of an unknown receiver. Furthermore, two cascade fuzzy inference systems are employed to evaluate the reliability of the data gathered from each beacon. The algorithm has been tested in different real world environments, where the anchor nodes are smart objects and the unknown node is any smart object held by the user to be localized. The performances of our algorithm has been compared with those of three well known localization algorithms (with a beacon density ranging from 0.03 to 0.1 beacon/m2) and results are shown. © 2016 IEEE.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/240569 Collegamento a IRIS

2016
Room occupancy detection: Combining RSS analysis and fuzzy logic
IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Autore/i: Baldini, A.; Ciabattoni, Lucio; Felicetti, R.; Ferracuti, Francesco; Longhi, Sauro; Monteriu', Andrea; Freddi, Alessandro
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: n this paper we focus our attention on the world of Internet of Things (IoT) objects and their potential for human indoor localization. Our aim is to investigate how Received Signal Strength (RSS) can be effectively used for identifying the position of a person at home, by exploiting common IoT communication networks. We propose a plug and play solution where the Anchor Nodes (ANs) are represented by smart objects located in the house, while the Unknown Node (UN) can be any smart object held by the user. The proposed solution automatically identifies the rooms where the smart objects are placed, by comparing a fuzzy weighted distance matrix derived from the anchor signals, with a threshold weighted distance matrix derived from the distances between rooms. The information can be easily integrated in any IoT environment to provide the estimation of the user position, without requiring the a priori knowledge of the positions of the anchor nodes. © 2016 IEEE.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/240570 Collegamento a IRIS

2016
Indoor thermal comfort control based on fuzzy logic
Advances in Chaos Theory and Intelligent Control
Autore/i: Ciabattoni, Lucio; Cimini, Gionata; Ferracuti, Francesco; Ippoliti, Gianluca; Longhi, Sauro; Azar, Ahmad Taher
Editore: Springer Verlag
Classificazione: 2 Contributo in Volume
Abstract: Control and monitoring of indoor thermal conditions represent crucial tasks for people’s satisfaction in working and living spaces. In the first part of the chapter we address thermal comfort issues in a working office scenario. Among all standards released, predicted mean vote (PMV) is the international index adopted to define users thermal comfort conditions in moderate environments. In order to optimize PMV index we designed a novel fuzzy controller suitable for commercial Heating, Ventilating and Air Conditioning (HVAC) systems. However in a residential scenario it would be extremely expensive to gather real time measures for PMV computation. Indeed in the second part of the chapter we introduce a novel approach for residential multi room comfort control based on humidex index. A fuzzy logic controller is introduced to reach and maintain comfort conditions in a living environment. Both control systems have been experimentally tested in the central east coast of Italy. Temperature regulation performances of both approaches have been compared with those of a classical PID based thermostat. © 2016, Springer International Publishing Switzerland 2016.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/237319 Collegamento a IRIS

2016
Tecnologie assistive per la vita indipendente
La Bioingegneria per il benessere e l'invecchiamento attivo
Autore/i: Longhi, Sauro; Ciabattoni, Lucio; Ferracuti, Francesco; Freddi, Alessandro; Monteriù, Andrea; Ortenzi, Davide; Romeo, Luca
Editore: Pàtron Editore
Luogo di pubblicazione: Bologna
Classificazione: 2 Contributo in Volume
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/241724 Collegamento a IRIS

2016
A thruster failure tolerant control scheme for underwater vehicles
MESA 2016 - 12th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications - Conference Proceedings
Autore/i: Ciabattoni, L.; Fasano, A.; Ferracuti, F.; Freddi, A.; Longhi, S.; Monteriù, A.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: This paper extends our previous work [1] on the design of a thruster failure tolerant control scheme for underwater vehicles. The proposed control scheme is based on the use of a suitable thruster allocation algorithm, which consists on a modified version of the Moore-Penrose pseudo inverse. In this work, each thruster of the underwater vehicle can rotate, offering a significant advantage to optimize its control. When a thruster experiences a failure, the resulting thrust force, which should be allocated to the failed actuator, is reallocated to the still faultless thrusters. Moreover, the angle of each thrusters is set to minimize the control effort. A bank of controllers is built so that each controller is designed to control the considered underwater vehicle under a specific actuator failure scenario. © 2016 IEEE.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/240565 Collegamento a IRIS

2016
Fault detection of nonlinear processes based on switching linear regression models
42nd Conference of the Industrial Electronics Society, IECON 2016
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Freddi, Alessandro; Ippoliti, Gianluca; Longhi, Sauro; Monteriu', Andrea
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/244862 Collegamento a IRIS

2016
Variable structure sensorless control of PMSM drives
Advances and Applications in Nonlinear Control Systems
Autore/i: Ciabattoni, Lucio; Corradini, Maria Letizia; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro; Orlando, Giuseppe
Editore: Springer Verlag
Classificazione: 2 Contributo in Volume
Abstract: In this chapter has been proposed a robust sensorless cascade control scheme for a Permanent Magnet Synchronous Motor (PMSM)drive.ADiscreteTime Variable Structure Control (DTVSC) is considered and the rotor position and speed are obtained through an Adaptive Extended Kalman Filter (AEKF). The performance of the filter is improved by an on line adjustment of the input and measurement noise covariances obtained by a suitably defined estimation algorithm. The proposed solution is experimentally tested on a commercial PMSM drive equipped with a control system based on a floating point Digital Signal Processor (DSP). © Springer International Publishing Switzerland 2016.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/237325 Collegamento a IRIS

2016
IoT based indoor personal comfort levels monitoring
2016 IEEE International Conference on Consumer Electronics, ICCE 2016
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Ippoliti, Gianluca; Longhi, Sauro; Turri, Giacomo
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/237320 Collegamento a IRIS

2016
An Open and Modular Hardware Node for Wireless Sensor and Body Area Networks
JOURNAL OF SENSORS
Autore/i: Ciabattoni, Lucio; Freddi, Alessandro; Longhi, Sauro; Monteriu', Andrea; Pepa, Lucia; Prist, Mariorosario
Classificazione: 1 Contributo su Rivista
Abstract: Health monitoring is nowadays one of the hottest markets due to the increasing interest in prevention and treatment of physical problems. In this context the development of wearable, wireless, open-source, and nonintrusive sensing solutions is still an open problem. Indeed, most of the existing commercial architectures are closed and provide little flexibility. In this paper, an open hardware architecture for designing a modular wireless sensor node for health monitoring is proposed. By separating the connection and sensing functions in two separate boards, compliant with the IEEE1451 standard, we add plug and play capabilities to analog transducers, while granting at the same time a high level of customization. As an additional contribution of the work, we developed a cosimulation tool which simplifies the physical connection with the hardware devices and provides support for complex systems. Finally, a wireless body area network for fall detection and health monitoring, based on wireless node prototypes realized according to the proposed architecture, is presented as an application scenario.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/229968 Collegamento a IRIS

2015
Humidex based multi room thermal comfort regulation via fuzzy logic
Proceedings of the International Symposium on Consumer Electronics, ISCE
Autore/i: Ciabattoni, Lucio; Cimini, Gionata; Ferracuti, Francesco; Ippoliti, Gianluca
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/228757 Collegamento a IRIS

2015
Multi-apartment residential microgrid monitoring system based on kernel canonical variate analysis
NEUROCOMPUTING
Autore/i: Ciabattoni, Lucio; Comodi, Gabriele; Ferracuti, Francesco; Fonti, Alessandro; Giantomassi, Andrea; Longhi, Sauro
Classificazione: 1 Contributo su Rivista
Abstract: In the residential energy sector there is a growing interest in smart energy management systems able to monitor, manage and minimize energy consumption. A key factor to curb household energy consumption is the amendment of occupant erroneous behaviors and systems malfunctioning. In this scenario energy efficiency benefits can be either amplified or neutralized by, respectively, good or bad practices carried out by end users. Authors propose a diagnostic system for a residential microgrid application able to detect faults and occupant bad behaviors. In particular a nonlinear monitoring method, based on kernel canonical variate analysis, is developed. To overcome the normality assumption regarding the signals probability distribution, Upper Control Limits are derived from the estimated Probability Density Function through Kernel Density Estimation. The proposed method, applied to a smart residential microgrid, is tested on experimental data acquired from July 2012 to October 2013.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/229210 Collegamento a IRIS

2015
Bayes error based feature selection: An electric motors fault detection case study
IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society
Autore/i: Ciabattoni, Lucio; Cimini, Gionata; Ferracuti, Francesco; Grisostomi, Massimo; Ippoliti, Gianluca; Pirro, Matteo
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/228763 Collegamento a IRIS

2015
Fuzzy logic based economical analysis of photovoltaic energy management
NEUROCOMPUTING
Autore/i: Ciabattoni, Lucio; Ferracuti, Francesco; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 1 Contributo su Rivista
Abstract: Since 2002 the European Union has seen a rapid growth in the photovoltaic (PV) sector. During the last two years incentives for PV installations were cut almost worldwide slowing the growth of the market. In this scenario the design of a new plant ensuring economic convenience is strongly related to household electricity consumption patterns and energy management actions. This paper presents a high-resolution model of domestic electricity use based on Fuzzy Logic Inference System. Taking into account consumers sensibility concerning the rational use of energy, the model gives as output a 1-min resolution overall electricity usage pattern of the household. The focus of this work is the use of a novel fuzzy model combined with a cost benefits analysis to evaluate the real economic benefits of load shifting actions. A case study is presented to quantify its effectiveness in the new net metering Italian scenario. © 2015 Elsevier B.V.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/228734 Collegamento a IRIS

2015
A novel LDA-based approach for motor bearing fault detection
Proceeding - 2015 IEEE International Conference on Industrial Informatics, INDIN 2015
Autore/i: Ciabattoni, Lucio; Cimini, Gionata; Ferracuti, Francesco; Freddi, Alessandro; Ippoliti, Gianluca; Monteriu', Andrea
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/228746 Collegamento a IRIS

2015
Residential energy monitoring and management based on fuzzy logic
2015 IEEE International Conference on Consumer Electronics, ICCE 2015
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Pagnotta, D. Proietti; Foresi, G.; Longhi, Sauro
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/228736 Collegamento a IRIS

2015
Indoor thermal comfort control through fuzzy logic PMV optimization
Proceedings of the International Joint Conference on Neural Networks
Autore/i: Ciabattoni, Lucio; Cimini, Gionata; Ferracuti, Francesco; Grisostomi, Massimo; Ippoliti, Gianluca; Pirro, Matteo
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/228745 Collegamento a IRIS

2015
An open and modular hardware node for wireless body area networks
International Work- shop on Micro-Nano-Bio-ICT Convergence: Current Research and Future Trends
Autore/i: Prist, Mariorosario; Ciabattoni, Lucio; Freddi, Alessandro; Longhi, Sauro; Monteriu', Andrea; Pepa, Lucia
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Health monitoring is nowadays one of the most im-portant markets due to the increasing interest in prevention andtreatment of physical problems. In this context the developmentof wearable, wireless, open source and non-intrusive sensingsolutions is still an open problem. Indeed most of the existingcommercial architectures are closed and provide little flexibility.An open hardware architecture for the design of a modularwireless sensor node for health monitoring is proposed in thispaper. Dividing the connection and sensing functions in twoseparate boards, compliant to the IEEE1451 standard, we addplug and play capabilities to analog transducers. Furthermore,we propose an open hardware wireless body area networksolution with fall detection and health monitoring capabilities.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/234074 Collegamento a IRIS

2015
On the design of observers robust to load variations for synchronous converters
2015 International Conference on Renewable Energy Research and Applications, ICRERA 2015
Autore/i: Ciabattoni, Lucio; Cimini, Gionata; Ferracuti, Francesco; Ippoliti, Gianluca; Longhi, Sauro; Miceli, Rosario; Orlando, Giuseppe
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/228743 Collegamento a IRIS

2015
Household electrical consumptions modeling and management through neural networks and fuzzy logic approaches
Complex system modelling and control through intelligent soft computations
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro
Editore: Springer International Publishing
Classificazione: 2 Contributo in Volume
Abstract: In recent years the European Union and, moreover, Italy has seen a rapid growth in the photovoltaic (PV) sector, following the introduction of the feed in tariff schemes. In this scenario, the design of a new PV plant ensuring savings on electricity bills is strongly related to household electricity consumption patterns. This chapter presents a high-resolution model of domestic electricity use, based on Fuzzy Logic Inference System. The model is built with a "bottom-up" approach and the basic block is the single appliance. Using as inputs patterns of active occupancy and typical domestic habits, the fuzzy model give as output the likelihood to start each appliance within the next minute. In order to validate the model, electricity demand was recorded over the period of one year within 12 dwellings in the central east coast of Italy. A thorough quantitative comparison is made between the synthetic and measured data sets, showing them to have similar statistical characteristics. The focus of the second part of this work is to develop a neural networks based energy management algorithm coupled with the fuzzy model to correctly size a residential photovoltaic plant evaluating the economic benefits of energy management actions in a case study. A cost benefits analysis is presented to quantify its effectiveness in the new Italian scenario and the evaluation of energy management actions. © Springer International Publishing Switzerland 2015.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/195507 Collegamento a IRIS

2014
Home energy management benefits evaluation through fuzzy logic consumptions simulator
Proceedings of the International Joint Conference on Neural Networks, IJCNN 2014
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/179118 Collegamento a IRIS

2014
An interoperable framework for home automation design, testing and control
2014 22nd Mediterranean Conference on Control and Automation, MED 2014
Autore/i: Ciabattoni, Lucio; Cimini, Gionata; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/175117 Collegamento a IRIS

2014
Modular design of a novel wireless sensor node for smart environments
MESA 2014 - 10th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, Conference Proceedings
Autore/i: Grisostomi, Massimo; Ciabattoni, Lucio; Prist, Mariorosario; Romeo, Luca; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/186510 Collegamento a IRIS

2014
Fuzzy logic home energy consumption modeling for residential photovoltaic plant sizing in the new Italian scenario
ENERGY
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 1 Contributo su Rivista
Abstract: In recent years, Italy has seen a rapid growth in the PV (photovoltaic) sector, following the introduction of the FIT (feed in tariff) scheme known as Conto Energia. In July 2013 the Italian government definitively cut FITs, leaving only tax benefits and a revised net metering scheme (known as “Scambio sul Posto”) for new PV installations. In this scenario, the design of a new PV plant ensuring savings on electricity bills is strongly related to household electricity consumption patterns. This paper presents a high-resolution model of domestic electricity use. The model is based on Fuzzy Logic Inference System. Using as inputs patterns of active occupancy and typical domestic habits, the fuzzy model give as output the likelihood to start each appliance within the next minute. The model has been validated with electricity demand data recorded over the period of one year within 12 dwellings in the central east coast of Italy. The tool has been used to evaluate the self consumption percentage to correctly size a residential photovoltaic plant in a case study. A cost benefits analysis is presented to show the effectiveness of PV-generation in the new Italian scenario.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/186506 Collegamento a IRIS

2014
Application of a wireless sensor networks and Web2Py architecture for factory line production monitoring
2014 IEEE 11th International Multi-Conference on Systems, Signals and Devices, SSD 2014
Autore/i: Grisostomi, Massimo; Ciabattoni, Lucio; Prist, Mariorosario; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/150102 Collegamento a IRIS

2014
Fuzzy logic simulator for energy management algorithms testing
MESA 2014 - 10th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, Conference Proceedings
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro; Bonci, Andrea
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/186509 Collegamento a IRIS

2014
Artificial intelligence and new technologies for photovoltaic systems in the Italian scenario
Autore/i: Ciabattoni, Lucio
Editore: Università Politecnica delle Marche
Classificazione: 8 Tesi di dottorato
Abstract: Il sempre più rapido declino delle fonti di energia tradizionali, la crescente domanda di energia e il problema ambientale hanno spinto negli ultimi anni la ricerca verso lo sfruttamento di nuove fonti di energia pulite. Sebbene inferiore ad altre fonti energetiche in termini di capacità installata il solare fotovoltaico (FV) è tuttora la più importante fonte di generazione distribuita (GD) del pianeta. La crescita del mercato italiano è stata spinta da una serie di decreti per l’incentivazione della tecnologia FV, iniziati nel 2005 con il cosiddetto "Primo Conto Energia". Le tariffe incentivanti per la produzione di energia da solare fotovoltaico sono state oggetto di continue modifiche fino al Giugno 2013 quando il governo ha deciso di eliminare definitivamente incentivi per i nuovi impianti installati. Con quasi 550,000 impianti e 17,4 GW di potenza installata, la generazione distribuita di FV ha un ruolo molto importante nello scenario italiano come parte integrante della rete nazionale. Sebbene da un lato il sistema elettrico benefici della presenza di sistemi di generazione distribuita, dall’altro sorgono numerosi problemi di integrazione dovuti alla natura dell’energia solare. Una questione importante da fronteggiare è quella della variabilità della produzione (ad esempio per via del rapido passaggio di nubi). In questo lavoro di tesi si cercherà di affrontare il problema mediante algoritmi di previsione basati su reti neurali e con l’ausilio di sistemi di storage dell’energia. Un ulteriore problema legato al FV è quello della perdita di efficienza dovuta all’innalzamento della temperatura del pannello. In questa discussione verrà mostrato e studiato un innovativo prototipo di un sistema attivo di raffreddamento della superficie dei moduli. Per ultimo verrà esaminato il problema della differenza temporale tra energia prodotta e consumo di utenti residenziali, sia dal punto di vista di energy management a livello domestico che mediante l’uso di batterie, necessarie per stoccare l’eccesso di energia nei periodi di produzione di picco.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/242873 Collegamento a IRIS

2014
Smartphone Based Fuzzy Logic Freezing of Gait Detection in Parkinson’s Disease
Mechatronic and Embedded Systems and Applications (MESA), 2014
Autore/i: Pepa, Lucia; Ciabattoni, Lucio; Verdini, Federica; Capecci, Marianna; Ceravolo, MARIA GABRIELLA
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The freezing of gait (FOG) is a common and highly distressing motor symptom of patients with Parkinson’s Disease (PD). Effective management of FOG is difficult given its episodic nature, heterogeneous manifestation and limited responsiveness to drug treatment. Clinicians found alternative approaches, such as rhythmic cueing. We built a smartphone-based architecture in agreement with acceptability and usability requirements which is able to gather data and information useful to detect FOG. In this work fusing together the information of freeze index, energy, cadency variation and the ratio of the derivative of the energy a novel Fuzzy Logic based algorithm is developed. Performances of the Fuzzy algorithm are compared with two other algorithms showing its capability to reduce false negative detection thus improving sensitivity and specificity
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/214516 Collegamento a IRIS

2014
A discrete-time VS controller based on RBF neural networks for PMSM drives
ASIAN JOURNAL OF CONTROL
Autore/i: Ciabattoni, Lucio; Corradini, Maria Letizia; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro; Orlando, Giuseppe
Classificazione: 1 Contributo su Rivista
Abstract: A method merging the features of variable structure control and neural network design is presented for speed control of a permanent magnet synchronous motor. The proposed control approach is based on a discrete-time variable structure control and a robust digital differentiator for speed estimation. Radial basis function neural networks are used to learn about uncertainties affecting the system. A stability analysis is provided and the ultimate boundedness of the speed tracking error is proved. Control performance has been evaluated by simulations using the model of a commercial permanent magnet synchronous motor drive.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/95662 Collegamento a IRIS

2013
Experimental validation of a dynamic linear model of photovoltaic-thermal collector
39th IEEE Photovoltaic Specialists Conference, PVSC 2013
Autore/i: Ciabattoni, Lucio; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/127075 Collegamento a IRIS

2013
Neural networks based home energy management system in residential PV scenario
39th IEEE Photovoltaic Specialists Conference, PVSC 2013
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/127076 Collegamento a IRIS

2013
Solar irradiation forecasting for PV systems by fully tuned minimal RBF neural networks
Smart Innovation, Systems and Technologies
Autore/i: Ciabattoni, Lucio; Ippoliti, Gianluca; Longhi, Sauro; Pirro, Matteo; Cavalletti, Matteo
Editore: Springer
Luogo di pubblicazione: Berlin Heidelberg
Classificazione: 2 Contributo in Volume
Abstract: An on-line prediction algorithm able to estimate, over a determined time horizon, the solar irradiation of a specific site is considered. The learning algorithm is based on Radial Basis Function (RBF) networks and combines the growing criterion and the pruning strategy of the minimal resource allocating network technique. An adaptive extended Kalman filter is used to update all the parameters of the Neural Network (NN). The on-line learning mechanism avoids the initial training of the NN with a large data set. The proposed solution has been experimentally tested on a 14 kWp PhotoVoltaic (PV) plant and results are compared to a classical RBF neural network. © Springer-Verlag Berlin Heidelberg 2013.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/83487 Collegamento a IRIS

2013
A fuzzy logic tool for household electrical consumption modeling
Proceedings 39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/127079 Collegamento a IRIS

2013
Design of a home energy management system by online neural networks
11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, ALCOSP 2013
Autore/i: Ciabattoni, Lucio; Ippoliti, Gianluca; Benini, Alessandro; Longhi, Sauro; Pirro, Matteo
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/108863 Collegamento a IRIS

2013
A smart lighting system for industrial and domestic use
2013 IEEE International Conference on Mechatronics, ICM 2013
Autore/i: Ciabattoni, Lucio; Freddi, Alessandro; Ippoliti, Gianluca; Marcantonio, Maurizio; Marchei, Davide; Monteriu', Andrea; Pirro, Matteo
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/88272 Collegamento a IRIS

2013
Online tuned neural networks for fuzzy supervisory control of pv-battery systems
2013 IEEE PES Innovative Smart Grid Technologies Conference, ISGT 2013
Autore/i: Ciabattoni, Lucio; Ippoliti, Gianluca; Longhi, Sauro; Cavalletti, Matteo
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/89662 Collegamento a IRIS

2013
Supervisory control of PV-battery systems by online tuned neural networks
2013 IEEE International Conference on Mechatronics, ICM 2013
Autore/i: Ciabattoni, Lucio; Cimini, Gionata; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro; Mainardi, Emanuele
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/88271 Collegamento a IRIS

2013
A novel photovoltaic-thermal collector prototype: design, modeling, experimental validation and control
Proceedings 39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013
Autore/i: Ciabattoni, Lucio; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/127080 Collegamento a IRIS

2012
Application of a supervised improved PID for the scheduling of energy feeding in a PV - Battery system
2nd IFAC Conference on Advances in PID Control, PID 2012
Autore/i: Ciabattoni, Lucio; Ippoliti, Gianluca; Cavalletti, Matteo; Rocchetti, Marco; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/78172 Collegamento a IRIS

2012
On line solar irradiation forecasting by minimal resource allocating networks
2012 20th Mediterranean Conference on Control and Automation, MED 2012 - Conference Proceedings
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro; Mainardi, Emanuele
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/75214 Collegamento a IRIS

2012
Solar irradiation forecasting using RBF networks for PV systems with storage
Proceedings 2012 IEEE International Conference on Industrial Technology, ICIT 2012
Autore/i: Ciabattoni, Lucio; Ippoliti, Gianluca; Longhi, Sauro; Cavalletti, Matteo; Rocchetti, Marco
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/74063 Collegamento a IRIS

2012
Online tuned neural networks for PV plant production forecasting
38th IEEE Photovoltaic Specialists Conference, PVSC 2012
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro; Mainardi, Emanuele
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/82383 Collegamento a IRIS

2011
Estimation of rotor position and speed for sensorless DSP-based PMSM drives
2011 19th Mediterranean Conference on Control and Automation, MED 2011
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/63363 Collegamento a IRIS

2011
Adaptive extended kalman filter for robust sensorless control of PMSM drives
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Autore/i: Ciabattoni, Lucio; Corradini, Maria Letizia; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro; Orlando, Giuseppe
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/64351 Collegamento a IRIS

2010
Robust speed estimation and control of PM synchronous motors via quasi-sliding modes
Proceedings of the 49th IEEE Conference on Decision and Control, CDC 2010
Autore/i: Ciabattoni, Lucio; Corradini, Maria Letizia; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro; Orlando, Giuseppe
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/46292 Collegamento a IRIS

2010
RBF neural networks based quasi sliding mode controller and robust speed estimation for PM synchronous motors
36th Annual Conference of the IEEE Industrial Electronics Society, IECON 2010
Autore/i: Ciabattoni, Lucio; Corradini, Maria Letizia; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro; Orlando, Giuseppe
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/50581 Collegamento a IRIS

2009
Modal and harmonic experimental validation of the vibration model of an elastic structure
2009 17th Mediterranean Conference on Control and Automation, MED 2009
Autore/i: Ciabattoni, Lucio; Grisostomi, Massimo; Ippoliti, Gianluca; Longhi, Sauro
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/46769 Collegamento a IRIS




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