A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation
Smart homes play a strategic role for improving life quality of people, enabling to monitor people at home with numerous intelligent devices. Sensors can be installed to provide a continuous assistance without limiting the resident’s daily routine, giving her/him greater comfort, well-bein...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-07-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/7/2310 |
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| author | Andrea Monteriù Mario Rosario Prist Emanuele Frontoni Sauro Longhi Filippo Pietroni Sara Casaccia Lorenzo Scalise Annalisa Cenci Luca Romeo Riccardo Berta Loreto Pescosolido Gianni Orlandi Gian Marco Revel |
| author_facet | Andrea Monteriù Mario Rosario Prist Emanuele Frontoni Sauro Longhi Filippo Pietroni Sara Casaccia Lorenzo Scalise Annalisa Cenci Luca Romeo Riccardo Berta Loreto Pescosolido Gianni Orlandi Gian Marco Revel |
| author_sort | Andrea Monteriù |
| collection | DOAJ |
| description | Smart homes play a strategic role for improving life quality of people, enabling to monitor people at home with numerous intelligent devices. Sensors can be installed to provide a continuous assistance without limiting the resident’s daily routine, giving her/him greater comfort, well-being and safety. This paper is based on the development of domestic technological solutions to improve the life quality of citizens and monitor the users and the domestic environment, based on features extracted from the collected data. The proposed smart sensing architecture is based on an integrated sensor network to monitor the user and the environment to derive information about the user’s behavior and her/his health status. The proposed platform includes biomedical, wearable, and unobtrusive sensors for monitoring user’s physiological parameters and home automation sensors to obtain information about her/his environment. The sensor network stores the heterogeneous data both locally and remotely in Cloud, where machine learning algorithms and data mining strategies are used for user behavior identification, classification of user health conditions, classification of the smart home profile, and data analytics to implement services for the community. The proposed solution has been experimentally tested in a pilot study based on the development of both sensors and services for elderly users at home. |
| first_indexed | 2024-04-14T06:33:03Z |
| format | Article |
| id | doaj.art-efc18b989e5c4c7a99e3b035c2bf1d5b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T06:33:03Z |
| publishDate | 2018-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-efc18b989e5c4c7a99e3b035c2bf1d5b2022-12-22T02:07:34ZengMDPI AGSensors1424-82202018-07-01187231010.3390/s18072310s18072310A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental ValidationAndrea Monteriù0Mario Rosario Prist1Emanuele Frontoni2Sauro Longhi3Filippo Pietroni4Sara Casaccia5Lorenzo Scalise6Annalisa Cenci7Luca Romeo8Riccardo Berta9Loreto Pescosolido10Gianni Orlandi11Gian Marco Revel12Department of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, ItalyDepartment of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, ItalyDepartment of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, ItalyDepartment of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, ItalyDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, 60131 Ancona, ItalyDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, 60131 Ancona, ItalyDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, 60131 Ancona, ItalyDepartment of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, ItalyDepartment of Information Engineering, Università Politecnica delle Marche, 60131 Ancona, ItalyElectrical, Electronics and Telecommunication Engineering and Naval Architecture Department, Università degli Studi di Genova, 16145 Genoa, ItalyItalian National Research Council, Institute for Informatics and Telematics (CNR-IIT), 56124 Pisa, ItalyDepartment of Information Engineering, Electronics e Telecommunications, University of Rome La Sapienza, 00184 Rome, ItalyDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, 60131 Ancona, ItalySmart homes play a strategic role for improving life quality of people, enabling to monitor people at home with numerous intelligent devices. Sensors can be installed to provide a continuous assistance without limiting the resident’s daily routine, giving her/him greater comfort, well-being and safety. This paper is based on the development of domestic technological solutions to improve the life quality of citizens and monitor the users and the domestic environment, based on features extracted from the collected data. The proposed smart sensing architecture is based on an integrated sensor network to monitor the user and the environment to derive information about the user’s behavior and her/his health status. The proposed platform includes biomedical, wearable, and unobtrusive sensors for monitoring user’s physiological parameters and home automation sensors to obtain information about her/his environment. The sensor network stores the heterogeneous data both locally and remotely in Cloud, where machine learning algorithms and data mining strategies are used for user behavior identification, classification of user health conditions, classification of the smart home profile, and data analytics to implement services for the community. The proposed solution has been experimentally tested in a pilot study based on the development of both sensors and services for elderly users at home.http://www.mdpi.com/1424-8220/18/7/2310smart homessmart home technologiesagingactivity of daily living |
| spellingShingle | Andrea Monteriù Mario Rosario Prist Emanuele Frontoni Sauro Longhi Filippo Pietroni Sara Casaccia Lorenzo Scalise Annalisa Cenci Luca Romeo Riccardo Berta Loreto Pescosolido Gianni Orlandi Gian Marco Revel A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation Sensors smart homes smart home technologies aging activity of daily living |
| title | A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation |
| title_full | A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation |
| title_fullStr | A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation |
| title_full_unstemmed | A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation |
| title_short | A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation |
| title_sort | smart sensing architecture for domestic monitoring methodological approach and experimental validation |
| topic | smart homes smart home technologies aging activity of daily living |
| url | http://www.mdpi.com/1424-8220/18/7/2310 |
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