Among sensible goals of active and assisted living paradigm is the unobtrusive monitoring of daily living activities. Based on such monitoring, anomalies and trends can be discovered, which possibly allows for early assessment of health issues and for prevention policies. However, when dealing with the home environment, and especially with older adults, obtrusiveness, usability, and cost concerns are of the utmost relevance. Smart objects can be designed to this purpose and deployed into the home: they usually feature low data rates and are customarily implemented by relying on conventional wireless sensor network approaches (ZigBee, Z-Wave, etc). This, however, results in ''ad hoc'' home networking, which is somehow obtrusive, complicated, and possibly expensive. In this paper, we discuss the implementation of behavioral sensors based on the familiar and ubiquitous Wi-Fi technology, suitable for a ''plug-and-play'' deployment. Sensors are connected to a cloud platform, embodying a genuine Internet of Things approach. With respect to conventional approaches, much better scalability, flexibility, and inexpensiveness can be attained. The main expected drawback comes from the higher power consumption, inherently needed to sustain much higher data rates. This paper focuses on such an issue, illustrating design techniques aimed at optimizing power consumption and battery lifetime. Performance results are shown, which definitely fall within a practical range and are fully comparable with more conventional approaches.
An IoT Approach for an AAL Wi-Fi-Based Monitoring System / Bassoli, Marco; Bianchi, Valentina; DE MUNARI, Ilaria; Ciampolini, Paolo. - In: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. - ISSN 0018-9456. - 66:12(2017), pp. 3200-3209. [10.1109/TIM.2017.2753458]
An IoT Approach for an AAL Wi-Fi-Based Monitoring System
BASSOLI, MARCO;BIANCHI, Valentina;DE MUNARI, Ilaria;CIAMPOLINI, Paolo
2017-01-01
Abstract
Among sensible goals of active and assisted living paradigm is the unobtrusive monitoring of daily living activities. Based on such monitoring, anomalies and trends can be discovered, which possibly allows for early assessment of health issues and for prevention policies. However, when dealing with the home environment, and especially with older adults, obtrusiveness, usability, and cost concerns are of the utmost relevance. Smart objects can be designed to this purpose and deployed into the home: they usually feature low data rates and are customarily implemented by relying on conventional wireless sensor network approaches (ZigBee, Z-Wave, etc). This, however, results in ''ad hoc'' home networking, which is somehow obtrusive, complicated, and possibly expensive. In this paper, we discuss the implementation of behavioral sensors based on the familiar and ubiquitous Wi-Fi technology, suitable for a ''plug-and-play'' deployment. Sensors are connected to a cloud platform, embodying a genuine Internet of Things approach. With respect to conventional approaches, much better scalability, flexibility, and inexpensiveness can be attained. The main expected drawback comes from the higher power consumption, inherently needed to sustain much higher data rates. This paper focuses on such an issue, illustrating design techniques aimed at optimizing power consumption and battery lifetime. Performance results are shown, which definitely fall within a practical range and are fully comparable with more conventional approaches.File | Dimensione | Formato | |
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