Abstract
Among sensible goals of active and assisted living paradigm is the unobtrusive monitoring of daily living activities. A lot of research has been going on continuous home and personal monitoring applications. There are many solutions were adapted by these technologies to make better remote monitoring applications. The traditional continuous home and personal monitoring systems which are implemented with traditional client server architecture which may fail in factors like low power consumption, un deterministic data delivery time, More sensitive to external connectivity issues temporary failures of servers , adhoc networks using ZigBee and Z wave etc. and also increase the cost of implementation. However, when dealing with the home environment, and especially with older adults, obtrusiveness, usability, and cost concerns are of the utmost relevance for active and assisted Living AAL joint program. With advent of cloud services, the continuous remote monitoring based applications became truly plug and play' approach implementation and also reduce the problems of temporary failures. One of the biggest challenges in this area is to make such application devices work with low power battery based applications . The main drawback comes from the higher power consumption, inherently needed to sustain much higher data rates. In this project, a solution is proposed to improve the low power consumption in Wi Fi sensors by making use of advanced RF based Microprocessor from Texas instruments CC3200 . Bed Occupancy sensor automation has been designed and implemented to test the feasibility of the approach. The TI CC3200 comes with ARM Cortex M4 as a core and inbuilt Wi Fi subsystem. The CC3200 provides different power modes to make the device enter into sleep or hibernate mode. This device will only enter only in work phase when the sensor is active state. During this phase, the processor sample and processes the sensor data and uploads to the cloud using REST API. Thing speak is an IoT cloud service used to present the sensory data as graphs, bar charts, and dashboards on the cloud remaining time it will enter into sleep phase to save the power of the device, so that it will extend the battery life time of the device. B. N. Meenakshi | Mrs. N. V. Durga Än IOT Based Low Power Health Monitoring with Active Personal Assistance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29603.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/29603/an-iot-based-low-power-health-monitoring-with-active-personal-assistance/b-n-meenakshi
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