Wireless sensor networks (WSN) consist of large numbers of sensor nodes, which are limited in battery power and communication range and have multi-modal sensing capabilities. In this chapter, energy-efficient data aggregation technique is proposed to improve the lifetime of the sensor. Here, the author has used three layer architecture by deploying mobile element/node, which can periodically visit cluster heads (CHs) at which first level data aggregation has been applied to eliminate redundancy. After collecting data from all CHs, mobile element itself will perform second level of data aggregation to eliminate further redundancy. After collecting data from CHs, mobile element will move towards base station/sink and transmits data to base station/sink in order to save energy of entire network. Here, the author has made an attempt to prove that in WSN during data gathering if mobile elements are used to collect the aggregated data from CHs, energy consumption of the entire network will be reduced. The proposed data aggregation with mobile node helps in improving the lifetime of the WSN.
The advanced digital technology and wireless transformation now enabling the user with the next generation to connect devices for home and presents challenges for senior citizens and disabled persons. Wireless sensor network provides a smart health solution for enabling computerized, continuous, physical signals, and performing data processing operations. There are some important parameters such as heart rate, body temperature, respiration rate, blood pressure, etc., that are captured real-time activity signals and analysed by the appropriate connected sensors. Biosensors are complete and continuously capture physiological parameters at any time and everywhere. The complete source of information is integrated with the smartphone devices and sometimes the most risk factor information is immediately sent to the remote hospitals. The main aim of this chapter is to focus on the overview of various advanced technologies like google glass, Fitbit, Microsoft Band, etc. for monitoring elder people and disabled persons.
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