Target tracking of binary wireless sensor networks in the domain of medicine and healthcare

Falling of the elderly has become a growing concern of the community due to the increase of the ageing population and the serious consequences caused by falling. Devising a fall detection system that is not only highly accurate and reliable, but energy efficient and durable is a challenge. In this paper, we proposed an energy efficient fall detection algorithm based on segmented sampling rates. Most of the time, the algorithm uses a low sampling rate to minimise the energy consumption, but a higher sampling rate when a possible fall is sensed. This unique design helps to increase the fall detection accuracy, while reducing the total energy consumption. Results of comprehensive performance evaluation show that the accuracy rate of the proposed fall detection algorithm is 98.33%, meanwhile, the system can save energy by 9.13% comparing to other algorithms running with a high sampling rate without an energy efficient strategy.

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Target tracking of binary wireless sensor networks in the domain of medicine and healthcare

Cited by 3 publications

References 20 publications

Bio-inspired Patrolling Scheme Design in Wireless and Mobile Sensor and Robot Networks

Bio-inspired Patrolling Scheme Design in Wireless and Mobile Sensor and Robot Networks

Glider assisted schemes to deploy sensor nodes in Wireless Sensor Networks

Real-time energy-efficient fall detection based on SSR energy efficiency strategy

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