Cognitive Wireless Sensor Network for Elderly Home Healthcare

The demand for Wireless Sensor Network (WSN) in healthcare applications insists several factors, such as optimum utilization of resources, energy efficiency and channel sharing. However, bulk packet forwarding in WSN results data quality deterioration that might affect on-time diagnosis. Multi-channel usage technique, for an instance Cognitive Wireless Sensor Network (CWSN) ensures better channel utilization and communication quality. The study proposes a Channel Quality based Payload Allocation (CQ-PA) technique in CWSN. The physiological data of the user are fragmented into individual payloads with respect to parameters such as, accelerometer, pulse rate and spO₂ and body temperature. The CQ-PA algorithm determines Channel Quality (CQ) metrics for all three available channels and eventually allocate appropriate payload in each channel. The proposed algorithm reduces computation complexity and also improves channel-overhearing. In this study, the participated nodes in CWSN, such as sensor nodes (S_n), relay node (R₁) and a destination node (D) are indigenously developed by using CC2530 microcontroller that consists of an inbuilt transceiver at 2.4 GHz. CQ is used to determine current state for each channel and the obtained results are observed better performance than traditional WSN.