Multi-agent-based smart power management for remote health monitoring

In the Internet of things (IoT) paradigm, wireless sensor networks (WSNs) contribute hugely by connecting all the devices for smart application purposes. The smart applications include smart healthcare system, as a key phenomenon of new era of medical service. Smart healthcare system consists of different techniques and approaches, and remote health monitoring is one of those important techniques of healthcare system, which helps doctors to monitor health of remotely located patients with different health statistics provided by sensors. This whole process should be fast, prompt in response and energy efficient which is tough with limited battery power of sensors. The article proposes a novel method for efficient utilization of power in WSNs, using artificial neural network-based technique self-organizing map (SOM) for clustering and distributed artificial intelligence (DAI) for power distribution in the nodes. The hybrid approach of SOM and multi-agent-based DAI results in better performance compared to other existing methods. The performance of the proposed method is validated with mathematical analysis and simulation results, which justifies the significance of the work for IoT environment.

Automated summary

Wireless sensor networks play a huge role in connecting devices for smart applications in the Internet of things (IoT) paradigm. One of the key smart applications is the smart healthcare system, which includes remote health monitoring using sensors to provide different health statistics. This article proposes a novel method that utilizes artificial neural network-based technique self-organizing map (SOM) for clustering and distributed artificial intelligence (DAI) for power distribution in the nodes. The hybrid approach of SOM and multi-agent-based DAI outperforms existing methods in terms of performance.