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

  • Special issue on Neural Computing for IOT based Intelligent Healthcare Systems
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Abstract

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.

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Acknowledgements

The project was suppored by National Natural Science Foundation of China (62071003, 41874174), the Fund of Key Laboratory of Electromagnetic Scattering (61424090107),  the Natural Science Foundation of Anhui Province (2008085MF186).

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Authors and Affiliations

  1. School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, China

    Pratik Goswami

  2. School of Electronics and Information Engineering, Anhui University, Hefei, China

    Amrit Mukherjee & Lixia Yang

  3. Department of Electrical Engineering, R.P.B.M. Jiaganj College of Engineering, Jiangi Azimganj, India

    Bishal Sarkar

Authors
  1. Pratik Goswami
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  2. Amrit Mukherjee
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  3. Bishal Sarkar
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  4. Lixia Yang
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Correspondence to Amrit Mukherjee or Lixia Yang.

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Goswami, P., Mukherjee, A., Sarkar, B. et al. Multi-agent-based smart power management for remote health monitoring. Neural Comput & Applic 35, 22771–22780 (2023). https://doi.org/10.1007/s00521-021-06040-4

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  • DOI: https://doi.org/10.1007/s00521-021-06040-4

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