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An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems.

Shadab Khan1, Yash Veer Singh2, Pushpendra Singh3

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Area of Science:

  • Biomedical Engineering
  • Computer Science
  • Artificial Intelligence

Background:

  • Rapid advancements in electronics technology enable sophisticated healthcare monitoring and control systems.
  • Limitations in current devices necessitate optimized utilization for efficient healthcare data management.
  • Internet of Things (IoT) based biosensor networks in healthcare face challenges with energy consumption during data transmission and collection.

Purpose of the Study:

  • To propose an optimized artificial intelligence system leveraging IoT biosensor networking for efficient data collection in healthcare.
  • To enhance the performance of healthcare systems through intelligent route optimization for data transmission.
  • To address energy efficiency challenges in IoT biosensor networks within healthcare settings.

Main Methods:

  • Implementation of an optimized artificial intelligence system for healthcare data collection.
  • Utilization of an optimized tunicate swarm algorithm (TSA) for route optimization in IoT biosensor networks.
  • Employing a fitness function incorporating distance, proximity, residual, and average node energy for TSA optimization.

Main Results:

  • The proposed method achieves optimal cluster head (CH) selection through TSA, resulting in lower energy consumption.
  • Demonstrated improvements in network stability period, lifetime, and throughput compared to existing methods.
  • Efficient data collection and transmission pathways established between patients and healthcare providers.

Conclusions:

  • The optimized AI system using IoT biosensors and TSA significantly improves energy efficiency in healthcare networks.
  • The proposed approach offers a robust solution for efficient data collection and transmission, enhancing healthcare system performance.
  • This research contributes to the development of more sustainable and effective IoT-based healthcare solutions.