Smart Healthcare System with Light-Weighted Blockchain System and Deep Learning Techniques

Area of Science:

• Wireless Sensor Networks
• Energy Efficiency in IoT
• Communication Protocols

Background:

• Wireless sensor networks (WSNs) face energy depletion challenges due to data relaying from distant nodes.
• Nodes near the base station often bear a disproportionate load, leading to premature energy exhaustion.
• Existing protocols struggle to balance energy consumption and network longevity effectively.

Purpose of the Study:

• To introduce the Improved Fuzzy Inspired Energy Effective Protocol (IFIEEP) for enhancing WSN energy efficiency and network lifetime.
• To develop a protocol that considers remaining energy, proximity, neighbor concentration, and cluster centrality for node selection.
• To investigate the impact of heterogeneity parameters, including supernode numbers and initial energy, on network performance.

Main Methods:

• Implementing the IFIEEP protocol with three distinct node types to reward high-performing nodes.
• Utilizing adaptive clustering on viable nodes to establish cluster leaders for efficient data transmission.
• Incorporating energy-intensive sensing energy aspects and heterogeneity parameters into the protocol's design.

Main Results:

• IFIEEP demonstrates minor gains in network lifetime with fewer supernodes but significant improvements (12.89% area coverage and 100% in some metrics) with more supernodes.
• The protocol enhances network stability, residual energy, and throughput compared to existing methods.
• The study highlights the importance of considering sensing energy and network heterogeneity for improved performance.

Conclusions:

• The IFIEEP protocol offers a viable solution for extending WSN operational lifespan and improving overall network efficiency.
• The protocol's effectiveness is particularly pronounced with increased numbers of supernodes and careful management of network heterogeneity.
• IFIEEP is designed for integration with blockchain technology applications, suggesting future advancements in secure and efficient WSNs.