Cognitive Edge-Driven Data Handling across Distributed Sensor Nodes for Robust Communication Networks

For applications such as smart cities, environmental monitoring, and industrial automation in critical infra, sensor networks are important, but they are confronted with serious issues regarding scalability, energy consumption, and reliable communication. To overcome these challenges, an adaptive smart sensor node communication framework (AS-SNCF) is proposed, which is an intelligent and efficient communication framework. A hexagonal grid deployment that provides uniform coverage is employed by AS-SNCF, and the nodes are divided into primary nodes (cluster heads) and secondary nodes (data collectors). It employs advanced quantum-inspired self-organizing clustering for dynamic cluster formation and bio-inspired neural routing for adaptive and energy-efficient multi-hop communication. The framework is based on event-driven sensing wherein nodes are activated only when critical thresholds are crossed, and lightweight data compression is applied to minimize transmission loads. Energy minimization and communication interference reduction are achieved through adaptive power control, and data handling based on priorities, whereby essential data is reliably sent with the support of self-healing system allowing the system to tolerate failure. AS-SNCF demonstrates a 45% increase in energy efficiency, a 38% reduction in latency, and a 42% improvement in scalability, making it a robust and efficient solution for complex and resource-constrained environments.