Energy-Efficient Clustering Protocol with Multi-Source Harvesting for Heterogeneous Wireless Sensor Networks in Agricultural IoT Deployments

Wireless Sensor Networks (WSNs) deployed in precision agriculture applications face a fundamental tension between the energy constraints of battery-powered sensor nodes and the high-frequency, long-duration data collection requirements of modern crop monitoring — soil moisture, leaf wetness, microclimate temperature gradients, pest acoustic signatures — that drive actionable irrigation, pesticide, and fertigation decisions. The classical LEACH (Low Energy Adaptive Clustering Hierarchy) and its variants address this tension through cluster-based topology management that balances the energy burden of data aggregation across nodes, but none of the existing protocols simultaneously addresses heterogeneous node energy profiles, multi-source energy harvesting integration, and adaptive modulation for link quality optimisation. This paper proposes a Hybrid Energy-Aware Clustering (HEAC) protocol that extends the LEACH-SEP framework with three innovations: energy-weighted cluster head election incorporating real-time harvesting power input from solar, RF, and thermoelectric sources; adaptive modulation switching between BPSK and 16-QAM based on the instantaneous SNR estimated from pilot symbols; and a predictive duty-cycling scheme that aligns sensor wake periods with predicted peak irradiance for solar-harvested nodes. Simulation across 100 sensor nodes in a 100m×100m field model over 2,000 rounds demonstrates 31.8% residual network energy after 1,000 rounds versus 18.4% for standard LEACH, a Packet Delivery Ratio of 95.4% versus 87.2%, and network lifetime extension of 68% measured as time to 50% node death. A 20-node testbed deployment in a tomato greenhouse in Coimbatore validates simulation outcomes within 8% deviation.