EECH HEED an adaptive hybrid clustering protocol for energy efficient soil monitoring in heterogeneous wireless...

Wireless Sensor Networks (WSNs) play a pivotal role in precision agriculture, especially for real-time soil health monitoring. However, the limited energy capacity of sensor nodes poses a significant challenge to achieving prolonged network lifetime and consistent data transmission. Existing clustering protocols often struggle with inefficient cluster head (CH) selection, limited adaptability to heterogeneous environments, and excessive control overhead. To address these issues, this paper proposes EECH-HEED, a hybrid and energy-efficient clustering model designed for soil monitoring in heterogeneous WSNs. The proposed protocol utilizes a dual-zone architecture: Zone 1, located near the base station, implements a HEED-based CH selection mechanism that considers both residual energy and communication cost for energy-aware clustering. Zone 2, positioned farther from the base station, employs an enhanced EECH-based hierarchical multi-hop clustering strategy, using residual energy and node degree to select primary and secondary CHs. Unlike the threshold-based hybrid clustering approach which, despite reducing redundant transmissions, relies on static thresholds-EECH-HEED introduces a dynamic threshold-based sensing mechanism. Here, hard and soft thresholds are continuously adjusted in real-time based on environmental change rates and node energy levels. This adaptive strategy significantly reduces energy consumption and extends the operational lifespan of sensor nodes. The model was rigorously tested using MATLAB simulations over 5000 rounds on a heterogeneous WSN setup inspired by real agricultural scenarios. Performance was benchmarked against leading protocols including LEACH, HEED, EECH, TCO, FPA, MIMO-HC, HTCCR, EEHP, and the HCRT model. EECH-HEED demonstrated marked improvements across multiple performance metrics-achieving a 33% reduction in Total Energy Consumption (TEC), a 15% increase in Packet Delivery Ratio (PDR), and a nearly 50% reduction in control overhead. It also recorded the lowest End-to-End Delay (190 ms) and the highest number of alive nodes by the end of the simulation. With its zone-based design, adaptive thresholding, and hierarchical energy-aware clustering, EECH-HEED presents a scalable and low-overhead solution for sustainable soil health monitoring. Future work includes its integration with UAV-based data collection systems and IoT platforms to support intelligent farming infrastructures.