Comparative Analysis of Scalable IoT Topologies for Optimal and Precise Greenhouse Environment Monitoring

Precision agriculture is vital for optimizing parameters for plant growth and health particularly in controlled environments like greenhouses. The Internet of Things (IoT) is a driver of this, and Wireless Sensor Networks provide a structured approach for data acquisition in these environments. While WSNs are widely implemented, there is limited empirical comparison of signal performance metrics across different sensor motes. This study presents a comparative analysis using the Received Signal Strength Indicator (RSSI) parameter of two different IoT devices, Iris Mote and Zolertia RE-Mote in a greenhouse environment, specifically at the K.C. Irving Environmental Science Centre Greenhouse at Acadia University. Results indicate that the Zolertia RE-Mote offers superior range, processing power, and energy efficiency, making it better suited for scalable deployments. These findings highlight the importance of environment specific testing for WSN deployment in precision agriculture.