Development of an Intelligent Post-Harvest Monitoring System Using IoT Sensors for Grain Storage in Nigeria

This study develops and validates an Internet of Things-based intelligent monitoring system for real-time surveillance of grain storage conditions in Nigerian grain silos and warehouses. Post-harvest losses in Nigerian grain storage are significantly exacerbated by the absence of real-time monitoring of temperature, humidity, CO2 levels, and insect activity indicators that are leading signals of storage condition deterioration. Current storage monitoring in Nigerian facilities relies on periodic manual inspections that miss the early warning window for corrective intervention. This study designs an IoT sensor node system using low-cost temperature-humidity sensors, CO2 sensors, and acoustic insect activity detectors, integrated with LoRaWAN wireless communication and a cloud-based data platform. Alert algorithms are programmed to detect storage condition anomalies and trigger SMS notifications to storage managers. The system is tested in four grain storage facilities in Kano, Abuja, Enugu, and Port Harcourt storing maize, sorghum, and rice at different scales from 50 to 500 tonnes. System performance including sensor accuracy, communication reliability, battery life, and alert response effectiveness is evaluated over six-month monitoring periods. Findings reveal that the IoT system achieves temperature and humidity measurement accuracy within 0.3 degrees Celsius and 2 percent relative humidity respectively. Communication reliability exceeds 95 percent for inter-node distances below 500 metres. Early warning alerts generated by the system enabled corrective actions that reduced grain losses by an estimated 73 percent compared to manually monitored control stores. The study recommends scaled deployment in national strategic grain reserve facilities.

Keywords: IoT, grain storage monitoring, post-harvest, smart agriculture, Nigeria.