Development of IoT Based Model for Monitoring and Optimizing Moisture Content in Rwanda School Feeding Maize Stores

This study explores the development of an Internet of Things (IoT)-based Model to monitor and optimize the moisture content of maize storage in the context of a school feeding program at Groupe Scolaire Cyeru, Rwanda. The objective was to address the critical issue of moisture control in maize storage, which directly impacts the quality and safety of food distributed to students. Using a mixed-methods approach, the study employed both qualitative and quantitative techniques, including surveys, interviews, document analysis, and direct observation, to gather comprehensive data on the current state of maize storage practices. The research involved 318 respondents from various stakeholders, including students, teachers, cooks, and administrative staff. The findings revealed a significant gap in moisture monitoring within the existing storage system. Based on this, an IoT-based model was developed, incorporating temperature and moisture sensors, a microcontroller, and a GSM module for real-time data collection and remote alerts. Python programming and Google Colab were utilized for data collection, processing, and analysis, enabling seamless integration of the collected data into a central system for further insights. This system aimed to optimize storage conditions and prevent spoilage, thereby improving the efficiency and sustainability of the school feeding program. The study highlights the potential of IoT technology, Python, and Google Colab in transforming food storage management, particularly in educational settings with limited resources.