A Smart IoT-Based Real-Time System for Monitoring Storage Conditions of Maize Grains

Abstract

Maize is a cereal with many uses across the world. In developing countries, it is valued for its dried cereal, which has been used as a stable source of food. This cereal may be boiled and eaten as it is or may be dried and ground and made into porridge or Ugali, a popular carbohydrate source. The storage of maize grains is critical to ensuring food security and preventing post-harvest losses due to spoilage, pest infestation, and unfavourable environmental conditions. Traditional storage monitoring methods entailed using support staff to visit storage areas and measure conditions using manual methods which are inefficient and labour-intensive, leading to delays in the detection of adverse storage conditions and spoilages. In this paper, an Internet of Things (IoT)-based real-time storage conditions monitoring system that leverages Long Range Wide Area Network (LoRaWAN) technology to enhance communication efficiency and data transmission over long distances with low power consumption is presented. The system consists of smart sensors deployed in maize storage facilities to collect environmental parameters such as temperature, humidity, and carbon dioxide (CO2) levels which are critical for maize storage. The collected data is transmitted via LoRaWAN to a cloud-based platform for real-time visualization, analysis and proactive detection of changing situations using Machine Learning (ML) techniques. This approach provides an efficient, scalable, and cost-effective solution for improving maize storage, especially in resource-constrained environments since it limits manual human intervention. In addition, the technology prevents losses due to fungal infections, resulting in adequate high-quality maize supply to curb hunger and improve livelihoods which is the second United Nations’ Sustainable Development Goals of alleviating hunger and achieving food security