Integrating Indigenous Knowledge and IoT for Smart Resource Management in Household Grain Flour Storage practices in South India

Abstract

Efficient management of household food and natural resources is essential for reducing post-harvest losses, improving food security, and promoting sustainable storage practices. Indigenous grain and flour preservation methods have traditionally utilized locally available materials such as neem, turmeric, tulsi, garlic, and wood ash; however, their effectiveness is strongly influenced by temperature, humidity, moisture, storage duration, and climatic variability. This study proposes an IoT-enabled smart resource management framework that integrates indigenous preservation practices with real-time monitoring for sustainable household grain flour storage. A six-bin modular storage system is designed with ESP32-based sensing nodes to monitor temperature, relative humidity, flour moisture, CO₂, volatile organic compounds, storage quantity, and storage duration. The collected data are intended to support continuous assessment of storage conditions, early identification of deterioration, and efficient utilization of preservation, storage, and energy resources. A secondary experimental dataset derived from published grain-storage studies will be used to evaluate the proposed framework through correlation analysis and Principal Component Analysis (PCA). The dominant storage parameters identified through PCA will support the development of a Storage Health Index (SHI) for classifying storage conditions and generating appropriate preservation and management recommendations. The proposed framework aims to reduce food wastage, optimize indigenous preservation resources, minimize unnecessary manual intervention and energy consumption, and improve household storage decision-making under variable climatic conditions. The study provides a sustainable pathway for integrating indigenous knowledge, IoT sensing, and data-driven resource management in household grain flour storage.