A review of smart monitoring and spoilage prediction of food grains stored in grain warehouses using IoT

Grain monitoring techniques contribute significantly to the supply chain industry in terms of reducing food waste, with the expansion of the worldwide demand for healthy food, the demand for healthy grains is also increasing. This motivated agriculturists and farmers to focus more on grain management and make efforts to implement effective techniques for monitoring and predicting grain quality and spoilage respectively. Conventional methods rely on approximating grain quality by measuring the temperature and estimating the moisture based on random manual checks. These techniques detect the grain spoiling fungus, or insects at a later stage and hence fail to prevent or control spoilage. The main parameters responsible for grain spoilage are temperature and relative humidity. Continuous monitoring of these parameters helps to detect infestation at an early stage. However it is difficult to accurately predict these parameters by considering the constant variation in external and internal environments. This review is focusing on smart monitoring processes using the IoT and it analyses existing work on spoilage prediction comprehensively to identify trends, challenges, gaps, and methodologies.