An Approach for the Development of a Sensing System to Monitor Contamination in Stored Grain

Autor: Rekha Kaushik, Jyoti Singhai
Rok vydání: 2019
Předmět:
Zdroj: 2019 6th International Conference on Signal Processing and Integrated Networks (SPIN).
DOI: 10.1109/spin.2019.8711604
Popis: In India, grain is the majorly produced and consumed type of food. However, 7-15% post-harvest stored grain is lost due to unscientific storage. Insects, molds, fungi and microorganisms present in it lead to qualitative as well as quantitative loss. Lack of control over environmental factors such as moisture content and temperature of grain in storage causes contamination and infestation. The survival and reproduction of insects/fungi are highly dependent on these factors. When grain spoilt due to insect growth, heat and water are produced and level of CO 2 in grain varies. Timely monitoring of environmental parameters enables the grain managers to maintain high quality of grain. Existing methods for monitoring of stored grain includes visual inspection, carbon dioxide measurement, trapping, oven heating, sampling and near infra-red spectroscopy. The cost of collecting environmental data using existing methods is labor intensive, expensive, time consuming and imprecise. To overcome these issues, sensor network will provide the means for monitoring quality of grain and provide early means to detect contamination and insect infestation in grain. In the proposed work, an approach for designing an integrated and real time environment monitoring sensing system in stored grain has been discussed. Also, methodology to analyze collected sensor is discussed. Sensor data can help in predicting the necessary information using classification and regression methods and to generate alerts for end users to take preventive measures.
Databáze: OpenAIRE