Early Detection of Onion Spoilage

– As technology advances and people become increasingly reliant on smartphones, it becomes crucial to develop technological solutions for agricultural challenges. Traditional storage methods can help prevent onion spoilage, but there are instances where spoiled onions may go unnoticed. To address this issue, implementing technology such as deep learning algorithms and sensors can be highly beneficial. While existing IoT frameworks have faced challenges in accurately predicting data due to environmental conditions, integrating image processing techniques can enhance accuracy. This paper presents a model developed using IDE, focusing on image processing to detect onion spoilage. By combining segmentation and object extraction processes, the model improves image features by removing background and irrelevant elements. With a model achieving 87% accuracy, the system then utilizes an IoT framework with sensors to monitor onion parameters and display spoilage stages on an LCD. This integrated system provides real-time spoilage information, aiding farmers and retailers in mitigating onion spoilage risks.