ML based grain quality inspection
Business challenges
Farmer's profitability: High-quality grain can fetch better prices and increase a farmer's profitability. Farmers need to ensure that their crops meet quality standards to get the best prices for their crops.
Vendor's reputation: Vendors who sell high-quality grain products can enhance their reputation, attracting new customers and increasing profits. Accurate grain quality assessments can help vendors ensure that they are providing the highest-quality products to their customers.
Compliance with industry standards: Both farmers and vendors need to ensure that they are in compliance with industry standards and regulations, and grain quality assessments can help ensure that they are meeting these standards.
Improved supply chain management: By monitoring and controlling the quality of grain throughout the supply chain, both farmers and vendors can improve their overall supply chain management and reduce the risk of disruptions.
Better decision making: Accurate and consistent grain quality assessments can provide valuable data and insights, which can be used by both farmers and vendors to make informed decisions about grain quality and production processes.
Food safety: Grain quality assessments can ensure that the grain products being sold are safe for consumption and do not pose a health risk to consumers.
Solution Overview
We have combined image processing and AI model to develop a grain quality estimation model that can be integrated into a mobile application.
With the help of Image segmentation, the model can extract individual grains from a heap and then classify each grain based on the classes provided.
By taking out a small heap from a sack, and then capturing a picture from the mobile, the platform will get the required healthy grain ratio as well as provide details for each type of grain.
The solution will reduce the time taken to segregate the grains based on quality and reduces less manpower than usually required.
The assessed data captured can be used to gain insights over different timespans (e.g., months) to make better business decisions.
Business value
Built a one of kind product that has no match in the evangelical domain.
User adaption is made easy. Sign language experts can login and record sign language gestures of Verses of different books and chapters easily.
The data is tagged, and gesture recognition models can be trained by non-technical team members easily in the web-based portal.
Trained models can be deployed in on-premise or cloud infrastructure.
