The process of grading agricultural products at the source hitherto has been extremely tenuous and expensive that it paved the way for manual subjectivity which consequently disrupts the flow of better quality food.

As food moves through its supply chain, agricultural trading, storage, and use worth billions occurs every year, without determining consistency, declining food value, and growing inefficiencies in the value chain.

• The Plight of Farmers due to Ambiguous Quality Assessment of Crops
  1. Disadvantageous position of farmers whose contributions are frequently ignored and rejected.
  2. The high cost of modern technology inhibits the farmers to perceive the precise value of commodities and to incorporate expensive modern farming techniques.
  3. The intermediaries with their exploitative measures manipulate farmers to offset their greedy means.
• The loss incurred in the value chain
  1. The ambiguous grading at the source disrupts the flow of better quality food and affects its subsequent pricing.
  2. Artificial intelligence is used on a platform to produce more accurate and repeatable outcomes faster than a trained human analyst and to store data accessible from every position on a cloud server.
  3. The technology makes it easy for institutional buyers to purchase commodities at fair prices lined to quality
  4. The assessed quality can be securely kept at our platform to enable the digitization of commodity quality across the supply chain.
  5. All our efforts in technology development are focused to help the brands to cater to the quality output to their customers

1. We endeavor to plug the gap and offer a radical new alternative to food grain quality testing.
2. We have devised a user-friendly smartphone-based solution that will analyze maize quality at the farm level in a cost-effective and time-saving way.
3. Using the combination of portable device sensors and the phone camera, its smart AI and IOT utilize machine learning and deep learning.
4. It provides more reliable results, exact value, pricing, and suitable industry based on its quality faster than a skilled human analyst or other devices available in the market.

1. Improved information and communication technology in our AI-based computer vision method accelerates agricultural productivity and promotes high-quality and high-yield agriculture products.
2. Our smartphone-based approach is the simplest and precise to revolutionize food grain main machine research worldwide.
3. The AI-based image analytics technology is easily understandable and gets the following outputs on the phone screen.
4. AI-based technology measures the quality of commodities with fast speed, ease of use, and minimal sample preparation.
5. The data of the quality report is saved in the evaluation. cloud server to monitor quality.

1. The portable device with AI precision backed up by computer vision and deep learning has two attached sensors for moisture detector & weight measuring tool and one detachable smartphone camera sensor, synced with the smartphone through Bluetooth.
2. The weighing tool measures the weight of the maize kernels to link the outcome with its morphological properties extracted using AI-based smartphone cameras.
3. The quality analysis process follows a segmentation stage based on an algorithm, an AI 3D rendering of each grain to build a mathematical model that shows 99.9% accurate prediction of kernels with fungus defects, fungal damage, organic impurity, tearing, etc.
4. The deep learning method scans and evaluates the parameters of the maize samples in a completely automated method without perspective distortions for forgery-less evaluation.