Analytics based on historical data helps improve the efficiency
Tracking ensures the goods are delivered on time and quickly act on customer complaints
Time taken to grade the goods is reduced by manifolds and ensures only quality goods are delivered
The client is a leading horticulturalists in India with many orchards across the country producing fruits/vegetables based on the territorial climatic conditions. They are so keen to take agriculture to the next level adapting to innovative technologies for grading and tracing fruits/ vegetables.
The client was grading the fruits/ vegetables manually due to which there was an increase in manpower and more time was taken for grading. So there was a possibility of human error while grading and delay in goods delivery to the respective retail outlets. And there was no system for traceability when there was negative feedback from the customer. Ultimately this led to an impact on their business growth.
Hubino designed a smart grading system to identify grading and a portal for tracing the produced goods. According to territorial compliances, grading parameters (eg. freshness, damage, size, and color) are defined in the system using images. Deep learning is the key to train the system with more images. An increase in the number of images increases the efficiency of the system. Based on the patterns fed into the system, the computer vision algorithms are intelligent
enough to grade them accordingly. The portal helps in complete traceability of the produced goods covering harvest, shipping, packaging, distributing, and retailing. It provides complete analytics and reports. Customer feedback can be recorded.
Time taken by the employees to grade the goods is reduced by manifolds making it time-efficient. This also ensures only quality goods are shipped or distributed to customers gaining customer satisfaction. Portal for tracking ensures the goods are received on time. This helps to quickly look into customer complaints and give a solution for the same. Detailed analytics based on historical data helps improve the efficiency.