Farmers are unable to find workers to perform tasks in farms, there is a very high labor shortage of more than 5 Million people required, labor cost is also very high. Another problem in farms is food waste and crop losses, representing 30% of losses for the farmers, harvesting food in a farm currently involves damaged produce, low hygiene, higher and significant risk of accidents in the farms.

 To solve all of these problems our team has developed a solution based in Artificial Intelligence and Robotics.

The MiFood Robot automates harvesting and collecting food in farms. The robot collects and stores food items including fruit and vegetables in farms faster and maximizes crops produced and enhances sustainability increasing efficiency and reducing co2 emission on harvesting.

The result is quicker harvesting time, food waste reduction, labor shortage reduction, more efficient collecting, lower labor costs, and reduced risk of accidents.

MiFood builds robot workers for farms to reduce food waste, crop losses by 30%, labour shortages, labour cost by 50%, co2 emissions and workplace accidents in every farm. 

The MiFood EOSC DIH pilot will investigate and test usage and possible integration of the MiFood robot and corresponding services and the selected EOSC services including the cloud, computational resources and the AI/ML services.

Challenge

• MiFood is analysing different solutions for improvement and further development of robotic solutions. With the new possible appliances new AI models are required, as well as integration with the Cloud services compared to the current solution. 

Work Plan

• TASK 1: Analysis with the EOSC services related with the AI/ML training (AI4EOSC related)
• TASK 2: Setup of the environment for the pilot
• TASK 3: Deploying the services on the Cloud infrastructure
• TASK  4:Feasibility study of using the AI4EOSC related services