Industrial Research And Consultancy Centre
MandiGo: A real-time GIS-based comprehensive market decision support system for farmers, consumers, and other stakeholders like wholesalers and retailers.

Host Institution: Indian Institute of Technology Bombay 

Funding Support: Technology Innovation Hub (TIH) for IoT & IoE (Grant TIH-IoT-2025) 

IRCC Project Code: RD/0125-TIHIR18-007 

#Prof. Parmeshwar Udmale (PI), C-TARA IIT Bombay 

#Mr. Dev Singal, 3rd Year UG Student, IIT Bombay 

#Mr. Abhay Kinagi, 2025 UG Graduate, IIT Bombay 

#Ms. Monika Shah, Sr. Project Software Engineer, IIT Bombay 

#Mr. Pranjal Animesh, App Developer, 2025 UG Graduate, IIT Bombay 

MandiGo: A real-time GIS-based comprehensive market decision support system for farmers, consumers, and other stakeholders like wholesalers and retailers. 

In the conventional agricultural market ecosystem, it has been seen that a significant disparity is there between the price at which farmers sell their agricultural produce and the price consumers pay at the end of the market supply chain. The main reason for the difference in selling and buying prices are due to the lack of real-time, location-specific price transparency. The majority of commodities are sold in wholesale market (APMCs) where the farmers can’t decide prices for their commodities. At Mandi’s/Markets farmers feel helpless and compulsion to sell at a price less than production cost, whereas consumers face the high price volatility, and most of the profit is taken by the intermediaries. By crowdsourcing data directly from all stakeholders in the supply chain, including AgMarkNet, and providing platform in the form of the tool provides market-level insights into commodity prices. In present platform, the commodity grading and arrivals/prices forecasting is being researched and we aim to integrate it in near future. 

The MandiGo Platform has potential to create social outcomes / impacts as mentioned under: 

  • Price discovery and transparency can reduce exploitation in the form of unfair market practices and empower farmers by improving their bargaining power. 
  • Farmers make informed choices on when and where to sell by using the real-time information (it will enable farmers to plan their sales to maximise profit and reduce losses). 
  • Consumers can have access to transparent pricing to buy fresh produce at reasonable rates at farm gate in nearby areas. 
  • Provide opportunities in the form of Farmers Digital Thela (first of its kind with geospatial capabilities), where farmers can sell products at the farm gate/specified georeferenced location, which is expected to open a window (a few days to weeks) for farmers to put their produce for sale before taking it to market. This is expected to reduce the hardships of taking produce to markets and of dealing with the compulsion to sell or the helplessness of farmers at the Mandi or Markets. 

  • The platform can strengthen the local economy in rural areas by providing entrepreneurship/business opportunities in the agricultural supply chain equipped with geospatial capabilities to optimize the supply chains. 

    The system is built on a scalable and research-oriented architecture: 

    Technical Architecture: 

  • Backend: Django & Django REST Framework (secure REST APIs) 
  • Database: PostgreSQL with geospatial capability 
  • Frontend: Responsive web interface (mobile-first) 
  • Deployment: Cloud-ready 

  • Security: Role-based access control with token authentication 

    Core Functionalities: 

  • Role-Based Trade Listing: Users register as farmers (sellers) or buyers or retailers. 
  • Geo-Tagged Crop Listings: Each listing includes quantity, price, and geographic coordinates. 
  • Geospatial Market Visualization: Map-based view.