Client Requirement:

As part of their initiative to provide a budgeted food program for the general public, our client, one of India’s State Government bodies, wished to improve their food distribution management processes. They wanted to analyze food consumption patterns, and the amount of raw material that was required for distribution. They needed to monitor and analyze Food Carts in mobile vans, in order to get real-time updates on food consumption status and any pilfering of food items.

Solution Overview:

In order to achieve real-time streaming of data from various locations, we implemented a robust and scalable Big Data Enterprise Platform for capturing video streams, and to monitor and process all the activities involved.

Dashboards in the application provided deeper insights on all food consumption parameters such as geo-location of the van, various food counters in operation, count of plates, raw materials of food being cooked, and the opening and closing stock of food bins. We also developed predictive models and business logic to determine any anomalies in the operations.

By means of an Edge device, the real-time status of food stock monitoring became accessible. The bins in the mobile vans were fitted with Edge Devices to manage the food consumption status such as weight check, food disbursement, stock levels, cooking reports etc.

Other operational information such as the health of the vans system, UPS, Camera, active time and bins temperature were also remotely managed and controlled. An active camera provided real-time view of day-to-day operations.

Thus, huge volumes of data could now be processed and analyzed, at scale. The data and its backup is pushed to the Cloud for analytics and for alerting. With live dashboards and historical reports, actionable insights on food consumption and distribution became accessible.


  • Improved cost and efficiency in food distribution process
  • Early notifications for cooking units to procure raw materials required for cooking
  • Reduction of Food wastage using real-time consumption forecast
  • Prevention of pilferage or theft of  food stocks
  • Facilitated petabyte-level data to be stored, scaled and processed
  • Better forecast and demand management

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