While the case studies are actual, the names and locations have been changed to protect the identity of the clients.
Background
Green farms is a hydroponic farm in Delhi. They specialize in growing a wide variety of exotic and leafy greens. They supply their produce directly to end-consumers following a weekly subscription model.
Green farms grow 17 different crops on their farm to offer a wide range to their consumers. However, managing the crop cycle of multiple crops often leads to misses and planning failures. Per their estimate, they could not use more than 76% of farm capacity at any point in time due to the inefficiencies in planning.
Problem Statement
How to increase farm utilization rate through efficient planning?
1. Different crops took a different amount of time to grow from seed to harvest-ready state.
2. Some crops were of single-cut variety, whilst some were multi-cut.
3. There was an up to (+/-)10% fluctuation in the demand cycle on a weekly basis.
Solution Approach
We implemented an Artificial Intelligence-based system to manage crop cycle & operational planning.
The following were the key features:
- A consolidated view of the crop status on the farm at any point in time.
- Ability to add different agronomist(s) and farm help(s) to the platform.
- System-generated crop plan based on customer demand pattern.
- Automatic generation of daily tasks based on crop plan.
- AI-based auto-correction and auto-updation of tasks based on ground learnings.
- An ability for farm help(s) to flag issues and report them to agronomist(s) in real time.
- GPS-based time/attendance/visit log of agronomist(s) and farm help(s).
- Remote monitoring and management capabilities for the farm owner.