Digital Crop Monitoring in Punjab
A 250,000-acre agribusiness revolutionized wheat yields using AI analytics and satellite data
Overview
By combining precision farming with predictive analytics, this project reduced water usage by 42% while increasing wheat yields by 37% across all managed land.
Project Scope
250,000 acres monitored across 3 agribusiness zones
Duration
4 growing seasons (2021-2024)
Technology
AI analytics + satellite imaging + IoT soil sensors
Challenges
This project addressed three major issues: inconsistent water availability due to erratic rainfall, fertilizer overuse causing soil degradation, and real-time monitoring limitations across vast farmland.
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Water Management
Traditional irrigation systems used 15-20% more water than necessary
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Soil Health
34% of monitored land showed signs of nutrient depletion
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Monitoring Gaps
72% of crop issues were detected too late for intervention
Solutions
1. Smart Irrigation Network
Installed 3,200 low-cost soil moisture sensors integrated with weather forecasts for predictive watering
2. AI Nutrient Planner
Machine learning algorithm optimized fertilizer use by analyzing soil samples and crop needs
3. Satellite Monitoring
Daily satellite imaging detected crop stress areas early, reducing yield loss by 28%
Key Results
37%
Increase in crop yield
42%
Water savings
68%
Reduction in fertilizer excess