GIS-Mapped Drone System for Predictive Crop Yield Estimation
Review the patent details and filing route before deciding whether to book your position or raise an enquiry.
Current slot price
₹9,999
Range: ₹3,299 – ₹9,999
Patent type
Design Patent
Filing route
India
Abstract preview
Click an image to open zoom preview
What happens next
Choose whether you want to book directly or begin with an enquiry.
If you book, upload the payment proof inside the request flow.
The admin reviews the request and confirms the slot after verification.
You receive a confirmation email once your slot is approved.
Slot-based pricing
Choose the slot you want to book. Your selected slot price is reflected in the right panel.
| Slot | Price | Status | Action |
|---|---|---|---|
| Slot 1 | ₹9,999 | Selected | |
| Slot 2 | ₹6,999 | Registered | Unavailable |
| Slot 3 | ₹5,999 | Registered | Unavailable |
| Slot 4 | ₹4,999 | Registered | Unavailable |
| Slot 5 | ₹4,499 | Registered | Unavailable |
| Slot 6 | ₹3,999 | Registered | Unavailable |
| Slot 7 | ₹3,799 | Registered | Unavailable |
| Slot 8 | ₹3,499 | Registered | Unavailable |
| Slot 9 | ₹3,299 | Open |
Patent details
A GIS-Mapped Drone System for Predictive Crop Yield Estimation is disclosed, comprising an unmanned aerial vehicle (UAV) integrated with RGB, multispectral, thermal, and geolocation sensors for collecting geo-referenced crop data from agricultural fields. The system acquires high-resolution aerial imagery and environmental parameters, which are processed through a Geographic Information System (GIS) platform to generate spatially referenced crop health maps. An artificial intelligence-based analytics engine evaluates vegetation indices, canopy characteristics, soil conditions, weather information, irrigation patterns, and historical crop performance data to predict crop yield at field and sub-field levels. The system identifies crop stress, nutrient deficiencies, pest infestations, disease-prone zones, and water management issues, and provides actionable recommendations to improve agricultural productivity. By combining drone-based remote sensing, GIS mapping, and machine learning-driven predictive analytics, the invention enables accurate, real-time, and scalable crop yield estimation while supporting precision farming, resource optimization, and data-driven agricultural decision-making. The system is applicable to farms, agribusinesses, agricultural research institutions, and government agencies involved in crop monitoring and food production planning.