Page 213 - AI for Good-Innovate for Impact Final Report 2024

AI for Good-Innovate for Impact

Use case – 50: Using Satellite Imagery and AI for Crop Monitoring

Services 50-AIPARAGRO

Country: Zimbabwe

Organization: abm^parassa IT/Digital Consulting

Contact person: Abel Mautsa abelmautsa@ gmail .com, +263713852018

Benhilda Mubaiwa benhildamubaiwa@ gmail .com ,+ 263773731535

50�1� Use case Summary Table

Domain Agriculture
The problem to be Crop monitoring using satellite image, complemented with drone
addressed images. Small scale farmers, and medium to large scale farmers
Production is labour intensive. Time investment, human error, timely
detection of crop related issues.
Key aspects of the Using Satellite, UAV and scouts imagery to monitor crop for irrigation,
solution plant nutrition, pest/weeds mangement and yield prediction.
Farmer connectivity is via mobile data via 3G, 4G, or VSAT links or fiber.
But image transmission is via telone.

Technology Satellite, UAV and Scouts imagery, Field boundary detection, NDRE,
keywords MSAVI, NDWI, NDMI, NDVI, Neural Network model.

Data availability Not available.
Current solution is based on the eos Data Analytics [1] (eos data analyt-
ics - satellite data analytics provider based in Ukraine) and telone
partnership.
Need to acquire satellite images, and drones images from farmers.
Metadata (type of Images (satellite or from drones)
data) Sensor data.

Model Training and The current commercial solution with eosda and telone uses different
fine-tuning type of models.

Testbeds or pilot • https:// eos .com/ blog/ eosda -enters -into -a -strategic -partnership
deployments -with -telone/
• https:// eos .com/ products/ high -resolution -images/
• https:// eos .com/ products/ crop -monitoring/

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