Flagship research · Agriculture
SPADE-AI
Smartphone-based soil analysis and crop-planning intelligence
- Agricultural AI
- Computer Vision
- Soil Science
SPADE-AI is an AI-driven agricultural initiative that uses smartphone images and environmental data to estimate soil properties and provide crop suitability and rotation recommendations through a Bengali-language mobile application. It aims to make precision agriculture more accessible while promoting sustainable farming, better soil management, and improved productivity.
How it works
- Step 1
Field capture
Farmers photograph soil samples with an ordinary smartphone in the field.
- Step 2
Spectral reconstruction
Deep-learning models estimate hyperspectral signatures and key soil properties.
- Step 3
Agro guidance
Fused climate and geospatial data deliver crop suitability and rotation advice.
Overview
SPADE-AI is an AI-driven initiative focused on using smartphone images and intelligent data analysis to support soil assessment and agricultural decision-making. It combines deep learning, spectral information, and relevant environmental and geospatial data to estimate soil characteristics and provide location-specific insights for crop suitability and rotation planning. The system is designed to make soil assessment and agricultural guidance more accessible through a Bengali-language mobile application, allowing farmers to obtain useful recommendations without relying entirely on costly and specialized testing. By supporting data-driven soil management and informed crop planning, SPADE-AI aims to contribute to sustainable agriculture, improved crop productivity, and better resource management in Bangladesh.
Team
Collaborators: University of Dhaka, Jessore University of Science and Technology
Publications and datasets
Research papers, models, and open datasets will be shared here as they are released.
Project updates
Milestones, fieldwork notes, and lab announcements will appear on our notices page.
View notices →