Revolutionizing crop disease management through Artificial Neural Networks, IoT sensors, and cloud-based services to empower farmers across Asia with smart agricultural solutions
Explore Our Technology
Our project revolutionizes crop disease management by introducing a smart agricultural diagnostic system across five Asian countries. We leverage Artificial Neural Networks (ANN), advanced image processing, IoT sensor networks, and cloud-based services to detect, classify, and manage plant diseases in major crops.
The system supports rice, jute, wheat, maize, and soybean crops with user-friendly software, mobile apps, and collaborative research platforms, ensuring scalability and sustainability across diverse agricultural ecosystems.
To develop an AI and IoT-based automated system for plant disease detection, classification, and management that supports sustainable agriculture and empowers farmers with cutting-edge technology solutions.
Advanced ANN models for accurate disease detection and classification
Wavelet filtering and RGB-HSV segmentation for precise analysis
Real-time monitoring of soil temperature, pH, and moisture levels
BdREN cloud integration for data storage and analysis
User-friendly mobile app for field-based disease diagnosis
Digital PCR and microscopy for pathogen validation
Comprehensive software solution with ANN models for disease detection in five target crops with offline and online capabilities.
IoT sensor networks providing continuous environmental data to track pathogen conditions and plant stress indicators.
Multilingual web platform connecting farmers and experts across five countries for knowledge sharing and collaboration.
ANN-based predictive models integrated into cloud platforms for proactive disease management and prevention.
Comprehensive workshops and training sessions for farmers and researchers on AI-based disease management.
Advanced data collection through surveys, FGDs, and field observations with over 500 farmers across 20 districts.
Patuakhali Science and Technology University, Bangladesh
Bangladesh Research and Education Network
Kyungpook National University, South Korea
University of Dhaka, Bangladesh
Jessore University of Science and Technology
Bangladesh Agricultural Research Council
Improving crop yields and food security through early disease detection and management systems.
Building resilient agricultural infrastructure through AI and IoT technology innovations.
Supporting climate-smart agriculture through technology-enabled adaptive farming practices.
Fostering international collaboration and knowledge sharing across Asia@Connect member countries.