Mobile App Development / SELECTED WORK
CropDoc – AI Crop Disease Detection App
CropDoc is an AI-powered agricultural mobile application that helps farmers identify crop diseases through image analysis, monitor crop health, manage detection records, and purchase agricultural products through an integrated shopping platform.
THE PROJECT
Built with purpose.
CropDoc is an AI-powered agricultural application designed to help farmers identify crop diseases from images and manage essential crop health information through a connected digital platform.
Developed as a collaborative project, CropDoc combines a Flutter mobile application, Firebase integration, Python-based disease detection functionality, and a responsive web admin dashboard built with Bootstrap and JavaScript.
The mobile application includes user registration and login, crop image uploads, AI-powered disease prediction, detection results, saved crop health records, notifications, community discussions, and an agricultural product shop with shopping cart and checkout functionality.
Farmers can upload crop images for analysis, review prediction results, access relevant crop information, and maintain a history of previous detections. The integrated shopping experience allows users to explore agricultural products, view product details, manage cart quantities, and proceed through checkout.
The administrative dashboard supports farmer profile management, product listings, inventory, delivery tracking, notifications, and community moderation, providing centralized control over the platform's operations.
A key development challenge was connecting image analysis, mobile application data, and administrative workflows into a consistent user experience. The team addressed this through modular development, image validation, improved error handling, and manual testing across mobile devices and web browsers.
The resulting solution brings together mobile development, artificial intelligence, real-time data management, agricultural e-commerce, and web administration in one integrated platform.
Developed as a collaborative project, CropDoc combines a Flutter mobile application, Firebase integration, Python-based disease detection functionality, and a responsive web admin dashboard built with Bootstrap and JavaScript.
The mobile application includes user registration and login, crop image uploads, AI-powered disease prediction, detection results, saved crop health records, notifications, community discussions, and an agricultural product shop with shopping cart and checkout functionality.
Farmers can upload crop images for analysis, review prediction results, access relevant crop information, and maintain a history of previous detections. The integrated shopping experience allows users to explore agricultural products, view product details, manage cart quantities, and proceed through checkout.
The administrative dashboard supports farmer profile management, product listings, inventory, delivery tracking, notifications, and community moderation, providing centralized control over the platform's operations.
A key development challenge was connecting image analysis, mobile application data, and administrative workflows into a consistent user experience. The team addressed this through modular development, image validation, improved error handling, and manual testing across mobile devices and web browsers.
The resulting solution brings together mobile development, artificial intelligence, real-time data management, agricultural e-commerce, and web administration in one integrated platform.