Abstract:
The Image-Based Plant Disease Diagnosis Application was a project commissioned by the Marriam Rural Welfare Organization (MRWO) to deal with the shortage of agricultural expertise in the Bahawalpur and Lodhran. The project uses Artificial Intelligence to enable farmers to identify Cotton and Wheat diseases instantly and, thus, directly mitigate losses of crops and reliance on broad-spectrum pesticides.
The sprints were conducted during the period of 1 to 29 December, 2025, via Jira. The scrum team operated at a steady velocity of 40 Story Points per sprint, and 50 Points in bug-intensive sprints. It was this adaptability in planning that helped the team to achieve tight deadlines and deal with complicated delivery problems. The solution is based on industry standards of mobile and cloud technology and is optimized to operate in remote and low-connectivity environments.
The project was able to provide a very accurate (>92%) diagnostic mobile application and Disease Trends Dashboard to the MRWO leadership. The four Sprints were completed within the planned timeframe. Major technical risks such as hardware limitations and latency of the system were addressed in advance, without affecting the schedule. On the financial side, the project was closed within the PKR 1,347,500 budget. This endeavor demonstrated the value of agile methodologies in social projects.
