AI Powered Precision Agriculture Software for Government and Farmers

The web portal provides the department with a centralized operational view of farmers, farms, fields, devices, stations, sensor conditions, forecasts, crop guidance, events, alerts, drone imagery and reports. Role-based administration supports employee and data management.

Farmer records are imported from the government API, with Excel available as a fallback. Each farmer can be connected with farm and field details such as location and size. IoT devices are registered, installed at a station and assigned to the appropriate field so analytics and alerts retain their operating context.

The sensor analytics dashboard brings station readings together for government monitoring. The farmer application shows readings from the nearest relevant station, including soil temperature, pH, moisture, salinity and electrical conductivity. Selected sensor information is stored for offline access.

Predictive and forecast views help department users assess how conditions may develop rather than relying only on current readings. This is decision support, not a validated forecast-accuracy guarantee.

When a measured value falls outside the range required by the crop in that field, the system raises an alert and generates a preventive suggestion. A department expert selects the appropriate action, adds context and approves the advisory before it is sent. Notifications can be scoped by district, block, GPU and ward.

Department officers can record a crop-specific farming method with explanatory text and photographs. Once published, farmers can read the same approved process in the mobile application while working in the field.

The department can maintain crop diseases, visible symptoms, identifying images and preventive methods. Farmers can compare the approved information with field conditions and follow the protection guidance published by the department. This is a curated knowledge workflow, not automated image diagnosis.

Officers can publish an event with its venue, schedule and highlights, then notify selected farmers or a geographic group. Farmers can review nearby opportunities and decide which events to attend.

The drone workflow covers field setup, regions of interest, flight path and altitude, image capture, processing, NDVI computation, data consolidation and map projection. The resulting layer separates healthy, moderately healthy and stressed vegetation so officers can identify where field investigation should begin.

The mobile experience brings sensor conditions, crop practices, protection guidance, events, notifications and early warnings to farmers. Its offline sensor-data capability is particularly important for field use in locations with weak connectivity.

Employee management, farmer and farm records, device and installation-station management, analytical dashboards and reports give the department a structured record for monitoring and program planning.

DreamzTech supported four station installations, delivered two multispectral drones, provided field training and participated in department review meetings. Following business-user testing, the platform was uploaded and configured in the government environment in March 2026.