Student Team
Prisha Sahai
IAMS Team · Grade 9 · Kanpur
Pritisha Srivastava
IAMS Team · Grade 9 · Lucknow
The Intelligent Agricultural Management System is an AI-powered sensor platform that senses, predicts, diagnoses, and recommends farm actions for rural farmers using smartphones, live sensor data, image diagnosis, and local-language guidance.
Agriculture consumes large water reserves without enough precision control or forecasting.
Pests, disease, and climate stress destroy crops when there is no early-warning system.
Groundwater depletion and borewell abandonment are accelerating across agricultural states.
Small and marginal farmers often lack data-driven guidance for farm decisions.
IAMS combines real-time sensor integration, AI recommendations, image diagnosis, and a mobile-first interface built for farmers rather than data scientists.
Collect soil, water, weather, crop, and imaging data.
Normalize, fuse, and detect trends in farm data.
Use multimodal AI reasoning for farm context and images.
Generate crop, irrigation, fertilizer, and protection plans.
Deliver clear advice in the farmer's language.
Soil pH, groundwater level, and crop health sync from connected IoT sensors.
A 0-100 score tracks long-term farm health across water, soil, and yield.
One tap pulls live field data from connected sensor hardware.
At-a-glance alerts for drought, flood, pest, disease, and heatwave risk.
Recommends the best crop and multi-season plan, such as rice to pulses to wheat.
Suggests precise timing, such as watering before sunrise for specific cycles each week.
Provides disease treatment, pest control, and NPK or organic fertilizer dosing.
The RAI assistant uses voice input, text-to-speech output, crop images, live sensor context, and session memory to give farm-specific answers instead of generic advice.
Farmers can speak and listen in supported Indian languages.
Camera images are analyzed for disease, pests, deficiency, and treatment steps.
The assistant knows live farm data such as soil pH and crop health.
Conversation history is remembered across the session for continuity.
pH levels, moisture, NPK nutrient profile, and fertility level.
Borewell level, depletion rate, and distribution uniformity.
Temperature, humidity, rainfall forecast, drought/flood risk, and heatwave alerts.
Health percentage, growth stage, and previous crop history.
Smartphone camera, gallery upload, drone imagery, and field cameras.
IAMS is designed to improve yield, reduce water use, prevent diagnosable crop loss, and deliver personalized advice in the farmer's own language.
Precision irrigation and crop selection can improve crop output.
Sensor-informed irrigation can reduce water usage.
Early image-based detection can prevent diagnosable crop loss.
Stable farming supports citizens whose food security depends on agricultural output.
Dashboard, recommendations, RAI assistant, and 11-language support.
Drone imagery integration and satellite data APIs for aerial crop analysis.
Government API integration and state-level rollout across pilot districts.
National IoT sensor mesh across farm clusters.