S.A.I

## Inspiration India faces a critical challenge of over-irrigation due to heavy and unpredictable rainfall, leading to water wastage and reduced crop productivity. This inspired us to create S.A.I, a system that ensures optimal water usage in agriculture. ## What it does S.A.I (Smart Agricultural Irrigation) uses soil moisture sensors, a Raspberry Pi 5, and a weather API to monitor soil conditions and forecast rainfall. If rain is expected in the next 3 days, the system prevents irrigation. If not, it irrigates accordingly. ## How we built it Sensors: Deployed 8 soil moisture sensors to monitor ground conditions. Hardware: Used Raspberry Pi 5 as the central processing unit. Software: Integrated a weather API to predict rainfall and automated the irrigation logic. Coding: Developed scripts to process sensor data and interact with the weather API. ## Challenges we ran into Calibrating soil moisture sensors for accurate readings. Ensuring reliable communication between the sensors and Raspberry Pi. Synchronizing irrigation decisions with weather API predictions. ## Accomplishments that we're proud of won 1st place for this idea at the national robotics and automation championship Successfully developed a system that reduces over-irrigation. Achieved seamless integration of hardware and software components. Created a scalable solution that can be adapted to various farm sizes. ## What we learned The importance of precision in sensor calibration. How to effectively integrate IoT systems with real-time APIs. Problem-solving under constraints, such as hardware limitations. ## What's next for S.A.I Adding machine learning to predict rainfall patterns more accurately. Expanding the system to include multi-crop irrigation strategies. Exploring solar power integration for sustainable operation.