S.A.I

this is a picture of the entire project assembled

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.