S.A.I

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  this is the whole 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

• 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.
  

Built With

• ai
• api
• ml
• openweather
• raspberry-pi
• soil