Inspiration

Agriculture faces several challenges, including inefficient irrigation, delayed crop disease detection, unpredictable weather conditions, and excessive use of water and fertilizers. Farmers often rely on manual monitoring, which can lead to reduced productivity and increased operational costs. We wanted to build an AI-powered solution that helps farmers make faster and smarter decisions using real-time data.

What it does

Agro AI is an AI-powered smart agriculture platform developed under KhetHub. It combines IoT sensors, computer vision, and predictive analytics to monitor soil moisture, temperature, humidity, crop health, and environmental conditions in real time.

The platform automatically recommends irrigation schedules, detects crop diseases, provides weather-based insights, and helps farmers optimize water usage and improve crop productivity through intelligent decision support.

How we built it

We built Agro AI using Python, Node.js, React.js, MongoDB, and AI/ML technologies. The hardware prototype integrates Raspberry Pi with IoT sensors such as soil moisture, temperature, humidity, and light sensors to collect real-time farm data.

The collected data is processed through AI models and displayed on an interactive dashboard that enables smart monitoring and automated decision-making.

Challenges we ran into

One of the biggest challenges was integrating multiple hardware sensors with the software platform while ensuring accurate real-time data collection. We also worked on improving AI prediction accuracy and creating a user-friendly dashboard suitable for farmers with different technical backgrounds.

Accomplishments that we're proud of

• Successfully developed a working IoT-based smart farming prototype.

• Built a real-time monitoring dashboard.

• Integrated AI-driven decision support for irrigation and crop monitoring.

• Designed a scalable platform that can support future smart agriculture applications.

What we learned

Through this project, we gained practical experience in Artificial Intelligence, IoT integration, embedded systems, full-stack development, cloud technologies, and teamwork. We also learned how AI can solve real-world agricultural problems and improve farming efficiency.

What's next

Our next goal is to transform Agro AI into a complete smart agriculture ecosystem under KhetHub by integrating drone-based crop monitoring, satellite imagery, advanced crop disease detection, weather forecasting, AI Agents, and precision farming technologies. We also plan to launch mobile applications and deploy the platform for real-world farmers.

Built With

• css
• dht11
• express.js
• git
• html
• iot
• javascript
• mongodb
• node.js
• opencv
• python
• raspberry-pi
• react.js
• relay-module
• soil-moisture-sensor
• tensorflow