Inspiration
Agriculture is the backbone of many economies, yet millions of farmers still rely on guesswork for irrigation, crop health monitoring, and disease management. Climate change, water scarcity, and unpredictable weather make farming even more challenging. We wanted to build an affordable, AI-powered solution that helps farmers make informed decisions using real-time data. This inspired us to create AgriTwin AI, a digital twin platform that brings precision agriculture within reach of every farmer.
What it does
AgriTwin AI creates a virtual digital twin of a farm by combining IoT sensor data, weather information, AI, and cloud technologies. The platform monitors soil moisture, temperature, humidity, and environmental conditions in real time. It provides smart irrigation recommendations, predicts crop yield, detects crop diseases from leaf images, sends weather-based alerts, and offers an AI assistant to answer farming-related questions. The interactive dashboard enables farmers to monitor and manage their farms from anywhere.
How we built it
We built the frontend using Next.js, React, and Tailwind CSS with an intuitive dashboard created using Vercel v0. The backend was developed with Node.js and integrated with AWS Aurora PostgreSQL and Amazon DynamoDB for storing user and sensor data. AWS Lambda and API Gateway handle backend services, while Amazon S3 stores uploaded images. The AI features use the Vercel AI SDK and an LLM for intelligent recommendations. IoT sensor data is simulated to demonstrate real-time monitoring and future hardware integration.
Challenges we ran into
One of the biggest challenges was integrating AI, cloud services, and simulated IoT data into a single, seamless platform within the hackathon timeline. Designing a user-friendly dashboard while ensuring scalability and real-time performance also required careful planning. Balancing innovation with practical usability was another key challenge.
Accomplishments that we're proud of
We successfully developed a working prototype that combines AI, IoT, cloud computing, and data visualization into one platform. We created a digital twin dashboard capable of monitoring farm conditions, providing intelligent recommendations, and demonstrating how precision agriculture can improve productivity and sustainability. We are especially proud of building a solution with real-world impact and the potential to scale globally.
What we learned
This project strengthened our understanding of cloud-native application development, AI integration, modern full-stack technologies, and scalable database design. We also gained valuable experience in teamwork, rapid prototyping, problem-solving, and designing technology that addresses real-world challenges.
What's next for AgriTwin AI
Our future roadmap includes integrating real IoT hardware such as ESP32-based sensors, adding satellite and drone imagery for advanced crop monitoring, supporting multiple regional languages with voice assistance, improving disease detection accuracy using computer vision, and expanding the platform with predictive analytics, carbon footprint tracking, and agricultural marketplace integrations. Our long-term vision is to make AgriTwin AI a globally accessible smart farming platform that empowers farmers through data-driven decision-making.
Built With
- ai
- amazon
- amazon-web-services
- api
- aurora
- chart.js
- css
- dynamodb
- esp32
- gateway
- iot
- lambda
- next.js
- node.js
- openai
- postgresql
- react
- s3
- sdk
- tailwind
- typescript
- v0
- vercel