Smart Agriculture IoT System Involving Sensor-Based Monitoring and Image Processing

Описание: Modern agriculture faces critical challenges such as resource overuse, unpredictable climate patterns, and declining soil health, leading to reduced productivity and sustainability. Farmers often lack access to real-time data for informed decision-making, resulting in inefficient irrigation, fertilizer wastage, and delayed harvesting. This gap is especially significant in rural and small-scale farming contexts. Our solution addresses these issues by providing a cost-effective, sensor-based smart farming system that enables precision agriculture through automation, real-time monitoring, and data-driven insights. It empowers farmers to optimize resource usage, improve yields, and adapt to changing environmental conditions, aligning with global goals for sustainable agriculture.


Developed an advanced smart agriculture system using Espressif Systems microcontrollers and Raspberry Pi for centralized data handling. Integrated multiple sensors(pH, NPK, TDS, moisture, LDR, DHT22, ultrasonic, OCR, TCS3200) and actuators (MOSFET-controlled pumps, LCD). Sensor data is transmitted via MQTT to a cloud-connected FastAPI backend with a real-time dashboard. Implemented machine learning models for fruit ripeness prediction using image processing, enabling automated harvesting decisions. The system automates irrigation and fertilization based on real-time soil and environmental data. Continuous deployment is handled via GitHub Actions. Designed to scale with further ML applications for crop disease detection, yield prediction, and precision farming analytics.

Our smart agriculture system uniquely combines multi-sensor data collection, real-time automation, and AI-driven decision-making in a low-cost, scalable design. It integrates soil, environmental, and nutrient sensors with Espressif microcontrollers and a Raspberry Pi hub to provide accurate, real-time insights. Distinctively, it features image-based fruit ripeness detection using machine learning, automated irrigation/fertilizer logic using MOSFETs, and a cloud dashboard for remote access. Unlike typical systems, ours supports modular sensor expansion and edge-processing capabilities. The seamless blend of hardware, cloud integration, and intelligent software makes it adaptable for small-scale and large farms, offering a future-ready, sustainable precision farming solution.


Our smart agriculture solution stands apart from competitors by combining a comprehensive suite of sensors—including NPK, pH, moisture, TDS, and light sensors—with real-time data collection via Espressif Systems microcontrollers and a Raspberry Pi gateway. Unlike generic sensor platforms, our system integrates image processing and machine learning to predict fruit ripeness, enabling data-driven harvesting decisions. Automated irrigation and fertilizer control are precisely tailored to soil conditions. The backend, built on FastAPI and deployed with CI/CD, ensures high performance and scalability. This level of integration, automation, and intelligent prediction is rarely found in comparable solutions, making ours uniquely impactful for precision farming.