IoT Based Greenhouse Monitoring and Controlling System Integrated with AI

Summary

The presentation discusses an IoT-based greenhouse monitoring and control system integrated with AI, aimed at enhancing agricultural practices in Pakistan. Key features include sensors for temperature, humidity, and moisture, alongside automated actuators for irrigation and cooling. The project addresses significant challenges in traditional farming, such as environmental control and disease management. The team developed a mobile application for remote monitoring and incorporated AI for plant health classification. The results indicate successful environmental management, though limitations include dependence on internet connectivity and the specific training of AI models. Future work aims to expand capabilities and improve functionality.

Takeaways

• 🌱 The project focuses on an IoT-based greenhouse monitoring and controlling system integrated with AI.
• 📊 Key sensors used include temperature, humidity, and moisture sensors for environmental monitoring.
• 💡 Actuators like exhaust fans and solenoid valves automate cooling and irrigation processes.
• 📱 The 'Gardner Arrow' app enables remote monitoring and control of greenhouse conditions.
• 🧪 The AI component includes a health classification model that identifies healthy vs. unhealthy plants.
• 🌍 This project aims to improve agricultural practices in Pakistan by utilizing modern technology.
• 📚 A literature review highlighted existing research on greenhouse monitoring but noted gaps in control mechanisms.
• 🛠️ The hardware setup includes an ESP32 microcontroller, cameras for visual monitoring, and a relay module.
• 📈 Results show effective control of greenhouse conditions, maintaining optimal temperature and moisture levels.
• 🚧 Limitations include dependency on internet connectivity and a focus solely on leaf health classification.

Q & A

What is the main focus of the presentation?

The presentation focuses on an IoT-based greenhouse monitoring and controlling system integrated with AI.

Who are the presenters of the project?

The presenters are Deepak Lal and Savira Basha, supervised by Dr. Gulsher Ali and Dr. Suresh Kumar.

What are the primary sensors used in the greenhouse system?

The primary sensors used are temperature, humidity, and moisture sensors.

What types of actuators are integrated into the system?

The system includes exhaust fans for cooling, solenoid valves for irrigation, and LEDs for heating and grow lights.

How does the system contribute to sustainable agriculture?

It automates monitoring and controlling the greenhouse environment, thereby promoting healthier crops and reducing labor requirements.

What are the key issues in the agricultural sector of Pakistan that this project addresses?

The project addresses the lack of technology, control over suitable environments for plants, and the prevalence of diseases in traditional agriculture.

What AI applications are mentioned in the project?

The project mentions applications for health classification of plants and a mobile app called Gardner that assists with monitoring.

What is the role of the Firebase database in the system?

Firebase is used to store real-time data from the sensors and to communicate this data to the mobile application.

What limitations does the project face?

The project requires a stable internet connection to function and currently focuses only on leaf health for AI classification.

What future developments are planned for the project?

Future developments include integrating growth metrics into the AI model and enhancing the application capabilities.