Inspiration: The inspiration behind our project was born from the recent money hike in fruits and vegetables due to low yielding. With thorough research we found that almost every plant is prone to various disease at any stage of their growth. What more? farmers are unable to track the moisture and humidity level whose knowledge is very crucial in keeping track of it’s health. These challenges include the difficulty of timely disease detection, the environmental impact of excessive pesticide use, and the lack of accessible technology to aid in plant care. Witnessing the struggles encountered by individuals in maintaining healthy plants and the environmental impact of conventional plant care methods, we were inspired to create a solution that bridges technology with horticultural expertise.
What it does? GreenGuard is a comprehensive plant disease detection and management system designed to simplify and elevate plant care. Its core functionality and purpose can be summarized as follows: • Disease Detection: GreenGuard utilizes advanced technology, including image recognition and AI algorithms, to accurately detect plant diseases in real-time. Users can simply take a photo of an affected plant, and the app provides an instant diagnosis. • Sustainable Agriculture: By promoting early disease detection and providing eco-friendly disease management solutions, GreenGuard contributes to sustainable agriculture practices. • User-Friendly Mobile App: GreenGuard is designed with user-friendliness in mind. Its intuitive mobile app interface makes it accessible to a wide range of users, from novice gardeners to experienced farmers. • Sensor Technology: For accurate data collection, GreenGuard integrates sensor technology, allowing users to monitor essential plant metrics such as soil moisture and humidity levels.
How we built it? Conceptualization: • The project started with extensive research into plant care challenges and the existing solutions available. Hardware Selection: To monitor essential plant metrics, we chose the DTH (DHT) sensor, which measures temperature and humidity. A water pump was selected to automate the watering process, ensuring that plants receive the right amount of moisture. ESP Integration: • We used ESP32 to interface with the DTH sensor, Moisture Sensor, water pump. • Arduino allowed us to collect real-time data on temperature and humidity and control the water pump accordingly.
- Image Recognition: For disease detection, we integrated a Python-based deep learning model using frameworks like TensorFlow . Users could upload photos of their plants through the app for disease diagnosis.
Challenges we ran into ESP Crash: Unexpected hardware failure. Model Training: Issues with dataset and model convergence.
Accomplishments that we're proud of: Creating a user-friendly cross-platform mobile app using Flutter ensured accessibility to Android users, expanding our project's reach. Sustainability Focus: Embracing sustainability in agriculture and plant care was a core achievement. Coordinated teamwork Working under such little time limit with coordination with team member
What we learned We learned about the essence of agriculture, and how IoT and ML techniques can be manipulated to overview the heath of plant.
What's next for GreenGuard? Fabrication methods: Use of map to find favorable condition for growth of plant, Experts overview, blog section, AR tech for height of plant
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