INTELL-i-GREEN is an intuitive platform that integrates personalized care solutions and real-time monitoring capabilities.
Picture this – AI playing plant detective, crafting custom plant/crop care plans, and a futuristic Plant Care Kit that sprinkles tech magic with remote wifi watering; uv light induction built using MVVM architecture with local caching using Room SQLite Database.
TEAM 1% PERCENTA
Hello, my name is Jalaj Singh, and I am participating solo in HACKWITHDELHI. I am an enthusiastic developer currently completing my Bachelor's in Computer Science from COER University in Haridwar, specializing in cybersecurity. My passion lies in creating innovative solutions that bridge technology with everyday life, and this project is a testament to that drive.
I discovered Hive through HACKWITHDELHI's tech community. The platform's reputation for fostering creativity and innovation in hackathons inspired me to participate and showcase my project, INTELL-i-GREEN.
Incorporation of an open-source API.
Implementation of Android Data Binding.
Adoption of MVVM Architecture coupled with Clean Architecture.
Utilization of Android Room SQLite Database for local caching.
Integration of theming in M3 for both Light and Dark modes.
Scan & Identification: Automatically identifies over 30k species recalling PlantNet Api.
Unique 1of 1 Wireless Prototype: IMAGINE GROWING YOU WHOLE GARDEN REMOTELY FROM ANY LOCATION. The INTELL-i-GREEN wireless prototype is a groundbreaking device that seamlessly integrates with our app to monitor plant health metrics like soil moisture, temperature, and light exposure in real-time. Its unique capability lies in providing precise, AI-driven care recommendations remotely, ensuring optimal plant growth and sustainable gardening practices.
Disease Prediction: Using RCNN (Region-based Convolutional Neural Networks), INTELL-i-GREEN analyzes real-time plant health data to accurately predict and prevent disease outbreaks. This advanced AI capability ensures timely interventions, safeguarding plant health and optimizing growth conditions.
Custom Care Plans: Generates personalized care plans with just one scan, complete with push notifications to keep users on track.
Disease Solutions: Provides actionable solutions for identified issues to effectively manage plant health.
Weather Integration: Syncs with weather APIs to offer smart, location-based plant care warnings, optimizing growth and protection. Utilizes weather APIs to analyze factors like rain, strong winds, high UV, and temperature changes. Using this data, it sends push notifications for optimal plant care, ensuring timely interventions and maximizing plant health.
Plus, our custom prototype's automatic watering, UV light integration, motion sensors, and sound deterrents ensure efficient and effective plant care, promoting optimal growth and sustainability.
This project takes advantage of best practices of common librairies and tools in IOS and web.
MobileApp Development: Utilizing Swift for iOS Development in Xcode. We plan to mitigate to Dart in Flutter.
Hardware Components: Arduino, soil moisture sensors, 5V relay modules for enhanced connectivity, DHT-11 sensor for temperature and humidity data , and Node mcu ESP8266 Wi-Fi module for remote control, LCD screen and I2C module for display of outputs, 3.7- 7.4v Battery, 12v lights.
API Integration: To power our plant identification feature and care recommendations, we're planning to integrate APIs or data sources that provide accurate plant data. This ensures that our app can deliver personalized care instructions based on the specific requirements of each plant species.
Sensors and IoT: The heart of our prototype lies in sensors and IoT technology, which enable data collection, decision-making, and automation. These components facilitate automated watering based on soil moisture levels and light manipulation to optimize plant growth. Our goal is to make PLANT growth and yield more efficient and precise.
MobileApp Development: Xcode for iOS. We plan to mitigate to Dart in Flutter
Hardware Components: Arduino, soil moisture sensors, 5V relay modules for enhanced connectivity, DHT-11 sensor for temperature and humidity data , and Node mcu ESP8266 Wi-Fi module for remote control, LCD screen and I2C module for display of outputs, 3.7- 7.4v Battery, 12v lights.
https://github.com/jojinkey/HACKWITHDELHI_1Percent
https://drive.google.com/drive/folders/1bmXMn4OhD0LHvPGvJXzinLQaIkd7csKm?usp=sharing
It was a great experience participating in HACKWITHDELHI. I learned a lot from the developers, participants, mentors and key speakers I met at the hackathon. The arrangements were excellent and the hackathon was smoothly conducted. Looking forward to attending another edition soon.
https://drive.google.com/file/d/1AnAXOfoPytGcg7huP--e92H-922U3DUB/view?usp=sharing