🪴 PLKIT, get EASY&SMART Farm R&D
An Integrated Smart Farm Management and Community Platform
- PLKIT-HW_Prototype_and_Specifications: Documentation for the hardware aspects of the PLKIT smart farm system, including layout, specifications, and prototype information.
- AI.analysis README: Detailed documentation for the AI.analysis module, which manages time series forecasting models using TSMixer.
- AI.chat README: Documentation for the AI.chat module, an AI-powered chatbot for smart farm management using GPT-4.
- BE.platform README: Backend service documentation for the community and market platform.
- EM.modules README: Overview of embedded modules for smart farm control using BLE.
- FE.dashboard README: Frontend dashboard documentation built on Enact and Node-RED for smart farm management.
- FE.web README: Web platform documentation for data sharing and community features.
Important
Effortless Deployment with IPK Packaging
PLKIT is packaged as an IPK file specifically for webOS, allowing seamless installation and maintenance on webOS devices. This ensures broad compatibility and ease of use across various webOS platforms, enhancing accessibility.
Tip
Optimized Multimedia Performance
PLKIT maximizes the multimedia capabilities of webOS to deliver smooth, high-quality video streaming. Users can monitor their smart farm in real time, with optimal video quality tailored to the screen size of their webOS device.
Tip
Support for Diverse Devices
With webOS compatibility across smart TVs, smartphones, and IoT devices, PLKIT is versatile and adaptable. This allows users to manage their smart farm from a wide range of devices.
Note
Consistent User Experience
By leveraging the powerful UX framework of webOS, PLKIT offers a seamless and intuitive user experience. The Enact framework integrates naturally with webOS, providing a familiar and user-friendly interface.
PLKIT combines cutting-edge technologies like BLE, FastAPI, Node-RED, and Enact UI to offer a robust smart farm ecosystem. It enables seamless farm management, from real-time data monitoring and device control to community-driven data sharing and AI analysis. The goal is to optimize agricultural processes and provide an accessible platform for users to manage, analyze, and share valuable farming data.
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|-- AI.analysis # FastAPI-based analysis service using TSMixer
|-- AI.chat # Smart Farm Expert Chatbot using GPT-4 and FastAPI
|-- BE.platform # Backend service for community and market operations
|-- EM.modules # Embedded modules for smart farm control with BLE
|-- FE.dashboard # Frontend dashboard built on Enact and Node-RED
|-- FE.library # Component library for the frontend
|-- FE.web # Web platform for data sharing and community features
|-- .docs # documents for PLKIT
`-- README.md # This file
- Description: A FastAPI-based service for managing and deploying time series forecasting models using TSMixer.
- Features:
- Model uploading and management
- Single data point predictions
- Robust logging and CORS support
- Technologies: FastAPI, PyTorch, MongoDB
- Description: A chatbot application leveraging GPT-4 to provide smart farm advice and support.
- Features:
- User persona setup for tailored responses
- Conversation logging for analysis
- AWS deployment-ready
- Technologies: FastAPI, OpenAI API, Uvicorn
- Description: A FastAPI-based backend for managing community and market functionalities.
- Features:
- User authentication (JWT-based)
- Community and market APIs
- Status management and CORS support
- Technologies: FastAPI, SQLAlchemy, JWT
- Description: Embedded systems for smart farm control using BLE.
- Features:
- BLE communication for Wi-Fi and MQTT setup
- Real-time control of LED, fan, heater, and water level
- Node-RED for automation
- Technologies: Arduino IDE, Node-RED, ESP32
- Description: An Enact-based dashboard for monitoring and controlling smart farms.
- Features:
- Real-time sensor data visualization
- Remote device control using WebSocket
- AI-based growth prediction
- Technologies: Enact, Node-RED, webOS
- Description: A component library for reusable UI elements in the frontend.
- Technologies: React, Styled-Components
- Description: A web platform for smart farm data sharing and community interaction.
- Features:
- Knowledge sharing and data trading
- Secure user authentication
- Community-driven content management
- Technologies: React, Axios, Styled-Components
- Python 3.8+
- Node.js and npm
- MongoDB
- Arduino IDE (for EM.modules)
- Virtual environment tools
-
Clone the Repository
git clone https://github.com/PLKIT/PLKIT.git cd PLKIT -
Set Up Virtual Environments for Python Projects
- Navigate to
AI.analysis,AI.chat, andBE.platformdirectories and create virtual environments. - Install dependencies:
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate pip install -r requirements.txt
- Navigate to
-
Install Node.js Dependencies for Frontend Projects
- Navigate to
FE.dashboard,FE.library, andFE.webdirectories and run:npm install
- Navigate to
-
Configure Environment Variables
- Use
.envfiles for sensitive information like database URIs and API keys.
- Use
- AI.analysis:
uvicorn app.main:app --reload
- AI.chat:
uvicorn app:app --reload
- BE.platform:
uvicorn main:app --reload
- FE.dashboard: Use
npm startto launch the Enact dashboard. - FE.web: Use
npm startto run the React-based web platform.
- Upload the Arduino code to ESP32 devices.
- Monitor and control the smart farm via the dashboard.
We welcome contributions! Follow these steps:
- Fork the repository and create a feature branch.
- Implement your changes and write clear commit messages.
- Submit a pull request for review.
- Follow PEP 8 for Python code.
- Use meaningful names for commits and branches.
- Ensure your code does not break existing features.
This project is licensed under the MIT License. See the LICENSE file for more details.
© 2024 PLKIT. All rights reserved.
Enjoy smart farming with PLKIT! 🌱