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⚡ BattSense – Battery Health Prediction Web App\n\n[![Live App](https://img.shields.io/badge/Live%20App-battsense.netlify.app-%237B3FE4?style=flat-square\u0026logo=netlify\u0026logoColor=white)](https://battsense.netlify.app)\n[![Follow on Twitter](https://img.shields.io/badge/Twitter-%40Sharvesh_14-1DA1F2?style=flat-square\u0026logo=twitter\u0026logoColor=white)](https://x.com/Sharvesh_14)\n\n\u003ctable\u003e\n  \u003ctr\u003e\n    \u003ctd\u003e\n      \u003cimg src=\"https://github.com/sharvesh1401/sharvesh1401/blob/main/profile%20image.png\" alt=\"Sharvesh Selvakumar\" width=\"200\"/\u003e\n    \u003c/td\u003e\n    \u003ctd\u003e\n      \u003cimg src=\"https://readme-typing-svg.demolab.com?font=Roboto\u0026size=28\u0026pause=1000\u0026color=7B3FE4\u0026width=435\u0026lines=Battery+SOH+Prediction;Machine+Learning+%2B+Web+App;DeepSeek+AI+Integration;Built+by+Sharvesh+Selvakumar\" alt=\"Typing animation\"/\u003e\n    \u003c/td\u003e\n  \u003c/tr\u003e\n\u003c/table\u003e\n\n\u003cbr/\u003e\n\n\u003e “Predict battery health with real data, real models — and real-time AI assistance.”\n\n---\n\n## 🌐 Overview\n\n**BattSense** is a web-based tool that predicts the **State of Health (SOH)** of lithium-ion batteries using machine learning.\n\nIt bridges the gap between raw sensor data and practical diagnostics through an interactive, browser-based dashboard.\n\nBuilt with **React + Vite + Tailwind CSS**, this frontend is paired with a trained ML model and enhanced with **DeepSeek AI** for intelligent analysis.\n\n---\n\n## 🔍 Key Features\n\n- 🔋 Predict SOH based on voltage, cycles, capacity, and temperature\n- 🧠 Powered by a **Random Forest Regressor** trained on real data\n- 💬 Built-in chatbot assistant using **DeepSeek API**\n- 📊 Sample output visualization + **Downloadable results**\n- 🧪 Configured for both web and ML experimentation\n\n---\n\n## 📦 Tech Stack\n\n![skills](https://skillicons.dev/icons?i=react,tailwind,typescript,vite,python,netlify,git\u0026theme=light)\n\n**Also includes:**\n\n- 📦 **PostCSS** – custom styling and plugin support  \n- 🧪 **Jest** – unit testing  \n- 🧭 **ESLint** – consistent code formatting  \n- 🧱 **Recharts** – data visualization  \n- 🧠 **DeepSeek API** – conversational AI assistant  \n- 📁 **Modular file aliasing** via Vite config\n\n---\n\n## 🖼️ Sample Output\n\n![SOH Prediction Chart](./image_2025-06-19_075905942.png)\n\n\u003e After prediction, the result is displayed and can be **downloaded** as a CSV for further analysis or reporting.\n\n---\n\n## 🧠 ML Model Details\n\n- Model: **Random Forest Regressor**\n- Dataset includes:\n  - Voltage  \n  - Current  \n  - Temperature  \n  - Charge cycles  \n  - Capacity\n- Target: **State of Health (SOH)**\n\nHandled:\n- Missing values  \n- Outliers  \n- Feature selection  \n\n**Metrics Used:**\n- Mean Squared Error (MSE)  \n- Root Mean Squared Error (RMSE)  \n- Mean Absolute Error (MAE)  \n- R² Score *(coming soon)*\n\n---\n\n## 🚀 Getting Started\n\n```bash\n# Clone the repo\ngit clone https://github.com/sharvesh1401/BattSense.git\ncd BattSense\n\n# Install frontend dependencies\nnpm install\n\n# Run the local dev server\nnpm run dev\n```\n\n\u003e For backend ML model usage, refer to `battery_soh_predictor.py` (not included in web build).\n\n---\n\n## 📁 Project Structure\n\n```\n├── src/                  # Frontend components \u0026 views\n├── image_*.png           # Sample output graph\n├── public/               # Static assets\n├── index.html\n├── package.json\n├── vite.config.ts\n├── tailwind.config.js\n├── postcss.config.js\n├── jest.config.cjs\n└── tsconfig.*.json       # TypeScript config files\n```\n\n---\n\n## 🛠 Improvements Planned\n\n- [ ] Connect directly to Python backend for live predictions  \n- [ ] Add downloadable dataset sample  \n- [ ] Expand model support (XGBoost, MLP)  \n- [ ] Add user authentication (optional)\n\n---\n\n## 🙋‍♂️ About Me\n\nI'm **Sharvesh Selvakumar**, an engineering student passionate about AI, clean energy, and responsible tech.\n\n🔗 [sharveshfolio.netlify.app](https://sharveshfolio.netlify.app)  \n🐦 [@Sharvesh_14](https://x.com/Sharvesh_14)\n\n---\n\n\u003e ⚡ Built for smarter batteries and better energy tech.  \n\u003e MIT License | © 2025 Sharvesh Selvakumar\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsharvesh1401%2Fbattsense","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsharvesh1401%2Fbattsense","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsharvesh1401%2Fbattsense/lists"}