Lightning Sentinel

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  LIGHTNING SENTINEL UI

About the Project

Lightning Sentinel is a solo-built project designed to make Bitcoin Lightning Network transactions more transparent. It helps users monitor real-time payments, detect anomalies, and understand risks — all while keeping their data private and on-device.

What Inspired Me

The Lightning Network is changing how we handle peer-to-peer payments, but tools for transaction monitoring haven’t kept pace. I wanted to create something lightweight, insightful, and private — no cloud AI, no central servers.

How I Built It

The frontend is built using React and Vite. It connects to a local LND node and streams transaction data through WebSockets. All AI analysis is done locally using TensorFlow.js, with Chart.js used to display trends and risks in a simple dashboard interface.

Challenges I Faced

Syncing real-time Lightning data with a responsive frontend was tricky. Running machine learning models in-browser also meant carefully balancing performance with accuracy. It took time to tune the interface to work smoothly with large volumes of transaction data.

What I Learned

This project taught me how to build fast, privacy-first AI applications. I explored Lightning node integrations, local inference using TensorFlow.js, and performance optimization techniques for handling real-time data inside React apps.

What’s Next

I’m planning to add federated learning so the AI can improve over time without sending data out. I also want to support additional crypto networks, create a Telegram alert bot, and make the interface mobile-friendly.

Built With

• bitcoinlightningnetwork
• chart.js
• lnd
• node.js
• react
• tailwindcss
• tensorflow.js
• vite
• websockets