InfraVision AI
InfraVision AI is a mobile-first tool that detects structural damage using real-time scans and LLM Rage DB with Pinecone, powered by Gemini 1.5 Flash, to deliver smart safety reports instantly.
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Description
📜 Project Description:
InfraVision AI is an AI-powered mobile-first infrastructure inspection tool that enables users to scan structures using their smartphone camera and instantly detect damages, generate safety reports, and visualize risk zones — all in real-time.
With growing concerns around structural collapses, bridge failures, and poor maintenance, InfraScan AI acts as a preventive solution to identify potential threats before they turn into disasters.
Built for engineers, safety inspectors, construction managers, and everyday users, this tool brings advanced infrastructure inspection to everyone’s fingertips.
🔍 Key Features:
📸 Real-Time Camera Scan – Capture or upload images of buildings, bridges, or infrastructure directly from your device.
🧠 AI Damage Detection – Uses Google Gemini 1.5 Flash trained with pinecone vector database LLM Rage database to analyze images and detect visible cracks, corrosion, instability, or structural issues.
📊 Instant Safety Report – Generates a visual damage report with severity level and action suggestions.
🧱 3D Visualization – Basic 3D rendering of detected damaged zones for better spatial understanding.
🌐 Mobile-First Experience – Lightweight, responsive UI built with React.js, optimized for smartphones.
🔐 Lightweight Auth System – Simple signup/login system to save user scans and reports for future reference.
⚙️ Tech Stack:
Frontend: React.js, Material UI, Bootstrap
AI & Image Processing: Google Gemini 1.5 Flash LLM Rage Database
Backend: Node.js, Express.js
Others: HTML5 Camera Access, Responsive Mobile Layout, JavaScript
🛠️ Innovations & Problem Solving:
Brings AI-powered structural safety to low-resource users using just a smartphone.
Replaces traditional manual inspections with automated visual analysis.
Aims to reduce accidents and fatalities due to undetected structural failures.
Can be extended to rural areas with poor inspection infrastructure, increasing safety accessibility.
🚀 Future Enhancements:
Secure JWT Authentication System
User Scan History Dashboard
Offline scan mode for disaster zones
Integration with Civil Engineering Rage Database for expert review
🏁 Final Words:
InfraVision AI proves that technology can save lives. By democratizing access to intelligent inspection tools, it opens up a new frontier in disaster prevention and infrastructure safety. Whether you’re a professional or a citizen — if you can scan, you can prevent.
Progress During Hackathon
🛠️ Progress During Hackathon During the hackathon, we built InfraVision AI completely from scratch, transforming an ambitious idea into a working MVP within the given timeframe. Our primary goal was to develop an AI-powered infrastructure inspection tool that could help detect structural damages in real-time using a mobile-first interface. We implemented a fully responsive frontend using React.js and developed a custom camera-based scanner that allows users to capture real-time images of infrastructure. These images are then processed using a Locally hosted LLM Rage Database integrated with Pinecone Vector DB, leveraging the power of Gemini 1.5 Flash for intelligent analysis. The AI model evaluates the structural condition, identifies damages, and generates a detailed 3D Visualization Report with safety ratings. We also built a lightweight authentication system and enabled offline-first capabilities for scanning in remote areas. Additionally, we ensured seamless UX across devices and integrated visual transitions and motion for smooth interaction. Despite the tight deadline, we were able to: Build the AI pipeline for infrastructure damage detection. Create a real-time camera input scanner. Connect it with Pinecone vector search for LLM embeddings. Deliver an end-to-end working demo with visual reports. This progress reflects our commitment to solving real-world problems through AI-powered innovation.