«Laziness is the engine of progress»: How I built an AI bot for electrical inspection

A veteran electrical engineer with 15 years of experience has built an AI-powered Telegram bot that detects common electrical installation violations from photos. Using YOLOv8 for image classification and FAISS for similarity search, the bot identifies issues like missing cable tags, improper earthing, and unsealed penetrations, generating reports with references to international standards. The developer trained the model on over 500 photos and deployed it on low-cost cloud hosting, making it freely available to construction professionals.

I've been in electrical construction for over 15 years. Started with installation, moved to commissioning, then became a chief project engineer. And you know what I realized over that time? The same mistakes happen over and over again. Missing tags, improper earthing, unsealed penetrations. Every single time. The same routine, eating up time and nerves. 📋 How I used to do inspections First, I carried a notebook, a tape measure, and a camera. Later — a smartphone and Excel. Then came "IT-based technical supervision" — bulky, inconvenient systems that only work on a PC, require licenses, and are built for large corporations. Even with them, inspections took hours. And worst of all — you had to configure them, train people, carry a laptop to the site. I needed a tool that: works in seconds, requires no training, is available right on the construction site, and can be used by anyone — from a foreman to a technician. 💡 The idea I'm not a programmer. But with the advancement of AI and neural networks, I realized I could make this happen. Why not use a neural network to detect violations from photos? I used: YOLOv8 for image classification, FAISS for similarity search, Telegram as the interface — so I wouldn't need to build a separate app. I collected a dataset: 500+ photos of violations and reference examples — from work, colleagues, and open sources. I trained the model for 50 epochs, then fine-tuned it on real-world photos. The hardest part wasn't the neural network. It was keeping the bot stable on the server without running out of memory. It wasn't completely free — but the costs are minimal: cloud hosting and Render ~$7–25/month . 🤖 What the bot can do today The bot now works in Telegram. Send a photo of a panel, cable tray, or cabinet — and it instantly detects: missing cable tags, improper earthing, unsealed penetrations, untrimmed cable tray studs, oxidation and rust, missing single-line diagrams. It generates a ready-to-use report with references to PUES, SP, GOST for Russia or IEC, NEC, BS 7671 international . One photo — up to three defects. Free. No installation required. It supports three languages: English, Russian, and Spanish. 🔥 What's next I'm currently collecting feedback from engineers, foremen, and installers. I want to: add more defect categories, retrain the model on real photos, export reports to PDF, integrate with project management systems. 🎯 Try it yourself The bot is free. Just send a photo — get a report. 👉 @ElectricalInspectorBot I'd love your feedback, ideas, and — of course — your photos of violations 😉