Smart Alcohol Detection & Safety System using Arduino Nano 33 IoT, MQ-3 Sensor, and Machine Learning

Step into the future of safety and innovation with this cutting-edge IoT + AI project. Built around the powerful Arduino Nano 33 IoT and the MQ-3 alcohol sensor, this system goes beyond traditional sensing by integrating machine learning and deep learning models for smart, real-world alcohol detection.

Unlike ordinary sensors that simply trigger on raw values, this project uses AI-driven interpretation to distinguish between true alcohol signals and false interferences like smoke, perfume, or sanitizers. Students will experience the thrill of building a real-world intelligent system that adapts, learns, and predicts with accuracy.

✨ Why it Stands Out for Students & Placements:
✔ Hands-on learning with Arduino Nano 33 IoT + MQ-3 sensor.
✔ Explore Machine Learning/Deep Learning integration for IoT.
✔ Build driver safety systems, smart car locks, and forensic tools.
✔ Perfect for academic submissions, placements, and industry exposure.
✔ Comes with 150+ page detailed report, full codebase, hardware kit, and future scope guidance.

📌 Applications You’ll Build:

• Smart Car Ignition Lock – prevents drunk driving.

• Driver Monitoring & Safety Devices.

• Police/Forensic Breath Analyzers.

• Alcohol Contamination Detection in Food Industry.

• Workplace Safety Monitoring Systems.

This is not just a project – it’s a career-boosting innovation that proves your expertise in IoT, Embedded Systems, and Artificial Intelligence, making you stand out in interviews and internships.

✅ Deliverables Included:

• Complete Hardware Kit (Arduino Nano 33 IoT, MQ-3 sensor, supporting modules).

• Full Source Code with Google Colab ML Training.

• Ready-to-Submit 150+ Page Documentation.

• Project Report, PPT, and Demo Video Support.

• Placement & Resume-boosting guidance.

👉 This is your gateway to building industry-grade IoT solutions while showcasing advanced AI-integration skills.