AlertIQ – Smart alerts for smart safety.

Inspiration:-

We aimed to build a system that can intelligently detect emergencies like falls, gas leaks, or crashes and respond instantly—especially to protect the elderly, isolated individuals, and drivers.

What it does:-

AlertIQ uses AI and IoT sensors to detect abnormal events (crashes, screams, gas leaks, etc.) and sends real-time alerts with GPS, emergency type, and live data to nearby responders.

How we built it:-

We integrated sound, motion, gas, and biometric sensors with an AI model trained to classify emergency events. A microcontroller collects data and triggers alerts via a connected IoT module.

Challenges we ran into:-

*Accurate detection of diverse emergencies *Avoiding false positives *Integrating multiple sensors *Ensuring real-time response with minimal latency

Accomplishments that we're proud of:-

*Built a working prototype that detects and classifies multiple emergency types *Achieved real-time alerting with GPS location *Designed a scalable and user-friendly system

What we learned:-

We deepened our understanding of sensor integration, real-time data processing, AI model training, and building practical, impactful safety solutions.

What's next for AlertIQ – Smart alerts for smart safety.:-

We plan to:

Add camera-based threat recognition Improve machine learning accuracy Develop a mobile app for user-friendly monitoring Pilot in smart homes and vehicles

Built With

• c
• c++
• c/c++-(for-microcontroller-programming)-frameworks-&-libraries:-tensorflow-lite-/-scikit-learn-(for-machine-learning)-arduino-ide-(for-embedded-development)-hardware:-esp32-/-arduino-uno-(microcontroller)-sensors:-microphone
• gas-sensor-(mq-series)
• heart-rate-sensor-(max30100)
• motion-sensor-(pir)
• python
• tensorflow