Inspiration
We were inspired by the everyday reality of motorbike taxis in Rwanda. They’re the fastest and most popular way to get around, but they also come with a high risk of accidents. Unfortunately, when an accident happens, emergency response times are often slow, and there’s no real system in place to track these incidents.
We wanted to create something that could save lives and improve safety not just for riders, but also for their passengers. That’s how L-Guard was born a smart helmet that doesn’t just protect your head but also helps in emergencies, tracks accident history, and even makes payments easier.
What it does
L-Guard is a smart IoT helmet that makes motorbike rides safer and more convenient. Here’s how:
Accident Detection & Alerts – If the rider gets into an accident, the helmet automatically detects the impact and sends alerts with their location to nearby hospitals, police, and emergency contacts. Accident Data Logging – It records key details like where and when the accident happened, helping track safety trends and improve responses. QR Code for Passengers – The helmet has a QR code that passengers can scan to check the rider’s details (license, accident history) and even make payments directly via Mobile Money (Momo). Admin Dashboard & Analytics – A web-based platform where authorities and stakeholders can monitor accident data, manage users, and improve road safety policies. How we built it We combined hardware, IoT, and software to make L-Guard a reality.
Sensors & Microcontrollers – We integrated accelerometers and gyroscopes to detect crashes, using an ESP32/Raspberry Pi to process data. Real-Time Alerts – When an accident happens, the system sends emergency alerts via Wi-Fi or GSM. Database & Backend – We used Firebase / PostgreSQL to store accident reports, user profiles, and ride history. Dashboard & Web App – Built with React.js for the frontend and Node.js / Flask for the backend, making it easy to visualize data and track incidents. QR Code & Payments – The QR system links to rider profiles and supports seamless cashless transactions.
Challenges we ran into Accurate Accident Detection – Finding the right way to differentiate a real crash from a minor bump was tricky. Connectivity Issues – Ensuring the helmet could send real-time alerts even in areas with weak network coverage was a challenge. Data Security – Protecting sensitive rider and passenger information was a top priority. Seamless Payments – Integrating Momo payments smoothly into our system took some effort. Accomplishments that we're proud of We successfully built a working prototype that can detect accidents and send alerts. The QR code system works, allowing passengers to check rider details and make quick payments. We developed a dashboard for real-time accident monitoring. We learned a ton about hardware-software integration, which wasn’t easy but super rewarding!
What we learned
How to fine-tune IoT sensors for accident detection. The power of real-time data management—storing and processing accident data efficiently. Why user experience matters—making a system that’s simple and effective for riders and passengers. How to work as a team under pressure—especially in a hackathon setting where time is limited! What's next for L-Guard? Improve accident detection with AI – We want to use machine learning to reduce false alarms. Expand payment options – Integrate more cashless payment methods beyond Momo. Partner with the government & insurance companies – To encourage adoption and improve road safety regulations. Mass production – Scale up manufacturing and get L-Guard helmets into the hands of riders. Develop a mobile app for riders – So they can track their accident history, earnings, and payments.
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