Real-time accident predictive algorithm with IoT readings connected to an airbag integrated in a helmet.
Local ML model in edge detection with very high accuracy (>99.9%)
Experimental design and data collection. Delivery of data warehouse, training cycle and DB data model and selection of internal DS staff with training and full transfer to the client.
Evix Safety had a critical challenge: detect crashes in real time to activate safety airbags in bicycle helmets. The challenge was to create a solution that predicted accidents with high accuracy, minimal anticipation and reduced memory consumption, which required an advanced AI solution.
Dribia joined Evix Safety to overcome obstacles in the field of road safety. We develop a predictive algorithm, called Merckx, built directly into the bicycle helmet. This state-of-the-art approach, implemented without connectivity (Edge), uses IoT readings to intelligently differentiate between accidents and other situations. Through meticulously designed experimental tests and an automatic update system, we manage to set a new safety standard for cyclists, paving the way for a safer future of bicycle travel.