1st Open Call
This project proposes a new prediction technique based on a probabilistic regression model that allows to predict the severity of a traffic accident for each of its occupants. The model is intended to provide a collective intelligence to the vehicle and also will be useful to improve the user’s driving behavior through the provision of collective road intelligence to the vehicle and the devices used in it.
A mobile application will be used to guide the driver and it will show alerts identifying possible black spots in the different routes, based on the results obtained by the proposed technique. These alerts that will appear in the mobile application can be verified or denied if traffic has already normalized at that kilometric point.
Sensorspark was born in July 2017 as a spin-off of the Miguel Hernández University in Spain, with its registered office in the UMH Scientific Park located at Elche (Alicante). The main activity of the company is focused on the exploitation of an architecture based on an app, a web of services and a powerful database technology based on Internet of Things and Big Data. The objective of this architecture is capture, processing and get value of data obtained from vehicles in traffic. This large amount of data collected is stored and processed at their servers. The company has developed a powerful mobile app, Carmetry®, that allows its users to control the performance of their vehicle and their driving skills, as well as keeping them informed of traffic events and breakdown risks in real time.