CADS: A Connected Assistant for Driving Safe

Drowsy and distracted driving, overspeeding, mechanical failures and bad road conditions are among the main causes of car accidents, many of which are fatal. Undoubtedly, coping with these issues will make our roads safer and decrease the daily loss of lives. In this paper, we propose a Connected Assistant for Driving Safe (CADS), capable of ensuring that both the driver and the car are performing at their best during driving trips. It achieves this by seamlessly and continuously monitoring various features related to the driver, the car and the road ahead, making sense of them and taking actions based on the extracted insights. The proposed CADS uses Computer Vision, Machine Learning and the Internet of things paradigm to enable its services. Moreover, using the LoraWAN protocol, these services can be delivered on a large scope. We present our solution's design and describe its architecture and its main components. We list all the features monitored by our solution and how they are used to provide its services, and then show how CADS surpasses existing solutions. Finally, we present a prototype of our solution alongside its main hardware and software components.