Develop synthetic neurophysiological models able to detect the onset of abnormal drivers' fitness (e.g. mental overload, fatigue, alcohol), analysing the concomitant variation of specific physiological parameters (brain, heart, ocular activity, skin sweating, facial expression).
Develop an Artificial Intelligence (AI) system that using biometric, positional and contextual data will create an "individual profile" of the driver usual behaviour. AI will be then able to monitor the user while driving, detect eventual anomalous behaviour and recognize its most probable cause.
Perform test in a set of simulators to collect data related to professional drivers in standard and altered conditions, to have a large database to feed AI.
Design and develop a new set of drugs/impairing substances screening device for police roadside controls with a sensitivity of 95%, and sensitivity of 90% at 100 ng/ml THC and 75ng/ml Metamphetamine, specifically studied to noticeably reduce the time needed (less than 2 minutes) and to be applied jointly with the indications provided from the cloud-based system.
Integrate information from the vehicle on board intelligence (speed, acceleration, steering, braking, use of gears), from the driver using non-intrusive IoT devices (i.e. biometrics, smart band) and other sensors, the tachograph, the user personal background and the environment.
Develop a cloud-based system to collect, store and process the data gathered from heterogeneous data sources, connect the different AI components and deliver information using web-based user interfaces and portable devices (i.e. smartphone, tablets).
Improve and customize, even developing specific add-ons, the Controller Area Network (CAN Bus) infrastructure equipping most of the recent cars: this device will collect CAN data from the vehicle, provide geolocation, driving contextual data, act as Bluetooth bridge for the drivers' wearables (non-intrusive IoT devices), environmental sensors, eye trackers, cameras and provide external communication with the cloud platform through long distance network (2G, 3G, 5G).
Develop smart tachographs to retrieve professional data with new crypto algorithms additional authenticated secure Global Navigation Satellite System (GNSS), additional features for remote early detection facilities (DSRC) and Bluetooth interface.
Integrate all the parts with a focus on interoperability, reliability, acceptability, ethics and security.
Perform controlled environment tests with 6 users to optimise the created tools.
Perform real tests in 3 different sites (Spain, Italy and Ireland), with at least 30 final users.
Create a network of partners and associates in academia and industry and a vibrant innovation ecosystem (start-ups and SMEs) for the quick market uptake of the technologies.
Establish interactions and collaborations that will last beyond the project end. Establish a network of associates interested in building research collaborations, evaluating outputs, participating in events and exchanging information.
Create new training modules for professional drivers and for road patrols based on the tests.
Use the results in the definition of a new fitness to drive regulation and other related regulation. Define and propose new operational standards at European level for a proper use of FitDrive solutions during the roadside controls and for medical periodic screenings of the professional drivers.
Create a complementary funding/commercial interest from the public and private sectors to ensure the sustainability, expansion and adoption.
Communicate and disseminate the results to all relevant stakeholders with target-oriented actions.
Foster the application of FitDrive tool to investigate and prevent other effects of altered conditions.