My-TRAC project aims to deliver an innovative application for seamless transport and an ecosystem of models and algorithms for Public Transport – PT user choice simulation, data analytics and affective computing. My-TRAC stands out from other technologies due to three main reasons. First, My-TRAC fosters unprecedented involvement of users during, before and after a trip through a smart Human-Machine interface and numerous functionalities such as crowdsourcing, group recommendations, data exchange. Second, the application implements a vast array of technologies, such as affective computing, Artificial Intelligence and user choice simulation, that fuse expertise from multiple fields. Third, My-TRAC facilitates engagement of multiple stakeholders by seamlessly integrating services and creating connections between Rail operators, Mobility-as-a-Service and other PT providers. My-TRAC application is a travel companion designed to operate similarly to a human companion; understanding traveller’s attributes and state-of-mind to derive conclusions from vague information as any human does. In addition, My-TRAC will be the traveller’s gateway to various services related to using PT, having Rail in the epicentre. My-TRAC application will also provide predictive information concerning disruptions and disturbances. It will not only display data but analyse them through innovative algorithms to provide improved recommendations. My-TRAC also involves PT operators through the “operators’ interface” where they can retrieve and visualize aggregated data on users’ movements and state-of-mind that will assist in strategic and dynamic operations. Data that the operators retrieve are aggregated and anonymized while all models and algorithms are applied on the mobile device of the user, seamlessly integrating the “privacy-by-design” concept. The consortium will test the idea in 4 pilot locations with the cooperation of local operators: NS (NL), ATTIKO Metro (GR), FGC (SP), Fertagus (PT).

JAM is an IoT solution (hardware & software), capable of reducing operational costs of businesses managing vehicle fleets by targeting the following key needs: - Fuel efficiency: fuel represented, in 2011, 32% of the total cost of fleet operation; - Maintenance costs: lack of maintenance shortens the vehicle lifetime and leads to excessive maintenance costs, fuel consumption, higher vehicle off-road time and losses in productivity; - Compliance with environmental regulations and reduction of CO2 emissions. JAM is connected to the mandatory vehicle interface for on-board diagnostics (OBD) and collects data from all vehicle sensors, using state of the art artificial intelligence to detect risks before malfunctions and breakdowns occur, allowing immediate interventions. Continuous monitoring of vehicle health allows the mechanical optimization of the fleet, reducing fuel costs and CO2 emissions. Although there are solutions in the market making use of the OBD interface to assess vehicles’ conditions, JAM introduces two breakthroughs. JAM is integrated in the 18 Billion Euros worth commercial telematics market as an aftermarket solution. The market is expected to grow to 42,8 Billion Euros by 2020. JAM’s feasibility was assessed during a SME Instrument Phase 1 project, and with this Phase 2 project we will be able to have a market ready version of JAM. Project break-even is expected to be met by the end of Phase 2 and in the short-term this project will create 12 additional highly qualified jobs.

Jam is an IoT solution (hardware & software), aiming to improve the efficiency of businesses operating medium/heavy-duty vehicle (e.g. passenger and distribution fleets) and industrial fleets (e.g. mining trucks and agriculture vehicles), targeting key needs: - Fuel efficiency: fuel represented, in 2011, 32% of the total cost of fleet operation - Compliance with environmental regulations and reduction of GHG emissions - Vehicle off-road (VOR) time and maintenance costs: Many operators put the cost of having a single VOR as being in the hundreds, if not thousands, euros/day According to Frost & Sullivan, the OBD market is expected to reach 117.8 million subscribers in 2019 and to become a billion-dollar industry by 2020. Although there are already solutions on the market for ECU interpretation on light-duty vehicles, the amount of new protocols, physical interfaces and differences in details in the way industrial vehicles operate constitute a barrier, not yet surpassed. Business and industrial fleets need an agnostic solution that allows optimizing the fleet management by reducing the maintenance costs and VOR time. Jam brings an innovative approach and focus on prevention and constant analysis of real-time vehicle data through a machine-learning algorithm allowing companies to save money on fuel costs, vehicle parts and hours of labour due to a more efficient management of fleet resources. Competitive advantages: - Designed for medium/heavy-duty and industrial vehicles - Agnostic system - Machine-learning algorithm that compares the ECU sensor data with historical data, predicting critical events - New eco-driving approach - Troubleshooting and scheduled repairs approach focused on prevention and constant analysis of real-time vehicle data The solution will be implemented at a global scale, starting in European markets: Portugal for early market uptake and testing; and then the biggest EU markets (Germany, UK, France, Poland, Italy and Spain).