EcoGo

Presentation of the project content

Subject of the innovation development

The project will develop a prototype by interfacing with an on-board device manufacturer and a partner providing vehicle tracking and vehicle asset protection services. The prototype will be capable of performing the analyses required for the economical operation of motor vehicles. Based on data from the vehicle tracking system and the technical and cost data of Seacon Europe’s Seafleet product already available on the market, the solution identifies correlations between vehicle usage patterns and the operating costs incurred.

Detailed presentation of the activities to be implemented

The EcoGo prototype is planned to be developed within the framework of a two-year R&D project, during which several types of activities will be carried out and several types of deliverables will be created across four work phases.

• Prototype planning and specification:
  The planning phase prepares and lays the foundation for development through specification and system design.
• Development of the data collection framework:
  The first phase of development focuses on implementing measurement, data transmission and data reception. It includes the establishment of the communication channel, the application of the prescribed data structures, the development of open interfaces, and the reception, preprocessing and storage of large volumes of data arriving from vehicles on a central platform.
• Data integration, analysis and visualization:
  The objective of the second phase of development is to process the data, filter out exceptional events related to vehicle use, provide an overview of the related alerts, and establish a system of messages and feedback. Through data analysis and the implementation of rules and evaluation algorithms, simple and complex queries are created that generate business-relevant information about vehicle driving.
• System integration, prototype testing and tuning:
  The development results will be integrated into a complex solution. Its evaluation and testing will take place in parallel with system integration. The objective is to verify the effectiveness of the developments, examine the efficiency of cooperation between the prototype components and interfaces, and carry out communication, integration, functional and user tests.

Presentation of the results to be achieved

EcoGo provides, through a new approach, the integration of the data assets and data services of GPS service providers and fleet operators. The prototype created during the development is an IT-based solution that focuses on the costs arising from vehicle use and, based on the analysis of vehicle usage patterns, aims to provide cost optimization information to vehicle operators and vehicle owners.

An important deliverable of the project is that the solution is based on objective vehicle usage data and the efficient cooperation of IT systems. Due to its open architecture, it enables the resulting hardware and software combination to be installed in a way tailored to the needs of a specific site or user. The prototype itself collects data generated in the vehicle using devices selected from one manufacturer’s product family, but as a solution it clearly aims to incorporate data services from several manufacturers. This also means that the central data analysis application can be made capable of processing different data contents in different ways, depending on what equipment is able to perform which measurements in the vehicles and transmit them from there. In this way, it becomes possible to manage fleets uniformly even when they are equipped with several types of devices or change rapidly and different vehicles must be handled. We aim to provide every manufacturer with the opportunity to supply data.

The richest source of information in motor vehicles is the CAN bus. In principle, it carries far more types of data than it is either possible or worthwhile to process. Almost everything can be measured there, but there are two serious obstacles in terms of access: the data are not easy to decode, and there is no real standard, meaning that even the model year within a given make and type can determine the access method. Based on this, our solution defines the analysis of a narrow data set that can essentially be handled uniformly and can also be easily measured by other sensors. Where possible, we use wireless sensors that can be installed easily and whose measurement signals can be processed by the installed device.

The capabilities of the data collection framework, developed using a data warehouse approach, include data collection and its supervision, the detection of anomalies, and support for the prevention of such events through the analysis of correlations that can be identified during vehicle use, including driver movements and manoeuvres, internal or external measurable parameters, and even the complex examination of processes extending over time.