Telemetry transformation towards industry 4.0 convergence - A fuel management solution for the transportation sector based on digital twins

The undergoing digital transformation of the global economy impacts the way freight transportation conduct businesses and interact with their customers. In parallel, concerns are increased in terms of environmental, social and ethical performance. Recent European Union regulation focused on the energy consumption and Greenhouse Gas emissions, with lower targets but also with the regular collection of real-world data, initially targeting heavy-duty vehicles, as environmental concerns were added to the economic considerations for a sustainable international transport. High precision fuel data with high density in time can help build the appropriate models and optimize operational costs, including direct or indirect factors (e.g., fuel consumption, waste and fraud), and eco driving (e.g., fuel efficient vehicle operation, drivers’ awareness). Taking into account the growing demand of a measurement process independent from the manufacturers, existing vertical data acquisition solutions often create silos with data organized separately, not harmonized, and being difficult to be compared and correlated. A holistic cyber physical approach is required to create knowledge and added value from all the related data streams and their associated events, resulting to implementation difficulties in terms of complexity, performance and costs. This paper reviews the need of the velocity, variety and volume of the required data in terms of fuel management and environmental impact, the benefits of their treatment, the practical problems of such implementations and how the digital twins concept applied in software models can help overcome them in a very elegant and efficient way, exhibiting superior performance for optimizing communication, real time business logic, reaction and quality control. Finally, a case study is presented, which based on the virtual actor pattern implementation gives practical and efficient solutions to the implemented architecture in terms of development effort, cost and resources optimization. Cloud services, data science and digital twins combined, constitute a cost driven and sustainable approach for fuel and eco-driving management in the transportation.