International audience

Nowadays the number of on-board sensors increases continuously due to their benefits in many different areas, such us driving efficiency, maintenance, autonomous driving, etc. Usually the vehicle itself and its users are those which take direct advantage from these benefits. By leveraging Internet-of-Things (IoT) technologies, it is possible to abstract data and functionalities provided by on-board sensors and actuators exposing relevant services outside the vehicle to external cloud-based applications and other vehicles. With these technologies the vehicle is thus transformed in an IoT object which can be part of external IoT platforms. This work focuses on the design and implementation of an in-vehicle IoT platform which exposes internal functionalities as IoT services enabling also the concept of “Virtual Sensor”, which leverages sensor fusion techniques to provide enhanced services combining raw data coming from on-board devices. This IoT platform solution is validated through a use case in which virtual real-time pothole detection sensor is implemented to evaluate the road surface conditions. In such use-case, multi-source sensing information - coming from 6LoWPAN sensors as well as Smartphones and Inertial Measurement Units - is fused, enabling IoT applications such as cooperative safety and early road maintenance.

Abstract: Resource efficiency assessment methods, along with eco-efficiency assessment methods are needed for various industrial sectors to support sustainable development, decision-making and evaluate efficiency performance. The combination of eco-efficiency with efficiency assessment allows to identify major inefficiencies and provides means to foster sustainability, through the efficient and effective material and energy use. Despite the available information for decision making, this proves to be a difficult task in the manufacturing industry, therefore, there is a real need to develop and use optimization techniques to enhance resource efficiency. In this context, and due to the lack of simple and integrated tools to assess and optimize resource efficiency, crossing the different environmental and economic aspects, arises the need to develop optimisations models, enabling support and optimize sustainable decision making process and identification of potential improvements. The optimisation method should provide robust knowledge to support decision-making, allow comparability of the results and consider a cost-saving approach to help set priorities. Moreover, the optimisation techniques should centre the process through design/configuration of the production system, without considering time, in order not to limit the physical agents.