Het project stelt een nieuw multi-drone scenario voor om een samenwerkend netwerk te creëren.

Bicycle manufacturing currently falls behind the fast technological developments in automotive industries. We propose to design, develop and test a smart cycling eco-system where bicycles communicate in realtime with each other, and with the urban transport infrastructure (e.g. traffic lights) to optimize the use and improve traffic safety, economical value, and efficiency. This require technologies and mechanisms to allow monitoring the bike, understanding the cyclist and the context, as well as data sharing between cyclists, industry, service providers, government, and urban planners. The new eco-system can drive decision-making, behaviour incentivisation, and ultimately investment, across government, and beyond. A key ingredient is an AI-enabled IoT ecosystem in which data is securely collected, shared, processed in combination with other data sources, and made available to establish new services. This allows to reliably identify relevant events (like dangerous situations), detect trends (like decreasing performance of components, allowing maintenance to be performed in time), and give new insights to the user (such as health and performance).

Production processes can be made ‘smarter’ by exploiting the data streams that are generated by the machines that are used in production. In particular these data streams can be mined to build a model of the production process as it was really executed – as opposed to how it was envisioned. This model can subsequently be analyzed and stress-tested to explore possible causes of production prob-lems and to analyze what-if scenarios, without disrupting the production process itself. It has been shown that such models can successfully be used to diagnose possible causes of production problems, including scrap products and machine defects.