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Optimising driver behaviour

The goal of this project is to minimise energy consumption of the electric buses, for the city of Eindhoven, through the development of a method to analyse data from several sources which generates insights in the relation between energy consumption (driving behaviour) and external factors, based on Machine Learning (ML) / Deep Learning techniques.

We will share our research during the talk of Petra Heck in research theme Artificial Intelligence, click here to learn more about this session

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All projects:

Aquarium Blue Team training Change Management Game Cities: Venlo Cooperative test robot II Corona speedtester Challenge Covid19 fast but secure testing Dashboard on Animal welfare Data Driven HLB Van Daal Data Quality Datics Butterfly SDM De Lockdown een tikkie terug Detect trends on a cliënt level Digital Authorization System Egg picking robot Eye-tracking FHICT Netlab automation FntsPresent Fontys Goede Start Global Goals Community Global Goals Community (GGC) HTES Pose tracking HTES1 Monitoring Robot Indoor Positioning at Low speed Industry 4.0 AAS security Intersect IoT security Machine learning in the aviation sector Machine learning models for object recognition – flag icon, 2D/3D objects Machine Management System Measure flower richness in agricultural areas Monitoring network New online identity Ruud Aerts sport Object Detection Offline OnScene Operation Room Optimising driver behaviour OWC Nepal data platform OWC Rwanda fundraising app Pharmapartners security PIDZ Loyalty Research Project AutoRepo Project Process-Mining Project Swimm PSV - My stadium Real Time Data Dashboard Research Digital Twins RigS Robot4Care Slimmer Kiezen Smart Office v2 Transferability and valorization document Smart Tactical Robot Student AI Learning Support (TEC) SVB Talent Engagement Branding Taxi on Spot Urban beamer Virtual Influencing Vitality Living Lab Wijkbeweegkaart Yokufa Youth performance prediction