Detecting anomalous behavior in stadium crowds with location analytics based on data collected with Wi- Fi and Bluetooth sensors in the Amsterdam Arena.
In this project we are going to address this problem, using the Amsterdam Arena stadium as a living laboratory. Based on detection of Wi-Fi and Bluetooth signals from smart phones, we will follow visitors’ locations in real time. We will develop algorithms and software to process locations in real time and to detect “abnormal” behaviour of a crowd that could lead to a disaster. Existing simulation models will be used to model normal and abnormal behaviour in crowds. Based on the results, we will train classifiers to detect abnormal behaviour during a public event. Our ultimate goal, to be achieved in follow-up projects, is to develop a system that interacts with the crowd in order to prevent escalation of risk situations into actual disasters. Such system will direct (groups of) individuals, e.g. to alternative exits, to minimize congestions during an emergency situation, with mass communication devices like screens or personal devices like smart phones.
Intelligent Data-driven optimization of charging-infrastructure: IDO-Laad
IDO-LAAD is a subsidy project lead by HvA that aims to increase the efficiency and effectiveness of charging infrastructure in the Netherlands by developing insights, (data) experiments, measures, simulations and forecasts based on data derived from the charging infrastructure.