Asset Management

Maintenance of the infrastructure is a substantial cost for municipalities. It is a challenge to determine which infrastructure needs to be prioritized and what the current quality is of the infrastructure.  

In order to predict the quality of the infrastructure predictive models can be used. In this project a predictive model was developed aimed at predicting the quality of roads in the Municipality of Zoetermeer using data. 

In this regard a neural network model was developed using Tensorflow in Python. The model is intended to be used the Municipality of Zoetermeer as well as other municipalities and CROW. Currently the model is improved by investigating the possibility to add new data sources.  

Furthermore the tool is improved through the development of a frontend element, which enables users to easily determine the predicted quality of the roads.  

Dr. Raymond Hoogendoorn
Senior Researcher
Raymond Hoogendoorn is a senior researcher in the field of data science. In 2012 he completed his PhD cum laude at Delft University of Technology. He did this at the Transport and Planning department of the Faculty Civil Engineering an Geosciences. NWO sponsored his project which was aimed at mathematically modelling driving behaviour in case of adverse conditions (for example during an evacuation).  Raymond completed a post-doc and was Assistant Professor at Delft University of Technology in the field of Intelligent Transport Systems (autonomous vehicles). Currently he conducts research in the field of applied data science for health, urban living and smart-mobility applications.