PDEng position: Data-driven prediction and reduction of excavation damages

Over the past five years, the excavation damages numbers have not decreased significantly. Authorities (Agentschap Telecom, and the Ministry of Economic Affairs) have raised their concerns about this since it is likely that the total work volume of excavation work will grow in the upcoming years. It thus becomes even more important to identify and predict excavation damages.

As the statutory owner of the utility exchange system KLIC, the Kadaster has the unique position to analyse patterns and root causes. They may be able to predict damage based on geo-data and the project information that stakeholders upload to their KLIC system before they perform digging activities. By combining census data, land parcels, infrastructure maps, maintenance data, historical incident data it may, for example, be possible to better sensitize the industry toward potential threats to excavation damage.
The challenge for Kadaster is to identify what data and which methods can be used to establish a model/platform that could support this analysis and prediction. This project follows a design science approach, in which you are expected to explore the problem context and literature, then iteratively make an innovative design of the data-driven approach, and validate it in a real-life setting. You will primarily focus on integration and analysis of (geo) data, and depending on the needs of the project, may extend this to software prototype development. You will work closely with professionals from Kadaster and Agentschap Telecom and spend around 50% of your time at the Kadaster office (Apeldoorn), and 50% at the University of Twente.

Goal

This PDEng, therefore, aims to develop a (geo) data-driven model/platform to identify patterns and causes of damage and make predictions about the likelihood that excavation damages occur on construction site.