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

For more than a decade, the construction industry had set the target to reduce the utility damage numbers to zero. The sector supported the initiation of the WIBON law (originally called WION) that regulated the utility location and planning information exchange between stakeholders (utility and excavation companies); introduced the utility statutory record exchange system KLIC in the eighties; established the KLO (utility sector board, kabel en leidingoverleg), and took many initiatives to raise risk awareness.

Although it is undeniable that the sector has professionalized and the Netherlands is an international front runner regarding the exchange of utility data, it remains very challenging to identify risks and avoid excavation damages.

The challenge

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 executive organization of WIBON, and operator of the KLIC-data exchange system, the Kadaster can access excavation process data to analyse, for example, patterns in, and causes of, past excavation incidents. By integrating this information with other geo-data (such as infrastructure maps, maintenance data, information about excavation techniques, historical digging or incident data) it may become possible to better sensitize the industry toward potential threats to excavation damage, or even predict incidents.

The challenge for the sector is to identify what data and which methods can be used to establish a model/platform that could support this analysis and prediction.

This culminates in the following goal of this PDEng, which is 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 sites.