Double Degree Program - Recent developments, such as Smart Cities and Internet of Things (IoT), result in an increase in the application of sensor devices from 16 billion in 2014 to 40.9 billion forecasted in 2020. The role of sensor technology is increasing in importance due to the decreasing costs of acquiring sensors and due to more practical implementations that are available on the market. In the meantime, the introduction of integrated contracts demands Dutch contractors to ensure availability and reliability of infrastructural assets to the client. Dutch contractors face the need to realize smart and innovative solutions for Asset Management (AM). The use of smart sensor technology to detect and predict asset performances during the maintenance phase of road infrastructure projects is still in its development phase. Meanwhile, the application of sensors to establish an asset network offers a great potential to the construction sector. This Double Degree graduation work is a combination of two master studies from the Technical University of Delft: Construction Management and Engineering (CME) and Geomatics for the Built Environment. The purpose of this study is to conduct an in-depth analysis that specifically focuses on expansion joints to test the proposed theory and to evaluate the set requirements for Smart Asset Management (SAM) of Braaksma (2016). SAM is defined as the collection, analysis, sharing, and exploitation of sensor data to balance performance, costs, and risks in managing assets in order to perform maintenance at the right moment and the right location. This research answers the following research question: How can sensor technology be used in the construction sector to facilitate Smart Asset Management during the maintenance phase of road infrastructure projects? SAM is a combination of an individual Smart Asset (SA) and a collection of assets in a Smart Asset Network (SAN). An individual SA allows to collect and analyse data from attached sensors. A SAN shares and exploits relevant sensor data between assets mutually. This network allows indicating the performance of each asset, regardless of the number of attached sensors. A theoretical implementation of an SA, by means of a proof-of-concept, builds on the current methods of asset monitoring in the construction sector and on a developed monitoring system. The proof-of-concept is able to collect and analyse sensor data by executing multiple runs on simplified representations of expansion joints. The use of intra-correlation, which is the correlation between sensors and asset, supports to indicate the degradation of the expansion joint, despite addressed limitations of the test set-up. The research indicates four influential aspects to be considered when realising an operational use of the SA. These aspects are (1) to manage expectations of Asset Managers, (2) to collect relevant sensor data, (3) to define proper ways to handle data transfer, and (4) to adapt current SAM systems. A use case for the expansion joint in an SAN builds on the current situation of adopting asset networks and on the analysed alignment of standards in Building Information Modeling (BIM) and sensors. The use case defines the components that are taken into account when the user requests information from the SAM system. The use case introduces inter-correlation, which is used to determine the extrapolation of sensor data from one asset to the other. In addition, a developed class diagram describes the SAN data model and its relation to the SensorThings API model, a recently released sensor standard by the Open Geospatial Consortium (OGC). The class diagram defines the link between BIM and sensor models. The use case continues on the class diagram and describes how SAN allows measuring the performance of each asset. The research indicates four influential aspects to be considered when realising an operational use of the SAN. These aspects are (1) to manage the willingness of Asset Managers to work and rely on a SAN, (2) to integrate and interpret sensor and BIM data sources, (3) to detect inter-correlation and needed calculation techniques, and (4) to determine the representativeness of sensor data. In addition, the requirements set for SAM have been evaluated by elaborating on the findings of the research into SA and SAN. The results serve as input for the research of Braaksma (2016). In conclusion, implementing the SAM scenario answers the research question by identifying SA and SAN as a way to incorporate sensor technology: it is able to measure asset performances and supports the realisation of SAM decision-making. This research investigates the added value of attaching sensors to expansion joints and provides a total of eight influential aspects to be considered when realising a SA and SAN for expansion joints. Also, this research includes a view on the extent to which components of BIM relate to sensor technology. The combination of using intra-correlation, inter-correlation and extrapolation is utilised in the developed use case. These results support the construction sector in the obtained responsibility to ensure availability and reliability of assets. Properly addressing the identified aspects of influence, acknowledging the importance of users in the process and investigating how to apply intra-correlation, inter-correlation and extrapolation in a pilot project are focal points for research in the near future. This research provides an insight in maintaining assets – expansion joints in specific – in such a way that individual asset performances can be detected and predicted, utilising the potential of sensor technology in assets networks.