Indoor localization has gained importance as it has the potential to improve various processes related to the lifecycle management of facilities, such as the manual search to find assets. In the operation and maintenance phase, the lack of standards for interoperability and the difficulties related to the processing of large amount of accumulated data from different sources cause several process inefficiencies. For example, identifying failure cause-effect patterns in order to prepare maintenance plans is difficult due to the complex interactions and interdependencies between different building components and the existence of the related data in multiple, fragmented sources.
Building Information Modelling (BIM) is emerging as a method for creating, sharing, exchanging and managing the information throughout the lifecycle of buildings. Radio Frequency Identification (RFID), on the other hand, has emerged as an automatic data collection technology, and has been used in different applications for the lifecycle management of facilities. The previous research of the author proposed permanently attaching RFID tags to assets where the memory of the tags is populated with their accumulated lifecycle information taken from a standard BIM database to enhance various lifecycle processes. This thesis builds on this framework and investigates several methods for supporting lifecycle management processes of assets by using BIM, RFID and visual analytics. It investigates the usage of location-related data that can be retrieved from a BIM and are stored on RFID tags. It also investigates the usage of RFID technology for indoor localization of RFID-equipped assets using handheld readers. The research proposes using the location data saved on the tags attached to fixed assets to locate them on the floor plan. These tags also act as reference tags to locate moveable assets using received signal pattern matching and clustering algorithms. Additionally, the research investigates extending BIM to incorporate RFID information. It provides the opportunity to interrelate BIM and RFID data using predefined relationships. For this purpose, a requirements’ gathering is performed to add new entities, data types, relationships, and property sets to the BIM. Moreover, the research investigates the potential of BIM visualization to help facilities managers make better decisions in the operation and maintenance phase of the lifecycle. It proposes a knowledge-assisted BIM-based visual analytics approach for failure root-cause detection in facilities management where various sources of lifecycle data are integrated with a BIM and used for interactive visualization exploiting the heuristic problem solving ability of field experts
