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The purpose of this study is to monitor the progress of construction activities in an automated way by using sensor-based technologies for tracking multiple resources that are used in building construction.

An automated on-site progress monitoring approach was proposed and a proof-of-concept prototype was developed, followed by a field experimentation study at a high-rise building construction site. The developed approach was used to integrate sensor data collected from multiple resources used in different steps of an activity. It incorporated the domain-specific heuristics that were related to the site layout conditions and method of activity.

The prototype estimated the overall progress with 95% accuracy. More accurate and up-to-date progress measurement was achieved compared to the manual approach, and the need for visual inspections and manual data collection from the field was eliminated. Overall, the field experiments demonstrated that low-cost implementation is possible, if readily available or embedded sensors on equipment are used.

Previous studies either monitored one particular piece of equipment or the developed approaches were only applicable to limited activity types. This study demonstrated that it is technically feasible to determine progress at the site by fusing sensor data that are collected from multiple resources during the construction of building superstructure. The rule-based reasoning algorithms, which were developed based on a typical work practice of cranes and hoists, can be adapted to other activities that involve transferring bulk materials and use cranes and/or hoists for material handling.

The main purpose of this study is to present an overview of the state of the art of the RFID technology in terms of data storage approaches in construction cases, and to identify the factors that require different approaches to data storage (e.g. on tags or on a remote database) in RFID applications in the construction industry.

A literature survey was conducted and the contexts of 37 construction industry cases were investigated to determine the factors that affect the decision of data storage approach and the types of information groups that were stored in each case. Additionally, 79 cases were reviewed from other industries to provide insights.

The literature review showed that, many cases in the construction industry preferred storing additional data on RFID tags such as identification, technical and historical information. The factors affecting the selection of data storage approach in RFID applications were identified: application environment, cost efficiency, multiple number of parties, need for monitoring up‐to‐date progress data, collecting environmental conditions, in situ (on‐board) data storage, industry‐related specifications, and reading range requirement.

The high proportion of cases which stored data on tags demonstrate that there is a need for tags/storage media that are specially designed for the construction industry because most tags currently have either minimum or limited memories.

The analysis of the investigated cases and the factors that were identified to be affecting the data storage approach decision making can assist construction practitioners and owners in selecting an appropriate data storage approach for their projects.

This paper aims to identify the local information items that are needed by search and rescue (S&R) teams for an effective disaster response following an earthquake. Currently, it is a challenging and time‐consuming task to collect most of this information from a disaster environment. It was envisioned that the local information identified can be stored on distributed databases that are placed in the buildings and will be used to improve S&R operations.

The information items are obtained through a literature review and via interviews conducted with experts from disaster response organizations. The data collected were triangulated to generate a data model, which was then validated internally and externally by expert feedback.

A data model including a detailed list of information items required during S&R operations was generated, along with justification of the information needs. The findings show that not only information related to buildings, but also other information related to the residents and the contents of the buildings are needed, such as residents' health information, and hazardous materials and their specific locations.

The data model presented can be used by researchers to further develop systems that can be used during an earthquake.

Previous studies have only provided a list of some important local information groups to be stored; however, they do not include in‐depth studies on the information needs of S&R teams following an earthquake. In this paper, information needs were fully explored and elaborated, and a data model was developed covering information items required for effective earthquake S&R.