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Bibliometric analysis, scientometrics and metasynthesis of Internet of Things (IoT) in smart buildings
Purpose: The Internet of Things has made the shift to the digital era possible, even though the Architecture, Engineering, and Construction (AEC) sector has not embraced nor integrated it within the core functions compared to other sectors. The need to enhance sustainable construction with the adoption of Internet of Things in this sector cannot be overemphasized. However, the real-world applications of Internet of Things in smart buildings remain relatively unexplored in the AEC sector due to several issues related to deployment and energy-saving potentials. Given these challenges, this paper proposes to identify the present state of development and research in Internet of Things and smart buildings, and identify Internet of Things clusters and applications in smart buildings.
Design/methodology/approach: Bibliometric analyses of papers from 2010 to 2023 using the Scopus database and scientometric evaluations using the VosViewer software were undertaken. The proper search keyword was identified by using the phrases “ Internet of Things” and “Smart Building”. A total of 1158 documents in all, written by 3540 different writers, representing 2285 different institutions from 97 different countries were looked at. A metasynthesis was conducted and a system of Internet of Things applications in a smart building is illustrated.
Findings: The development of IoT and Smart Buildings is done in two phases: initiation (2010-2012) and development (2013-2023). The IoT clusters comprised internet of things, energy efficiency, intelligent buildings, smart buildings, and automation; while the most commonly used applications were analysed and established. The study also determined the productive journals, documents, authors, and countries.
Research limitations/implications: Documents published in the Scopus database from 2010 to 2023 were considered for the bibliometric analysis. Journal articles, conference papers, reviews, books, and book chapters written in English language represent the inclusion criteria, while articles in press, conference reviews, letters, editorials, undefined sources, and all medical and health publications were excluded.
Practical implications: The results of this study will be used by construction stakeholders and policymakers to identify key themes and applications in IoT-enabled smart buildings and to guide future research in the policymaking process of asset management.
Originality/value: The study utilised bibliometric analysis, scientometrics and metasynthesis to investigate internet of things applications in smart buildings. The study identified internet of things clusters and applications for smart building design and construction.
Keywords: Artificial intelligence, bibliometrics, internet of things, network sensors, smart buildings
Monitoring Workers on Construction Sites using Data Fusion of Real-Time Worker’s Location, Body Orientation, and Productivity State
Traditionally, on-site construction production monitoring depends primarily on manual processes that are time-consuming and error-prone. State-of-the-art technologies have been utilized lately to improve these processes to support timely decisions pertinent to the productivity and safety of onsite operations. This research introduces a novel construction site monitoring system to track workers' location, body orientation, and productivity state. The developed system uses Bluetooth Low Energy (BLE) based reference transmitting beacons fixed on job sites and a set of receiving beacons mounted on workers’ hardhats, chests, and wrists. The system works via three modules, i.e. (i) RTLS (Real-Time Location System) module; (ii) body orientation detection module; and (iii) productivity state detection module.
The RTLS module is developed to continuously track the location of the workers and subsequently extract the actual labor workspaces. The RTLS is explicitly designed for construction by satisfying requirements for widespread on-site adoption, including cost efficiency, deployability, scalability, adjustability to the construction site dynamism, and the expected accuracy. The main features of the developed RTLS are (i) substituting commonly used BLE receivers with BLE receiving beacons; (ii) proposing a modular infrastructure placement strategy; (iii) deploying Trilateration and Min-Max as localization techniques; (iv) post-processing the worker’s estimated locations.
As per the body orientation detection module, it identifies workers' body orientation on the job sites, using the impacts of signal blockage by a human body to identify an approximate worker's body orientation. It works based on geometrical relationships and Received Signal Strength Indicator (RSSI) values between the chest-mounted receiving beacon and the reference transmitting beacons. Last but not least, the productivity state detection module determines workers' productivity state (i.e., direct work, support work, delay) and travel state, using the accelerometer sensor embedded in the body-mounted receiving beacons. Consequently, the collected data of the system modules are fused to augment real-time knowledge of workers' status on job sites