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This paper looks at the implications of increases in system speed and density for the interconnection system, noting particularly the increased requirements placed on the substrate and tracking system. It reviews the properties required of substrates and the limitations derived from the materials used and the processes needed to put tracks on them. Those areas where these requirements are in conflict are highlighted, including such low technology problems as the limited size availability of substrate prepregs which may limit the tracking density achievable on the newer, more advanced low dielectric materials. Some limitations and trade‐offs are identified.

This paper aims to present a highly accessible and affordable tracking model for earthmoving operations in an attempt to overcome some of the limitations of current tracking models.

The proposed methodology involves four main processes: acquiring onsite terrestrial images, processing the images into 3D scaled cloud data, extracting volumetric measurements and crew productivity estimations from multiple point clouds using Delaunay triangulation and conducting earned value/schedule analysis and forecasting the remaining scope of work based on the estimated performance. For validation, the tracking model was compared with an observation-based tracking approach for a backfilling site. It was also used for tracking a coarse base aggregate inventory for a road construction project.

The presented model has proved to be a practical and accurate tracking approach that algorithmically estimates and forecasts all performance parameters from the captured data.

The proposed model is unique in extracting accurate volumetric measurements directly from multiple point clouds in a developed code using Delaunay triangulation instead of extracting them from textured models in modelling software which is neither automated nor time-effective. Furthermore, the presented model uses a self-calibration approach aiming to eliminate the pre-calibration procedure required before image capturing for each camera intended to be used. Thus, any worker onsite can directly capture the required images with an easily accessible camera (e.g. handheld camera or a smartphone) and can be sent to any processing device via e-mail, cloud-based storage or any communication application (e.g. WhatsApp).

Construction suffers from “peculiarities” that concern the temporary natures of the construction site, project teams and unique product design. Considering the digital transformation of construction, new solutions are being investigated that can provide consistent data between changing projects. One such source of data manifests in the tracking of logistics activities across the supply chain. Construction logistics is traditionally considered a site management activity focused solely on the “back end” of projects, but an expanded logistics focus can unlock new avenues of improvement. This study aims to understand the requirements and benefits of such a consistent thread of data.

From a research project with one of Australia’s largest contracting companies, this paper details a series of construction tracking tests as an empirical case study in using Bluetooth low energy aware tracking technology to capture data across the manufacture, delivery and assembly of a cross-laminated timber structural prototyping project.

The findings affirm the tracking of expanded logistics data can improve back-end performance in subsequent projects while also demonstrating the opportunity to inform a project’s unique front-end design phase. The case study demonstrates that as the reliability, range and battery life of tracking technologies improve, their incorporation into a broader range of construction activities provides invaluable data for improvement across projects.

As a live case study, this research offers unique insights into the potential of construction tracking to close the data loop from final site assembly back to the early project design phase, thus driving continual improvement from a holistic perspective.

The future construction site will be pervasive, context aware and embedded with intelligence. The purpose of this paper is to explore and define the concept of the digital skin of the future smart construction site.

The paper provides a systematic and hierarchical classification of 114 articles from both industry and academia on the digital skin concept and evaluates them. The hierarchical classification is based on application areas relevant to construction, such as augmented reality, building information model-based visualisation, labour tracking, supply chain tracking, safety management, mobile equipment tracking and schedule and progress monitoring. Evaluations of the research papers were conducted based on three pillars: validation of technological feasibility, onsite application and user acceptance testing.

Technologies learned about in the literature review enabled the envisaging of the pervasive construction site of the future. The paper presents scenarios for the future context-aware construction site, including the construction worker, construction procurement management and future real-time safety management systems.

Based on the gaps identified by the review in the body of knowledge and on a broader analysis of technology diffusion, the paper highlights the research challenges to be overcome in the advent of digital skin. The paper recommends that researchers follow a coherent process for smart technology design, development and implementation in order to achieve this vision for the construction industry.

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.

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 meat industry is seeking to establish reassurance on traceability and production techniques that may help to promote confidence in the integrity and origin of their products. This paper reviews research and development activities for traceability and trackability in the meat industry. Achievements of individuals and research groups developing tools and techniques to improve the production process in handling and cutting meat portions for end users are discussed. In addition software/hardware, logistics and technical requirements for tracking material in a production process are introduced. With the aid of such established tools and techniques coupled with novel proposals, the authors offer a practical solution for the development of a tracking and traceability system within the meat industry. The proposed prototype system is capable of identifying and handling a product and the information attached to it throughout the production process to retail packs.

Tracking of shipments is an important element of customer service in the transportation industry; and essential for logistics services as merge‐in‐transit. However, contemporary tracking systems are designed for use within a single company, and are thus invariably inadequate for multi‐company environments. The single company focus has led to a reduced span of monitoring and a diluted accessibility of information due to proprietary tracking codes and information architectures centred on the tracking service provider. This paper presents a novel forwarder‐independent approach for solving the difficulties of tracking in multi‐company supply networks. The research argues that the proposed tracking approach is superior to contemporary approaches for material flow tracking in short‐term multi‐company distribution networks.

Given increasing user aspirations for comfort, connectivity, health, safety and security, the building services subsector now plays an even greater role in construction. It also contributes heavily to construction debris. Hypothesising that improved materials control can help reduce construction debris considerably, this paper aims to investigate relevant critical production shortcomings that generate construction debris in building services works.

Relevant previous research studies on main causes of waste are first reviewed. Findings from a brainstorming exercise at a focus group meeting provide the basis for a series of structured face‐to‐face interviews with experienced site supervisors. Subsequent analysis of the interview findings, together with deductive reasoning, leads to the development of the proposed improvement strategies.

The most significant causes of production shortcomings identified in the study are poor coordination of processes or trades, inappropriate site storage and inadequate protection of materials. Industrial management principles help to develop suitable building services storage principles and to propose an industrial flow pattern incorporating barcoding and RFID tracking technologies.

These findings are a useful comparative reference for other countries, where the study methodology may be replicated to generate region‐specific findings.

By applying the suggested proposals at the material control stage, this important but little studied subsector can both reduce production shortcomings and help lessen the burden on local landfills by reducing “conflicts” between competing resources and storage areas, and by the early mobilisation of specialist contractors to resolve uncertainties and reduce rework.

The purpose of this paper is to discuss an integrated decision analysis framework for the investment justification of implementing alternative information and communication technology (ICT)-based logistics systems in the construction industry so as to enhance the decision-making process in selecting the best alternative.

An integrated framework is proposed that is composed of a set of interrelated evaluation and analysis techniques that allow the identification and quantification of costs, benefits and risks involved in implementing ICT systems to mitigate problems that hinder the efficient operation of construction logistics. Such techniques include decision trees and multi-attribute decision-making under uncertainty that can be applied to the logistics planning of any new build construction project.

The probabilities of providing benefits vary among the alternatives, and the probabilities will replace the uncertainties surrounding the impacts of the alternative ICT systems in addressing the identified construction logistics problems with chance events so as to estimate the expected cost of each alternative with respect to each selection attribute.

This paper shows that it is almost certain that the analysed alternative ICT system will provide benefit because its probability of benefit is almost equal to 1.

The framework captures the existing problems of logistics in construction process, potential solution that can address the problems through the implementation of ICT systems and the decision-making process in the selection of appropriate ICT solution. The output of the framework will help to make knowledge-based decision in selecting the best ICT system for addressing construction logistics problems.