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To improve insufficient management by artificial management, especially for traffic accidents that occur at crossroads, the purpose of this paper is to develop a pro-active warning system for crossroads at construction sites. Although prior studies have made efforts to develop warning systems for construction sites, most of them paid attention to the construction process, while the accidents that occur at crossroads were probably overlooked.

By summarizing the main reasons resulting for those accidents occurring at crossroads, a pro-active warning system that could provide six functions for countermeasures was designed. Several approaches relating to computer vision and a prediction algorithm were applied and proposed to realize the setting functions.

One 12-hour video that films a crossroad at a construction site was selected as the original data. The test results show that all designed functions could operate normally, several predicted dangerous situations could be detected and corresponding proper warnings could be given. To validate the applicability of this system, another 36-hour video data were chosen for a performance test, and the findings indicate that all applied algorithms show a significant fitness of the data.

Computer vision algorithms have been widely used in previous studies to address video data or monitoring information; however, few of them have demonstrated the high applicability of identification and classification of the different participants at construction sites. In addition, none of these studies attempted to use a dynamic prediction algorithm to predict risky events, which could provide significant information for relevant active warnings.

The safety management of construction machines is of primary importance. Considering that traditional construction machine safety monitoring and evaluation methods cannot adapt to the complex construction environment, and the monitoring methods based on sensor equipment cost too much. This paper aims to introduce computer vision and deep learning technologies to propose the YOLOv5-FastPose (YFP) model to realize the pose estimation of construction machines by improving the AlphaPose human pose model.

This model introduced the object detection module YOLOv5m to improve the recognition accuracy for detecting construction machines. Meanwhile, to better capture the pose characteristics, the FastPose network optimized feature extraction was introduced into the Single-Machine Pose Estimation Module (SMPE) of AlphaPose. This study used Alberta Construction Image Dataset (ACID) and Construction Equipment Poses Dataset (CEPD) to establish the dataset of object detection and pose estimation of construction machines through data augmentation technology and Labelme image annotation software for training and testing the YFP model.

The experimental results show that the improved model YFP achieves an average normalization error (NE) of 12.94 × 10^–3, an average Percentage of Correct Keypoints (PCK) of 98.48% and an average Area Under the PCK Curve (AUC) of 37.50 × 10^–3. Compared with existing methods, this model has higher accuracy in the pose estimation of the construction machine.

This study extends and optimizes the human pose estimation model AlphaPose to make it suitable for construction machines, improving the performance of pose estimation for construction machines.

Construction safety management (CSM) has been intensively researched in the last four decades but hitherto mostly aimed at understanding root causes of accidents, recommending preventive measures and evaluating their implications. However, a systematic effort to present a comprehensive picture of construction safety research is hardly witnessed. Therefore, the study aims to investigate construction safety research contributors, ontologies, themes, evolution, emerging trends and future directions using quantitative and qualitative content analysis.

A total of 877 journal articles were extracted using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and Scopus literature database and were analyzed using VOSviewer and Nvivo tools to present a comprehensive picture of the CSM body of knowledge.

The study observed rapid growth in construction safety research with contributions from various countries, organizations and researchers. This study identified 3 research levels, 8 project phases, 10 project types, 6 research instruments and 19 research data sources along with their usage in the research domain. Further, the study identified 13 emerging research themes, 4 emerging research trends and an observed paradigm shift from reactive to proactive CSM approach.

The comprehensive study on the emerging themes and findings on proactive CSM has strategic implications to practice to incorporate safety. The identified future directions can assist researchers in bridging the existing gaps and strengthening emerging research trends.

The study presents a comprehensive picture of the CSM body of knowledge using the content analysis approach that was absent in past literature and opened future research avenues.

Measuring onsite productivity has been a substance of debate in the construction industry, mainly due to concerns about accuracy, repeatability and unbiasedness. Such characteristics are central to demonstrate construction speed that can be achieved through adopting new prefabricated systems. Existing productivity measurement methods, however, cannot cost-effectively provide solid and replicable evidence of prefabrication benefits. This research proposes a low-cost automated method for measuring onsite installation productivity of prefabricated systems.

Firstly, the captured ultra-wide footages are undistorted by extracting the curvature contours and performing a developed meta-heuristic algorithm to straighten these contours. Then a preprocessing algorithm is developed that could automatically detect and remove the noises caused by vibrations and movements. Because this study aims to accurately measure the productivity the noise free images are double checked in a specific time window to make sure that even a tiny error, which have not been detected in the previous steps, will not been amplified through the process. In the next step, the existing side view provided by the camera is converted to a top view by using a spatial transformation method. Finally, the processed images are compared with the site drawings in order to detect the construction process over time and report the measured productivity.

The developed algorithms perform nearly real-time productivity computations through exact matching of actual installation process and digital design layout. The accuracy and noninterpretive use of the proposed method is demonstrated in construction of a multistorey cross-laminated timber building.

This study uses footages of an already installed surveillance camera where the camera's features are unknown and then image processing algorithms are deployed to retrieve accurate installation quantities and cycle times. The algorithms are almost generalized and versatile to be adjusted to measure installation productivity of other prefabricated building systems.

The purpose of this paper is to investigate the critical time window for pro-active construction accident prevention and response. Large to small organisations throughout the entire construction supply chain continue to be challenged to adequately prevent accidents. Construction worker injuries and fatalities represent significant waste of resources. Although the five C’s (culture, competency, communication, controls and contractors) have been focusing on compliance, good practices and best-in-class strategies, even industry leaders have only marginal improvements in recorded safety statistics for many years.

Right-time vs real-time construction safety and health identifies three major focus areas to aid in the development of a strategic, as opposed to tactical, response. Occupational safety and health by design, real-time safety and health monitoring and alerts and education, training and feedback leveraging state-of-the-art technology provide meaningful predictive, quantitative and qualitative measures to identify, correlate and eliminate hazards before workers get injured or incidents cause collateral damage.

The current state and development of existing innovative initiatives in the occupational construction safety and health domain are identified. A framework for right-time vs real-time construction safety and health presents the specific focus on automated safety and health data gathering, analysis and reporting to achieve better safety performance. The developed roadmap for right-time vs real-time safety and health is finally tested in selected application scenarios of high concern in the construction industry.

A strategic roadmap to eliminate hazards and accidents through right-time vs real-time automation is presented that has practical as well as social implications on conducting a rigorous safety culture and climate in a construction business and its entire supply chain.

The purpose of this research is to examine one agency's experience with their early intervention program (EIP), exploring the specifics of the program as well as the characteristics of the officers who were identified by their EIP criteria.

Using data from calendar year 2000 that were provided from the Internal Affairs Bureau of a large Southern police department, the characteristics of EIP and non‐EIP flagged officers, the classifying criteria examined, and the issue of productivity and opportunity investigated as they related to the classification criteria.

EIP officers were more likely to be younger, male, and have fewer years of experience. Additionally, these officers made more arrests, filed more use of force reports, and used higher levels of force. All qualifications were based on the use of force. The findings highlighted the importance of considering the productivity of an officer along with the EIP criteria: opportunity (defined as the number of use of force reports filed) and the use of high force were inversely related. Among officers with the highest proportion of high force usage, none was classified as an EIP officer.

Findings are based on a single year from a single agency. No controls were able to be made for geographic assignment, potentially an important consideration.

A very useful source of information for agencies wishing to adopt or modify an EIP program.

As one of the first empirical analyses of EIPs, the research presented here sparks a debate on a number of issues, including the definition of “opportunity” and how agencies can improve their EIP systems.

Briefly reviews previous literature by the author before presenting an original 12 step system integration protocol designed to ensure the success of companies or countries in their efforts to develop and market new products. Looks at the issues from different strategic levels such as corporate, international, military and economic. Presents 31 case studies, including the success of Japan in microchips to the failure of Xerox to sell its invention of the Alto personal computer 3 years before Apple: from the success in DNA and Superconductor research to the success of Sunbeam in inventing and marketing food processors: and from the daring invention and production of atomic energy for survival to the successes of sewing machine inventor Howe in co‐operating on patents to compete in markets. Includes 306 questions and answers in order to qualify concepts introduced.

Develops an original 12‐step management of technology protocol and applies it to 51 applications which range from Du Pont’s failure in Nylon to the Single Online Trade Exchange for Auto Parts procurement by GM, Ford, Daimler‐Chrysler and Renault‐Nissan. Provides many case studies with regards to the adoption of technology and describes seven chief technology officer characteristics. Discusses common errors when companies invest in technology and considers the probabilities of success. Provides 175 questions and answers to reinforce the concepts introduced. States that this substantial journal is aimed primarily at the present and potential chief technology officer to assist their survival and success in national and international markets.

The main objective of this study is to develop a tsunami emergency response plan for a coastal community by adopting a community‐based disaster preparedness approach.

A multi‐strategy research design utilizing both quantitative and qualitative methods was used. The weaknesses and strengths of the different agencies involved in responding to the 2004 tsunami disaster were identified through a focus group discussion. A survey was used to assess the preparedness of the community. Tsunami awareness and education were imparted through lectures, sermons, radio talk shows, informal briefings, workshops and printed materials. Tsunami evacuation routes, safe zones, warning protocols and evacuation plans were finalized through a consultation process with the community. A tsunami evacuation plan was verified during a table‐top exercise and was tested through a drill.

It is evident from the study that a community‐based approach (where the local community is taken as the primary focus of attention in disaster reduction) to tsunami mitigation and preparedness is viable. This process has provided an opportunity for tapping traditional organizational structures and mechanisms (including formal and informal community leaders) and capability‐building activities with the community disaster committees and volunteers.

Tsunami 2004 is the first ever tsunami disaster experienced in the country and thus the study provides significant lessons learned from the event. The community‐based approach to disaster preparedness is not the current practice in the country. Thus, the study demonstrates that the approach is a viable tool to enhance community preparedness to tsunami and other types of disasters as well.

Gives an in depth view of the strategies pursued by the world’s leading chief executive officers in an attempt to provide guidance to new chief executives of today. Considers the marketing strategies employed, together with the organizational structures used and looks at the universal concepts that can be applied to any product. Uses anecdotal evidence to formulate a number of theories which can be used to compare your company with the best in the world. Presents initial survival strategies and then looks at ways companies can broaden their boundaries through manipulation and choice. Covers a huge variety of case studies and examples together with a substantial question and answer section.