Visual recording devices such as video cameras, CCTVs, or webcams have been broadly used to facilitate work progress or safety monitoring on construction sites. Without human intervention, however, both real-time reasoning about captured scenes and interpretation of recorded images are challenging tasks. This article presents an exploratory method for automated object identification using standard video cameras on construction sites. The proposed method supports real-time detection and classification of mobile heavy equipment and workers. The background subtraction algorithm extracts motion pixels from an image sequence, the pixels are then grouped into regions to represent moving objects, and finally the regions are identified as a certain object using classifiers. For evaluating the method, the formulated computer-aided process was implemented on actual construction sites, and promising results were obtained. This article is expected to contribute to future applications of automated monitoring systems of work zone safety or productivity.

Abstract:Recently, an increasing number of green residential buildings have been developed worldwide owing to active promotion from the authorities and increasing interest from customers. However, in the same way as traditional residential buildings, the construction of green residential buildings faces various risks. The aims of this study are to identify and assess the diverse risks in green residential building construction projects, compare their risk criticalities with those in traditional counterparts, and propose helpful risk mitigation measures. To achieve these goals, a comprehensive literature review was first conducted, and a questionnaire was then administered to 30 construction companies in Singapore. Survey results showed that "complex procedures to obtain approvals", "overlooked high initial cost", "unclear requirements of owners", "employment constraint", and "lack of availability of green materials and equipment" were the top five critical risks in green residential building construction projects. Survey results also showed that green residential building projects were facing risks at a more critical level than those traditional residential building projects. Additionally, this study proposed fourteen risk mitigation measures to tackle the risks in green residential building construction projects. This study has contributed to the body of knowledge by identifying and evaluating the critical risks and mitigation measures in green residential building construction projects. Meanwhile, the findings from this study can also provide an in-depth understanding of risk management in green residential building construction projects to practitioners and thus benefit the practice.

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