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As construction projects increase in complexity, there are growing challenges with conventional monitoring methods in terms of efficiency, safety, and competitiveness. Traditional supervision techniques are labour-intensive, intermittent, and prone to errors. Hence, this study statistically evaluates the potential advantages of photogrammetry, sensors, and algorithms to enable continuous automated monitoring. The results of this survey were analysed to compare manual and automated monitoring systems. The outcome shows that the Malaysian construction industry is aware of Automated Monitoring Innovations for Efficient and Safe Construction Practices. The top ranked factor was Photogrammetry which had a relative importance index (RII) of 0.821 for straightforward site monitoring and 0.812 for accelerated 3D BIM modelling. The RII for sensors to track labourers, apparatus, and progress in real time was 0.82, while the RII for hazard anticipation was 0.796. Automation achieved a reduction in fatigue by 0.784, labour intensity by 0.792, and time demands by 0.768, as measured by the RII. A conceptual framework is developed that incorporates measurable improvements in schedules, safety, and quality control. Automated solutions, as opposed to human examinations which are prone to error, provided exhaustive geographical data and ongoing surveillance notwithstanding obstacles pertaining to cost, cybersecurity, privacy, and integration. Construction monitoring must incorporate new technology, strategic change management, data investments, and supporting regulations to increase profitability, safety, and efficiency as competition and complexity increase.
Musarat et al. (Tue,) studied this question.