Intelligent technologies for construction machinery using data-driven methods

Along with the rapid development of infrastructure worldwide, traditional manual operations have been a concern that restricts the high efficiency, safety, and quality of construction sites. Benefiting the significant improvements of smart manufacturing and artificial intelligence (AI), intelligent construction machinery has been considered a novel solution to address human operations' shortcomings, which are mainly reflected in prognostic and health management (PHM), environment perception, and automation control. Relevant data-driven methods have achieved important advancement while lacking a comprehensive summary. Hence, this paper surveyed a wide range of research works reported in the literature which realized few-manned or unattended construction sites. At first, several widely-used AI algorithms and their variations were introduced. Secondly, three aspects were discussed in detail: PHM applications based on experiment environments, environment perception systems in terms of information mediums, and automation control methods according to training mechanisms. Finally, several research outlooks and challenges were put forward.