This paper presents the developments achieved via the Social Cooperation Program “Intelligent Construction Sys- tem,” from three primary perspectives: environmental mea- surements, improvements in remote operability, and im- provements in efficiency and automation of remote opera- tion. For improvements in remote operation, environmental measurements of the disaster sites are critical. Therefore, a method to integrate the data from drones and ground-based vehicles in order to generate 3D maps was proposed. Another method for estimating the changes in soil volumes through a 3D map based on drone data was also proposed. Finally, to estimate the trafficability in disaster sites, a cone index-based method employing spectral images was proposed. Improving remote operability is essential to facilitate improved working conditions for operators. Considering this, a method provid- ing human operators with a bird’s-eye view of remotely op- erated machinery from any perspective was proposed. Addi- tionally, to avoid the tumbling of remotely operated machin- ery, a running stability presentation method was proposed; this method presented the human operator with a tumble risk index. For improving efficiency and automation, an au- tomatic camera control method, based on requirements of construction machine operators, was proposed. Using this method, the need for a dedicated human camera operator could be bypassed. Furthermore, for the automatic mea- surement of construction time and content, a method based on deep learning and using cameras for recognizing the ac- tions of construction machinery was proposed. Preliminary experiments on some of the proposed methods in real envi- ronments yielded promising results.