AN ATTEMPT TO DEVELOP AN AUTOMATIC CONCRETE COMPACTION JUDGMENT SYSTEM BASED ON AI

Abstract

Even if high-quality materials are used and properly mixed, the full potential performance of the concrete will not be exhibited if the concrete is improperly placed and compacted. Conventionally, the degree and the completion time of concrete compaction have been determined by visual judgment and feeling based on the experience of engineers. In recent years, with the decrease in the number of engineers and work style reforms, it is required to improve the productivity of concrete construction, and it is desired to develop labor-saving or unmanned technology while ensuring the quality of concrete. The authors have devised and verified a system in which AI can replace the conventional concrete compaction judgement of engineers. As a result, it is shown that AI can realize the concrete compaction judgment close to that of the engineers by learning the training dataset consists of pairs of the frame image taken by the video camera and compaction judgment of engineers, and its usefulness was comfirmed through evaluation experiments.