[CS15-43] Development of the image processing method or estimating axel load by use of Deep Leraning
Keywords:Artificial Intelligence, Neural Network, Load Estimation, Traffic Load, Fatigue Damage
IoT technology is being developed dramatically in a civil engineering field. However the big data accumulated in the daily and regular maintenance activities is underutilized so far. Additionally, there are serious bottleneck, that is, manpower shortage for maintenance of huge number of existing civil engineering structures.
The authors developed an artificial intelligence system that is able to estimate axle load. The system is trained by big data which contains the captured image of overloaded vehicles and results of axle load measured from WEIGH-IN-MOTION. The accuracy of the system is about 60 % and issues for the accuracy improvement are discussed in this paper.
The authors developed an artificial intelligence system that is able to estimate axle load. The system is trained by big data which contains the captured image of overloaded vehicles and results of axle load measured from WEIGH-IN-MOTION. The accuracy of the system is about 60 % and issues for the accuracy improvement are discussed in this paper.
Please log in with your participant account.
» Participant Log In