Due to the large number of people wishing to attend, we have increased the capacity of the venue.For "R&D on Learning-Based Percussive Analysis Technology," the presenter has been changed due to unavoidable circumstances.
For details, please check the program.
In Japan, many bridges, tunnels, and other items of public infrastructure were constructed during an era of rapid growth; now, they are all becoming superannuated concurrently. How to maintain and manage this infrastructure has become an urgent social issue; similar issues have also arisen regarding not only large structures, but also types of infrastructure such as water pipes and power poles. Moreover, in some fields, such as power-plant and industrial infrastructure, experienced engineers are in short supply; consequently, some tasks are approaching the limits of conventional labor-intensive maintenance. Under these circumstances, there is a need to shift from after-the-fact response to pre-emptive maintenance. Accordingly, expectations are high regarding the use of artificial intelligence that can monitor large volumes of sensor data.
For this seminar, we have invited Professor Takehisa Yairi (University of Tokyo), a researcher at the forefront of this field. Professor Yairi will give an overview of abnormality detection methods based on machine learning, and present examples of applications. We will also present examples of the latest research by AIST.