Smart City Technologies

Pedestrian tracking has become increasingly important in recent years to realize human-centric applications such as crowd navigation, facility design, evacuation planning, and path analysis. We propose a novel system that simultaneously tracks pedestrians and crowds using a laser range scanner (LiDAR). When the crowd density is not relatively high, the proposed system accurately captures the movement trajectory of each individual to achieve granular path analysis, while when the crowd density is extremely high, the system automatically switches to an algorithm that accurately estimates the number of pedestrians in the area. In addition, by capturing and sharing indoor human behavior and social information with LiDAR and multiple smartphones, "personal + crowd + social" navigation can be realized, and demonstration tests are ongoing in a commercial building in Osaka.

We are conducting research on disaster prevention and mitigation technologies using information communication and sensing technologies. Every year in Japan, torrential rains and typhoons cause flooding, which results in a lot of damage. When damage occurs, what is important is how quickly and correctly we can assess the damage. The more quickly and accurately we can assess the situation, the less time it will take to rescue people, and the more accurately we can allocate limited resources such as people and equipment. Currently, however, it takes a long time to assess the damage in detail, and when people are dispatched, secondary damage and human costs are incurred. In response to this, we are conducting research on the use of drones to efficiently assess the situation during a disaster.

We are conducting research on achieving energy conservation and improving quality of life in households without imposing any burden on residents by installing various sensors to monitor their activities. Our work focuses on developing methods to interpret resident behavior from ambiguous sensor data, such as motion sensors, and establishing a framework for determining acceptable behavior patterns based on the analysis of collected sensor data.

We are engaged in research on "Digital Twin" technology, which aims to replicate all people and objects in the real world in a virtual space in real time. This allows for simulations and analyses within the virtual environment, with the results being fed back into the real world.