—First of all, what kind of research do you do, Assistant Professor Kishimoto?

Kishimoto: My research focuses on urban planning for disaster mitigation using computer simulations. Specifically, I examine effective measures to reduce property and human damage during a major earthquake in the Tokyo Metropolitan Area, which is an urban area with a high density of buildings.

For example, the Tokyo Metropolitan Government has designated emergency transportation roads as lifelines for rescue operations following a major earthquake. If those roads become impassable, it would severely impact not only the transportation of emergency supplies but also rescue and firefighting activities. Therefore, preventing building collapses along those roads is essential to maintain their function during a large earthquake.

To address this, I simulate which buildings are likely to collapse based on their seismic resistance and which roads would be blocked by the debris from these collapsed buildings. These simulations, based on the data from past earthquakes, allow us to estimate the impact of such collapses on emergency transportation roads. Using these results, I collaborate with relevant departments of the Tokyo Metropolitan Government and incorporate the findings into urban planning to reduce disaster risks.

—When did this kind of research start?

Song: The state of communication radio waves can be expressed by channel state information (CSI). Around ten years ago, a tool that can obtain the CSI of Wi-Fi communication radio waves was released. Since then, research into the integration of communication and sensing has become popular around the world. Going forward, sensing is expected to become a common function of communication radio waves. I believe that all smartphones will be equipped with bio-sensing functions in about five to ten years.

In this way, sensing services will ultimately be provided by companies. The key to sensing will be how to process the acquired information and analyze it with better accuracy. To solve such issues, I am focusing on research for processing radio signals.

In the near future, millimeter wave base stations will be installed in various places, and I hope that we will be able to use these radio waves to detect people’s movements over a wide area, not just indoors.

—It sounds like your research is truly an initiative for realizing smart cities!

Kishimoto: If I may, I would like to ask a question to Assistant Professor Song. You said that Wi-Fi radio waves can detect people’s movements, breathing rate, and heart rate inside a room. However, wouldn’t there be interference from various sources such as refrigerators and microwaves within homes?

Song: Wi-Fi has two frequencies: 2.4 GHz and 5 GHz. Microwaves and other devices use the 2.4 GHz band and can cause interference to close frequencies. However, they can operate without interference if the frequencies are different enough.

Also, I am currently improving the accuracy of analysis by using AI to learn the data acquired through communication radio waves. AI learning will make it possible to estimate the correlation between changes in radio wave strength and phase and people’s health conditions based on sensing data.

Kishimoto: What about when there are many people in a room?

Song: Currently, we are able to make reliable estimates when there are only a few people in a room. Research is still being conducted on large numbers of people. However, after listening to what Assistant Professor Kishimoto said earlier, I am interested in building a sensor network. By processing the data form the sensor network, it might be possible to estimate the health condition of each individual, even when there are a large number of people in a room.