This year's unusually hot spring has ended and the rainy season has begun. "Your country's four seasons are beautiful." It is nice to hear overseas visitors compliment Japan. However, transition from spring into summer brings intensified climatic activities, foreboding the upcoming torrential downpour and typhoon season.
In recent years, we have seen locally-concentrated torrential rains which have lasted several days. In addition to affecting urban transportation systems, such extreme weather sometimes causes large-scale disasters, such as river flooding and mudslides. What is frightening about natural disasters is that they are powerful enough to destroy large structures like roads and bridges and their potential damage may spread at a faster than expected speed.
We cannot prevent natural disasters from occurring, but we can predict their occurrence and scale and prepare countermeasures. We now have various information and communication technology (ICT) solutions that were not available 10 years ago. This article will introduce ICT solutions for disaster prevention and mitigation, which reduce the amount of damage caused by natural disasters or avoid damage altogether.
Detecting Signs of Disasters Efficiently at a Low Cost
There are primarily two types of ICT solutions for disaster prevention and mitigation. The first one is real-time monitoring to detect signs of a disaster; the second one is disaster simulation to prepare for future natural disasters.
Real-time monitoring is designed to quickly detect the occurrence or an abnormality that indicates a sign of a disaster. Early detection enables evacuating from the disaster area before the condition worsens as well as taking measures to prevent the damage from spreading.
One example of ICT-based systems for detecting abnormalities is infrastructure status monitoring. Sensors with communication capability are embedded in infrastructure like bridges and support posts to continuously monitor conditions. Data gathered by the sensors are then analyzed to detect any sign of strength deficiency due to degradation over time or other causes. The system gathers a massive amount of sensing data and carries out big data analysis in consideration of the environment and structure strength at the time. It allows reinforcement work before strength deficiency reaches a critical point.
A system for detecting the signs of a natural disaster works in a similar manner. Sensors are embedded in relevant infrastructure to continuously monitor the condition. Sensing data that have been collected are analyzed to detect any sign of a disaster. For example, when there is a danger of flooding caused by heavy rain, monitoring river water levels with sensors enables finding signs of flooding.
The issue here is the costs associated with deploying sensors. For example, using fiber optics for measuring water levels in drainage pipes requires dedicated cables, which are very costly to install. Using battery-powered sensors, on the other hand, requires frequent battery changes, which gives rise to high maintenance costs.
Fujitsu's Sewer System Flood Detection Solution solves the cost problem. A water level sensor is attached to an iron manhole cover and data of water levels are transmitted to a server periodically via the Internet and accumulated. When water reaches the pre-set level, an alert is sent to personnel in charge of disaster prevention.
With this solution, to measure water levels, existing iron manhole covers are replaced with special ones to install water-level measuring devices (water level sensor, sensor node (wireless communications device), etc.). Therefore, the system does not require major construction work, keeping implementation costs down. Moreover, in addition to a battery, water-level sensors are also powered by a thermoelectric converter unit, which efficiently converts energy arising from temperature changes on the iron manhole cover into electricity by using thermal storage material. This system decreases the frequency of replacing batteries, thereby reducing maintenance costs as well. From the result of a field trial conducted in the City of Koriyama in Fukushima Prefecture, Fujitsu Laboratories estimated that the thermoelectric converter extended the battery replacement cycle to 5 years.*
Costing less than conventional methods, the system quickly detects sudden rises in drainage pipe water levels, enabling a quick response to reduce flood damage caused by locally-concentrated torrential downpours.
- *: The frequency of battery replacement may vary depending on climate conditions and device settings.
Predicting Tsunami Damage and Simulating People's evacuation during Disaster
Since the Great East Japan Earthquake of 2011, a tsunami-resistant community has been proactively promoted as part of large-scale natural disaster planning. Japan has rolled out infrastructure for offshore tsunami observations, and to utilize this infrastructure for disaster mitigation the development of a broad range of tsunami prediction methods is being advanced.
In Japan, with its diverse topographical features, there are significant differences among each region with regard to the degree of tsunami risk and level of urgency for evacuations in the case of a tsunami, and moreover, with the degree of difficulty in predicting tsunamis. For example, simulating a major earthquake in the Nankai Trough, it is anticipated that there will be regions where a tsunami would hit within minutes following an earthquake, while it may take over an hour to reach Kawasaki or other parts inside Tokyo Bay. In order to more effectively implement measures to reduce disaster risk from a major tsunami that could occur in the future, a system requires predictions that consider the characteristics of each region in addition to the present prediction system that covers the entire country.
Here, I will introduce one government-industry-academia project that uses regionally-customized tsunami predictions for the Kawasaki coastal zone. In the Kawasaki coastal zone, the project uses tsunami inundation and human evacuation simulation technologys, which are jointly developed by the International Research Institute of Disaster Science at Tohoku University and Fujitsu Laboratories, to explore an earthquake and tsunami threat envisaged by the Earthquake Research Institute at the University of Tokyo. The specific themes being considered are: (a) increasing the accuracy of predictions of wave profiles at the coast, (b) real-time flooding analysis, (c) ways of utilizing regional prediction information and (d) understanding the characteristics of coastal tsunami behavior.
What is interesting about the project is that it simulates people's behavior and movement as well as the tsunami itself, such as changes in waveform and areas to be flooded. If we can simulate how people evacuate and what turmoil is created when a tsunami strikes, it tells us how certain changes in the community facilitate disaster mitigation. This provides us with valuable data/information that directly helps community development.
Disaster simulation is often used for planning preemptive disaster prevention measures. The latest ICT like supercomputers now enables us to run accurate real-time simulations. Using the observation data for predicting disasters, we will be able to quickly execute exactly the right evacuation to save our lives and disaster mitigation measures, even when facing natural disasters on a scale not previously experienced.
Be Prepared for Emergencies
Implementing a system for finding signs of natural disasters and creating communities that reflect the result of disaster simulation will definitely make our communities safer than ever. However, the most important thing during a disaster is for individuals to make the right decisions and take the right actions. Even if we have a disaster response solution, unless we actively use it and act on it, disaster cannot be prevented or mitigated. It may be a good idea to start by checking what disaster solution is implemented in the area where your home or office is located and preparing an action plan in case of an emergency.
- Author Profile
Nikkei BP Intelligence Group Clean Tech Laboratory Chief Research Officer
- Mr. Hayashi joined Nikkei BP after graduating from the School of Engineering at Tohoku University in 1985. As a reporter and the editor-in-chief for the outlets such as Nikkei Datapro, Nikkei Communications and Nikkei Network, he has covered stories and contributed articles on topics encompassing cutting-edge communications/data processing technologies, as well as standardization/productization trends. He consecutively held the post of chief editor for Nikkei BYTE from 2002, Nikkei Network from 2005, and Nikkei Communications from 2007. In January 2014, he became the Chief Director of Overseas Operations after acting as the publisher for magazines including ITpro, Nikkei Systems, Tech-On!, Nikkei Electronics, Nikkei Monozukuri, and Nikkei Automotive. He has served at his present post since September 2015. Since August 2016, Mr. Hayashi has been writing a regular column, "Creating the Future with Automated Driving," in The Nikkei Digital Edition. Furthermore, he published the "Overview of International Automated Driving Development Projects" in December 2016 and the "Overview of International Automated Driving/Connected Cars Development" in December 2017. Mr. Hayashi has also been a judge for the CEATEC Award since 2011.