The stabbing incident in front of the University of Tokyo occurred in January 2022.
The stabbing of three people, including a student taking the Common University Entrance Examination, shocked the students and others involved in the incident.
In response to this incident, universities and the Metropolitan Police Department have been working to build and strengthen security systems, but the chronic shortage of security guards has made it difficult to ensure complete safety with conventional human security alone.
This article explains the importance of security at examination centers and the need for AI security as a further security enhancement and preventive measure.
Random incidents have occurred in Japan in places where large numbers of people congregate, increasing the importance of security in places where large numbers of unspecified people congregate.
Actual incidents include the Akihabara Street Incident in 2008, the Noborito Street Incident in Kawasaki City in 2019, and the Keio Line stabbing incident in 2021. In addition, the most recent slashing incident on a train at Akihabara Station at the beginning of 2024 will be fresh in our minds.
From a psychological point of view, the reason why people choose such crowded places to commit crimes is characterized by the fact that perpetrators tend to have a strong motive of "desire for destruction" or "extended suicide (involving others in one's own suicide). [Note 1] Against this background, there is a strong need to strengthen security systems on a daily basis, as incidents and accidents may occur in unexpected places and at unexpected times.
In addition, the Common University Entrance Examination held in January each year is likely to attract a large number of people, mainly students, to the campuses where the examinations are held, and on the day of the examinations, students and related parties will also be concentrating on the tests, making it likely that they will be less vigilant.
In fact, since a stabbing incident occurred in front of the University of Tokyo in 2022, police officials and campus administrators are being asked to further strengthen security systems to prevent a similar incident from happening again.
［Note 1] [Faculty of Psychology] Extended Suicide and Indiscriminate Mass Murder｜Kansai International University
https://www.kuins.ac.jp/news/2022/01/post_448.html
In discussing security at college entrance test sites, let us look back at the situation at the time in the 2022 murder in front of the University of Tokyo.
First, the assailant was in possession of the following three weapons.
● Kitchen knife (blade length: 12 cm)
●Folding saw (20 cm)
● Knife (blade length: approx. 6 cm)
None of these items are wide enough to fit into a small bag.
In addition, plastic bottles and bottles (3L worth) containing flammable liquids were also brought on their way to the crime scene, causing a blizzard in several places in the Todaimae station! The police officer was also found to have been in the station with the bottles and bottles.
According to his statement after the incident, he had the intention to set fire to the train in addition to the station premises, but it is also possible that he may have set fire directly to people.
The incident occurred around 8:30 a.m., and many students were probably trying to arrive an hour before the start of the exam. Since the assailant was a 17-year-old male high school student at the time, his presence in front of the University of Tokyo at that time was not at all unnatural.
As for the number and deployment of security guards and the number and location of security cameras on that day, the official website of the University of Tokyo states the following
The Yasuda Auditorium Security Office conducts standing patrols at the Main Gate, Akamon Gate, Yayoi Gate, and Noseimon Gate, patrols by patrol vehicles and on foot, and monitors for suspicious persons using security cameras. Security is also provided inside the buildings by the respective building management departments. Reference: Crime prevention measures on campus, etc. | The University of Tokyohttps://www.u-tokyo.ac.jp/ja/students/campus-life/h13_06_01.html
The above information suggests that the area in front of the main gate of the Faculty of Agriculture at the University of Tokyo's Yayoi Campus is within the scope of expected security measures.
In addition to the conventional security measures, the number of security guards was increased due to the large number of people expected to gather on the day of the Common Entrance Examination for University Admission, so the security system is considered to have been adequate.
Now, let us consider the issues in security based on what we have seen so far.
Assuming that the security system, including the number and assignment of security guards and the number and locations of security cameras, is adequate, the following two issues remain.
●The assailant's appearance was so familiar to the public that they did not suspect the assailant
●The assailant's appearance was so familiar to the scene that it could not be suspected
For the first, if it is at the time of entry, measures can be taken through baggage screening.
However, if the incident occurred on the street before entering the university campus, as in this case, it would be difficult to take countermeasures.
Also, it would be difficult to find the second case if the assailant was mixed in with the large number of students taking the entrance exam on the day of the incident. In particular, since the assailant was a student, it would have been difficult to detect any signs of the incident if he had been familiar with the atmosphere of the day.
In order to solve the above two problems, it is necessary to detect and check for suspicious persons who are planning to commit dangerous acts in advance.
Specific methods include checking for "behavior patterns often seen in suspicious persons," keeping an eye out for minor discrepancies in the appearance of luggage, clothing, etc., and having a security guard call out to anyone who falls into this category.
However, even these methods may not completely solve the problem, since it is difficult to see each individual when they are mixed in with a large number of examinees. In addition, since many students are in a naïve state of mind before the exam, it is possible that security guards may not be able to talk to them for fear of being misunderstood.
Therefore, the two important points are "comprehensive monitoring by methods other than visual observation" and "highly accurate detection of discomfort" based on a statistical analysis of the behavior of the majority of the students gathered on the day of the examination.
Against this backdrop, the use of cutting-edge technologies such as AI is attracting attention as a key means of solving problems while maintaining the safety of venues.
AI Security asilla," the AI security system developed by Asilla, has a full range of functions to solve these two issues.
As mentioned above, there is a limit to the amount of conventional human-only security alone that can be used to provide security for the crowds at university entrance test sites. Therefore, there is a need to improve the quality of security while utilizing limited human resources.
Police authorities are making efforts to utilize AI and other advanced technologies to strengthen crime prevention measures. In particular, AI cameras with AI functions are attracting attention as a potential aid to crime prevention measures.
Since its release at the end of January 2022, the AI security system "AI Security asilla ("asilla")" has seen a rapid increase in demand for use in a variety of facilities, mainly large complexes and commercial facilities, but also office buildings, medical care facilities, university campuses, stations and infrastructure.
Asilla," which employs the world's top class behavior recognition AI, has high detection accuracy for human movement, enabling early detection when a person enters a no-entry area set up within a facility. By expanding the scope of use of existing security cameras, a robust security system has been established, and efficient collaboration with security guards contributes to improving the security level of the entire facility.
Here, we will explain what can be done with "asilla," an AI security system that utilizes behavior recognition AI.
For example, if a violent act such as punching occurs on campus, AI can detect it as "nuisance behavior" in a few seconds as a movement deviating from "violence" based on learned normal behavior.
If a person enters a restricted area on campus, the AI immediately detects it and alerts security guards and other relevant personnel instantly.
In the unlikely event of an intruder from the outside, AI can detect unusual behavior, such as loitering in the vicinity or looking around, and can detect suspicious persons before they take any action.
Early detection of such behavior is expected to lead to the prevention of incidents and accidents.
In "asilla," AI learns the images from security cameras autonomously.
It analyzes the images in real time and compares them with normal behavior patterns to detect abnormal movements.
For example, if an unusual behavior is detected in a camera image, an alert is sent to relevant personnel and security guards as "strange behavior. This allows for quick detection of incidents and accidents that are easily missed by humans.
By detecting signs of accidents and incidents in this way, more effective crime prevention measures are expected to be realized.
Asilla's AI security system can utilize existing cameras without any new investment or effort. While reducing the burden on security guards, the AI provides thorough support 24 hours a day, 365 days a year, enabling the provision of high quality security without omissions.
We encourage you to consider implementing AI security to further improve the quality of security on your campus.
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