3.4 MAJOR EVENTS SCREENING, SURVEILLANCE AND BEYOND JAPAN The Government of Japan has initiated cooperation with several tech companies as part of an AI development policy to maximize security and prevent crime or terrorism interfering with the success of major events. As the next host country for the Olympic Games, for instance – an event which is expected to bring an estimated 600,000 overseas visitors – enhancing security is a top priority for national authorities in Japan, including the National Police Agency (NPA). In April 2019, NPA established a new office of “Advanced Technology Planning” that seeks to leverage the beneficial use of advanced technologies, such as AI. The Police Information Communication Research Centre of the National Police Academy is additionally exploring three pilot applications that could strengthen security surrounding major events. These include the use of AI to: identify the models of cars in surveillance footage, analyse suspicious financial transactions that may indicate the laundering of money, and help identify movements or actions that may be considered suspicious. The Prefecture Police in Tokyo is similarly developing AI-enabled tools in pilot form that focus on identifying areas of high crime risks, which can serve to support in determining optimal patrol routes or crime prevention techniques. Law enforcement in other prefectures in Japan, such as Kanagawa, have also been working on hotspot statistics to inform predictive policing. Utilizing deep learning methods, prefecture police are developing a tool to detect, analyse and predict the location and time that crimes and accidents are likely to happen based on statistics and relevant data feeds. To make these predictions the tool takes into consideration factors such as time of the day, place, weather, geographical condition, urban mobility and various data feeds from past crimes and accidents in the area, as well as knowledge of criminology. Predictive policing supports police officers in detecting patterns of crimes and accidents; providing holistic overview in an active crime investigation; and, finally, reducing the possibility of crime by implementing a refined patrol route.
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Utilizing deep learning methods, prefecture police are developing a tool to detect, analyse and predict the location and time that crimes and accidents are likely to happen based on statistics and relevant data feeds
