[Media Release] Fujitsu Develops AI Technology to Quickly Solve Urban Security Positioning Problems
May 10, 2016
The University of Electro-Communications and Fujitsu Laboratories Ltd. today announced the development of a high-speed algorithm that uses mathematical game theory as an artificial intelligence technology to aid in the development of security planning. This will work to solve city-scale road network security problems, such as where best to position checkpoints when trying to catch a criminal.
For security measures at locations where people gather, it is often not possible to completely seal off all intrusion or escape routes with limited security resources, so it is necessary to effectively deploy security personnel and to minimize anticipated damage. The formulation of security plans has relied on the experience of experts and intuition, but in recent years there has been a focus on game theory, which mathematically describes both offence and defense, as a technology to support expert decision-making. However, it has been difficult to apply game theory to a city-scale security problem of catching criminals at checkpoints in real-world cities because the processing volume expands exponentially with the scale of the road network.
Now, using Fujitsu Laboratories’ proprietary network contraction technology, Fujitsu Laboratories and the University of Electro-Communications have developed an algorithm to rapidly solve city-scale road network security problems. Compared with previous technology, this makes it possible to find the theoretically optimal security plan 20 times faster, on average, for a 100-node problem, and 500 times faster, on average, for a 200-node problem. For 200,000-node problems, on the scale of Tokyo’s 23 wards, where formulating a plan would have taken several days with previous technology, this technology can generate a security plan in approximately five minutes, enabling interactive planning support.
For more details, please see the file below,