Conventional
methods
Map ofactual crime
occurrence
Crime Nabi

The municipal police force
in Belo Horizonte, thecapital of the state of Minas
Gerais, was one of the firstin Brazil to introduce Crime
Nabi for use on patrols. In
December 2023, a function
newly developed to support
effective operation of thecity’s surveillance cameras
was officially implemented.

A NOVEL SOLUTION TO PUBLIC SECURITY:

JAPAN’S AI -BASEDCRIME PREDICTION
A new technology from Japan that harnesses AI to predict the occurrence of likely crimes has come into the spotlight inBrazil, a Latin American country facing serious public security issues. As a system boasting a high level of prediction
accuracy and ease of use, what does this innovative technology do to change policing operations on the ground and,
consequently, society in general?
Latin America is a rapidly
growing part of the world,
yet it faces substantial societal
challenges, including disparity andenvironmental destruction. It has aseriously high crime rate, with somesurveys indicating that around halfof the top 20 most dangerous cities
in the world lie in the region. Japan
has endeavored for many years
already to assist those countries’
efforts to tackle such problems.
In Brazil, for example—an early
adopter of Japanese-style Koban

police boxes for community-based
policing—Japan has continuously
dispatched experts and provided
training for over two decades now
to aid in the system’s spread. Morerecently, meanwhile, another new
technology has come out of Japanthat may enhance public security
drastically: Crime Nabi, a crimeprediction system utilizing AI
that has garnered attention for its
effectiveness.
Created by Singular Perturbations
Inc., a startup developing solutions

for crime reduction, the system
predicts, in detail and with highaccuracy, both when and wherecrimes are likely to occur andmeticulously formulates optimalroutes for patrol. Simulationsin Japan have demonstrated thesystem to be over 50% more
effective than conventional methods
in its coverage of locations
where crimes occur. Though it
uses reams of data—including
on past crime occurrence,demographics, geographic data,

and weather—that normallywould require an enormous
amount of time and money toprocess through conventional
computational methods, thecompany’s proprietary algorithmhas succeeded in much faster dataprocessing and lower costs.
In Japan, Crime Nabi has
primarily been used for crimeprevention patrols by localgovernments. Hoping to use
this system to improve public
safety in other countries, Singular
Perturbations
expandedits
operations to Brazil in 2021,
given the country’s pressing needfor heightened crime prevention.
The following year, the company
launched an experimental projectin Belo Horizonte, the capitalof the state of Minas Gerais, toaddress the problem of metal cable
theft, and the number of crimes
plummeted by approximately 69%.
The results were widely heralded,
and four state military police andtwo municipal police forces inBrazil, as well as one in Honduras,
have since piloted the systemaiming at implementation.

Left: The red points and lines in the map on the left indicate areas where actual crimes have occurredin Tokyo Prefecture. The map showing Crime Nabi’s predictions (lower right) is notably more detailed
and accurate than the one made using conventional methods (upper right).
Right: After becoming a victim of pickpocketing, KAJITA Mami, a theoretical physicist who later
founded Singular Perturbations as its CEO, started researching crime-prediction systems in her belief
that crimes with a standard modus operandi could be predicted through an algorithm.

Another key feature of Crime
Nabi is its easy-to-use design. By
simply entering such variables as
the final destination, transit areas,and distance in a dedicated mobileapp, the system will present a routethat prioritizes passage throughareas with a high probabilityof crime. Even if an emergency
dispatch interrupts the original
patrol, the system updates theroute from the current location
whenever the user makes a new
search and resumes the patrol. The
routes and times of each patrol
are automatically recorded andcan be used as electronic journals
and data to improve predictions.
“No matter how accurate a system
Below left: A pilot project on police patrols in
Honduras, one of the Latin American countries
besides Brazil to have started to introduce
Crime Nabi for security.
Below right: The Crime Nabi mobile app, whichuses GPS positioning, considers factors such as
the time of day and the surrounding area’s crime
situation to immediately calculate the optimum
route on patrol.

may be, it would be meaningless if
people didn’t use it. We handle all
the complicated calculations andtroublesome work so that police
officers can concentrate on fightingcrime,” says Singular Perturbations
CEO KAJITA Mami.
The app was originally developed
to support citizen participationin crime prevention activities inJapan—another major reason
for its user-friendly interface. “InJapan, we have a culture of thepolice, government, and citizens
working together to prevent
crime. Both the Koban systemand this app originated from thatfoundation,” says Kajita.
While fortifying its business in
Latin America, the company is also
surging ahead with such efforts asdeveloping technology enablinghighly accurate predictions evenin areas where crime data isunavailable, as well as conducting
a pilot project for robot patrols
based on their crime predictions.
“There will come an age whenrobots, self-driving cars, drones,
and other autonomous systems
work together for security. Our aim
is to contribute to the optimizationof security and thus realize a saferworld.”