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How these cities use predictive analytics to ensure safety

How these cities use predictive analytics to ensure safety
Although relatively new technology, many cities are already using predictive analytics to protect people and assets. Here is an overview of some of the major projects in this sector from across the world.
Although relatively new technology, many cities are already using predictive analytics to protect people and assets. Here is an overview of some of the major projects in this sector from across the world.

“In North America, for example, the majority of cities are in the early stages of implementing their ‘smart’ strategy,” said Lisa Brown, Senior National Director of Municipal Infrastructure and Smart Cities at Johnson Controls and Donal Sullivan, VP, and GM at Johnson Controls Ireland. “According to our 2018 Smart City Indicator Survey, thirty percent of respondents indicated their strategy is either under discussion or in the preparation phase. In terms of those who have taken action, thirty-seven percent of respondents have published their smart city strategy and twenty-nine percent are implementing their strategic program.”

The U.S. and the U.K.

In the US alone, there have been at least two dozen cities, including Seattle and Tacoma, Los Angeles, San Francisco, and Oakland among others that have experimented with software created by PredPol to be used for “predictive policing” activities.

“The cities involved used the software as a resource allocation tool to reduce costs and simultaneously reduce criminal activities,” explained Brian Schwab, Founder and Principal Consultant at S3SDC. “The analytics used in these experiments covered a total area encompassing at least 6 million people and focused on petty (or misdemeanor) crime prediction. Areas observed in these cities ranged from 22,500 square feet (150 feet x 150 feet) up to 250,000 square foot area plots (500 feet by 500 feet) where data suggested criminal activity had been high in the past.”

The analysis used to make the determination of which area to apply the analytics was conducted in each city using three to 10 years of crime data broken down into increments of three, seven, 14 or 28-day time scales. The basis for crime prediction was the assumption that specific crimes would be repeated in the same areas (repeat victimization).

In the U.K., the city of Kent has also been trialing PredPol’s software. London, which is known for its extensive video surveillance camera network that includes more than 500,000 units, has also been making use of analytics.

“Obviously, the video provides a great deal of information to combat crime and provide assistance in investigations which is helpful in city operations,” said Giovanni Gaccione, Justice & Public Safety Practice Leader at Genetec. “In addition to video, London is also using another key element to help improve maneuverability: public transportation data. To get around London, travelers use a Transport for London Oyster smartcard to pay for journeys on a bus, Tube, tram, rail, and other services.”

London’s city managers use Oyster card travel data to monitor where delays are and then notify the cardholder in real-time of better route options. This data not only provides information on how Oyster card users typically move, but it also allows for an intervention that can instantly improve the travel experience.

The Middle East

Dubai has had more success in establishing an AI-based predictive policing platform as part of the “Dubai 2021” program.

“While details of the exact components used in this system are not available, this program has been touted by Dubai authorities as being highly successful, as shown by the fact the city has established a complete General Department of Artificial Intelligence within the Dubai Police,” Schwab said. “To date, this program has reportedly resulted in the apprehension of more than 100 wanted criminals. The equipment used in this program is used to predict criminal activity as well as enhance traffic safety and road security.  The city aims to completely integrate AI into 100 percent of all policing activities by the year 2031.”


In 2013, Singapore, one of the world’s most economically and technologically advanced countries, launched its “Safe City Test Bed” project. The focus of this project was to test and leverage technology to improve public safety and security.

Singapore’s government invested US$104 million in ICT, acoustic and mobile phone sensors, crime control equipment, and police-controlled video surveillance cameras equipped with predictive analytics in security-sensitive areas.

“The city also implemented anomaly detecting analytics for social media platforms that attempt to identify abnormal activity on social media sites using keywords of interest identified as possibly threatening to public safety and security,” explained Schwab. “While much of the safe city testbed platform is still reactive in nature, the predictive analytics used successfully predicts how crowds will form by visually presenting information from video surveillance cameras leveraged with GPS data of ground units support events. This platform includes software for facial recognition and behavior analysis as well as detecting items left behind and automatically generates alerts for collaborating agencies.”


Another city that has been making headway in implementing analytics is Tokyo, which is often called the world’s safest city. Gaccione pointed out that Tokyo has invested heavily in a security infrastructure that protects its citizens.

“From tactile paving in the streets and walkways that are designed to help the visually impaired navigate the city safely, to well-lit roadways, side streets, and alleys, the City of Tokyo has worked to improve safety and livability,” Gaccione said. “Police officers are abundant throughout the city and are stationed in more than 1,200 small huts and can be called upon in a moment’s notice. These efforts – coupled with traditional security components like video and access control – combine to improve city life and keep things running smoothly.”
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