Bhavesh Kumar

Senior Correspondent, IFSEC Global

August 11, 2015

Sign up to free email newsletters

Download

The State of Physical Access Control in EMEA Businesses – 2020 Report

NYPD Launches Era of Predictive Policing as it Pilots Crime-Forecasting Software

NYPD Steps into the Era of Predictive Policing with Crime-Forecast Software Testing

Joi Ito under CC BY 2.0

The NYPD is testing crime forecasting software that collates the crime history of neighbourhoods to forecast criminal activity.

The city’s three police precincts will pilot the software – called Hunchlab and developed by Azavea – over the next two years, according to an NYPD spokesperson.

The software analyses temporal patterns, weather, environmental risk factors, socioeconomic indicators, historic crime levels and near-repeat patterns to help the police department predict future crime patterns and deploy resources accordingly.

The NYPD’s existing crime data warehouse will also be replaced by the data fusion system, allowing real-time access to internal and external data sources such as sensors, licence plate readers, city and state databases and social media, according to Capital New York.

“Predictive policing will allow the NYPD to make better data-driven decisions about deployments,” said the NYPD in its announcement. “The Department has been experimenting with custom-built algorithms that have been shown to be better predictors of crime incidents than traditional hotspot analysis.”

The cost for setting up the a data centre is pegged at $10m whereas the analytics and related Compstat upgrades will cost about $45m, according to the report’s estimates.

Download the Intruder Alarm Report 2020

Download this report, produced in conjunction with Texecom, to discover how increasing processing power, accelerating broadband speeds, cloud-managed solutions and the internet of things and transforming the intruder alarm market, and whether firms are adopting these innovative new technologies.

AlarmReport-Main-19

Related Topics

Subscribe
Notify of
guest
0 Comments
Inline Feedbacks
View all comments