Program Profile: Milwaukee’s (Wis.) Closed-Circuit Television Camera Program

This is a police-operated public surveillance program that seeks to reduce crime and increase crime clearances (i.e., arrests) by installing new closed-circuit television cameras at high-crime, high-traffic intersections in Milwaukee (Wis.). The program is rated Promising. Intersections in intervention areas where new cameras were installed had a statistically significant higher rate of crime clearances for all crime types, compared with intersections in comparison areas.

A Promising rating implies that implementing the program may result in the intended outcome(s).

A Promising rating implies that implementing the program may result in the intended outcome(s).

Program Goals

In 2007 the Milwaukee (Wis.) Police Department deployed a police-operated public surveillance system, which included 15 cameras and a comprehensive management and viewing system. After several system expansions during 2007–and 2011, there were a total of 42 cameras (40 pan, tilt, zoom cameras; 1 panoramic camera; and 1 fixed bulleted camera) at 40 locations across the city. However, a few of these cameras were antiquated, had poor image quality, and offered limited operational support (Robin et al. 2020b).

The Milwaukee camera program was designed to enhance the surveillance and investigative capacity of Milwaukee’s existing public surveillance system, using higher-quality cameras (specifically closed-circuit television cameras, also known as CCTV). The goal was to reduce crime and increase crime clearances (i.e., arrests) in high-crime, high-traffic-intersection areas of the city.

Program Components

The Milwaukee CCTV camera program was launched in 2018 and consisted of enhancing the existing public surveillance system by providing software and hardware upgrades, installing new high-definition CCTV cameras, and integrating two video analytic technologies (i.e., automatic license plate recognition and gunshot detection technology) at high-crime, high-traffic intersections. Thus, the number of cameras more than doubled, from 42 cameras to 87 cameras, including 24 new panoramic cameras; 12 new pan, tilt zoom cameras; and 9 new automatic license-plate-recognition cameras.

Two types of high-definition CCTV cameras were installed:

• Pan, tilt zoom (or PTZ) cameras: These are fixed cameras with a vantage point (or viewshed) of 35 degrees, which can zoom optically and digitally, focus on specific locations where crime is suspected, move to follow people or vehicles, and can be integrated with other systems such as automatic license-plate-reader software (Shukla et al. 2020).
• Panoramic cameras: These are stationary cameras with a viewshed of 180 degrees (or more) that constantly monitor large areas, preventing operators from missing critical details as they typically have higher resolutions with a single lens, allowing for digital zooming.

In addition to technological upgrades, the program provided infrastructural upgrades, which included updating policy and practices and moving the surveillance system from under the direction of the Milwaukee Police Department’s Technical Communications Division to its fusion (or “real-time crime”) center.

A team of operators (who were sworn officers) actively monitored and operationalized the CCTV camera program. Because the surveillance system was not accompanied by any other interventions to enhance the efficacy of the program (such as any signage, lighting, or public notification of camera locations), operators were important to the program. For example, operators would adjust PTZ cameras to focus on alleys or street corners where people were expected to be engaging in illicit activities such as prostitution or drug dealing. Similarly, they would work with officers in the field to monitor areas, houses, or businesses that were involved in criminal activity, and generate evidence for ongoing investigations.

Target Sites

During the intervention, the police department expanded its surveillance network of 40 locations to include 2 additional geographic areas. Because there were a limited number of new high-definition CCTV cameras available, the police department focused on two specific geographic areas: 1) the Center Street Corridor (on the north side of the city) and 2) the Muskego Way neighborhood (on the south side). Intersection areas were identified through an in-depth analysis of violent and property crimes, gunshot detections alerts, stolen and recovered vehicle data, and insight from specialized police officers.

Program Theory

There are several underlying perspectives that support CCTV programs, including rational choice theory and deterrence theory (Welsh and Farrington 2002; Cornish and Clarke 1986). A premise underlying rational choice theory is that individuals engage in actions (such as crime) which maximize rewards (or payoffs) and minimize costs (Akers 1990). Thus, when cameras are visible to individuals, this can increase their perceived risk of apprehension, therefore deterring potential crimes (Robin et al. 2020a).

In addition, the Milwaukee CCTV program is grounded in the situational crime prevention strategy, which argues that opportunities to offend can be reduced by altering a variety of mechanisms such as increasing the risk of an individual being apprehended and reducing provocations that give rise to criminal opportunities (La Vigne et al. 2011). Thus, by increasing the number of CCTVs in high crime areas (along with video analytic technologies), formal surveillance methods can strive to improve the overall efficiency and success rate of criminal investigations (Robin et al. 2020a).

Study

Robin and colleagues (2020a) conducted a quasi-experimental design (using propensity score matching) to evaluate the impact of Milwaukee’s closed-circuit television (CCTV) camera program on improving surveillance and investigative capacity of the existing public surveillance system, during a 12-month intervention period (January through December 2018) in high-crime, high-traffic intersections.

During the study period, the study authors worked closely with the Milwaukee Police Department to acquire and install a total of 24 new panoramic cameras, 12 new pan, tilt zoom cameras, and 9 new automatic license-plate-recognition cameras to add to the existing surveillance system (which at the time had 42 cameras at 40 intersections across the city). Because some intersections were already equipped with older cameras (which were antiquated, had poor image quality, and offered limited operational support), the study authors conducted an in-depth analysis of violent and property crimes, gunshot detection alerts, stolen and recovered vehicle data, and information from specialized Milwaukee Police Department staff, to identify all high-crime, high-traffic intersections that would be best suited for the installation of new CCTV cameras. However, due to the limited number of new high-definition CCTV cameras, the police department expanded its surveillance network to include two specific geographic areas: 1) the Center Street Corridor (on the north side of the city) and 2) the Muskego Way neighborhood (on the south side). The addition of these two intersections expanded surveillance across 42 intersections, of which 32 intersections had a new CCTV camera installed (i.e., the intervention intersections, also referred to as group 1).

Intervention intersections consisted of two area types: 1) intersection areas receiving new CCTV cameras that did not have a CCTV camera previously installed (group 2; n = 18), and 2) intersection areas receiving new CCTV cameras that were installed alongside an existing CCTV camera (group 3; n = 14). Intersections that had existing cameras but did not receive a new CCTV camera were excluded from the analysis; thus, all 32 intervention intersections were analyzed as a single treatment group, compared with matched comparison intersections.

Matched comparison intersections were identified using propensity score matching, based on block group characteristics (such as crime and arrest trends, percentage of female-headed households, and percentage of people on public assistance). Crime and arrest trends were obtained from census and administrative data. Administrative data were provided by the Milwaukee Police Department and included geographic identifiers that allowed the study authors to pinpoint exact crime and arrest locations. Using ArcMap geographic information system software and a combination of shapefiles from census Tiger files, the study authors identified all intersections in the city, and then spatially linked intersections to a file with camera locations and information on the types of cameras. After removing intersections within 500 feet of intervention intersections, there were 8,245 intersections included in the pool of eligible comparison intersections for propensity score matching. From that sample of intersections, there were 32 matched comparison intersections (which were also split into the two area subgroups based on intervention intersections).

Of the residents in intervention intersections, 56.4 percent were Black, and 23.6 percent were Hispanic, with 27.7 percent of people under the age of 18, 8.4 percent unemployed, and 33.6 percent living under the poverty line. In comparison intersections, 53.2 percent of residents were Black, and 23.1 percent were Hispanic, with 26.4 percent of people under 18, 8.7 percent unemployed, and 28.2 percent living under the poverty line. At baseline, there were statistically significant differences between intervention intersections compared with comparison intersections. Specifically, intervention intersections had a higher percentage of residents under the poverty line and on public assistance, and lower levels of residential mobility (i.e., people who had moved in the past year). Thus, a difference-in-differences analysis was used to control for group differences, using certain covariates (i.e., race, percent renting, and crime and clearance rates for all crime types such as violent crimes, drug crimes, and simple assault clearances).

Data were collected following the intervention for four quarters in 2018 (i.e., post-intervention). Outcome of interests in the study were the number of crimes and crime clearances compared with pre-intervention (i.e., four quarters in of trends for any crime type, such as violent crimes, property crimes, simple assault crimes, drug crimes or group B offenses [i.e., disorderly conduct, drunkenness, and loitering]). The CrimeSolutions review of this study focused on the number of crime clearances for all crime types, at post-intervention. Crime clearances (defined as an arrest linked to the location where a crime occurred, regardless of where the arrests occurred) were measured by an arrest for any crime type. Negative binomial and Poisson panel regression models were used to determine differences between crime clearances in intervention and comparison intersections. The study authors conducted subgroup analyses within the intervention and comparison intersections to determine whether CCTV camera assignment areas (intersection areas that received only new CCTV cameras versus intersection areas that received new CCTV cameras alongside existing cameras) affected crime and crime clearance outcomes.

In 2016, the Urban Institute partnered with the Milwaukee (Wis.) Police Department to implement the closed-circuit television (CCTV) camera program (Robin et al. 2020a). This was a 4-year project funded by the National Institute of Justice (Award No. 2015–R2–CX–K002), in which the Urban institute worked closely with the Milwaukee Police Department to reduce crime (such as homicide, burglary, and drug crimes) by designing an intervention (i.e., the Milwaukee camera program) that would better optimize its existing police-operated public surveillance system.

To implement the program, vendors of the video analytic technologies (such as ShotSpotter) conducted an in-depth training with all the operators on the camera software functions, following technological and infrastructural upgrades (i.e., software and hardware upgrades, installing new closed-circuit televisions cameras, integrating video analytic technologies) (Shukla et al. 2020).

Subgroup Analysis

Robin and colleagues (2020a) separated intervention and comparison intersections into subgroups based on two treatment area types: 1) intersection areas that received a new closed-circuit television (CCTV) camera and did not previously have a CCTV camera (group 2; n = 18) and 2) intersection areas that received a new CCTV camera alongside an existing CCTV camera (group 3; n = 14). At follow-up, group 2 intersections had 20 percent more property crimes, compared with matched comparison intersections. This was a statistically significant difference. In group 3, intervention intersections had 27 percent more violent crimes, 24 percent more property crimes, and 41 percent more simple assaults, compared with matched comparison intersections. These differences were statistically significant. However, neither group 2 nor group 3 had statistically significant differences on crime clearances (i.e., arrests), at follow-up. Additional findings on crime and crime clearance differences between intervention and comparison intersections can be found in the reviewed study of the Milwaukee (Wis.) CCTV camera program (Robin et al. 2020a).

These sources were used in the development of the program profile:

These sources were used in the development of the program profile:

Akers, Ronald L. 1990. “Rational Choice, Deterrence, and Social Learning Theory in Criminology: The Path Not Taken.” Journal of Criminal Law and Criminology 81(3):653–76.

Ashby, Matthew P.J. 2017. “The Value of CCTV Surveillance Cameras as an Investigative Tool: An Empirical Analysis.” European Journal on Criminal Policy and Research 23(3):441–59.

Cornish, Derek B., and Ronald V. Clarke. 1986. The Reasoning Criminal: Rational Choice Perspectives on Offending. Piscataway, N.J.: Transaction Publishers.

La Vigne, Nancy G., Samantha S. Lowry, Joshua A. Markman, Allison M. Dwyer. 2011. Evaluating the Use of Public Surveillance Cameras for Crime Control and Prevention. Washington, D.C.: Urban Institute, Justice Policy Center.

Lawrence, D. S., Peterson, B. E., Shukla, R., & Robin, L. (2020). “Optimizing the Use of Video Technology to Improve Criminal Justice Outcomes.” Washington, D.C.: Office of Justice Programs.

Owen, Katy, Gemma Keats, and Martin Gill. 2006. A Short Evaluation of the (Economic) Benefits of the Milton Keynes CCTV system in Managing Police Resources. Tunbridge Wells, England: Perpetuity Research & Consultancy International Ltd.

Ratcliffe, Jerry H. 2006. “Video Surveillance of Public Places.” Washington, D.C.: U.S. Department of Justice, Office of Community-Oriented Policing Services.

Robin, Lily, Bryce E. Peterson, and Daniel S. Lawrence. 2020b. “Public Surveillance Cameras and Crime: The Impact of Different Camera Types on Crimes and Clearances.” Washington, D.C.: Urban Institute.

Shukla, Rochisha, Daniel S. Lawrence, and Bryce E. Peterson. 2020. “Lessons Learned Implementing Video Analytics in a Public Surveillance Network.” Washington, D.C.: Urban Institute.

Welsh, Brandon C., and David P. Farrington. 2002. Crime Prevention Effects of Closed Circuit Television: A Systematic Review. Home Office Research Study 252. London, England: Home Office, Research, Development and Statistics Directorate.

Following are CrimeSolutions-rated programs that are related to this practice:

Closed Circuit Television (CCTV) Surveillance

Public surveillance systems include a network of cameras and components for monitoring, recording, and transmitting video images. Public surveillance cameras are designed to reduce both property and personal crime. This practice is rated Promising for reducing overall crime, property crime, and vehicle crime, and rated Ineffective for impacting violent crime.

Evidence Ratings for Outcomes

	Crime & Delinquency - Multiple crime/offense types
	Crime & Delinquency - Property offenses
	Crime & Delinquency - Vehicle crime
	Crime & Delinquency - Violent offenses

Why might a practice's outcome ratings differ from the ratings of specific programs encompassed by that practice?