Study finds brighter street lighting reduces violent crime

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Published: 2026-10-07T16:01:12.677Z • Permanent link

Researchers at Rutgers University–Newark have published groundbreaking findings that shed light on the relationship between street lighting and crime rates. A city-wide experiment involving the installation of LED lights in Newark, New Jersey, demonstrated a significant reduction in violent crime and burglaries. According to data collected by the university's crime mapping team, the introduction of LED lights illuminated crime hot spots throughout the city reduced violent crime by nearly 46% and burglaries by 58%.

Led by Dr. Jennifer Eberly, a professor of criminology at Rutgers University–Newark, the research team utilized advanced data analytics and machine learning algorithms to analyze crime patterns and identify the most effective areas for street lighting. The team collaborated with the City of Newark and the New Jersey Department of Transportation to implement the LED lighting system, which consisted of 10,000 new streetlights installed across the city. The experiment began in July 2019 and concluded in December 2020, with the data collected during this period serving as the basis for the study's findings.

Notably, the study's results are in line with the expectations of law enforcement officials and policymakers, who have long recognized the importance of street lighting in preventing crime. According to Newark Police Commissioner John F. McKeon, the city's crime rate has been trending downward over the past few years, and the installation of LED lights is seen as a key factor in this trend. "We've seen a significant reduction in crime, particularly in areas where we've increased lighting," McKeon said. "We're hopeful that this study will provide valuable insights for other cities looking to improve public safety.

The findings of this study have significant implications for the AI and tech ecosystem, particularly in the fields of urban planning, public safety, and data analytics. Companies such as Philips and GE Lighting, which specialize in LED lighting solutions, are already taking notice of the study's results and exploring ways to integrate similar technology into their products. Researchers at institutions such as the University of California, Berkeley, and the Massachusetts Institute of Technology (MIT) are also building on the study's findings, using advanced machine learning algorithms to analyze crime patterns and identify areas where street lighting can be most effectively deployed.

The study's results also have broader implications for policymakers and researchers, who are increasingly recognizing the importance of data-driven approaches to crime prevention. The use of data analytics and machine learning algorithms to analyze crime patterns and identify areas where street lighting can be most effectively deployed is seen as a key factor in the study's success, and is likely to be a major focus area for researchers and policymakers in the coming years. As the field of crime prevention continues to evolve, it is likely that we will see more studies like this one, which use advanced data analytics and machine learning algorithms to shed light on the complex relationships between street lighting, crime rates, and public safety.

The study's findings are part of a larger trend towards the use of data analytics and machine learning algorithms in urban planning and public safety. In recent years, cities around the world have begun to adopt data-driven approaches to crime prevention, using advanced algorithms and machine learning techniques to analyze crime patterns and identify areas where street lighting can be most effectively deployed. This approach has been successful in cities such as New York, Los Angeles, and Chicago, where data-driven crime prevention strategies have led to significant reductions in crime rates.