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The technological intervention has yielded staggering results, with the city recording a 47% drop in robberies and 53% decline in chain-snatching incidents over the past year.
The backbone of this success is an AI-driven system that processes decades of historical crime data to forecast future incidents. Representative Image: Canva
In recent years, the integration of technology into law enforcement has shifted from a futuristic concept to a daily operational reality in Karnataka’s capital. The Bengaluru City Police have undergone a significant digital transformation, adopting Artificial Intelligence (AI) and predictive analytics to address the persistent challenges of urban street crime.
By moving away from traditional reactive policing and toward a proactive, data-first model, the department has turned the Silicon Valley of India into a testing ground for high-tech public safety.
The technological intervention has yielded staggering results, with the city recording a 47% drop in robberies and a massive 53% decline in chain-snatching incidents over the past year.
The Predictive Policing Model
The backbone of this success is an AI-driven system that processes decades of historical crime data to forecast future incidents. Instead of static patrolling, the AI identifies temporal hotspots, specific locations and time windows where crimes are statistically likely to occur.
For instance, if data shows a spike in chain snatching in Jayanagar between 6:00 AM and 8:00 AM, patrol units are pre-emptively stationed there. Hoysala and Cheetah patrol units are now dispatched based on real-time AI recommendations, ensuring that police presence is highest exactly where and when the risk is greatest.
The city’s surveillance infrastructure, significantly bolstered under the Safe City Project, now acts as a digital dragnet. Thousands of CCTV cameras at junctions, railway stations, and bus terminals are linked to a Facial Recognition System (FRS). This system cross-references live feeds against a centralized database of known offenders.
If a history-sheeter is detected in a sensitive area, an automated alert is sent to the nearest officer’s handheld device. Additionally, Automatic Number Plate Recognition (ANPR) cameras have made it increasingly difficult for criminals to use stolen or blacklisted vehicles by flagging suspicious histories for rapid interception.
Smart Detection and Behavioral Analysis
The Command and Control Centre is now equipped with software capable of loitering detection. The AI flags unusual behaviour, such as a motorcycle circling a specific residential block multiple times or individuals lingering near jewellery stores.
This allows operators to dispatch a patrol to investigate before an overt act is committed.
The statistics for the 2024–25 period highlight a transformative trend in city safety, featuring a 53% reduction in chain snatching and a 47% reduction in robbery. Burglary and house break-ins have also seen a downward trend with higher recovery rates of stolen property.
Furthermore, the time taken to identify and apprehend suspects has been slashed by nearly 30% due to the availability of digital evidence trails.
Citizen Empowerment via the Suraksha App
The Bengaluru city police have also integrated AI into the citizen-facing Suraksha App. The app now provides safety scores for different neighbourhoods based on real-time data and allows for SOS triggers that transmit live audio and GPS coordinates directly to the police dashboard.
Bengaluru Police Commissioner B. Dayananda noted that while technology serves as a massive force multiplier, it is the integration with ground-level personnel that makes it effective. The department plans to expand these capabilities to include advanced behavioural analysis and predictive modelling for traffic-related crimes in the coming phase.
With these results, Bengaluru has established a new national benchmark, proving that in the fight against street crime, the algorithm is becoming as powerful as the badge.
February 24, 2026, 15:48 IST
The technological intervention has yielded staggering results, with the city recording a 47% drop in robberies and a massive 53% decline in chain-snatching incidents over the past year.
The Predictive Policing Model
The backbone of this success is an AI-driven system that processes decades of historical crime data to forecast future incidents. Instead of static patrolling, the AI identifies temporal hotspots, specific locations and time windows where crimes are statistically likely to occur.
For instance, if data shows a spike in chain snatching in Jayanagar between 6:00 AM and 8:00 AM, patrol units are pre-emptively stationed there. Hoysala and Cheetah patrol units are now dispatched based on real-time AI recommendations, ensuring that police presence is highest exactly where and when the risk is greatest.
The city’s surveillance infrastructure, significantly bolstered under the Safe City Project, now acts as a digital dragnet. Thousands of CCTV cameras at junctions, railway stations, and bus terminals are linked to a Facial Recognition System (FRS). This system cross-references live feeds against a centralized database of known offenders.
If a history-sheeter is detected in a sensitive area, an automated alert is sent to the nearest officer’s handheld device. Additionally, Automatic Number Plate Recognition (ANPR) cameras have made it increasingly difficult for criminals to use stolen or blacklisted vehicles by flagging suspicious histories for rapid interception.
Smart Detection and Behavioral Analysis
The Command and Control Centre is now equipped with software capable of loitering detection. The AI flags unusual behaviour, such as a motorcycle circling a specific residential block multiple times or individuals lingering near jewellery stores.
This allows operators to dispatch a patrol to investigate before an overt act is committed.
The statistics for the 2024–25 period highlight a transformative trend in city safety, featuring a 53% reduction in chain snatching and a 47% reduction in robbery. Burglary and house break-ins have also seen a downward trend with higher recovery rates of stolen property.
Furthermore, the time taken to identify and apprehend suspects has been slashed by nearly 30% due to the availability of digital evidence trails.
Citizen Empowerment via the Suraksha App
The Bengaluru city police have also integrated AI into the citizen-facing Suraksha App. The app now provides safety scores for different neighbourhoods based on real-time data and allows for SOS triggers that transmit live audio and GPS coordinates directly to the police dashboard.
Bengaluru Police Commissioner B. Dayananda noted that while technology serves as a massive force multiplier, it is the integration with ground-level personnel that makes it effective. The department plans to expand these capabilities to include advanced behavioural analysis and predictive modelling for traffic-related crimes in the coming phase.
With these results, Bengaluru has established a new national benchmark, proving that in the fight against street crime, the algorithm is becoming as powerful as the badge.
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