Pramesh S Jain
The Bengaluru city police claimed to have mitigated the fire cracker menace at night time during Deepawali festival with about 41 per cent of complaints reported after the 10 pm firecracker deadline were contained through proactive AI-based detection.
Kuldeep Kumar R Jain,Joint commissioner of Police (administration),said that the enforcement cameras installed at the strategic locations across the city are designed to spot firecrackers and smoke in public places and instantly alert the command centre,which then dispatches jurisdictional Hoysala units.This system has drastically reduced air and noise pollution,he said.
The technology,used for the first time in Bengaluru city effectively to contain busting fire crackers especially during the night time past deadline which affected the people especially aged,ill and children .
The AI-Powered Firecracker Detection and Response Initiative successfully validated the Bengaluru Safe City Project’s capability to integrate advanced AI tools for real-time civic enforcement.
Through collaboration between the Bengaluru City Police with IT companies the project demonstrated measurable improvements in situational awareness,enforcement accuracy,and public safety.
This initiative establishes a strong precedent for leveraging Safe City infrastructure to implement AI-based governance systems across India’s major urban centers,Kuldeep Kumar Jain,said .
The initiative leveraged the city’s expansive Safe City surveillance network,which includes more than 7,500 cameras and Integrated Command and Control Centre (ICCC) infrastructure.
A Firecracker Detection Video AI app from Awiros Appstack,powered by the Awiros Video Intelligence OS, analysed live feeds from over 200 existing cameras located in high-density residential and commercial areas such as Srirampuram,KR Market,HSR Layout,Haralur, and Marathahalli.
Explaining the functions,the AI algorithms were programmed to detect firecracker flashes,smoke,
and crowd hyperactivity in real time.
Upon detection,the system automatically generated alert packets containing location details,timestamps,and visual evidence.
These alerts were instantly transmitted to the ICCC and field units via WhatsApp,enabling control room operators to verify incidents and coordinate immediate police response.
With the 41 per cent of the total complaints attended in real quick time on pro active basis,the police also claimed that they have managed to reduce the noise and air pollution in the city drastically .
The deployment and use of technology demonstrated how new video-AI use cases can be developed, integrated,and made operational within a week—transforming existing cameras.
