A major Indian municipal corporation was operating over 10,000 CCTV cameras across its urban sprawl, yet most footage sat unwatched in storage servers. Traffic congestion was worsening every quarter, incident response times averaged over 45 minutes, and city administrators had no unified dashboard to coordinate operations. The existing surveillance infrastructure was passive, fragmented, and unable to deliver actionable intelligence at scale.
Aptibit deployed Visylix across the entire 10,000 camera network in a phased rollout spanning four months. The platform integrated AI models for real time traffic analysis, automatic number plate recognition (ANPR), crowd density monitoring, and face recognition at key checkpoints. A centralized command center was established with live dashboards, automated alerting, and cross camera forensic search. Edge processing nodes were installed at major junctions to ensure sub second latency for traffic signal optimization.
Measurable Impact
Technologies Used
The Challenge: A City Watching Blind
Despite a massive investment in physical camera infrastructure, the municipal corporation had no effective way to analyze or act on the video data being generated. Operators were responsible for monitoring hundreds of feeds each, making it physically impossible to detect incidents in real time. Traffic management relied on manual observation and outdated signal timing, leading to daily gridlock at over 200 major intersections.
The city administration recognized that the existing camera network was an untapped asset. What they needed was not more cameras but intelligence layered on top of the cameras they already had. They required a platform that could unify all feeds, apply AI analytics, and surface actionable insights to the right personnel at the right time.
After evaluating multiple vendors, the corporation selected Aptibit Technologies and the Visylix platform for its proven ability to handle large scale deployments, its comprehensive suite of AI models, and its flexible architecture supporting both cloud and edge processing.
The Solution: Visylix at City Scale
Aptibit engineers conducted a thorough site survey covering all 10,000 camera locations, assessing network bandwidth, camera quality, and processing requirements. The deployment was structured in four phases: first connecting the core 2,500 cameras at major junctions and government buildings, then expanding to arterial roads, public spaces, and finally residential zone perimeters.
The Visylix platform was configured with multiple AI models running simultaneously. ANPR engines processed vehicle data at every major intersection, feeding an adaptive traffic signal control system that adjusted timing based on real time density. Crowd detection models monitored public gathering areas, marketplaces, and transit hubs, automatically alerting the command center when density thresholds were exceeded.
A purpose built command center was established with a video wall displaying live AI analytics dashboards. Operators could now search across all 10,000 cameras by face, vehicle plate, or time window in seconds. Automated workflows pushed alerts for specific events directly to field teams via mobile notifications.
Implementation and Integration
One of the most significant technical challenges was ensuring reliable performance across a heterogeneous camera network. The existing infrastructure included cameras from over 15 different manufacturers with varying resolutions, codecs, and connectivity standards. Visylix universal camera adapter layer handled this diversity seamlessly, normalizing all feeds into a unified processing pipeline.
Edge computing nodes were deployed at 120 strategic locations to perform latency sensitive analytics like ANPR and traffic density measurement locally, reducing bandwidth requirements and enabling sub second response times. These edge nodes synchronized with the central Visylix cloud instance, ensuring all data remained available for historical analysis and forensic search.
Results and Ongoing Impact
Within six months of full deployment, the city reported a 32% reduction in traffic congestion at AI optimized intersections. Incident detection and response time dropped from an average of 45 minutes to under 3 minutes, with automated alerts reaching the nearest patrol unit instantly. The ANPR system maintained 98.6% accuracy across all weather conditions, enabling automated enforcement for stolen vehicles and traffic violations.
The municipal corporation has since expanded the deployment to include environmental monitoring and waste management analytics. The project was recognized as one of India top smart city AI implementations in 2026, and Aptibit continues to support the deployment with quarterly model updates and 24/7 platform monitoring.
City officials have reported that the data generated by Visylix is now being used to inform urban planning decisions, from optimizing bus routes based on passenger flow data to identifying pedestrian safety hotspots that require infrastructure upgrades.
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