Law Enforcement
Empowering law enforcement agencies with real-time face recognition, people search, and crowd analytics — ensuring faster response, safer cities, and evidence-ready intelligence.
Traditional surveillance systems capture video but lack intelligence. Officers must manually review hours of footage to locate suspects or track missing persons — leading to missed leads, delayed actions, and inefficient manpower use.
Typical challenges:
- Manual face matching is time-consuming and error-prone
- Limited ability to search across large camera networks
- No real-time alerts for person of interest detection
- Difficulty estimating or managing crowd density during events
NAYAN’s AI-Powered People Analytics Platform integrates with existing city and police camera networks to automatically:
- Recognize and identify faces across live and recorded feeds
- Track movements of suspects or missing individuals in real time
- Generate alerts when a match is detected from watchlists or databases
- Count and analyze crowd density and flow for better resource deployment
- Each detection event is automatically logged with timestamped video + face evidence, ensuring tamper-proof audit trails and instant retrieval for investigations.
Percentage Coverage of Cities increase from 0.1% Due to CCTV’s to 50% Due to AI Dashcams
Washington
California
Huntington
The system supports locating missing persons, tracking suspects, finding persons of interest in large events or public spaces, and searching across multiple cameras and past recordings. You can query by face image, watch-list entry or descriptive filters (e.g., last seen at location X).
The platform is built to deliver high recognition precision (typically in the high 90s percentile) under good lighting and resolution. Accuracy depends on camera quality, angle, occlusion (e.g., masks), and watch-list size. We support continuous learning and human-in-loop verification for optimal results.
Yes. The people-counting module detects and tracks individual heads or silhouettes in defined zones, aggregates counts over time, monitors density trends, and triggers alerts when preset thresholds (e.g., occupancy, crowd surge) are crossed.
Absolutely. Once a person is recognised or manually selected, the system can reconstruct their path across multiple cameras, log dwell times in zones, identify entry and exit points, and generate a movement timeline with video snapshots.
Every alert event is logged with metadata (time, camera ID, watch-list match or count threshold), a short video clip, extracted image(s), and sign-off metadata. The log is stored securely with access audit streams and supports export for legal or investigative processes.
The platform supports standard RTSP/ONVIF camera streams and can connect to existing CCTV networks. It can be deployed on-premises or in the cloud, supports large scale streams, and offers APIs and dashboard interfaces for law-enforcement operators and administrators.
- Face match alert: “Watch-list face detected: camera X, time Y”.
- Person path alert: “Tracked individual moved through zones A → B → C in last n minutes.”
- Crowd alert: “Zone Z civic plaza exceeds capacity threshold; current count = K.”
All alerts are actionable, and lead directly to evidence export options and dashboard itemisation.
The platform offers a role-based dashboard that shows alerts live, searchable person-match logs, crowd-count heat-maps, movement trails, and export tools for reports. Administrators can define watch-lists, zones, thresholds and manage user permissions.