Building secure, smarter, safer environments with AI-Driven video analytics for Smart Cities

Integrating video analytics into existing video surveillance systems to extract intelligence from video content drives safer, smarter, more efficient environments.

In this video, we explore the key focus areas in creating smart cities; traffic analysis, near-miss incidents, crowd management with traffic flow analysis, anomaly detection; all aimed at creating safer public spaces. We also emphasize the crucial role that real-time event alerts play in integrating these elements

Transforming transport with intelligent traffic management

AI-driven video analytics for vehicle tracking with real-time event alerts empowers operators to:

  • Predict Peak Traffic Hours: Analyze patterns to forecast and manage traffic congestion.
  • Identify Vehicle Offenses: Detects violations like speeding, lane violation, driving the wrong way, illegal parking, and unauthorized entry.
  • Manage Vehicle Entry: Control access to restricted areas.
  • Search for Specific Vehicles: Accurate and swift detection of vehicles using advanced search and find capabilities with license plate recognition.
  • ANPR: Used for traffic management, law enforcement, and security purposes in smart cities.

Crowd management and pedestrian flow analysis

Effective crowd management is essential for maintaining order and safety in densely populated areas, whether at fixed venues like stadiums or temporary sites such as festivals or street markets. Smart cities employ AI-driven video analytics to:

  • Send Pedestrian Alert Notifications: Notify operators of unusual pedestrian activity.
  • Track Persons of Interest: Identify and monitor individuals based on metadata.
  • Analyze Pedestrian Traffic Flow: Assess crowd density and movement patterns to prevent overcrowding.
  • Pedestrian Search: Utilize multi-attribute search for rapid and precise pedestrian localization.

Near-miss incidents

AI-driven video analytics provide immediate alerts and actionable insights regarding near-miss incidents, focusing on patterns involving pedestrians, cyclists, and vehicles, including transit and emergency fleets. This system also monitors traffic violations, assesses traffic volumes, and evaluates the efficiency of signalized intersections. Specific monitored incidents include:

  • Pedestrian Crossing Motorway: Detects pedestrians crossing motorways, alerting to potential dangers.
  • Pedestrian Walking in Bicycle Lane Area: Identifies pedestrians in bicycle lanes, reducing collision risks.
  • Vehicle Driving or Parking in Forbidden Areas: Monitors unauthorized vehicle activities.
  • Vehicle Driving in the Wrong Direction: Detects vehicles moving against traffic flow.
  • Pedestrian Loitering or Potential Violent Behavior: Recognizes unusual pedestrian behavior that may indicate loitering or violence.

Anomaly detection 

AI-driven video analytics enhance safety by detecting anomalies and identifying changes in behavior, for example:
  • Left Luggage: Identify unattended items that may pose a threat.
  • Fire and Smoke: Detect potential fire hazards early.
  • Weapons: Spot firearms and other weapons.
  • Violence: Recognize aggressive behavior to prompt immediate intervention.
  • Suspicious activity: For example, loitering in restricted areas, sudden crowd formation, or erratic movements can trigger alerts

Real-time event alerts: As a unified feature

Real-time alerts sent to relevant personnel, ensures a prompt response to incidents. This unified feature enhances the coordination and effectiveness of smart city operations.

AI-driven video analytics that works at scale and speed

Safety is of paramount importance for smart city initiatives, and leveraging the power of AI-driven video analytics, cities can speed up investigative work, reduce crime rates and enhance security without the need for additional surveillance cameras. This integration delivers impactful results with:

  • Increased Public Safety: Real-time detection and alerting improve responsiveness.
  • Better Situational Awareness: Advanced meta-search and detection capabilities provide comprehensive oversight.
  • Traffic Anomaly Detection: Identify and respond to accidents, road blockages, and other traffic issues in real time.
  • Rapid Post-Event Analysis: Advanced metadata search accelerates investigation processes with accuracy.


Integrating AI-driven video analytics into existing surveillance operations has and continues to revolutionize urban management. Smart cities are more secure, efficient, and responsive, setting new standards for a sustainable urban living environment. With AI-driven video analytics, cities can ensure safer environments for residents, making urban areas not just smarter, but also more livable.

Smart Safety Platform.

Our Smart Safety Platform supports Martyn’s Law with AI-driven video analytics that automates your surveillance for a safer more secure environment.

Features include: Video search, search against appearance type, pedestrian monitoring, people counting and flow, vehicle detection and behavioural analysis along with real-time alerts and automated workflows.

Smart Safety Platform: People Counting : Anomoly Detection : Behaviour analytics : Crowd Intelligence
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