WF 202212_2 World’s Longest Standing Multi-Sensory AI Company

Autonomous Surveillance – Trusted by Police Worldwide

Autonomous Surveillance – Trusted by Police Worldwide

With projects in 70 countries, our track record in real-time, autonomous surveillance speaks to our dedication to empowering law enforcement with cutting-edge AI. Police forces worldwide from Dubai to the USA & Bangkok trust our technology. See here for our end to end analytics for complex scene.

Hong Kong Police has adopted our AI solution 
for the past 8 years

Since 2017, the Hong Kong Police Force has applied our patented “Facial Recognition-in-a-Crowd”, Crowd management & others to improve public safety and streamline operations. Our systems have helped officers detect and respond to threats quickly, manage large crowds, prevent stampede. Their long-term adoption of our system has reflected our system accuracy and performance has exceeded their everyday challenges of law enforcement.

Announcement: Selected by Western Australia Police

We are thrilled to announce that Western Australia Police has selected us as their partner for our advanced surveillance & real-time response systems. Their long-term vision includes deploying the Autonomous Response capabilities that we’ve successfully implemented in Singapore & other global cities. 

Incident Response Time Improved by  80%

Autonomous Response System is crucial in real-time crisis management. During a major incident in Singapore’s Little India some time back, where a bus accident had led to a riot, our system followed an efficient protocol:

  • Detected the escalation within seconds
  • Autonomously locating the nearest responders and sending directions & incident footage to their smartphones
  • Enabled police to arrive within two minutes, with ambulances & fire services following swiftly
  • Successfully reduced response time by 80%

By continuously monitoring, detecting threats & coordinating responses without the need for human intervention, the system proved essential in enhancing public safety and operational efficiency. Over time, our capabilities have transformed autonomous response systems.

Unmatched Police Capabilities & Advantages

  • Multi-Sensory AI: Integrating video, sound, & smell, our AI provides powerful solutions for surveillance, crime detection, and crowd management.
  • Autonomous & Mobile-Ready: Operates independently, sending incident alerts to responders’ smartphones, removing the need for large control rooms & allowing flexible remote management.
  • Range of Use Cases: Supports crime detection, crowd control, traffic monitoring, license plate recognition, missing person searches & hazardous behavior detection with anonymized tracking for privacy.
  • Cost-Effective & Scalable: Utilizes existing CCTV & low-resolution cameras, requiring 90% less storage & bandwidth, with no need for GPUs, lowering costs.
  • Privacy-Focused: Advanced protections ensure anonymity while maintaining GDPR compliance.
  • Local Advantage: Developed in Hong Kong, providing reliable local support without open-source dependencies.

Contact Us to Understand How We Can Work With You!

Follow all the action on LinkedIn!

As WildFaces continues to drive innovation in AI and smart cities, we encourage you to stay connected with us. Follow our LinkedIn page for the latest updates, industry insights, and future projects. Join our growing community and be part of the journey as we shape the future of intelligent technology.

Follow us on LinkedIn here

About WildFaces:

WildFaces’ patented “On-The-Move” Artificial Intelligence (AI) based analytics system, WildAI, provides video, sound and smell analytics from moving sensors/ cameras on drones, moving robots and body-worn cameras. Such systems have been implemented on numerous government and commercial sites worldwide.

Applications range from anonymized tracking (with privacy protection) and traffic congestion management to sound and smell analytics.

WildAI requires minimal training, is computing light (does not require GPUs) and can be deployed very quickly. It:

  • Operates in real-time even when the sensor is “On-the-move”.
  • Requires little data training – no labelling, no deep learning
  • Is infrastructure light – fewer cameras required
  • Is computation light

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