Intelligent Visual Surveillance Solution

In today's uncertain world, there is an increasing need for a higher level of security to protect against crime, vandalism and terrorism. CCTV is recognised as an effective way of detecting crime and enhancing public safety. However, the mounting number of surveillance cameras has lead to an information overload, where operators are unable to extract the relevant information because conventional CCTV records everything with little or no intelligence.

SmartVeillance solves this problem by using artificial intelligence to prioritize video observations so that the system can trigger alerts and bring important security issues to the attention of security staff.

SmartVeillance uses advanced image analysis techniques to detect and segment activity, detect, identify and track objects and events, and record information in real-time. Artificial intelligence is used to prioritize these observations so that the system can automatically trigger alerts and bring important security issues to the attention of security staff.

SmartVeillance’s vertical suite of surveillance and detection intelligence solutions includes:

Traffic Management and Monitoring

Carpark Management

Smart and Safe City

Retail Business Intelligence



For more information visit the SmartVeillance Website




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DOWNLOAD BROCHURE
Brochure SmartVeillance Safe City 2015.pdf
File Size: "1 MB"
Brochure SmartV Drone Services 2016.pdf
File Size: "5 MB"
Brochure SmartV CarparkManagement 2015.pdf
File Size: "782 KB"
Brochure SmartV CarparkManagement 2015.pdf
File Size: "782 KB"
Brochure SmartV Automobile Incidents Reporting and Alerts2016.pdf
File Size: "1 MB"
Customer Testimonial - License Plate Recognition New Zealand (JIT 2016 1).pdf
File Size: "5 MB"
Safe City PoC (SAINS Yearbook 2013).pdf
File Size: "2 MB"
Reference Sites Safe City - Iskandar Malaysia and New Zealand Carpark (JIT2013-2).pdf
File Size: "3 MB"
Reference Site UTeM (JIT2011-2).pdf
File Size: "3 MB"
Case study Safe City - Iskandar Malaysia (JIT2011 1).pdf
File Size: "1 MB"
Case Study UTHM (JIT2009-2).pdf
File Size: "1 MB"