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ISC West, the world's largest security industry trade show, is just around the corner. This in-person show gathered more than 1,000 manufacturers and over 30,000 visitors from all over the world in...

Detecting high-risk scenarios before they escalate is one of the core motivations behind the development of artificial intelligence (AI) for security applications. With AI in the quiver, operators deploying surveillance solutions can move beyond mere monitoring to leverage every video frame and piece of data available to identify threats and inform emergency response.

Video surveillance is commonly associated with security. But in most cases, it's used to record incidents and assist in investigations after the fact rather than prevent undesirable events.

The Deep Learning market is expected to grow by 43% by 2024, up to a net value of $18bn, according to a new report by MarketWatch. One application of Deep Learning software is an anti-poaching and public safety program currently being trialed in South African wildlife parks.

Technology used in creating safe urban environments is now being used in South Africa’s wildlife parks to catch and deter poachers.

More than 1,000 rhinos were killed last year as a result of poaching, with gangs now moving to neighbouring countries. Intelligent CISO hears from one woman who is trying to combat poaching thanks to Artificial Intelligence.

When a three-year-old was recently kidnapped in Shenzhen, China, it took a matter of hours for the offender to be tracked down and the child to be reunited with his parents.

Until recently, IP surveillance cameras sent only a multimedia stream to video management software, using well-defined formats and a fixed set of compression/decompression tools. So cooperation between video hardware manufacturers and software developers was stuck in a rut of sorts.