More crowded aisles and productive conversations continued to set the tone on the second day of ISC West in Las Vegas. No big technology breakthroughs have surfaced, but there is plenty of interest, and some degree of curiosity, about whether (and when) the recent hype about artificial intelligence (AI) and deep learning will translate into usable products.

Vertical market solutions

Yesterday we saw a tremendous amount of traffic in the booth, and today is more of the same,” said Miguel Lazatin, Director, Product and Channel Marketing, Hanwha Techwin America. The layout of the Hanwha Techwin booth is different this year, although the “footprint” is the same size. “We lessened the number of kiosks within the booth, which allows for better flow, and the ability to accommodate more customers and do the demonstrations more effectively and focus more on product solutions,” Lazatin adds.

We are introducing products in new categories for Hanwha Techwin,” Lazatin says. “We have new thermal cameras, new stainless steel cameras, new multi-sensor cameras, as well as new mobile products. We are expanding our product set to address new applications and new markets.” The new products are tailored and specific solutions for those new markets, which include food processing plants, oil refineries and areas where Hanwha Techwin has not played in the past.

Although there is a lot of talk about deep learning and artificial intelligence at this year’s show, there don’t appear to be a lot of actual products being introduced in those categories. Companies of all shapes and sizes are embracing the new buzzwords, leaving some attendees unsure how these new ideas — or marketing concepts? — fit into the “real world.”

Hanwha's new products are tailored and specific solutions for those new markets, which include food processing plants and oil refineries
 Hanwha Techwin America lessened the number of kiosks within the booth, which allows for better flow

Meeting customer needs with AI

A key to leveraging the value of new technologies such as AI and deep learning is to get beyond the buzzwords and position the new capabilities in the context of actual end user benefits such as operation efficiency and automation, says Stuart Rawling, Director of Global Business Development, Pelco by Schneider Electric. “The customer doesn’t care about buzzwords, he just wants to know what are the benefits? What solutions are we offering?” At the show, Pelco announced a new alliance with IBM that will leverage Big Blue’s advanced knowledge of deep learning and analytics, and combine it with Pelco’s VideoExpert video management system (VMS). “We have a version of that integration at the show, but the real news is that we are merging our development plans to solve specific use case problems,” says Rawling.

Video analytics in the cloud

Cloud applications are also gaining traction, including the Avigilon Blue cloud platform. “It allows integrators to manage everything from one easy, central site,” says Willem Ryan, Avigilon’s VIce President, Global Marketing and Communications. “They can respond quicker and with knowledge of what the system is doing.” Video analytics are built in as an inherent part of our solution. Any IP cameras — Avigilon or ONVIF-conformant — become equipped with analytics when they are connected to the Blue platform. A new announcement at the show is Avigilon’s ACC System Health Monitoring, a new service added to the Blue platform. Health monitoring enables integrators to be more proactive in their service and keep systems running smoothly.

Cloud allows you to scale how you can manage systems and service systems rather than having to go on site to upgrade systems,” says Ryan. “People think it’s a buzzword, but really it’s a means to an end to make systems more secure, more efficient, more responsive. We’re putting a lot of investment in it.”

Avigilon also continues to upgrade its Appearance Search product to enable faster review of stored video
A new announcement at the show is Avigilon’s ACC System Health Monitoring, a new service added to the Blue platform

Building RMR for customers

The cloud also enables integrators to build more recurring monthly revenue (RMR). A cloud approach that encompasses products and ongoing service ensures that an integrator continues to “touch” customers. “For us, they can package this around service in a new way,” says Ryan. “The customer doesn’t have to worry about a large capital expense in the beginning. And as new capabilities come along, they can be added. So it becomes a way to sell a package around their company, service and products; but less about the products and more about a platform that allows them to sell their [integration] company in a new way. What we’re hearing is, it’s a change in mindset, and you need buy-in from the top of the organisation. And the sales people have to get used to selling in a different way. It’s going to take time, and our industry needs to evolve. Customers love the flexibility. And integrators need stickier customers and better profit margins.”

Avigilon also continues to upgrade its Appearance Search product to enable faster review of stored video. Now a search for video related to an investigation can begin with a physical description of a person (rather than using a reference image as a starting point in the search).

There’s one more day for attendees to roam the aisles of ISC West in search of new and useful technologies. Foot traffic historically drops off on the final day, but that just leaves more quality time for interaction among those staying until the bitter end. Count me among that group, and I will have much more to report after the show ends.

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Larry Anderson Editor, SourceSecurity.com

An experienced journalist and long-time presence in the US security industry, Larry is SourceSecurity.com's eyes and ears in the fast-changing security marketplace, attending industry and corporate events, interviewing security leaders and contributing original editorial content to the site. He leads SourceSecurity.com's team of dedicated editorial and content professionals, guiding the "editorial roadmap" to ensure the site provides the most relevant content for security professionals.

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Artificial intelligence is changing intrusion detection dynamics in the security industry
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The human brain is estimated to have 86 billion neurons; in comparison, the newest Nvidia GPU Volta has 21 billion transistors (the equivalence of a neuron), which offers the performance of hundreds of CPUs for deep learning.AI can learn continuously 24 hours per day every day, constantly acquiring, retaining and improving its knowledge In addition, unlike humans, AI can learn continuously 24 hours per day every day, constantly acquiring, retaining and improving its knowledge. With such enormous processing power, machines using Nvidia GPU and similar chips can now distinguish faces, animals, vehicles, languages, parts of speech, etc. Depending on the required complexity, level of details, acceptable error margin, and learning data quality, AI can learn new objects within as fast as a few seconds using Spiking Neural Network (SNN) to a few weeks using Convolution Neural Network (CNN). While both SNN and CNN offer advantages and drawbacks, they outperform tradition security systems without AI in terms of efficiency and accuracy. According to the research reports of MarketsandMarkets, the market size of perimeter intrusion detection systems is projected to increase from 4.12 billion USD in 2016 to 5.82 billion USD in 2021 at a Compound Annual Growth Rate (CAGR) of 7.1%. Meanwhile, the predicted market of AI in security (both cyber security and physical security) will grow from 3.92 billion USD in 2017 to 34.81 billion USD by 2025, i.e., with an impressive CAGR of 31.38%. Legacy perimeter intrusion detection systems Legacy perimeter intrusion detection systems (PIDSs) are typically set up with the following considerations: Geographical conditions: landscape, flora, fauna, climate (sunrise, sunset, weather conditions, etc.), whether there are undulations in the terrain that would block the field of view of cameras Presence or lack of other layers of physical protection or barriers Integration with other systems in the security network: camera, storage, other defensive lines (door, lock, alarm, etc.) Types of alarm triggers and responses System complexity: intrusion detection with various types of sensors, e.g., microwave sensors, radar sensors, vibration sensors, acoustic sensors, etc. Length of deployment Local regulations: privacy protection, whether the cameras/sensors must be visible/hidden/buried, etc., electromagnetic interferences that may affect other systems such as oil rigs or power plants Human involvement: on-site personnel arrangement, human monitoring, human action in response to alarms AI object detection can easily distinguish different types of people and objects Pain points and benefits of AI The conditions listed above correspond to certain requirements of an intrusion detection systems: minimal false alarm, easy setup and maintenance, easy integration, and stable performance.AI by nature is designed to learn, adapt itself and evolve to work in multiple conditions: it should be integrated with existing video recording systems  Minimal false alarms: False alarms lead to increased cost and inefficiency but are the main problem of PIDSs without AI technology, where animals, trees, shadows, and weather conditions may trigger the sensors. AI object detection can easily distinguish different types of people and objects, e.g., in a region set up to detect people, a car driving by, a cat walking by, or a person’s shadow will not trigger the alarm. Therefore, the amount of false alarms can be reduced by 70% to orders of magnitude. Easy setup and maintenance: Legacy PIDSs without AI must account for terrain, line of sight of cameras, sensor locations; any changes to the system would require manual effort to recalculate such factors and may disturb other components in the system. In contrast, AI PIDSs enable the system administrator to access the entire system or individual cameras from the control room, configure the region and object of interest in the field of view of cameras within minutes, and adjust with ease as often as necessary. Computing knowledge and even specific security training are not required to set up a secured PIDS with AI because AI PIDS is designed to relieve humans from knowing the inner working of machines. Easy integration with complementary technologies: Legacy PIDS without AI relies on physical technology, which are often proprietary and require complete overhaul of systems to function smoothly. 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