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ReconaSense Provides Adaptive Physical Security Using Artificial Intelligence

Larry Anderson
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Physical security has been stuck in a forensic and siloed mindset for decades, while the rest of the enterprise has evolved and transformed into proactive, connected operations. A new security management platform based on artificial intelligence (AI) seeks to change that status quo by using modern tools for unification, analytics and controls.

AI-based security management 

“Security teams are managing more moving parts than ever,” says Clayton Brown, Co-Founder of ReconaSense. “As it stands today, the industry can’t keep pace with the digital transformation and the ‘smart’ movement. Physical security must transition from forensic security to proactive, risk-adaptive security.”

ReconaSense says the company is changing the physical security industry with AI-based technology and a risk-adaptive approach

ReconaSense says the company is changing the physical security industry with AI-based technology and a risk-adaptive approach. “We’re focused on making security integrated, adaptive and proactive,” says Brown. The flagship product, ReconAccess, is a risk-adaptive physical access control system. It controls who can go where, when, in a building. Taken a step further, ReconAccess analyses risk to prevent an authorized person from entering a room if there is a danger or threat present. It also can spot abnormal activity that may warrant further investigation, i.e., insider threats.

ReconAccess unification security solution

ReconAccess is part of a unification platform that includes geospatial AI, mobile apps and analytics. ReconaSense helps organizations to mitigate risk effectively in two ways. First, the system pulls in data from disparate systems into a unified language. And then, it enables users to proactively identify risk and threats before they become issues. “We provide actionable guidance and unprecedented visibility so that they can implement appropriate controls for quick remediation and risk mitigation,” says Brown. 

In general, ReconaSense will improve life safety, future-proof physical security, and provide enhanced situational awareness, he says.

Application programming interfaces (APIs)

By creating a database translation layer through application programming interfaces (APIs), ReconaSense normalizes diverse data into a common language, or database. Previous unification platforms have presented data from different systems into a common presentation layer.

ReconaSense goes deeper by extracting, transforming and loading these diverse languages into a common format for humans and machines alike to understand what is going on across their operation in real-time.

ReconaSense was honored with the Security Industry Association (SIA) New Product Showcase Award for Access Control Software at ISC West 2019

Security and risk unification

The ReconaSense security and risk unification platform integrates and translates siloed data across systems, devices and applications into a common language, which makes it easier to focus on what matters most and keep risk at bay.

“We can change permissions in real time based on any individual behavior or environment,” says Brown. “Being able to assess risk on both sides of the door enables organizations to not only improve security but also improve life safety. We are also positioned to detect insider threats and to streamline operations overall.”

Security and data integration

ReconaSense provides a common operating picture integrating all the incoming security and relevant data across an organization ReconaSense provides a common operating picture integrating all the incoming security and relevant data across an organization. The security intelligence platform can detect early warning signs and abnormal events and implement remediation actions swiftly. The platform can more deeply integrate 3rd-party data systems, analyze and score the data for risk trends, and then activate changes with a native access control system based on this intelligence.

ReconaSense works with traditional security integrators as its exclusive channel. They are actively adding more dealers to the network. At this point, distribution is not on the roadmap, but could be beyond the current horizon as the industry matures.

Intelligent approach to physical security

"The market is ready for the new technology",says Brown. “We must continue to educate integrators and end users on the need to move to a more proactive, intelligent and integrated approach for physical security,” he says. “We have to help demonstrate that AI is not as scary or far away as you think. It’s here today.”

In one year, ReconaSense expects to grow its team and partner network significantly and to be deployed in a variety of sites across North America. The current team consists of technologists, engineers, IT and physical security experts and data scientists. ReconaSense is headquartered in Austin, Texas, and has a technology center in New York.

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Author profile

Larry Anderson
Larry Anderson Editor, SecurityInformed.com & SourceSecurity.com

An experienced journalist and long-time presence in the US security industry, Larry is SecurityInformed.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 SecurityInformed's team of dedicated editorial and content professionals, guiding the "editorial roadmap" to ensure the site provides the most relevant content for security professionals.

People mentioned in this article

Clayton Brown
Clayton Brown ReconaSense
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Those fundamentals include keeping the customer first, putting the right people in the right roles, and executing technical support well. Keeping the customer first, putting the right people in the right roles, and executing technical support well  “We have to provide customer service from when we receive an order, to acknowledging it, to processing it and shipping the order,” says Takahashi. “Another piece is to deliver revisions to a product in a faster time period and introduce new products to the market in a timely way. In terms of market presence, we learn that people haven’t really heard from Pelco in a while. We have to get in front of integrators and consultants more aggressively than we have in the past.”   “It’s up to us to prove that we belong and can sustain and support customers moving forward,” he adds. “We will get new opportunities, but we will need to execute them. If we do that, we will grow.” Brand optimism Takahashi sees more reasons for optimism. “In spite of the problems, we are a big company with thousands of customers, a massive footprint, 10 offices around the world and people in over 40 countries. We are a strong, known brand around the world. These are a great foundation to grow from; we just have to execute better.” These are a great foundation to grow from; we just have to execute better Pelco’s new parent company, Transcom Capital Group, was another reason Takahashi was attracted to the position. He says Transom is led by “amazing professionals” that specialize in “transformational culture and how to diffuse best practices in an organization.” At Pelco, Transom has already led surveys, workshops and focus groups throughout the organization to create a vision, mission and values covering how the company wants to present itself in the market. From those values will emanate new process and policy improvements to move the company in the right direction. New visions and missions The company’s new, collectively developed vision is “to make the world safer.” The mission is “to deliver distinctive video solutions and world-class customer experiences.” The company’s new, collectively developed vision is “to make the world safer.” The company’s culture is built on six values: innovation and excellence, customer focus, integrity, respect and recognition, collaboration, and ownership. “We believe this is what will help drive our culture moving forward, and it’s the mindset of all of us as one team with one goal that will give us something to be proud of,” says Takahashi. “As we move into the new era of Pelco, you will see excitement internally and externally,” he adds “Everybody’s really eager to see Pelco come back and be a significant player.” Three horizons to success The idea is to look inward and improve on the current, successful product lines Takahashi sees three horizons that summarize the company’s path to future success. The first horizon is to focus on the fundamentals of what the company does today. The idea is to look inward and improve on the current, successful product lines, such as the VideoXpert video system and on-board video analytics. The second horizon will be to look at ways to advance the current feature set, whether “to build, partner or buy.” Building partnerships will be part of that success, such as the partnerships they are already building with Briefcam and Anyvision. The third horizon will be to expand their innovation, based on feedback from end users, dealers and consultants. “I want to get very deeply connected with our customer base,” says Takahashi. “Are we on the right path? Should we explore other partner relationships? We need to bring those minds together to expand our vision.” The focus should be on solving three business problems – mitigating risk, ensuring compliance and saving money. Looking ahead to ISC West in the spring, Takahashi expects Pelco to emerge as a more proactive company that is eager to engage. “We have a lot of stories to communicate, and we have not been as active as we should,” he says.

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Can AI Video Analytics Ever Really Be Intelligent?
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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. Artificial intelligence–powered video analytics is a highly promising trend that fundamentally changes the way things work. Extracting manageable data from a video stream can help recognize risky situations early on, minimizing damage and, ideally, completely avoid emergencies. At the same time, AI significantly expands the areas of application of video surveillance beyond security systems. AI significantly expands the areas of application of video surveillance beyond security systems However, the hype around this new, trendy technology prevents the potential user from choosing quality solutions in a wide variety of products. This often leads to over-expectation, followed by a complete let-down. Can AI-powered video analytics really be the key to a technological breakthrough in video surveillance? 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What AI can do Just what can artificial intelligence do in video surveillance systems at this stage of development? It can't quite analyze a sequence of events and understand the "logic" of what's happening in the cameras' field of view. At least not yet. But it's probable that AI will learn to do this in the next few years. But neural network analytics can already detect, classify, and track objects very well, providing high accuracy even in busy scenes. Artificial intelligence can be used in the real world to: detect smoke and flames for early fire warning at open areas (forest, open warehouse, parking lot, etc.); distinguish people/vehicles from animals and other moving objects, e.g. to protect the perimeter of a nature park from poachers; distinguish a person in a helmet and protective clothing from a person without them to prevent accidents at a dangerous production facility or construction site; count objects of a specific type, e.g. cars in a parking lot, people in the sales floor, wares moving on a conveyor belt, etc. in non-security-related solutions. Those are just a few examples. After training a neural network, it can tackle other, similar tasks, too. Generally, a neural network trained in specific conditions isn't replicable. In other words, it won't work as well under different conditions. On the other hand, developers have learned how to quickly train AI for the needs of a specific project. The most important requirement is having enough video footage. Somewhat apart from that is the use of neural networks in facial and automatic number-plate recognition. This is an example of reproducible neural networks (train once, deploy everywhere), which makes them more appealing commercially. If non-reproducible neural networks have only recently become economically feasible due to the rapid evolution of specialized hardware (aforementioned Intel's product, for example), then the use of AI in facial recognition and ANPR has been well established for a long time. The use of AI in facial recognition and ANPR has been well established for a long time Another kind of AI analytics that we'll explore is behavior analytics. This function, probably more than any other, is bringing video surveillance systems closer to understanding what's happening on camera. Its potential is vast. How Behavior Analytics Works From a technical point of view, behavior analytics combines artificial intelligence with a classic algorithmic approach. A neural network trained on a multitude of scenarios can determine the position of the bodies, heads, and limbs of humans in the camera's field of view. The algorithm outputs an array of data containing descriptions of their poses. Conditions can be set for data to detect a specific pose, such as raised hands, prostrated or crouching persons. Developers can use this to quickly create new detection tools to identify potentially dangerous behavior specified by a government or business client. There's no need for additional training of the neural network. How Behavior Analytics Can Be Deployed Someone crouched down next to an ATM could be a technician, CIT guard, or burglar. Bank security should be notified in any of the cases. 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Timely response to an alarm helps avoid material damages or, in other situations, casualties. Practically any pose that indicates potentially dangerous behavior can be detected An area of potential development for behavior analytics is the ability to analyze a sequence of poses by the same person or a combination of poses and relative positions of several individuals. That will be the next level of evolution in AI's use in video surveillance: moving from "detecting" to "understanding" behavior in real time. In its most basic form, this type of analytics can be deployed to detect deviations from the search procedure in correctional facilities when a person being inspected must assume a pre-defined sequence of poses. A more advanced form allows it to detect any kind of abnormal behavior, such as a brawl breaking out in a public space. Ideally, behavior analytics can predict dangerous situations based on nearly imperceptible cues gleaned from collected statistics and a Big Data analysis. At the moment, this sounds like pure fantasy, but what seemed like whimsy not too long ago is now a reality with AI. It's already beaten humans in chess and the game of Go (Weiqi). Will artificial intelligence be able to outplay humans at charades one day? It's entirely possible that we'll soon see for ourselves.

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