Artificial intelligence (AI)

Alarm.com has introduced Ambient Insights for alarm response, a new solution that recognises activity around a property and delivers contextual information to monitoring stations in the event of an alarm. Monitoring stations can use this real-time data to prioritise alarms and dispatch police, fire, or emergency medical services to properties faster. Ambient Insights also allows for responses to a wider range of emergencies and reduces dispatches for false alarms. Prioritising and assessing alarms For every alarm signal, Alarm.com can determine whether the alarm may have been caused by unusual activity, and the likelihood that the alarm may be cancelled by the property owner. With Ambient Insights, monitoring stations can use this information to assess and prioritise alarms within their queues and allow time for a customer to cancel a possible false alarm. Combined with other contextual data provided by Alarm.com’s visual verification service and alarm response portal, Ambient Insights also empowers monitoring stations to provide relevant information to public safety dispatchers and first responders. Smart monitoring Ambient Insights for alarm response is the next step to use AI and adaptive machine learning for smart monitored security " “Alarm.com has long applied machine intelligence to generate contextually aware insights proactively for property owners,” said Dan Kerzner, chief product officer at Alarm.com. “Ambient Insights for alarm response are the next step in our multi-year vision to use AI and adaptive machine learning to define the next generation of smart monitored security. We’re especially proud of this solution as it allows for a better customer experience and helps the industry reduce false alarm dispatches.” Improving public safety Ambient Insights for alarm response builds on the success of the company’s Insights Engine, a proprietary machine-learning capability that safeguards homes and businesses by identifying patterns and insights in the growing set of data generated by devices and sensors in a connected property. By learning the unique activity patterns of any home or business, Alarm. com-powered systems can respond to unusual activity on the property owner’s behalf. Now with the expansion of Ambient Insights to include alarm response, Alarm.com seeks to improve public safety and enhance the value of professionally monitored security. Emergency response “We’re thrilled with this latest innovation from Alarm.com, which is going to revolutionize emergency response and enable security providers to offer an even smarter, more differentiated customer experience,” said Pam Petrow, president and CEO of Vector Security. “The public safety implications are key. We’ll be able to get the right information to the right people at the right time in critical moments—precisely when it matters most.” Delivering protection solutions Ambient Insights delivers information to property owners and monitoring station operators to deliver unmatched protection Alongside numerous other award-winning Alarm.com security features, Ambient Insights delivers important information to both property owners and monitoring station operators, enabling Alarm. com-powered solutions to deliver unmatched protection. The new solution will complement ongoing initiatives by security industry committees to speed and streamline alarm response, including The Monitoring Association's new proposed Alarm Validation Standard. By providing Ambient Insights to monitoring stations earlier in the alarm response process, Alarm.com aims to maximise the downstream benefits of this information for first responders and property owners. Providing opportunities “From my 20-plus years in public safety, this is exactly what we’ve needed all along,” said Alicia Burns, public safety technology alliance manager for Alarm.com. “Ambient Insights for alarms, in conjunction with The Monitoring Association's proposed Alarm Validation Standard, will provide significant opportunities to make it possible for alarm responders to make better-informed decisions.”

Vector Flow, Inc., the innovator of AI and data-driven physical security solutions, announces that their Security Operations Centre (SOC) Automation Suite is proven to reduce false and nuisance alarms by over 80% in real-world applications. This enormous reduction in false alarms not only dramatically improves SOC efficiency and productivity, it lets SOC operators focus on real alarms and provide improved services. Juniper Networks, a pioneer in networking solutions company, deployed the SOC Automation Suite and noticed a significant drop in false alarms within the first 24 hours, and within a few weeks experienced an 80% drop in the total number of false-positive and nuisance alarms. Initiating video verification As an additional benefit from the system, Juniper Networks was also able to identify specific devices within their security system that needed adjustments or repairs. "Vector Flow’s AI platform solves chronic false alarms problems out of the box. We didn't have to teach it anything. It started learning from our data and started eliminating thousands of false alarms right away. This reduces our risks and costs while helping us focus on real security issues," said Loren Hansen, CPP, CISSP, Safety/Security Technology Manager at Juniper Networks. Current security systems are designed so that a SOC is notified whenever an alarm occurs Current security systems are designed so that a SOC is notified whenever an alarm occurs. Based on standard SOC procedures, each notification may require between 2 and 30 minutes of the operator’s time to verify the alarm, initiate video verification to observe activity, and in some cases dispatch a security officer to the source of the alarm to investigate. Global monitoring centres With hundreds-to-thousands of such alarms every day, large organisations bear significant costs for this time and effort, or accept elevated risks and liabilities if limited resources are unable to review every alarm. The Vector Flow SOC Automation Suite monitors and optimises thousands of connected devices automatically, eliminating many manual tasks and gathering and processing a quantity of data that supports sophisticated analysis and actionable insights. “The high number of false-positive and nuisance alarms flooding global monitoring centres and distracting operators from genuine emergencies is a situation that has gone on far too long,” says Ajay Jain, Founder and CEO of Vector Flow. Machine learning techniques The innovative solution simplifies and improves physical security operations while delivering tangible ROI “Our expertise in understanding the underlying data and applying the right mix of artificial intelligence and machine learning techniques helped us detect and remediate such false alarms from the root. Vector Flows SOC Automation Suite pays for itself with tangible ROI. Eventually, we foresee that Juniper Networks achieves 95% elimination of false alarms as the system continues to learn from the customer’s environment.” Vector Flow’s innovative data-driven physical security platform is built on a foundation of advanced AI algorithms capable of processing and analysing vast amounts of data from otherwise disparate security systems and applying automation playbooks to reduce cost and risk. The innovative solution simplifies and improves physical security operations while delivering tangible ROI and lowering TCO, enabling new levels of physical security automation.

The accuracy and performance of video analytics have been hugely enhanced in recent years, due to deep learning, high-performance computing, and big data analysis. According to asmag.com, 2021 is seeing wider adoption of AI and deep learning in particular making video surveillance and detection even more accurate, while lowering costs. The effect is to speed up post-incident investigation by allowing searching and filtering based on criteria such as personal characteristics or types of object. There is no doubt that video analytics driven by deep learning AI is becoming more common in video surveillance, whether on the periphery in cameras or at the core in NVRs/DVRs and the cloud. Cooper-I series Vendors including Dahua Technology offer cameras and recording equipment with AI video analytics functionality. Cooper-I series supports both H.264 and H.265 compression and comes with SMD Plus and AI Coding features In fact, Dahua’s range of AI products has become so wide, which it is now bringing the technology to many more users by including it in entry-level products – such as the Cooper-I series range of XVR digital video recorders. The Cooper-I series supports both H.264 and H.265 compression and comes with smart motion detection (SMD Plus) and AI Coding features. Dahua is the only manufacturer that includes AI functionality in its entry-level digital video recorders, providing users with all the advanced capabilities of AI, but at a more cost-effective price. Smart motion detection SMD Plus is enabled by default without any additional configuration needed can accurately identify people and vehicles while filtering out false alarms created by other objects, either in real-time or when searching recorded video. Using deep-learning algorithms which analyse a scene intuitively by recognising objects and patterns as humans do, rather than just registering pixel changes means a dramatic increase in detection accuracy and a consequent reduction in false alarms. AI coding Although offering users the potential for 4K Ultra High Definition images, there are potential drawbacks to the technology such as theoretically needing four times the bandwidth and storage capacity that increase the total cost of ownership. The AI Coding function of the Cooper-I series, however, saves more than 50% of bandwidth and storage space compared with only conventional H.264/H.265 coding. Combining the company’s HDCVI 6.0 Plus features with cutting-edge AI, Dahua delivers AI functionality for its complete HDCVI (HD over coax) range. Other benefits According to a report on the scope of video surveillance and intelligent analytics trends from Omdia in July 2020, the key benefits of recorder-based AI software are: There is no requirement to replace existing cameras Recorders provide more processing power and improve the performance of video analytics, compared with an edge- based hardware There is easier integration with other security or business intelligence solutions Recorders can run more analytics functions per camera feed Analytics using more than one channel such as object-tracking across multiple cameras is easier to process centrally. The report also highlights the importance of accurate detection of suspicious events, especially in high-security environments for critical infrastructure, where a missed security event could have catastrophic consequences. Growing AI market The growing use of video analytics and AI is confirmed in a 2020 report by IFSEC Global on video surveillance, which says that the overwhelming majority (71%) of security professionals believe that analytics software has reached a point where it can provide real value to them. A small majority (54%) continue not to use analytics in their own surveillance systems, demonstrating that there is still a significant untapped market for analytics. 71% said they believed video analytics has reached a point where it can provide real value The report also ranks the main reasons security professionals would invest in video analytics, top of which is the reduction in false alarms. This shows that false alarms continue to challenge the industry and finding methods to reduce them such as implementing AI-based video analytics is a major priority. An overwhelming majority of respondents to the survey (71%) said they believed video analytics has reached a point where it can provide real value. Performance and accuracy The accuracy and performance of video analytics have improved immeasurably in recent years, and users are embracing the technology in increasing numbers. This means that products such as Dahua’s Cooper-I series with SMD Plus and AI coding functions are set to contribute to the greater take-up of video analytics and AI, helping to satisfy the demand for advanced functionality at entry-level prices. It will be interesting to revisit this subject in a couple of years to see how these products have contributed to the wider use of AI among security professionals.

Security and Safety Things GmbH and Prosegur, one of the largest security companies in the world, have announced their collaboration on the development of a new Security Operations Centre (SOC) environment, leveraging the intelligence of innovative Artificial Intelligence infused video analytics and the expertise of Prosegur human operators to improve security services for customers around the globe. Prosegur will incorporate innovative, AI-infused video analytic applications from the Security & Safety Things (S&ST) platform into the Prosegur ‘SOC as a service’ offering. Edge analytic applications The edge analytic applications, which run directly on cameras or devices equipped with the S&ST operating system, will intelligently pre-filter incoming events from customer locations and augment human decisions for enhanced alarm monitoring, management and response. These new levels of automation increase serviceability to customers and reduce the number of truck rolls, which in turn allows Prosegur to more efficiently deploy its service and support operations. “Enhancing real-time monitoring with artificial intelligence helps improve the real-time operational decision-making, which ultimately results in better security and quicker response times for our clients,” said Matt Sack, Executive Chairman of Prosegur Security USA. “We greatly value our partnership with Security & Safety Things for their collaborative approach to creating customised and innovative solutions that deliver added value to our clients, and we look forward to continuing to jointly drive innovation for the whole industry.” AI video analytics We are proud to be innovating with Prosegur to drive additional value for their business and their customers" The Security & Safety Things open platform enables the deployment of AI enabled analytics applications on devices running the open S&ST operating system. These apps are highly customisable to the customer use case or vertical need and can run on a wide variety of cameras from different manufacturers and form factors. The analytics apps can detect with very low latency the relevant details in a scene and bring these to the attention of operators, providing them with true situational awareness needed for rapid response to prevent incidents and save lives without the need to monitor dozens of video feeds. “The Security & Safety Things business model of making AI video analytics available for customers around the globe through an open Application Store is unique in the industry. We are proud to be innovating with Prosegur to drive additional value for their business and their customers,” said Hartmut Schaper, Chief Executive Officer, Security & Safety Things. Licence plate recognition “This partnership provides a blueprint for how new business models can be innovated using open platforms and AI, and underscores once more that joint innovation will shape the future of our industry.” The nearly 100 unique applications available in the S&ST Application Store provide end-users with security operational intelligence for their application - foot traffic in a retail store, the presence of employee-worn safety equipment in a warehouse, queue counting and management at a stadium, licence plate recognition for contactless parking or weapons detection for a campus. All together more than 50 use cases are currently covered serving the needs of at least 20 industry verticals.

Amongst the many negative consequences of the pandemic is a rise in violent and abusive behaviour across society. Health workers have experienced it on a regular basis. So too have police officers and public transport workers. Unfortunately, violence and abuse towards shop workers is also endemic in British society. To address this problem which, in truth, has been on the rise since long before the emergence of COVID-19, we need better deterrents. The ability to prosecute these offences is one such deterrent, but just as important is the ability to deescalate situations before they spill over into unacceptable or unlawful behaviour. Major retail customers In both instances, organisations of all sizes are now recognising that the answer could involve greater use of rapidly advancing body worn camera technology. Andy Marsh, the Chief Constable of Avon and Somerset Police, is one of the police officers responsible for introducing body worn cameras to the UK police force, where they are now in widespread use. Andy Marsh is one of the police officers responsible for introducing body worn cameras to the UK police force He explains that “The reason the majority of people don’t speed or drink-drive is that rational human beings weigh up the risk and consequences of breaking the law and getting caught. Body worn cameras help provide appropriate ‘desistance’, especially where there are forward-facing screens so the person interacting with the wearer can see themselves and their behaviour.” Evidence shows that if a forward-facing camera is switched on before the intervention becomes hostile, it will generally lead to a de-escalation – as often as 90% of the time, according to one of our major retail customers. Digital evidence investigations Only a tiny handful of abusive incidents ever translate into arrests and prosecutions. A key issue is a lack of clear evidence – how to get past the usual impasse of one person’s word against the other. Body worn cameras break the deadlock and allow organisations to report incidents to the police with confidence, knowing that they will lead to action. Marsh suggests that “We usually see an earlier admission, an earlier guilty plea and a more appropriate sentence, where body worn camera footage is in play.” The technology has come on in leaps and bounds in recent years. For example, it’s now possible to record high-definition footage on a lightweight device that’s barely the size of a palm. And it’s not just about the evidence organisations gather themselves. Many police forces are looking at ways to make it easier for businesses and the public to collaborate on digital evidence investigations. Body worn cameras This is good for the victims of crime because it means we get the evidence more quickly" “We’ve created an online crime portal in Avon and Somerset which people can use to pass digital evidence and material to us without an officer having to attend their premises. This is good for the victims of crime because it means we get the evidence more quickly and can take action more swiftly to resolve that issue,” adds Marsh. Our body worn cameras can now even support facial recognition thanks to new, smart AI on the devices themselves, which can scan and process faces within a three-metre distance against a pre-defined database of people (which we call a watchlist). Any matches trigger alerts or additional camera activity such as recording and streaming, while the facial recognition data of people not on the watchlist itself is not recorded or saved to assuage privacy concerns. Similar criminal behaviour Where could this technology come in handy? Well, staff at gambling venues or in-store retail workers could undoubtedly benefit from the ability to quickly spot known fraudsters or addicts who have requested that venues refuse their custom. Stewards at mass sporting events could play a key role in helping to identify people who have been banned from attending. The primary reason for using body worn cameras is to increase the safety of frontline workers The primary reason for using body worn cameras is to increase the safety of frontline workers, deescalating confrontations and limiting the use of force. AI-powered facial recognition can also serve this purpose by helping them make better-informed choices about how to handle specific situations. For example, it is a massive advantage to police officers on the beat to understand that the person they are dealing with may have a history of similar criminal behaviour. Facial recognition technology But it’s also an advantage within retail, where aggressive incidents are on the rise and staff need all the help they can get to determine what an appropriate response should be to a particular customer incident. In fact, extensive consultation with our retail, police, transport and gambling customers indicates that introducing facial recognition technology to body worn cameras could be instrumental, not just in helping to prevent crime, but in tracking down vulnerable and missing people too. Of course, facial recognition technology has to be balanced against the need to protect the privacy of ordinary citizens. Video recording using body worn cameras has to be done proportionately – the same is true for the use of facial recognition technology. The technology also has to be compliant with GDPR, Data Protection, the Information Commissioners recommendations and so on. Positive working environment Violent and abusive incidents affect everyone in the immediate vicinity and create a culture of fear Importantly, it should be for a specific, proportionate and justifiable reason which, of course, means it should never be used for indiscriminate mass surveillance. Every organisation using this technology must remember that a facial recognition system match is not proof of someone’s identity, but rather, an indication of likelihood to help inform the user rather than dictate the course of action. Violent and abusive incidents affect everyone in the immediate vicinity and create a culture of fear and apprehension. This is why it’s so important to get on top of the problem – both on a societal and at an organisational level. Body worn cameras have a vital role to play, as an evidence-gathering tool and as a deterrent that empowers the wearer and creates a more positive working environment. Deterring unlawful behaviour One of the critical roles these cameras play is in staff training, providing real-world video evidence that can be used to educate and upskill workers across a variety of industries. Society’s problem with abusive and violent behaviour cannot be solved by technology alone. But with exceptional quality camera footage now a reality, and the possibility of AI technology at the device level in real-time, body worn cameras will only get better at deterring unlawful behaviour and helping to protect hardworking frontline staff. Alasdair Field is CEO of video technology provider Reveal, which works with UK police forces and major brands such as Matalan, JD Sports and Boots to help them improve staff safety, deescalate confrontations and reduce violent and abusive incidents.

Have you ever stopped to consider the volume of new data created daily on social media? It’s staggering. Take Twitter, for instance. Approximately 500 million tweets are published every day, adding up to more than 200 billion posts per year. On Facebook, users upload an additional 350 million photos per day, and on YouTube, nearly 720,000 hours of new video content is added every 24 hours. While this overwhelming volume of information may be of no concern to your average social media user posting updates to keep up with family and friends, it’s of particular interest to corporate security and safety professionals who are increasingly using it to monitor current events and detect potential risks around their people and locations—all in real-time. Meet the fast-paced and oft-confusing world of open-source intelligence (OSINT). What is Open Source Intelligence (OSINT)? The U.S. Department of State defines OSINT as, “intelligence that is produced from publicly available information and is collected, exploited, and disseminated promptly to an appropriate audience to address a specific intelligence requirement.” The concept of monitoring and leveraging publicly available information sources for intelligence purposes dates back to the 1930s. The British Broadcast Corporation (BBC) was approached by the British government and asked to develop a new service that would capture and analyse print journalism from around the world. Monitoring and identifying potential threats Originally named the “Digest of Foreign Broadcast, the service (later renamed BBC Monitoring which still exists today) captured and analysed nearly 1.25 million broadcast words every day to help British intelligence officials keep tabs on conversations taking place abroad and what foreign governments were saying to their constituents. OSINT encompasses any publicly accessible information that can be used to monitor and identify potential threats Today, OSINT broadly encompasses any publicly accessible information that can be used to monitor and identify potential threats and/or relevant events with the potential to impact safety or business operations. The potential of OSINT data is extraordinary. Not only can it enable security and safety teams to quickly identify pertinent information that may pose a material risk to their business or people, but it can also be captured by anyone with the right set of tools and training. OSINT for cybersecurity and physical threat detection Whether it be a significant weather event, supply chain disruptions, or a world health crisis few saw coming, the threats facing organisations continue to increase in size and scale. Luckily, OSINT has been able to accelerate how organisations detect, validate, and respond to these threats, and it has proved invaluable in reducing risk and informing decision-making – especially during emergencies. OSINT is typically shared in real-time, so once a situation is reported, security teams can then work on verifying critical details such as the location or time an incident occurred or provide the most up-to-date information about rapidly developing events on the ground. They can then continue to monitor online chatter about the crisis, increasing their situational awareness and speeding up their incident response times. OSINT applications OSINT can help detect when sensitive company information may have been accessed by hackers  Severe weather offers a good example of OSINT in action. Say an organisation is located in the Great Plains. They could use OSINT from sources like the National Weather Service or National Oceanic and Atmospheric Administration (NOAA) to initiate emergency communications to employees about tornado warnings, high winds, or other dangerous conditions as they are reported. Another common use case for OSINT involves data breaches and cyber-attacks. OSINT can help detect when sensitive company information may have been accessed by hackers by monitoring dark web messaging boards and forums. In 2019, T-Mobile suffered a data breach that affected more than a million customers, but it was able to quickly alert affected users after finding their personal data online. OSINT is a well-established field with countless applications. Unfortunately, in an ever-changing digital world, it’s not always enough to help organizations weather a crisis. Why OSINT alone isn’t enough? One of the core challenges with leveraging OSINT data, especially social media intelligence (SOCMINT), is that much of it is unstructured and spread across many disparate sources, making it difficult to sort through, manage, and organise. Consider the social media statistics above. Assuming a business wanted to monitor all conversations on Twitter to ensure all relevant information was captured, it would need to both capture and analyze 500 million individual posts every day. Assuming a trained analyst spent just three seconds analysing each post, that would amount to 1.5 billion seconds of labor—equivalent to 416,666 hours—just to keep pace. While technology and filters can greatly reduce the burden and help organisations narrow the scope of their analysis, it’s easy to see how quickly human capital constraints can limit the utility of OSINT data—even for the largest companies. Challenges with OSINT OSINT data collection includes both passive and active techniques, each requiring a different level of effort and skill Additionally, collecting OSINT data is time-consuming and resource-intensive. Making sense of it remains a highly specialised skill set requiring years of training. In an emergency where every second count, the time required to sift through copious amounts of information takes far longer than the time in which an organisation must take meaningful action to alter the outcome. Compounding the issue, OSINT data is noisy and difficult to filter. Even trained analysts find the need to constantly monitor, search, and filter voluminous troves of unstructured data tedious. Artificial intelligence and machine learning have helped weed through some of this data faster, but for organisations with multiple locations tasked with monitoring hundreds or thousands of employees, it’s still a challenging task. Adding to the complexity, collecting OSINT data isn’t easy. OSINT data collection includes both passive and active techniques, each requiring a different level of effort and skill. Passive vs Active OSINT Passive OSINT is typically anonymous and meant to avoid drawing attention to the person requesting the information. Scrolling user posts on public social media profiles is a good example of passive OSINT. Active OSINT refers to information proactively sought out, but it often requires a more purposeful effort to retrieve it. That may mean specific login details are needed to access a website where information is stored. Lastly, unverified OSINT data can’t always be trusted. Analysts often encounter false positives or fake reports, which not only take time to confirm accuracy, but if they act on misinformation, the result could be damage to their organisation’s reputation or worse. So, how can companies take advantage of it without staffing an army of analysts or creating operational headaches? A new path for OSINT Organisations can leverage the benefits of OSINT to improve situational awareness and aid decision-making Fortunately, organisations can leverage the benefits of OSINT to improve situational awareness and aid decision-making without hiring a dedicated team of analysts to comb through the data. By combining OSINT data with third-party threat intelligence solutions, organisations can get a cleaner, more actionable view of what’s happening in the world. Threat intelligence solutions not only offer speed by monitoring for only the most relevant events 24/7/365, but they also offer more comprehensive coverage of a wide range of threat types. What’s more, the data is often verified and married with location intelligence to help organisations better understand if, how, and to what extent each threat poses a risk to their people, facilities, and assets. In a world with a never-ending stream of information available, learning how to parse and interpret it becomes all the more important. OSINT is a necessary piece to any organisation’s threat intelligence and monitoring system, but it can’t be the only solution. Paired with external threat intelligence tools, OSINT can help reduce risk and keep employees safe during emergencies and critical events.

As the COVID-19 pandemic wanes and sporting venues open-up to full capacity, a new disturbing trend has hit the headlines - poor fan behaviour. Five NBA teams have issued indefinite bans on fans, who crossed the line of unacceptable behaviour, during the NBA playoffs. Major League Baseball stadiums have a recurring problem with divisive political banners being strewn over walls, as part of an organised campaign, requiring fan ejections. There was a brawl between Clippers and Suns fans after Game 1 of their playoff series. And, the U.S. vs. Mexico Nations League soccer game over the Fourth of July weekend had to be halted, due to fans throwing objects at players and screaming offensive chants. Cracking down on poor fan behaviour Security directors are consistently reporting a disturbing uptick in poor fan attitude and behaviour With players across all major sports leagues commanding more power than ever before, they are demanding that sports venues crack down on poor fan behaviour, particularly when they are the targets of that behaviour. Whether it’s an extension of the social-media divisiveness that’s gripped society, or people unleashing pent up negative energy, following 15 months of social isolation, during the COVID-19 global pandemic, security directors are consistently reporting a disturbing uptick in poor fan attitude and behaviour. They’re also reporting a chronic security guard shortage, like many businesses that rely on relatively low-cost labour, finding candidates to fill open positions has been incredibly difficult. Low police morale To add the third component to this perfect storm, many police departments are struggling with morale issues and officers are less likely to put themselves into positions, where they could wind up in a viral video. According to the Police Executive Research Forum, police officer retirements in the U.S. were up 45% in the April 2020 - April 2021 period, when compared to the previous year. Resignations were up 18%. In this environment, officers may be less likely to undertake fan intervention unless it’s absolutely necessary. This can seem like the worst of times for venue security directors, as they need more staff to handle increasingly unruly patrons, but that staff simply isn’t available. And, because the security guard staffing industry is a commoditised business, companies compete almost solely on price, which requires that they keep salaries as low as possible, which perpetuates the lack of interest in people participating in the profession. Digital Transformation There is only one way out of this conundrum and that is to make security personnel more efficient and effective. Other industries have solved similar staffing and cost challenges through digital transformation. For example, only a small percentage of the total population of restaurants in the U.S. used to offer home delivery, due to cost and staffing challenges of hiring dedicated delivery personnel. Advent of digital efficiency tools But with the advent of digital efficiency tools, now virtually all restaurants can offer delivery But with the advent of digital efficiency tools, such as UberEATS and DoorDash, now virtually all restaurants can offer delivery. Likewise, field-service personnel are digitally connected, so when new jobs arise, they can be notified and routed to the location. Compare this to the old paper-based days, when they wouldn’t know about any new jobs until they picked up their work schedule at the office, the next day and you can see how digital transformation makes each worker significantly more efficient. Security guards and manned guarding The security guard business has never undergone this kind of digital transformation. The state-of-the-art ‘technology’ has never changed - human eyes and ears. Yes, there are video cameras all over stadiums and other venues, but behind the scenes is a guard staring at a bunch of monitors, hoping to identify incidents that need attention. Meanwhile, there are other guards stationed around the stadium, spending most of their time watching people who are doing nothing wrong. Think about all the wasted time involved with these activities – not to mention the relentless boredom and ‘alert fatigue’ from false-positive incident reporting and you understand the fundamental inefficiencies of this labour-based approach to security. Now think about a world where there’s ubiquitous video surveillance and guards are automatically and pre-emptively notified and briefed, when situations arise. The fundamental nature of the security guards profession changes. Instead of being low paid ‘watchers’, they instead become digitally-empowered preventers. AI-based screening and monitoring technology This world is happening today, through Artificial Intelligence-based screening and monitoring technology. AI-powered weapons-detection gateways inform guards, when a patron entering the venue is carrying a gun, knife or other forbidden item. Instead of patting down every patron with metal in their pockets, which has been the standard practice since walk-through metal detectors were mandated by sports leagues following 9/11, guards can now target only those who are carrying these specific items. Video surveillance and AI-based analytics integration Combining surveillance video with AI-based advanced analytics can automatically identify fan disturbances Combining surveillance video with AI-based advanced analytics can automatically identify fan disturbances or other operational issues, and notify guards in real time, eliminating the need to have large numbers of guards monitoring video feeds and patrons. The business benefits of digitally transformed guards are compelling. A National Hockey League security director says he used to have 300 guards manning 100 walk-through metal detectors. By moving to AI solutions, he can significantly reduce the number of scanning portals and guards, and most importantly redeploy and gain further operational efficiencies with his overall operational strategy. Changing staffing strategy This changes the staffing strategy significantly and elevates the roles of guards. Suddenly, a US$ 20-per-hour ‘job’ becomes a US$ 40-per-hour profession, with guards transformed into digital knowledge workers delivering better outcomes with digitally enabled staffs. Beyond that, these digitally transformed guards can spend a much higher percentage of their time focused on tasks that impact the fan experience – whether it’s keeping weapons out of the building, pro-actively dealing with unruly fans before a broader disruption occurs, or managing business operations that positively impact fan patron experience. Digitally transforming security guards Perhaps most important, digitally transforming security guards elevates the profession to a more strategic level, which means better pay for the guards, better service for clients of guard services, and an overall better experience for fans. That’s a perfect storm of goodness for everyone.

A new generation of video cameras is poised to boost capabilities dramatically at the edge of the IP network, including more powerful artificial intelligence (AI) and higher resolutions, and paving the way for new applications that would have previously been too expensive or complex. Technologies at the heart of the coming new generation of video cameras are Ambarella’s newest systems on chips (SoCs). Ambarella’s CV5S and CV52S product families are bringing a new level of on-camera AI performance and integration to multi-imager and single-imager IP cameras. Both of these SoCs are manufactured in the ‘5 nm’ manufacturing process, bringing performance improvements and power savings, compared to the previous generation of SoCs manufactured at ‘10nm’. CV5S and CV52S AI-powered SoCs The CV5S, designed for multi-imager cameras, is able to process, encode and perform advanced AI on up to four imagers at 4Kp30 resolution, simultaneously and at less than 5 watts. This enables multi-headed camera designs with up to four 4K imagers looking at different portions of a scene, as well as very high-resolution, single-imager cameras of up to 32 MP resolution and beyond. The CV52S, designed for single-imager cameras with very powerful onboard AI, is the next-generation of the company’s successful CV22S mainstream 4K camera AI chip. This new SoC family quadruples the AI processing performance, while keeping the same low power consumption of less than 3 watts for 4Kp60 encoding with advanced AI processing. Faster and ubiquitous AI capabilities Ambarella’s newest AI vision SoCs for security, the CV5S and CV52S, are competitive solutions" “Security system designers desire higher resolutions, increasing channel counts, and ever faster and more ubiquitous AI capabilities,” explains John Lorenz, Senior Technology and Market Analyst, Computing, at Yole Développement (Yole), a French market research firm. John Lorenz adds, “Ambarella’s newest AI vision SoCs for security, the CV5S and CV52S, are competitive solutions for meeting the growing demands of the security IC (integrated circuit) sector, which our latest report forecasts to exceed US$ 4 billion by 2025, with two-thirds of that being chips with AI capabilities.” Edge AI vision processors Ambarella’s new CV5S and CV52S edge AI vision processors enable new classes of cameras that would not have been possible in the past, with a single SoC architecture. For example, implementing a 4x 4K multi-imager with AI would have traditionally required at least two SoCs (at least one for encoding and one for AI), and the overall power consumption would have made those designs bulky and prohibitively expensive. By reducing the number of required SoCs, the CV5S enables advanced camera designs such as AI-enabled 4x 4K imagers at price points much lower than would have previously been possible. “What we are usually trying to do with our SoCs is to keep the price points similar to the previous generations, given that camera retail prices tend to be fairly fixed,” said Jerome Gigot, Ambarella's Senior Director of Marketing. 4K multi-imager cameras “However, higher-end 4K multi-imager cameras tend to retail for thousands of dollars, and so even though there will be a small premium on the SoC for the 2X improvement in performance, this will not make a significant impact to the final MSRP of the camera,” adds Jerome Gigot. In addition, the overall system cost might go down, Gigot notes, compared to what could be built today because there is no longer a need for external chips to perform AI, or extra components for power dissipation. The new chips will be available in the second half of 2021, and it typically takes about 12 to 18 months for Ambarella’s customers (camera manufacturers) to produce final cameras. Therefore, the first cameras, based on these new SoCs, should hit the market sometime in the second half of 2022. Reference boards for camera manufacturers The software on these new SoCs is an evolution of our unified Linux SDK" As with Ambarella’s previous generations of edge AI vision SoCs for security, the company will make available reference boards to camera manufacturers soon, allowing them to develop their cameras based on the new CV5S and CV52S SoC families. “The software on these new SoCs is an evolution of our unified Linux SDK that is already available on our previous generations SoCs, which makes the transition easy for our customers,” said Jerome Gigot. Better crime detection Detecting criminals in a crowd, using face recognition and/or licence plate recognition, has been a daunting challenge for security, and one the new chips will help to address. “Actually, these applications are one of the main reasons why Ambarella is introducing these two new SoC families,” said Jerome Gigot. Typically, resolutions of 4K and higher have been a smaller portion of the security market, given that they came at a premium price tag for the high-end optics, image sensor and SoC. Also, the cost and extra bandwidth of storing and streaming 4K video were not always worth it for the benefit of just viewing video at higher resolution. 4K AI processing on-camera The advent of on-camera AI at 4K changes the paradigm. By enabling 4K AI processing on-camera, smaller objects at longer distances can now be detected and analysed without having to go to a server, and with much higher detail and accuracy compared to what can be done on a 2 MP or 5 MP cameras. This means that fewer false alarms will be generated, and each camera will now be able to cover a longer distance and wider area, offering more meaningful insights without necessarily having to stream and store that 4K video to a back-end server. “This is valuable, for example, for traffic cameras mounted on top of high poles, which need to be able to see very far out and identify cars and licence plates that are hundreds of meters away,” said Jerome Gigot. The advent of on-camera AI at 4K changes the paradigm Enhanced video analytics and wider coverage “Ambarella’s new CV5S and CV52S SoCs truly allow the industry to take advantage of higher resolution on-camera for better analytics and wider coverage, but without all the costs typically incurred by having to stream high-quality 4K video out 24/7 to a remote server for offline analytics,” said Jerome Gigot. He adds, “So, next-generation cameras will now be able to identify more criminals, faces and licence plates, at longer distances, for an overall lower cost and with faster response times by doing it all locally on-camera.” Deployment in retail applications Retail environments can be some of the toughest, as the cameras may be looking at hundreds of people at once Retail applications are another big selling point. Retail environments can be some of the toughest, as the cameras may be looking at hundreds of people at once (e.g., in a mall), to provide not only security features, but also other business analytics, such as foot traffic and occupancy maps that can be used later to improve product placement. The higher resolution and higher AI performance, enabled by the new Ambarella SoCs, provide a leap forward in addressing those scenarios. In a store setup, a ceiling-mounted camera with four 4K imagers can simultaneously look at the cashier line on one side of the store, sending alerts when a line is getting too long and a new cashier needs to be deployed, while at the same time looking at the entrance on the other side of the store, to count the people coming in and out. This leaves two additional 4K imagers for monitoring specific product aisles and generating real-time business analytics. Use in cashier-less stores Another retail application is a cashier-less store. Here, a CV5S or CV52S-based camera mounted on the ceiling will have enough resolution and AI performance to track goods, while the customer grabs them and puts them in their cart, as well as to automatically track which customer is purchasing which item. In a warehouse scenario, items and boxes moving across the floor could also be followed locally, on a single ceiling-mounted camera that covers a wide area of the warehouse. Additionally, these items and boxes could be tracked across the different imagers in a multi-headed camera setup, without the video having to be sent to a server to perform the tracking. Updating on-camera AI networks Another feature of Ambarella’s SoCs is that their on-camera AI networks can be updated on-the-fly, without having to stop the video recording and without losing any video frames. So, for example in the case of a search for a missing vehicle, the characteristics of that missing vehicle (make, model, colour, licence plate) can be sent to a cluster of cameras in the general area, where the vehicle is thought to be missing, and all those cameras can be automatically updated to run a live search on that specific vehicle. If any of the cameras gets a match, a remote operator can be notified and receive a picture, or even a live video feed of the scene. Efficient traffic management With the CV52S edge AI vision SoC, those decisions can be made locally at each intersection by the camera itself Relating to traffic congestion, most big cities have thousands of intersections that they need to monitor and manage. Trying to do this from one central location is costly and difficult, as there is so much video data to process and analyse, in order to make those traffic decisions (to control the traffic lights, reverse lanes, etc.). With the CV52S edge AI vision SoC, those decisions can be made locally at each intersection by the camera itself. The camera would then take actions autonomously (for example, adjust traffic-light timing) and only report a status update to the main traffic control centre. So now, instead of having one central location trying to manage 1,000 intersections, a city can have 1,000 smart AI cameras, each managing its own location and providing updates and metadata to a central server. Superior privacy Privacy is always a concern with video. In this case, doing AI on-camera is inherently more private than streaming the video to a server for analysis. Less data transmission means fewer points of entry for a hacker trying to access the video. On Ambarella’s CV5S and CV52S SoCs, the video can be analysed locally and then discarded, with just a signature or metadata of the face being used to find a match. No actual video needs to be stored or transmitted, which ensures total privacy. In addition, the chips contain a very secure hardware cyber security block, including OTP memory, Arm TrustZones, DRAM scrambling and I/O virtualisation. This makes it very difficult for a hacker to replace the firmware on the camera, providing another level of security and privacy at the system level. Privacy Masking Another privacy feature is the concept of privacy masking. This feature enables portions of the video (say a door or a window) to be blocked out, before being encoded in the video stream. The blocked portions of the scene are not present in the recorded video, thus providing a privacy option for cameras that are facing private areas. “With on-camera AI, each device becomes its own smart endpoint, and can be reconfigured at will to serve the specific physical security needs of its installation,” said Jerome Gigot, adding “The possibilities are endless, and our mission as an SoC maker is really to provide a powerful and easy-to-use platform, complete with computer-vision tools, that enable our customers and their partners to easily deploy their own AI software on-camera.” Physical security in parking lots With a CV5S or CV52S AI-enabled camera, the camera will be able to cover a much wider portion of the parking lot One example is physical security in a parking lot. A camera today might be used to just record part of the parking lot, so that an operator can go back and look at the video if a car were broken into or some other incident occurred. With a CV5S or CV52S AI-enabled camera, first of all, the camera will be able to cover a much wider portion of the parking lot. Additionally, it will be able to detect the licence plates of all the cars going in and out, to automatically bill the owners. If there is a special event, the camera can be reprogrammed to identify VIP vehicles and automatically redirect them to the VIP portion of the lot, while reporting to the entrance station or sign how many parking spots are available. It can even tell the cars approaching the lot where to go. Advantages of using edge AI vision SoCs Jerome Gigot said, “The possibilities are endless and they span across many verticals. The market is primed to embrace these new capabilities. Recent advances in edge AI vision SoCs have brought about a period of change in the physical security space. Companies that would have, historically, only provided security cameras, are now getting into adjacent verticals such as smart retail, smart cities and smart buildings.” He adds, “These changes are providing a great opportunity for all the camera makers and software providers to really differentiate themselves by providing full systems that offer a new level of insights and efficiencies to, not only the physical security manager, but now also the store owner and the building manager.” He adds, “All of these new applications are extremely healthy for the industry, as they are growing the available market for cameras, while also increasing their value and the economies of scale they can provide. Ambarella is looking forward to seeing all the innovative products that our customers will build with this new generation of SoCs.”

Imagine a world where video cameras are not just watching and reporting for security, but have an even wider positive impact on our lives. Imagine that cameras control street and building lights, as people come and go, that traffic jams are predicted and vehicles are automatically rerouted, and more tills are opened, just before a queue starts to form. Cameras with AI capabilities Cameras in stores can show us how we might look in the latest outfit as we browse. That’s the vision from Panasonic about current and future uses for their cameras that provide artificial intelligence (AI) capabilities at the edge. Panasonic feels that these types of intelligent camera applications are also the basis for automation and introduction of Industry 4.0, in which processes are automated, monitored and controlled by AI-driven systems. 4K network security cameras The company’s i-PRO AI-capable camera line can install and run up to three AI-driven video analytic applications Panasonic’s 4K network security cameras have built-in AI capabilities suitable for this next generation of intelligent applications in business and society. The company’s i-PRO AI-capable camera line can install and run up to three AI-driven video analytic applications. The AI engine is directly embedded into the camera, thus reducing costs and Panasonic’s image quality ensures the accuracy of the analytics outcome. FacePRO facial recognition technology Panasonic began advancing AI technology on the server side with FacePRO, the in-house facial recognition application, which uses AI deep learning capabilities. Moving ahead, they transitioned their knowledge of AI from the server side to the edge, introducing i-PRO security cameras with built-in AI capabilities last summer, alongside their own in-house analytics. Moreover, in line with the Panasonic approach to focus more on collaboration with specialist AI software developers, a partnership with Italian software company, A.I. Tech followed in September, with a range of intelligent applications, partially based on deep learning. Additional collaborations are already in place with more than 10 other developers, across the European Union, working on more future applications. i-PRO AI-capable security cameras Open systems are an important part of Panasonic’s current approach. The company’s i-PRO AI-capable cameras are an open platform and designed for third-party application development, therefore, applications can be built or tailored to the needs of an individual customer. Panasonic use to be a company that developed everything in-house, including all the analytics and applications. “However, now we have turned around our strategy by making our i-PRO security cameras open to integrate applications and analytics from third-party companies,” says Gerard Figols, Head of Security Solutions at Panasonic Business Europe. Flexible and adapting to specific customer needs This new approach allows the company to be more flexible and adaptable to customers’ needs. “At the same time, we can be quicker and much more tailored to the market trend,” said Gerard Figols. He adds, “For example, in the retail space, enabling retailers to enhance the customer experience, in smart cities for traffic monitoring and smart parking, and by event organisers and transport hubs to monitor and ensure safety.” Edge-based analytics offer multiple benefits over server-based systems Edge-based analytics Edge-based analytics offer multiple benefits over server-based systems. On one hand, there are monetary benefits - a cost reduction results from the decreased amount of more powerful hardware required on the server side to process the data, on top of reduction in the infrastructure costs, as not all the full video stream needs to be sent for analysis, we can work solely with the metadata. On the other hand, there are also advantages of flexibility, as well as reliability. Each camera can have its own individual analytic setup and in case of any issue on the communication or server side, the camera can keep running the analysis at the edge, thereby making sure the CCTV system is still fully operational. Most importantly, systems can keep the same high level of accuracy. Explosion of AI camera applications We can compare the explosion of AI camera applications to the way we experienced it for smartphone applications" “We can compare the explosion of AI camera applications to the way we experienced it for smartphone applications,” said Gerard Figols, adding “However, it doesn’t mean the hardware is not important anymore, as I believe it’s more important than ever. Working with poor picture quality or if the hardware is not reliable, and works 24/7, software cannot run or deliver the outcome it has been designed for.” As hardware specialists, Figols believes that Panasonic seeks to focus on what they do best - Building long-lasting, open network cameras, which are capable of capturing the highest quality images that are required for the latest AI applications, while software developers can concentrate on bringing specialist applications to the market. Same as for smartphones, AI applications will proliferate based on market demand and succeed or fail, based on the value that they deliver. Facial recognition, privacy protection and cross line technologies Panasonic has been in the forefront in developing essential AI applications for CCTV, such as facial recognition, privacy protection and cross line. However, with the market developing so rapidly and the potential applications of AI-driven camera systems being so varied and widespread, Panasonic quickly realised that the future of their network cameras was going to be in open systems, which allow specialist developers and their customers to use their sector expertise to develop their own applications for specific vertical market applications, while using i-PRO hardware. Metadata for detection and recognition Regarding privacy, consider that the use of AI in cameras is about generating metadata for the detection and recognition of patterns, rather than identifying individual identities. “However, there are legitimate privacy concerns, but I firmly believe that attitudes will change quickly when people see the incredible benefits that this technology can deliver,” said Gerard Figols, adding “I hope that we will be able to redefine our view of cameras and AI, not just as insurance, but as life advancing and enhancing.” i-PRO AI Privacy Guard One of the AI applications that Panasonic developed was i-PRO AI Privacy Guard Seeking to understand and appreciate privacy concerns, one of the AI applications that Panasonic developed was i-PRO AI Privacy Guard that generates data without capturing individual identities, following European privacy regulations that are among the strictest in the world. Gerard Fogils said, “The combination of artificial intelligence and the latest generation open camera technology will change the world’s perceptions from Big Brother to Big Benefits. New applications will emerge as the existing generation of cameras is updated to the new open and intelligent next generation devices, and the existing role of the security camera will also continue.” Future scope of AI and cameras He adds, “Not just relying on the security cameras for evidence when things have gone wrong, end users will increasingly be able to use AI and the cameras with much higher accuracy to prevent false alarms and in a proactive way to prevent incidents." Gerard Figols concludes, “That could be monitoring and alerting when health and safety guidelines are being breached or spotting and flagging patterns of suspicious behaviour before incidents occur.”

Travel volumes at airports have been increasing of late, although still below the 2.5 million or so passengers the Transportation Security Administration (TSA) screened every day, on average, before the pandemic. As passengers return, they will notice the airport security experience has changed during the pandemic – and many of the changes are likely to continue even longer. Need for touchless technology The lowest U.S. air travel volume in history was recorded last April, with approximately 87,500 passengers. As passenger traffic plummeted, the aviation community sought to explore the potential of new technologies to make security checkpoints more contactless and flexible when the traffic numbers return. The pandemic has seen an increase in touchless technology deployed in the screening area. Used for cabin baggage screening, Computed Tomography (CT) produces high-quality, 3-D images to enable a more thorough analysis of a bag’s contents. Imaging Technology Millimeter-wave body scanners began replacing metal detectors globally as a primary screening method Enhanced Advanced Imaging Technology (eAIT), which uses non-ionising radio-frequency energy in the millimeter spectrum, safely screens passengers without physical contact for threats such as weapons and explosives, which may be hidden under a passenger’s clothing. Millimeter-wave body scanners began replacing metal detectors globally as a primary screening method.  AI algorithms Other innovations include an automatic screening lane, centralised image processing, and artificial intelligence (AI). Looking ahead, AI algorithms have the ability to clear most passengers and bags automatically, making the process smoother and freeing up staff to focus only on alarms. The pandemic’s need for contactless screening may accelerate the adoption of AI.   CAT machine Credential Authentication Technology (CAT) machines automatically verify identification documents presented by passengers during the screening process. The TSA continues to accept expired Driver’s Licenses and state-issued IDs for up to a year after expiration, based on the premise that license renewals may be delayed and/or more difficult during the pandemic. The REAL ID enforcement deadline was extended to Oct. 1, 2021.  Health precautions Checkpoint health precautions have been a part of the airport screening experience since early in the pandemic. Last summer, the TSA announced the “Stay Healthy. Stay Secure” campaign, which included requirements such as social distancing among travelers, ID verification without physical contact, plastic shielding installed at various locations, and increased cleaning and disinfecting. In January 2021, President Biden signed an Executive Order requiring travellers to wear face masks when in airports and other transportation facilities (to remain in effect until May 11). Checkpoint screening Clear is a privately owned company that provides expedited security that uses biometrics either a person’s eyes or face to speed along the process of getting people through checkpoints. TSA officers wear masks and gloves at checkpoints and may also wear eye protection or clear plastic face shields. The limits on allowable liquids a passenger may take on board were broadened to include a hand sanitiser container of up to 12 ounces, one per passenger in a carry-on bag. A paradigm shift Just as aviation security changed after 9/11, the COVID-19 crisis is expected to lead to a paradigm shift to create a safer and more secure environment. Measures were implemented so that passengers, staff and other stakeholders could have continued assurance and confidence in airports amid and after the pandemic.

SAFR from RealNetworks, Inc., a pioneer in high accuracy, low bias facial recognition, announces a collaboration with Dains, a Korean company that specialises in unmanned people and asset counting solutions. As part of the collaboration, SAFR is providing its AI-based computer vision technology to increase the accuracy of people counting to prevent duplicates of customers and employees. The combined solution was recently deployed at the National Memorial Hall of the Korean War Abductees in Paju, Gyeonggi-do. Unmanned counting system Since there is no entrance fee for the memorial, accurate statistics on the number of unique visitors were required. Dains developed an unmanned counting system with a feature to prevent counting duplication by utilising SAFR's face recognition technology. Using SAFR facial recognition, the system can ignore multiple re-entries from visitors With ceiling-mounted camera counting systems, it is difficult to avoid duplicate counts when the same person enters or exits the premises multiple times. Employees entering and exiting would also skew count accuracy. Using SAFR facial recognition, the system can ignore multiple re-entries from visitors while opted-in staff can be removed from the total count entirely. Ceiling-mounted cameras Ceiling-mounted cameras can rarely be used to identify individuals due to their limited field of view. SAFR facial recognition enables cameras to be installed at standard surveillance mounting heights so as to reliably capture individuals and events. Dains plans to expand the unmanned counting product using SAFR's face recognition technology to additional markets. It also plans to offer options for analysing visitor gender and age, enhanced employee attendance management, and access control.

LibertySpace, a provider of flexible offices, workshops, industrial and self-storage spaces, has chosen Yardi® Kube space management and Yardi Kube access control to manage six locations within its growing portfolio. Yardi® Kube space management will help LibertySpace streamline operations, provide real-time availability for members and foster community connection. Yardi Kube access control will enable 24/7 access to offices and meetings room, offering its members more flexibility and security. Providing better experience "We wanted a solution that would improve internal processes but also helped build our brand," said Jerry Alexander, Managing Director at LibertySpace. "Yardi's connected platform provides the tools to manage our portfolio and allows for growth. We can use a white label app and connect with our members in real-time, providing better communication and an enhanced experience." "We're delighted to continue working with LibertySpace as they adopt Yardi Kube space management and Yardi Kube access control," said Justin Harley, Regional Director at Yardi®. "We are always looking at ways to develop our platform and provide a better experience for our clients and their members."

Calipsa, a provider of deep-learning-powered video analytics for false alarm reduction, announced that Edmonton, Alberta-based GPS Security Group is using its false alarm filtering platform. GPS, which offers a complete range of security services across Alberta, British Columbia and other parts of Western Canada, is the third Canadian central monitoring station to adopt the cloud-based Calipsa technology. Deep learning technology Calipsa’s software uses artificial intelligence with deep learning technology to recognise genuine alarms caused by human or vehicle movement. More than 90% of notifications resulting from nuisance factors such as animals, lighting, weather or foliage are filtered out, helping operators reduce their response times to genuine threats. We’ve engaged Calipsa as a strategic growth partner to assist with reducing false video alarms" The GPS Security Group’s Fredy Ramsoondar, Corporate Senior Security Solutions Advisor and Private Investigator, said GPS is adopting Calipsa’s AI-powered video analytics across its video surveillance sites to support the sustained growth of its monitoring division. “We’ve engaged Calipsa as a strategic growth partner to assist with reducing false video alarms, allowing our operators to focus on only genuine alarms,” he said. “We anticipate widespread benefits, including improved customer service, operational efficiency and employee morale.” Cloud-based technology Tara Biglari, Calipsa’s Regional Sales Director, Americas, said its false alarm reduction software is easily scalable, making it ideal for any growing video monitoring station. “This is an exciting time of growth for the GPS team and we’re happy to partner with them to provide the highest level of customer service,” she said. “The installation of our cloud-based technology requires no onsite hardware devices and we keep our service always current with remote upgrades.” A platform dashboard enables station managers to monitor the software’s performance, including detecting idle cameras that may need replacement or moving to a better position.

BIRD Aerosystems, a globally renowned provider of innovative defence technology and solutions, which protect the air, sea and land fleets of governments and related agencies, has delivered a complete ASIO Maritime Surveillance Task Force Solution to an undisclosed African government. ASIO Maritime Task Force Solution The ASIO Maritime Task Force Solution, provided to the undisclosed African nation, includes multiple Cessna Citation CJ3 aircraft that the company converted into Maritime Patrol Aircraft, together with BIRD's advanced mission management system (MSIS), which was also installed on a number of vessels, as well as at the naval HQ command. BIRD Aerosystems' ASIO Maritime Task Force Solution provides customers with an integrated Aerial-Naval-Land solution. It facilitates maritime and coastal surveillance, patrol and survey of borders and strategic assets, and Exclusive Economic Zone (EEZ) monitoring capabilities. Advanced mission management system ASIO Maritime Task Force Solution delivers an extremely powerful and flexible maritime patrol solution Leveraging BIRD's advanced mission management system (MSIS) for complete mission operational support, including planning, execution, debriefing, online mission updates, and complete situational awareness between all segments (airborne, naval and ground) within the task forces, the ASIO Maritime Task Force Solution delivers an extremely powerful, comprehensive and flexible maritime patrol solution, enabling efficient detection, tracking and interception of any suspicious activity at sea. Ronen Factor, the Co-Chief Executive Officer and Founder at BIRD Aerosystems, stated “BIRD's ASIO Maritime Task Force Solution, including the Cessna Citation CJ3 aircraft, will be used to defend the customer's territorial waters, with an emphasis on detecting illegal fishing, oil theft, and smuggling.” He adds, “Rapidly deployed in multiple configurations, ASIO enables even small crews to deliver detailed and comprehensive surveillance information, covering large geographic areas.”

Artificial intelligence (AI) is simultaneously an emerging technology, a common term in popular culture, and a buzzword in the security industry. But these aspects of the term can lead to misunderstanding in the marketplace. AI technology is continuing to emerge, but what is the reality today? How do depictions of AI in popular culture impact how it is understood in the real world of security? As a buzzword, at what point does marketing hype garble our understanding of reality? We asked this week’s Expert Panel Roundtable: What are the misconceptions about AI in security? 

The idea of touchless systems has gained new levels of prominence during the last year, driven by the global COVID-19 pandemic. Contactless systems have been part of the industry’s toolbox for decades, while technologies like facial and iris recognition are finding new uses every day. We asked this week’s Expert Panel Roundtable: Which security markets are embracing touchless, contactless systems and why? 

Adoption of General Data Protection Regulation (GDPR) by the European Union in 2016 set a new standard for data privacy. But adherence to GDPR is only one element, among many privacy concerns sweeping the global security community and leaving almost no product category untouched, from access control to video to biometrics. Because privacy concerns are more prevalent than ever, we asked this week’s Expert Panel Roundtable: What is the impact on the physical security market?