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Securing Intelligent Transportation Systems (ITS) in the transportation industry is multi-faceted for a multitude of reasons. Pressures build for transit industry players to modernise their security systems, while also mitigating the vulnerabilities, risks, and growth-restrictions associated with proprietary as well as integrated solutions. There are the usual physical security obstacles when it comes to increasingly integrated solutions and retrofitting updated technologies into legacy systems. Starting with edge devices like cameras and intelligent sensors acquiring video, analytics and beyond, these edge devices are now found in almost all public transportation like buses, trains, subways, airplanes, cruise lines, and so much more. You can even find them in the world’s last manually operated cable car systems in San Francisco. The next layer to consider is the infrastructure and networks that support these edge devices and connect them to centralized monitoring stations or a VMS. Without this layer, all efforts at the edge or stations are in vain as you lose the connection between the two. And the final layer to consider when building a comprehensive transit solution is the software, recording devices, or viewing stations themselves that capture and report the video. The challenge of mobility However, the transportation industry in particular has a very unique challenge that many others do not – mobility. As other industries become more connected and integrated, they don’t usually have to consider going in and out or bouncing between networks as edge devices physically move. Obviously in the nature of transportation, this is key. Have you ever had a bad experience with your cellular, broadband or Wi-Fi at your home or office? You are not alone. The transportation industry in particular has a very unique challenge that many others do not – mobility Can you trust these same environments to record your surveillance video to the Cloud without losing any frames, non-stop 24 hours a day, 7 days a week, 365 days a year? To add to the complexity – how do you not only provide a reliable and secure solution when it’s mobile, traveling at varying speeds, and can be in/out of coverage using various wireless technologies? Waiting to upload video from a transport vehicle when it comes into port, the station, or any centralized location is a reactive approach that simply will not do any longer. Transit operations require a more proactive approach today and the ability to constantly know what is going on at any given time on their mobile vehicles, and escalate that information to headquarters, authorities, or law enforcement if needed; which can only occur with real-time monitoring. This is the ultimate question when it comes to collecting, analyzing, and sharing data from mobile vehicles – how to get the video from public transportation vehicles alike to headquarters in real time! Managing video data In order to answer this question, let’s get back to basics. The management and nature of video data differs greatly from conventional (IT) data. Not only is video conducted of large frames, but there are specific and important relationships among the frames and the timing between them. This relationship can easily get lost in translation if not handled properly. This is why it’s critical to consider the proper way to transmit large frames while under unstable or variable networks. The Internet and its protocols were designed more than two decades ago and purposed for conventional data. Although the Internet itself has not changed, today’s network environments run a lot faster, expand to further ranges, and support a variety of different types of data. Because the internet is more reliable and affordable than in the past some might think it can handle anything. However, it is good for data, but not for video. This combination makes it the perfect time to convert video recording to the Cloud! Video transmission protocol One of the main issues with today’s technology is the degradation of video quality when transmitting video over the Internet. ITS are in dire need for reliable transmission of real-time video recording. To address this need a radical, yet proven, video transmission protocol has recently been introduced to the market. It uses AI technology and to adapt to different environments in order to always deliver high quality, complete video frames. This protocol, when equipped with encryption and authentication, enables video to be transmitted reliably and securely over the Internet in a cloud environment. One of the main issues with today’s technology is the degradation of video quality when transmitting video over the Internet Finally, transportation industry has a video recording Cloud solution that is designed for (massive) video that can handle networks that might be experiencing high error rate. Such a protocol will not only answer the current challenges of the transportation industry, but also make the previously risky Cloud environment safe for even the most reserved environments and entities. With revolutionary transmission protocols, the time is now to consider adopting private Cloud for your transportation operations.
For decades, the nature of global safety has been evolving. From physical security threats like large-scale terrorist attacks and lone actor stabbings to chemical threats such as the Salisbury poisonings and even microbiological threats such as COVID-19, new challenges are constantly arising and the threat landscape we operate in today is constantly changing. Compounding the complexity of the security issues is the complexity and nature of attacks. With the economic downturn, there is the traditional rise in theft, violence and other crimes. Compound this with unmanned businesses and work-at-home staff, and there is a perfect storm for a rise in security threats. Artificial intelligence (AI) and specifically the branch of AI known as machine learning (ML), was already causing widespread disruption in many industries, including the security industry. AI has been a driving force to replace labor-based business models with integrated data and actionable intelligence that is context-aware. It has become apparent that AI will play a big part in the ongoing fight against both pandemics such as COVID-19, as well as other threats that we may face in the future. With all of this in mind, 2021 is poised to be a big year for AI growth. While AI is going to continue to impact our lives in dozens of ways, from smart sensors to face mask compliance detection, the following reflects a few top trends and challenges that I have my eye on for 2021 as we close out this year. The rise of smart city investments One such example is the increasing development of smart cities and how AI can be leveraged to build safe communities. To date, we’ve seen an increase in the number of smart city programmes around the globe; cities that are beginning to deploy innovative technologies for the management and ease of life services. Compounding the complexity of the security issues is the complexity and nature of attacks Typical development of a city includes standard infrastructure - roads, schools, power, water, transportation. Now, internet, data and AI capabilities are part of the standard infrastructure requirements for all new developments. AI promises to deliver increased efficiencies with the infrastructure that will accommodate growing populations while reducing our impact on the environment, resources, and communities. Global cities now account for more than half of the world’s population, and the United Nations projects the number to balloon to 68% by mid-century. Owing to both demographic shifts and overall population growth, that means that around 2.5 billion people could be added to urban areas by the middle of the century, predicts the UN Department of Economic and Social Affairs (DESA). With an increase in population has come an increase in global spending on smart city initiatives to drive down the impact of growing urban concentration. Global spending on smart city initiatives is expected to total nearly $124 billion this year, an increase of 18.9% over 2019, according to IDC's Worldwide Semiannual Smart Cities Spending Guide, while Singapore, Tokyo, London and New York as the big spenders - expected to spend more than $1 billion in 2020. Using AI-driven technology to create safer public and private spaces Today, security solutions driven by AI are being developed and can be covertly deployed across a range of physical environments to protect the population in a more efficient, and accurate manner. As we look ahead to the future of public safety, it’s clear that new AI technology can dramatically improve the effectiveness of today’s physical security space. One such deployment is the use of video object recognition/computer vision software that can be integrated into existing video monitoring security (VMS) systems. These enhanced VMS systems can be deployed both inside and outside of buildings to identify risks and flag threats, such weapons, aggressive behaviours, theft, and safety compliance. This helps to minimize the impact of a breach by an early alert to onsite security in real-time to the location and nature of the potential threat, allowing them to intervene before a loss occurs. These same AI-enabled video solutions can similarly be used to provide advanced business operations in retail, logistics, and manufacturing organizations. Multi-sensor security solutions Also, targeted magnetic and radar sensor technologies, concealed in everyday objects like planter boxes or inside walls, can now scan individuals and bags entering a building for concealed threat objects. Using AI/machine learning, these two sensor solutions combined can identify metal content on the body and bag and match the item to a catalog of threat items, such as guns, rifles, knives and bombs. Security solutions driven by AI are being developed and can be covertly deployed across a range of physical environments Without this advanced multi-sensor solution, it becomes nearly impossible to discover a weapon on a person's body before it appears in an assailant’s hands. This multi-sensor solution allows for touchless, unobtrusive access to a building, but allows for immediate notification to onsite security when a concealed threat is detected. The hidden technology thus empowers security staff to intercept threats before they evolve into a wider scale attack, while also maintaining the privacy and civil liberties of the public, unless, of course, they are carrying a concealed weapon or pose a physical threat. With the advent of sophisticated surveillance and technological innovation, a level of caution must be exerted. Despite the ongoing global debate, there remains little regulation about the use of AI technologies in today’s physical security space. One thing is certain; it must be deployed in the right place, at the right time, with the right privacy and civil liberty protection objectives. People don’t want to be protected by omnipresent, obstructive and overbearing security systems that infringe on their privacy and civil liberties. They want a proper balance between security and their current way of life, one that must be fused together. Technology and tracing COVID-19 Machine learning-based technologies are playing a substantial role in the response to the COVID-19 pandemic. Traditionally, the key purpose of surveillance systems has been to detect and deter threats, including the detection of visible and hidden weapons and abnormal behavior. While this, of course, remains a primary focus, today we are seeing how surveillance systems defend against new invisible threats, as well as rapidly automate the process of contact-tracing to capture and contain a virus before it spreads. Again, the ability to track and trace through parsing algorithms that can manage through enormous amounts of data provides a highly scalable and rapid response mechanism to control the spread of threats. AI has demonstrated potential for identifying those displaying symptoms of infectious diseases, without requiring physical human contact Although the threat may not be visible, it is just as destructive. By incorporating AI into existing technologies, government, healthcare and security professionals can monitor public spaces and environments through the combined use of digital and thermal video surveillance cameras and video management systems); just one of the solutions being explored. AI has demonstrated potential for identifying those displaying symptoms of infectious diseases, without requiring physical human contact. By Using AI-powered video analytic software, businesses can monitor face masks, social distancing and large gathering compliance and also detect elevated body temperature. Critically, technology must be capable of both identifying and tracking the virus but also be unobtrusive. An unobtrusive system that is adaptable enough to be deployed across a range of environments where the public gathers in enclosed spaces is necessary to be effective. Security in 2021 Technology has proven itself to be a valuable ally in times of crisis. For smart cities, the use of innovative AI/machine learning technologies will help optimize security solutions in areas that are brimming with potential. As we look ahead to the future of security in a world that is impacted by such a wide range of threats, from physical to chemical to microbiological, it’s clear that new technologies, specifically AI can dramatically improve the effectiveness of security systems and help us to better defend against a wide spectrum of threats. Technology has a huge role to play in making our communities safe in 2021 and beyond, but for security systems to be effective, they must not be oppressive or obstructive. This will ensure they have the full support of the public - the key to success.
Critical infrastructure facilities that must secure large areas with extended outer boundary and numerous entry points, present a particularly difficult challenge when it comes to perimeter protection. As such, true end-to-end perimeter protection calls for the utilization of a sophisticated, multi-layered solution that is capable of defending against anticipated threats. Integrated systems that incorporate thermal imaging, visible cameras, radar and strong command and control software are crucial for covering the various potential areas of attacks. Let’s look at these technologies and the five key functions they enable to achieve an end-to-end solution that provides intrusion detection, assessment and defense for the perimeter. 1. Threat Recognition The first step in effectively defending against a threat is recognizing that it’s there. By combining state-of-the-art intrusion detection technologies, facilities can arm themselves with a head start against possible intruders. An exceptionally important aspect of effective perimeter protection is the ability to conduct 24-hour surveillance, regardless of weather conditions, environmental settings, or time of day. Visible cameras do not perform as well in low light scenarios and inclement weather conditions. However, thermal imaging cameras can provide constant protection against potential intruders, regardless of visual limitations, light source or many environmental factors. In fact, facilities such as power stations located near bodies of water can use thermal cameras to create what is known as a “thermal virtual fence” in areas where they are unable to utilize the protection of a physical fence or wall. Deterring suspicious activity can be achieved through real-time two-way audio, a simple but powerful tool Critical infrastructure applications require not only continuous video surveillance and monitoring, but also a solution that yields highly reliable intrusion detection, with fewer false alarms. This need makes advanced video analytics a must for any adequate surveillance system. Features like dynamic event detection and simplified data presentation are game changing in supporting accurate intrusion analysis and facilitating a proactive response. Advanced analytics will provide multiple automated alarm notification options, including email, edge image storage, digital outputs or video management software (VMS) alarms. Incorporating high quality, unique and adaptive analytics can virtually eliminate false alarms, allowing security personnel to respond more efficiently and effectively, while also lowering overall cost for the end user. While surveillance technologies such as radar, thermal imaging and visible cameras, or video analytics work well on their own, utilizing all of these options together provides an advanced perimeter detection system. For example, ground surveillance radar can detect possible threats beyond the fence line as they approach and send a signal to pan-tilt-zoom (PTZ) cameras, triggering them to slew to a specific location. From there, embedded analytics and visible cameras can further identify objects, notify authorized staff, and collect additional evidence through facial recognition or high-quality photos. 2. Automatic Response Systems Once an intrusion attempt is discovered, it is important to act fast. Organizing a response system that can initiate actions based on GPS location data, such as the slewing of PTZ cameras, automated intruder tracking or activated lighting sensors, greatly increases staff’s situational awareness while easing their workload. For instance, thermal imagers deployed in conjunction with video analytics can be used to generate an initial alarm event, which can then trigger a sequence of other security equipment and notifications for personnel to eventually respond to. Having all of this in place essentially lays the entire situation out in a way that allows responders to accurately understand and evaluate a scene. Power stations located near bodies of water can use thermal cameras to create a “thermal virtual fence” in areas where they are unable to utilize the protection of a physical fence or wall 3. Deterring Suspicious Activity After the designated auto-response mechanisms have activated and done their job, it is time for responders to acknowledge and assess the situation. From here, authorized personnel can take the next appropriate step toward defending against and delaying the threat. Deterring suspicious activity can be achieved through real-time two-way audio, a simple but powerful tool. Often, control room operators can diffuse a situation by speaking over an intercom, telling the trespasser that they are being watched and that the authorities have been notified. This tactic, known as ‘talk down’, also allows officers to view the intruder’s reaction to their commands and evaluate what they feel the best next step is. If individuals do not respond in a desired manner, it may be time to take more serious action and dispatch a patrolman to the area. 4. Delay, Defend, Dispatch And Handle The possible danger has been identified, recognized and evaluated. Now it is time to effectively defend against current attacks and slow down both cyber and physical perpetrators’ prospective efforts. Through the use of a well-designed, open platform VMS, security monitors can manage edge devices and other complementary intrusion detection and response technologies, including acoustic sensors, video analytics, access control and radio dispatch. A robust VMS also enables operators to control functions such as video replay, geographical information systems tracking, email alerts and hand-off to law enforcement. With the right combination of technologies, facilities can take monitoring and evidence collection to the next level The primary purpose of the delay facet of the overall perimeter protection strategy is to stall an attempted intrusion long enough for responders to act. Access control systems play a key role in realizing this objective. When a security officer sees a non-compliant, suspicious individual on the camera feed, the officer can lock all possible exits to trap them in one area all through the VMS. 5. Intelligence: Collect Evidence And Debrief More data and intelligence collected from an event equals more crucial evidence for crime resolution and valuable insight for protecting against future incidents. With the right combination of technologies, facilities can take monitoring and evidence collection to the next level. One innovative resource that has become available is a live streaming application that can be uploaded to smart phones and used for off-site surveillance. This app gives personnel the power to follow intruders with live video anywhere and allows operators to monitor alarm video in real-time. Geographic Information System (GIS) maps are computer systems utilized for capturing, storing, reviewing, and displaying location related data. Capable of displaying various types of data on one map, this system enables users to see, analyze, easily and efficiently. Multi-sensor cameras, possessing both visible and thermal capabilities, provide high-contrast imaging for superb analytic detection (in any light) and High Definition video for evidence such as facial ID or license plate capture. Integrating these two, usually separated, camera types into one helps to fill any gaps that either may normally have. Still, in order to capture and store all of this valuable information and more, a robust, VMS is required. Recorded video, still images and audio clips serve as valuable evidence in the event that a trial must take place to press charges. Control room operators can use data collection tools within their VMS to safely transfer video evidence from the field to the courtroom with just a few clicks of their mouse. More advanced video management systems can go a step further and package this data with other pertinent evidence to create a comprehensive report to help ensure conviction.
The Insights from the Field series features insight from FLIR experts who recommend, deploy, and use thermal imaging technology every day. FLIR discusses the diverse applications of thermal technology in security, safety, and equipment protection for critical infrastructure. Epidemics and pandemics can leave large enterprises that employ and receive thousands of people vulnerable to widespread infection and business interruptions. Without the right entry protocols in place, an employee who has symptoms of an infectious disease, such as a fever, could enter a facility and put the entire workforce at risk of exposure. Skin temperature screening Elevated Skin Temperature Screening Major businesses are ramping up their workforce safety best practices by deploying FLIR thermal cameras for elevated skin temperature measurement. Registered with the U.S. Food and Drug Administration (FDA), these non-contact thermal cameras measure skin surface temperature at the inner canthus (or corner of a person's eye). FLIR thermal cameras that are engineered for elevated skin temperature screening can achieve accuracies of ±0.3°C FLIR thermal cameras that are engineered for elevated skin temperature screening can achieve accuracies of ±0.3°C (0.5°F) over a temperature measurement range of 15°C to 45°C (59°F to 113°F). This aligns with the U.S. FDA Guidance for Industry and Food and Drug Administration Staff as well as with ISO/TR 13154 specification. FLIR provides an array of cameras for elevated skin temperature screening in multiple form factors—including handheld, tripod mounted, or fixed-mounted—optimized for a variety of application needs. Measuring body temperature Infrared thermography can detect elevated skin temperatures, which may indicate the presence of a fever. When followed by a screening with a medical device designed specifically for measuring body temperature, such as a thermometer, the use of an infrared camera as an adjunctive diagnostic tool may help contain or limit the spread of viral diseases such as bird flu, swine flu, or COVID-19. In the wake of COVID-19, businesses across the critical infrastructure market rapidly adopted thermal cameras for elevated skin temperature screening. In the utilities sector, the Office of Cybersecurity, Energy Security and Emergency Response notes how energy utilities are updating their entry protocols in response to COVID-19. Practices now include wellness questionnaires to check for symptoms as well as temperature checks conducted through tools such as thermal cameras. Screening all patients GM deployed 377 FLIR thermal cameras across 72 sites to help limit the spread of COVID-19 General Motors (GM) is one of the manufacturers of motor vehicles, has over 85,000 employees in the United States, and has some plants that employ 1,000 people in a given shift. In May 2020, GM deployed 377 FLIR thermal cameras across 72 sites to help limit the spread of COVID-19. Healthcare facilities are also installing FLIR solutions; for example, the VA Medical Center in Manchester, New Hampshire deployed FLIR thermal cameras to screen all patients and staff for elevated skin temperature prior to them entering the building. In the transportation sector, Emirates airlines deployed FLIR thermal cameras at departure gates for all U.S. gateways beginning in March 2020. Guests traveling on U.S. bound flights out of the Dubai International Airport are screened for elevated skin temperature. Radiometric thermal cameras As more critical infrastructure organizations deploy thermal cameras for elevated skin temperature screening, they will likely prompt greater long-term adoption and integration of radiometric thermal cameras into the overall security and safety solution. Here’s why. While temperature screening of employees and guests often falls under the purview of Environmental Health and Safety or Occupational Health and Safety teams, not every business has a dedicated EHS or OHS staff. As a result, many organizations are tasking their security teams to vet and implement screening solutions. Security officers as well as security equipment, such as surveillance cameras and metal detectors, are already in place at key entry points in a facility. As a result, many security officers must play a dual role as the frontline personnel required to use handheld or tripod mounted thermal cameras to conduct elevated skin temperature screening. Video surveillance solutions It’s important to use a high-resolution thermal camera for elevated skin temperature screening Adding a thermal camera for elevated skin temperature screening is a logical addition to existing video surveillance solutions. As critical infrastructure businesses shift their attention toward the long-term implementation of thermal cameras for elevated skin temperature screening, there are multiple deployment practices to consider. Here are the a few recommendations from FLIR’s team of experts. Choose a Certified Camera – To ensure optimal reliability and deployment success, choose a thermal camera specifically designed for elevated skin temperature screening with a 510(k) filing (K033967) with the U.S. Food and Drug Administration. When looking to integrate this thermal camera into an existing video management system, make sure the camera is ONVIF-compliant. Other screening standards should be considered including ISO/TR 13154:2017 and IEC 80601-2-59:2017. Select a Camera with High Resolution – It’s important to use a high-resolution thermal camera for elevated skin temperature screening so one can capture the right pixels to yield accurate readings. Delivering consistent measurements Ensure Proper Distance for Screening – Distance matters. Make sure the camera is placed at the manufacturer’s recommended distance away from the individual so the camera can focus. Ensure the camera is stabilized so that the camera will deliver consistent measurements. Place a neutral backdrop a few feet behind the location where the person will be screened, and only screen one person at a time to identify temperature anomalies. It is more susceptible to environmental interferences and more likely to generate measurement errors Measure the Right Spot – While the forehead is easier to quickly screen, it is more susceptible to environmental interferences and more likely to generate measurement errors. Research has shown that the corner of the eye—the region medially adjacent to the inner canthus—provides a more accurate estimate of core body temperature than other areas of skin. Specific skin temperature This is because skin at the canthi is thin (decreasing insulating effects), is less exposed to environmental factors, and is directly over major arteries which increase blood flow and heat transfer. Set an Alarm Threshold – For FLIR cameras with a Screen-EST™ mode, set an alarm upon detection of a specific skin temperature compared against a sample average of temperature value. Because skin temperature can vary multiple degrees throughout the day based on the environment and other factors, FLIR Screen-EST mode gathers temperatures from several individuals to determine an average that can be updated throughout the screening operation. This is a defining feature and capability for the FLIR cameras for elevated skin temperature screening.
Teledyne Technologies Incorporated (“Teledyne”) and FLIR Systems, Inc. (“FLIR”) jointly announced that they have entered into a definitive agreement under which Teledyne will acquire FLIR in a cash and stock transaction valued at approximately $8.0 billion. “FLIR’s commitment to innovation spanning multiple sensing technologies has allowed our company to grow into the multi-billion-dollar company it is today”. Permanent financing Under the terms of the agreement, FLIR stockholders will receive $28.00 per share in cash and 0.0718 shares of Teledyne common stock for each FLIR share, which implies a total purchase price of $56.00 per FLIR share based on Teledyne’s 5-day volume weighted average price. The transaction reflects a 40% premium for FLIR stockholders based on FLIR’s 30-day volume weighted average price. Net leverage at closing is expected to be 4.0x adjusted pro forma EBITDA with leverage declining to less than 3.0x As part of the transaction, Teledyne has arranged a $4.5 billion 364-day credit commitment to fund the transaction and refinance certain existing debt. Teledyne expects to fund the transaction with permanent financing prior to closing. Net leverage at closing is expected to be approximately 4.0x adjusted pro forma EBITDA with leverage declining to less than 3.0x. Different semiconductor technologies Teledyne expects the acquisition to be immediately accretive to earnings, excluding transaction costs and intangible asset amortisation, and accretive to GAAP earnings in the first full calendar year following the acquisition. “At the core of both our companies is proprietary sensor technologies. Our business models are also similar: we each provide sensors, cameras and sensor systems to our customers. However, our technologies and products are uniquely complementary with minimal overlap, having imaging sensors based on different semiconductor technologies for different wavelengths,” said Robert Mehrabian, Executive Chairman of Teledyne. Multiple sensing technologies “For two decades, Teledyne has demonstrated its ability to compound earnings and cash flow consistently and predictably. Together with FLIR and an optimized capital structure, I am confident we shall continue delivering superior returns to our stockholders.” We could not be more excited to join forces with Teledyne through this value-creating transaction" “FLIR’s commitment to innovation spanning multiple sensing technologies has allowed our company to grow into the multi-billion-dollar company it is today,” said Earl Lewis, Chairman of FLIR. “With our new partner’s platform of complementary technologies, we will be able to continue this trajectory, providing our employees, customers and stockholders even more exciting momentum for growth. Our Board fully supports this transaction, which delivers immediate value and the opportunity to participate in the upside potential of the combined company.” Global customer base Jim Cannon, President and Chief Executive Officer of FLIR, said, “We could not be more excited to join forces with Teledyne through this value-creating transaction. Together, we will offer a uniquely complementary end-to-end portfolio of sensory technologies for all key domains and applications across a well-balanced, global customer base." "We are pleased to be partnering with an organization that shares our focus on continuous innovation and operational excellence, and we look forward to working closely with the Teledyne team as we bring our two companies together to capitalize on the important opportunities ahead.” Approvals and timing Teledyne announced improved preliminary financial results for the fourth quarter and full year 2020 In a separate press release issued, Teledyne announced improved preliminary financial results for the fourth quarter and full year 2020. The Teledyne press release is available on the company’s official website. FLIR noted that it expects to meet or exceed the full year fiscal 2020 guidance it provided on October 30, 2020. The transaction, which has been approved by the boards of directors of both companies, is expected to close in the middle of 2021 subject to the receipt of required regulatory approvals, including expiration or termination of the applicable waiting period under the Hart-Scott-Rodino Antitrust Improvements Act, approvals of Teledyne and FLIR stockholders and other customary closing conditions. Conference call and webcast Evercore is acting as exclusive financial advisor and McGuireWoods LLP is acting as legal advisor to Teledyne in connection with the transaction. Goldman Sachs & Co. LLC is acting as exclusive financial advisor and Hogan Lovells US LLP is acting as legal advisor to FLIR in connection with the transaction. Teledyne has entered into a 364-day senior unsecured bridge facility credit agreement with Bank of America as sole lead arranger and administrative agent. Teledyne and FLIR will host a conference call to discuss the acquisition. A live webcast of the call can be accessed at Teledyne’s website. One can connect to the website at least 15 minutes prior to the start of the call to allow adequate time for any software download that may be required. A replay will be available on the company’s website approximately three hours after the call and will be available for approximately one month.
Facemasks are a critical tool for fighting the spread of COVID-19 virus and are proven to be most effective when face coverings are worn universally. As stores and businesses reopen, ensuring all occupants wear a facemask is essential. However, the additional resources required to monitor patrons can further strain businesses already struggling to meet other sanitation and social distancing guidelines. Deep Learning solutions are capable of automatically detecting anyone in violation of facemask guidelines, saving employee time and ensuring safer environments. Deploying Deep Learning solutions Deep learning is a form of machine learning that uses neural networks with many ‘deep’ layers between the input and output nodes. By training a network on a large data set, a model is created that can be used to make accurate predictions based on unseen data. In this case, the network can be trained to detect not only facemasks, but if a facemask is worn correctly on a person’s face. A fully functioning deep learning system can be developed and deployed in a matter of days A fully functioning deep learning system can be developed and deployed in a matter of days. Using a FLIR Firefly DL camera, FLIR Systems’ engineers developed a system for detecting compliance and flagging users who may be in violation of PPE (Personal Protection Equipment) guidelines. Facemask detection dataset The facemask detection dataset used 2 publicly available libraries with over 1000 images to provide examples of people with, without, and incorrectly wearing facemasks in different environments. Other cameras suited for this purpose include the Blackfly S GigE. Each image in the facemask dataset was annotated with bounding boxes showing object locations and class labels indicating which faces had the mask on, which did not, and if they were worn appropriately. Deep learning developers and solution integrators can easily expand this solution to cover more complex and robust use cases for deployment in the real world. For example, the neural network can be trained to detect face shields, gowns, gloves, and other PPE within high risk/high traffic environments like hospitals and airports.
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