FLIR Systems Network / IP Cameras(222)
Monochrome, 320 × 240 pixels resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 12/24 V DC, PAL, NTSC, Composite video output, PAL and NTSC compatible, Ethernet/IP, Modbus TCP, TCP, UDP, SNTP, RTSP, RTP, HTTP, ICMP, IGMP, ftp, SMTP, SMB (CIFS), DHCP, MDNS (Bonjour), uPnP, -40 ~ +70 C (-40 ~ +158 F), 95Add to Compare
1/3 inch, Colour / Monochrome, 1920 x 1080 resolution, Digital (DSP), Colour: 0.2 firstname.lastname@example.org, B/W: 0.1 email@example.com lux, Auto Iris, Direct Drive, 12 V DC / 24 V AC / PoE, 3 ~ 10.5, Wide Dynamic Range, 1920 x 1080, 25/30 fps, Back Light Compensation, Auto Gain Control, White Balance, 1/15 ~ 1/10,000s, PAL, NTSC, Zoom, 1vpp, 1 x BNC, 75Ohms, H.264, MJPEG, 1x RJ45 10/100/1000 Mbps, IPv4, TCP, UDP, RTP, RTSP, HTTP, ICMP, FTP, SMTP, DHCP, UPnP, IGMP, SNMP, ONVIF Profile S, NTP, 25 W, 940 , 285 x 96 x 94, IP66, IK10, -40 ~ +50 C (-40 ~ +122 F) w/ 12VDC/24VAC/PoE+, -10 ~ +50 C (14 ~ 122 F) w/ PoE, Internet Explorer 8, 9, 10, and 11, 10 ~ 90, HDAdd to Compare
1/3 inch, Colour / Monochrome, 2688 x 1520 resolution, Digital (DSP), Network, 0.3 (colour) / 0.04 (BW), 0 with IR illuminator ON lux, Auto Iris, Direct Drive, PoE, Motion Activated, Wide Dynamic Range, Inclusion DVR/ Web Server, Back Light Compensation, Auto Gain Control, White Balance, 1.0 ~ 1/10,000s, ±50, PAL, NTSC, Fully compliant multi-stream H.264 main/high/SVC/baseline profile, MJPEG (FHD) , 10/100/1000 Ethernet, auto sensing, half/full duplex (RJ45), , IPv4/v6, TCP/IP, UDP Unicast / Multicast, RTP, RTSP, HTTP, HTTPS, ICMP, FTP, SMTP, DHCP, PPPoE, UPnP, IGMP, SNMP, SNTP, QoS, ONVIF Profile S, IEEE 802.1X, 6 W indoor, 13 W outdoors with heater / IR, 980, 218 x 99, IP66, IK10, -40 ~ +50 C (-40 ~ +122 F), Internet Explorer 9+, 95, HDAdd to Compare
1/3 inch, Colour / Monochrome, 2.1 MP resolution, Digital (DSP), Megapixel, Colour: 0.2 firstname.lastname@example.org, B/W: 0.1 email@example.com lux, Auto Iris, Direct Drive, 12 V DC / 24 V AC / POE , Wide Dynamic Range, 1920 x 1080, Back Light Compensation, Auto Gain Control, White Balance, H.264, M-JPEG, 1x RJ45 10/100/1000Mbps (IEEE 802.3/802.3u/802.3ab) , IPv4, TCP, UDP, RTP, RTSP, HTTP, HTTPS, ICMP, FTP, SMTP, DHCP, UPnP, IGMP, SNMP, ONVIF Profile S, NTP , 8 W, 330, 125 x 82 x 52, -10 ~ +50 C (14 ~ 122 F), Internet Explorer 8, 9, 10, and 11, 10 ~ 90, HDAdd to Compare
Monochrome, 320 x 240 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 16 ~ 44 V DC (w/lens heaters), PoE, 19, Auto Gain Control, NTSC, Zoom, H.264, MPEG-4 & M-JPEG, 21 W (w/heaters), 234 x 117 x 104, 1,800 w/o sun shield, IP66, IP67, -50 ~ +70 C (-58 ~ +158 F), 0 ~ 95Add to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 13, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 13, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, PAL, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
1/3 inch, Colour / Monochrome, 2048 x 1536 resolution, Digital (DSP), Network, 0.03 (colour)/0.01 (BW), 0 Lux with IR illuminator ON lux, Auto Iris, Direct Drive, PoE , Motion Activated, Wide Dynamic Range, Inclusion DVR/ Web Server, Back Light Compensation, Auto Gain Control, White Balance, 1/7.5 ~ 1/10,000s, ±50, PAL, NTSC, H.264, MJPEG, 10/100, auto sensing, half / full duplex (RJ45), TCP, UDP, ICMP, HTTP, HTTPS, FTP, DHCP, DNS, DDNS, RTP, RTSP, RTCP, PPPoE, NTP, UPnP, SMTP, SNMP, IGMP, 802.1X, QoS, IPv4, IPv6, SSL, LDAP, 5 ~ 12 W, 180 x 86 x 80 , -40 ~ +50 C (-40 ~ +122 F), Internet Explorer 10+, 90, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 25, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 25, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, PAL, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 35, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 35, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, PAL, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 50, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 50, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, PAL, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 75, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 75, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, PAL, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 26 ~ 106, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 480 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 26 ~ 106, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, PAL, 348 x 467 x 326, 16,400, IP66, -40 ~ +70 C (-40 ~ +158 F), 0 ~ 95, HDAdd to Compare
640 x 512 resolution, Digital (DSP), Thermal, Auto Iris, Direct Drive, 24 V AC, 24 V DC, 75, Wide Dynamic Range, Back Light Compensation, Auto Gain Control, NTSC, IPV4, HTTP, UPnP, DNS, NTP, RTSP, RTCP, RTP, TCP, UDP, ICMP, IGMP, DHCP, ARP, 348 x 467 x 326, 18,500, IP66, -32 ~ +55 C (-26 ~ +131 F), 0 ~ 95, HDAdd to Compare
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IP camera products updated recently
Urban populations are expanding rapidly around the globe, with an expected growth of 1.56 billion by 2040. As the number of people living and working in cities continues to grow, the ability to keep everyone safe is an increasing challenge. However, technology companies are developing products and solutions with these futuristic cities in mind, as the reality is closer than you may think. Solutions that can help to watch over public places and share data insights with city workers and officials are increasingly enabling smart cities to improve the experience and safety of the people who reside there. Rising scope of 5G, AI, IoT and the Cloud The main foundations that underpin smart cities are 5G, Artificial Intelligence (AI), and the Internet of Things (IoT) and the Cloud. Each is equally important, and together, these technologies enable city officials to gather and analyze more detailed insights than ever before. For public safety in particular, having IoT and cloud systems in place will be one of the biggest factors to improving the quality of life for citizens. Smart cities have come a long way in the last few decades, but to truly make a smart city safe, real-time situational awareness and cross-agency collaboration are key areas which must be developed as a priority. Innovative surveillance cameras with integrated IoT Public places need to be safe, whether that is an open park, shopping center, or the main roads through towns Public places need to be safe, whether that is an open park, shopping center, or the main roads through towns. From dangerous drivers to terrorist attacks, petty crime on the streets to high profile bank robberies, innovative surveillance cameras with integrated IoT and cloud technologies can go some way to helping respond quickly to, and in some cases even prevent, the most serious incidents. Many existing safety systems in cities rely on aging and in some places legacy technology, such as video surveillance cameras. Many of these also use on-premises systems rather than utilising the benefits of the cloud. Smart programming to deliver greater insights These issues, though not creating a major problem today, do make it more challenging for governments and councils to update their security. Changing every camera in a city is a huge undertaking, but in turn, doing so would enable all cameras to be connected to the cloud, and provide more detailed information which can be analyzed by smart programming to deliver greater insights. The physical technologies that are currently present in most urban areas lack the intelligent connectivity, interoperability and integration interfaces that smart cities need. Adopting digital technologies isn’t a luxury, but a necessity. Smart surveillance systems It enables teams to gather data from multiple sources throughout the city in real-time, and be alerted to incidents as soon as they occur. Increased connectivity and collaboration ensures that all teams that need to be aware of a situation are informed instantly. For example, a smart surveillance system can identify when a road accident has occurred. It can not only alert the nearest ambulance to attend the scene, but also the local police force to dispatch officers. An advanced system that can implement road diversions could also close roads around the incident immediately and divert traffic to other routes, keeping everyone moving and avoiding a build-up of vehicles. This is just one example: without digital systems, analyzing patterns of vehicle movements to address congestion issues could be compromised, as would the ability to build real-time crime maps and deploy data analytics which make predictive policing and more effective crowd management possible. Cloud-based technologies Cloud-based technologies provide the interoperability, scalability and automation Cloud-based technologies provide the interoperability, scalability and automation that is needed to overcome the limitations of traditional security systems. Using these, smart cities can develop a fully open systems architecture that delivers interoperation with both local and other remote open systems. The intelligence of cloud systems can not only continue to allow for greater insights as technology develops over time, but it can do so with minimal additional infrastructure investment. Smart surveillance in the real world Mexico City has a population of almost 9 million people, but if you include the whole metropolitan area, this number rises sharply to over 21 million in total, making it one of the largest cities on the planet. Seven years ago, the city first introduced its Safe City initiative, and ever since has been developing newer and smarter ways to keep its citizens safe. In particular, its cloud-based security initiative is making a huge impact. Over the past three years, Mexico City has installed 58,000 new video surveillance cameras throughout the city, in public spaces and on transport, all of which are connected to the City’s C5 (Command, Control, Computers, Communications and Citizen Contact) facility. Smart Cities operations The solution enables officers as well as the general public to upload videos via a mobile app to share information quickly, fixed, body-worn and vehicle cameras can also be integrated to provide exceptional insight into the city’s operations. The cloud-based platform can easily be upgraded to include the latest technology innovations such as license plate reading, behavioral analysis software, video analytics and facial recognition software, which will all continue to bring down crime rates and boost response times to incidents. The right cloud approach Making the shift to cloud-based systems enables smart cities to eliminate dependence on fiber-optic connectivity and take advantage of a variety of Internet and wireless connectivity options that can significantly reduce application and communication infrastructure costs. Smart cities need to be effective in years to come, not just in the present day, or else officials have missed one of the key aspects of a truly smart city. System designers must build technology foundations now that can be easily adapted in the future to support new infrastructure as it becomes available. Open system architecture An open system architecture will also be vital for smart cities to enhance their operations For example, this could include opting for a true cloud application that can support cloud-managed local devices and automate their management. An open system architecture will also be vital for smart cities to enhance their operations and deliver additional value-add services to citizens as greater capabilities become possible in the years to come. The advances today in cloud and IoT technologies are rapid, and city officials and authorities have more options now to develop their smart cities than ever before and crucially, to use these innovations to improve public safety. New safety features Though implementing these cloud-based systems now requires investment, as new safety features are designed, there will be lower costs and challenges associated with introducing these because the basic infrastructure will already exist. Whether that’s gunshot detection or enabling the sharing of video infrastructure and data across multiple agencies in real time, smart video surveillance on cloud-based systems can bring a wealth of the new opportunities.
Several major players vigorously employ biometric recognition technologies around the globe. Governments use biometrics to control immigration, security, and create national databases of biometric profiles. Being one of the most striking examples, the Indian Aadhaar includes face photos, iris, and fingerprints of about 1.2 billion people. Financial institutions, on their part, make use of biometrics to protect transactions by confirming a client's identity, as well as develop and provide services without clients visiting the office. Besides, biometric technology ensures security and optimizes passenger traffic at transport facilities and collects data about customers, and investigates theft and other incidents in retail stores. Widespread use of biometrics Business, which suddenly boosted the development of biometrics, is an active user of biometric technology Business, which suddenly boosted the development of biometrics, is another active user of biometric technology. Industries choose biometric systems, as these systems are impossible to trick in terms of security, access control, and data protection. Being in demand in business, these three tasks are also relevant for the industry. However, the use of biometrics at industrial sites is discussed unfairly seldom. Therefore, it is the face identification that is the most convenient there, as workers often use gloves, or their hands may be contaminated, and the palm pattern is distorted by heavy labor. All these features make it difficult to recognize people by fingerprints or veins and significantly reduce identification reliability. Therefore, industries seek facial recognition solutions. Thus, let us demonstrate the application of face recognition technology at different enterprises, regardless of the area. Facial recognition use in incident management Facial biometric products are known to automate and improve the efficiency of security services by enriching any VMS system. These systems provide an opportunity of instantly informing the operator about recognized or unrecognized people, and their list membership, as well as save all the detected images for further security incident investigation. Furthermore, some sophisticated facial biometric systems even provide an opportunity to build a map of the movements of specific people around a site. Besides, it is relevant not only for conducting investigations but also in countering the spread of the COVID-19 virus. Identifying and tracking COVID-19 positive cases Therefore, if an employee or visitor with a positive COVID-19 test enters a facility, the system will help to track his/her movement and identify his/her specific location. It will also help to take the necessary measures for spot sanitary processing. Thus, the introduction of biometric facial recognition at the industrial enterprise can improve and speed up the incidents’ response and investigations without spending hours watching the video archive. Access control system to secure physical assets The right access control system can help industries secure physical and informational assets The right access control system can help industries secure physical and informational assets, cut personnel costs, and keep employees safe. Facial recognition systems may enrich access control systems of any company by providing more security. As biometric characteristics, by which the system assesses the compliance of a person with the available profiles in the database, cannot be faked or passed. The human factor is also reduced to zero, due to the fact that while identity documents can be changed, the inspector can make a mistake or treat his/her task carelessly, be in collusion with an intruder, the biometric system simply compares a person in front of the camera with the biometric profiles database. Biometric facial identification software For example, RecFaces product Id-Gate, a specialized software product for reliable access control to the site, checks the access rights by using biometric facial identification alone or in conjunction with traditional IDs (electronic passes, access keys, etc.), which means that there is almost a zero probability of passing to the site by someone else's ID. The access control system’s functionality allows one to strictly account the number and time of all the facility’s visitors and also track their movement. When unauthorized access is attempted or a person from the stop list is detected, Id-Gate sends an automatic notification to the access control system and operator. Enhanced data and information security Even despite the division of access to different industrial enterprise areas, the security service needs to provide independent information system security. Employees with the same facility access rights may have different access rights to data. However, in that case, a personal password is not enough, as an employee may forget it, write it down and leave it as a reminder, tell a colleague to do something for him/her during the vacation, or just enter it at another person’s presence. Password-free biometric authentication systems make the procedure user-friendly and secure Password-free biometric authentication Password-free biometric authentication systems make the procedure user-friendly and secure. Such systems usually provide an option of two-step verification when successful password entry is additionally confirmed by biometric recognition. Hence, it is particularly relevant due to the current lockdown in many countries. To sum up, the application of biometric technologies solves several issues of the industry, such as: Optimizes and partially automates the work of the security service, as it provides reliable identification and verification of visitors/employees, reduces the amount of time spent on finding a person on video and making a map of his/her movements, without spending hours on watching video archive in case of investigation. Provides a high level of reliability and protection from unauthorized access to the enterprise and the information system. Provides a two-step verification of the user/visitor (including password and biometric data) and almost eliminates the risk of substitution of user data/ID.
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.
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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