Day: June 3, 2020

With the increased prevalence of  IP-based video surveillance systems on the market, and the growing adoption of higher resolution HD and megapixel cameras, organizations and system integrators must take into account how implementing these systems can impact their network resources. Without realistic system design considerations, organizations can risk significant network and storage cost overruns while also compromising the reliability of their network to support applications that are critical to their business operations. By implementing an advanced video management system (VMS), an organization can effectively manage video streams on their network using built-in camera and software functionalities to optimize network resources and bandwidth consumption. With such optimizations, a VMS will also help to decrease networking and storage costs over the lifetime of a video surveillance system. Challenges For organizations choosing to implement or expand an IP video surveillance system, the ability to efficiently manage video streams and storage is crucial to ensure the best use of the network and reduce costs associated with deploying and operating the system. While organizations continue to benefit from greater network speeds and capacity, the use of IP-based video systems can generate a significant increase in the amount of data traveling on their network as a result of: Deploying high-definition and megapixel cameras, Additional cameras to address a need for coverage across Larger areas, Increases to the number of users accessing video, Recording and maintaining redundant video recordings, Transferring video from one site to another to maintain long-term orcentralized recordings. When planning and designing an IP video surveillance system, an organization must take into account the unique aspects of its security environment and its business operations in order to ensure the reliable transmission of video and avoid overloading available network resources. For example, certain deployments will require greater flexibility to manage video streams and bandwidth due to their complex nature,further driving the need for advanced video management capabilities. These scenarios can include: Distributed sites requiring operators to connect to remote cameras, Cameras connected to networks with limited bandwidth such as DSL, wireless, or cellular, Sharing bandwidth with other operation-critical applications because video is not the top priority for the business. It is equally important for organizations to realize that optimizing the use of network resources does not necessarily require large capital investments but is more a matter of putting the right solutions in place. With bandwidth and storage representing important ongoing costs of operating an IP system, organization scan significantly reduce the Total Cost of Ownership (TCO) of their video surveillance system by investing in solutions that allow them to optimize their use of bandwidth and storage based on the requirements of their application. This white paper will focus on those unique and powerful capabilities that one should look for in a VMS in order to optimize the use of network resources and reduce the costs associated with operating an IP-based surveillance system. Optimizing network resource utilization VMS applications allow an organization to manage its security infrastructure including video cameras, encoders, and recording servers, within the unique context of the organization’s deployment. The effectiveness of the VMS will depend on its ability to handle the demands of the operating environment, whether those demands include deploying a system in sites with limited bandwidth, monitoring cameras across distributed locations, or ensuring that multiple operators can access necessary video streams in the case of an incident, regardless of the number of concurrent requests. Although system administrators will intuitively manage video quality settings and define recording settings and schedules, addressing the needs of a specific security department can require manual intervention and adjustment. While most VMS applications support these features, some VMS applications also support powerful functionalities and technologies that serve to further reduce the total cost of operating an IP video system. In fact, organizations can deploy a surveillance system that operates with greater efficiency on their network by choosing a VMS application that supports the following capabilities: End-to-end multicast transmission, Stream redirection and multicast-to-unicast conversion, Multi-streaming, Video caching, Archive transfer. By leveraging some or all of these capabilities, organizations can significantly reduce the number of servers required to manage and store video, reduce their network bandwidth requirements, and reliably scale their system while minimizing their investment in new infrastructure. A. Video stream transmission: unicast and multicast I n IP video surveillance, unicast and multicast are the two most commonly used methods to transmit video from cameras to client workstations. While all VMS platforms can configure unicast, only a few also offer multicast transmission, and, among these, even fewer support end-to-end multicast that provides communication from the edge device (IP cameras and encoders) to the workstation. Though many VMS platforms may claim multicast support, the majority will only provide limited support for multicast transmission between the recording server and the client station, and require multicast to be set for all cameras on the server, or even implemented system wide. It is important for organizations to consider that certain VMS provide far greater flexibility with regards to transmission, in order to implement the best design for their application. This includes the ability to set up cameras per select network branch or per viewer and the ability to automatically detect the ideal transmission method for different segments of the network, thereby allowing organizations to optimize the performance of their video surveillance system and minimize the network resources that are required. i. Unicast overview Unicast is usually done in TCP or UDP and requires a direct connection between the source and the destination. Unicast only works if the source has the capability to accept concurrent connections when multiple destinations want to view or record the same video at the same time. In IP video surveillance, unicast involves a camera streaming as many copies of the video feed as are requested by the destinations, so a 6 Mbps video stream that is requested by three operators will produce a transmission of 18 Mbps of data across multiple network segments (6 Mbps per stream x 3 requests = a total of 18 Mbps). This…

Around the world, governments are responding to the unprecedented circumstances related to the coronavirus (COVID-19) epidemic. In many countries and regions, authorities have placed restrictions on their citizens movements and have increased guidance on the basic hygiene required to reduce the spread of the virus. The primary aim of this activity is to reduce the reproduction number (Ro ) of COVID-19 by limiting contact between groups of people as much as possible. Similarly, many government and healthcare authorities have provided guidance on the key symptoms associated with the disease. One of the key symptoms is an increased body temperature or fever. How can thermal cameras help? There are several activities and approaches being applied to help reduce the reproduction rate of COVID-19. These include self-isolation methods such as working from home, improved basic hygiene such as increased hand washing and the deployment of personal protective equipment (PPE) to reduce the prospect of infection. Similarly, when symptoms appear there is clear guidance on what to do next. Primarily this involves limiting social contact through self-isolation for up to 14 days. Medical professionals should be contacted digitally if symptoms persist or deteriorate. Ultimately, prior to any vaccine being available, the fight against COVID-19 is being led by the ability to detect symptoms and isolate people suspected of an infection. This is a combined effort between different key workers and technology applications. Thermal cameras can play a part in this coordinated approach. These cameras provide thermal imaging for body temperature solutions which can quickly and accurately identify people with elevated body temperatures, one of the key symptoms of COVID-19. These solutions can provide organizations with an additional layer of protection to their facility from increased exposure to the coronavirus. Organizations can then decide how best to deploy this information based on region, culture and the critical nature of the facility. In some circumstances a security officer may ask the person to scan their temperature using a medically approved sensor. In others, the person may be denied access to the facility. Ultimately, it is a decision for each organization on how best to deploy the solution. Thermal body temperature solutions An important distinction to make in the overall societal response to COVID-19 is that body temperature solutions are not a medical solution. They cannot identify the virus and they do not protect organizations or individuals from catching the virus. Thermal body temperature solutions are a tool that can support the identification of a key symptom of the disease. They can help organizations identify people showing these symptoms, but they do not diagnose or treat COVID-19. However, this does not mean that thermal body temperature solutions do not add value in the overall response. In fact, they provide a non-invasive method to check body temperature, can do this at faster rates than hand-held scanners and at a greater (potentially safer) distance. The deployment of these solutions in a facility may even encourage positive behaviour with staff more likely to stay at home when they are unwell with a fever. Thermal body temperature solutions require, at a minimum, a radiometric thermal camera to measure temperature differences in people entering the field of view. More advanced solutions will use blackbody devices to help calibrate the temperature measurement, especially in less controlled environments where the elements can influence the reading. AI (artificial intelligence) algorithms can also be integrated to help target the temperature reading on the most accurate part of the body, typically the forehead or near the eyes. The blackbody calibration tool consists of a target object whose temperature is precisely known and controlled. Specifically, this is important in human temperature measurement where accuracy to +/- 0.3 degrees Celsius is advised by many international standards organizations. By deploying the blackbody calibration tool, it is easier to establish an accurate relationship between gray level and temperature. Essentially there is known, fixed temperature object in the field of view which can be used to calibrate and measure all other objects’ temperatures. Using this method, false temperature alarms caused by environmental influence can be effectively reduced, and the accuracy of the thermal body temperature solution can be controlled to more precise parameters. However, monitoring accuracy does depend on the stability of the body temperature and it is recommended to install the system in a stable environmental condition to ensure that the skin temperature is stable. The emergence of AI technology, and specifically face detection algorithms, will play an important role in the evolution of these solutions too. Algorithms can help complete more accurate temperature tests. Cameras can do this by locating specific areas of the face such as the forehead or eyes, more accurately. This could be critical in the case of people wearing masks. Combining thermal cameras and facial detection can enable thermal body temperature solutions to combine accurate temperature scanning with the best face location to take the measurement from, improving the overall measurement accuracy. It should also be noted that the facial detection, as opposed to recognition, is used to improve the accuracy of the solution with better positioning of the measuring point on the face. It is not used to detect specific individuals and does not break privacy compliances (such as GDPR). While there remain challenges to the effectiveness of thermal imaging cameras for measuring human body temperature in public areas, especially when face masks are commonplace, the introduction of facial detection and AI can improve the accuracy of temperature scanning. Managing expectations for use Comparisons can be made between the current stage of the market for thermal body temperature solutions and another physical security technology – video analytics. Here, the expectation level for object detection or activity tracking algorithms was extremely high. The expectation was that video analytics would be near 100 percent accurate in spotting, identifying and tracking objects through the field of vision. However, analytics would sometimes misunderstand a scene, potentially alerting to the same object multiple times or mis-allocating an object – essentially false alerts. The reality was that these solutions…