CQR Intruder Warning Devices

As anyone who has ever flown on a commercial airline since 2001 knows, security measures at airports are well enforced and the emphasis on traveller safety is all around the airport and its grounds. Mass transportation, meanwhile, presents a special but not any less significant challenge when it comes to determining security issues. These facilities need to develop the means to protect a constantly changing and large population of passengers. And unlike airports these facilities often have hundreds of points of entry and exit on multiple modes—buses, subways, light rail, commuter trains, even ferries. About 2 million Americans will use the nation’s airways on a given work day, while 35 million people will board some form of public transportation. In fact, statistics have shown that nearly 11 billion trips are taken on public transportation every year. In some large metropolitan areas in North America where mass transit is well established, more than 20 percent of the area’s inhabitants get around via public transportation.About 2 million Americans will use the nation’s airways on a given work day, while 35 million people will board some form of public transportation Solving mass transit security For transportation officials and their security providers, solving the mass transit security issue begins with determining the key concerns and then creating the proper responses via security systems, policies and procedures to mitigate the risks. Although vandalism and graffiti are very visible signs of criminal behaviour in mass transit settings such as bus stops and subway stations, this is not where transportation officials typically focus their energy. Fences and gates can secure out-of-service buses and train cars, as can remote surveillance methods to keep such vandalism at a minimum. Instead, it is the day-to-day safety and security of transit riders and employees that should become the highest priority. This begins with creating the safest environment possible that is highlighted with appropriate signage and, when necessary, audible warnings, and supporting that with technology, such as surveillance cameras, that will document what has happened if an incident occurs.Analytics can also be useful in alerting security about other suspicious behaviours at a transit stop, such as an untended bag or package Crime prevention in transportation Analytics can also be useful in alerting security about other suspicious behaviours at a transit stop, such as an untended bag or package Incidents of concern within a transit setting can take several forms, ranging from legitimate accidents or crimes to false claims such as faked fall down the stairs to potential and actual suicides. Bus and subway stations also have become magnets for homeless people who may put themselves and others in harm’s way by trying to access less secure public areas within a station as temporary shelters. If someone is injured on a subway platform and the transit provider is held liable, it could be on the hook for hundreds of thousands, if not millions of dollars. Suicides are a major concern for operators, with personnel now being trained to look for individuals who seem distressed, are loitering in the area or are intentionally putting themselves in a dangerous situation, such as standing too close to the edge of a platform. The deployment of video analytics, which can be programmed to send alerts when certain pre-set actions occur, can help determine when such dangerous behaviours come into play. Analytics can also be useful in alerting security about other suspicious behaviours at a transit stop, such as an untended bag or package or a person going into a restricted area. Whether it is on the bus, train or ferry or at the stops themselves, cameras and intuitive video management systems are the key to both active and forensic transit security. Some cities use buses that are up to 60 feet long and those can be equipped with up to a dozen cameras Train security and safety By using the proper cameras and recording systems in a transit environment, quick-acting personnel can locate a person of interest who boarded a train at one station, follow him during his trip and produce a crisp, clear identifiable image at the end. Those setting up the system thus should keep in mind proper camera positioning, resolution and motion-based changes to framerates or other compression settings. A typical 30-foot bus often has six cameras—one each at the front and middle doors, two more within the bus and then one looking forward and another looking behind the bus. The latter two are important in the event of accidents to verify liability. Some cities use buses that are up to 60 feet long and those can be equipped with up to a dozen cameras.Train stations often deploy high-definition cameras to better support facial recognition software to get that actionable image Train cars are similarly equipped with two to four cameras to view activity down the centre aisle. Within the stations themselves, there can be from 15 to 30 or more cameras capturing wide-angle shots. Train stations, which have a restricted point of egress, often deploy high-definition cameras to better support facial recognition software to get that actionable image. Installing the right technology for the solution Although bandwidth and storage can be a concern, with motion-based recording, the resolution can be bumped up during event, resulting in a 1-megapixel stream jumping to 4 or even 8mbps when needed. By changing the resolution on demand, end users can cut their storage needs significantly. Transportation settings often rely on the same technology used in other security installations, primarily mini dome cameras, although there are some mini transit domes built specifically for the environment with the proper aesthetics. Because of vandalism threats, transit typically avoids pendant mounts, which can be more easily grabbed and damaged. Temperature ratings for cameras also come into play in cold climates with cameras often getting outdoor exposure.Today’s new buses and trains are constructed with the cameras onboard and newer stations also take security into consideration at the earliest design stage As trains and buses move along their routes, especially those that service outlying areas, Internet connectivity becomes an issue as well. Because it may be difficult for video to be sent in transit, security bus barns are equipped with Wi-Fi so video from onboard cameras can be downloaded at the end of the day. And the use of hardened recorders at the stations allows security personnel to retrieve recorded video. Transit security with modern technology Today’s new buses and trains are constructed with the cameras onboard and newer stations also take security into consideration at the earliest design stage. Older infrastructure from long-standing subway and bus terminals can prove to be a challenge when adding security, but these issues aren’t insurmountable. Often the solution is to add more cameras to cover the same square footage because of less-than-ideal sight lines and to place conduit wherever it works best, which may mean positioning it under platforms or in other out-of-the-way places within older stations. Looking ahead, transit security will continue to evolve, not only as new stations and modes of transportation are added to the system, but in terms of communicating with commuters. People can expect to get mass notification alerts on their mobile devices, and those same devices can provide vital data to transportation entities to better develop their overall systems.

In the state of the residential security market today, we see many who are offering home security packages that rely on numerous sensors and multiple devices to provide a comprehensive coverage of the home and provide peace of mind. Each individual sensor or device within the package provides a specific functionality, and the user finds himself burdened by an overwhelming amount of sensors and devices. This overload is intensified by the penetration of additional IoT and smart devices into the home, such as pet-cams or smart speakers that add to the burden of installation and maintenance. In addition, we are witnessing the rise in popularity of DIY security devices, indicating that users are looking for models and technologies that provide both contract flexibility and simplicity of use. The past years have seen major advancements in radar technology, which have brought the formerly military technology into the consumer space. Radars provide interesting prospects for home security and smart homes due to several inherent characteristics which give it an advantage over existing technologies. The resolution of an advanced radar sensor enables not only presence detection, but also provides advanced features for security, automation and well-being Advanced security and automation features Of primary importance, a consumer designed radar sensor provides the user with full privacy, but the use of radar is also beneficial because it is indifferent to environmental, temperature and lighting conditions. In addition, radar signals (at certain frequencies) are capable of penetrating through almost any type of material, enabling concealed installation, robust monitoring in cluttered spaces and even the coverage of several separate rooms with only one device. In terms of capabilities, simple time of flight 2-antenna radar sensors, which have been around for a while, do not provide much additional value in comparison to existing solutions and are not necessarily competitive in terms of pricing. However, the new generation of radar sensors are also opening up new capabilities previously achieved with optics only. Today, the resolution of an advanced radar sensor is high enough to enable not only presence detection, but also to provide advanced features for security, automation and well-being, all in one. Imagine for example, that the security sensor installed in your elderly parent’s home could also detect a fall having occurred, monitor the breathing of a baby or even leaks in your wall. Due to the unique field of view that radar provides as well as the multi-functional potential, this technology will be the key to the awaited convergence of smart home functionalities and minimisation of home devices. The security sensor installed in your elderly parent’s home could also detect a fall having occurred Secret of the consumer radar A radar sensor’s accuracy and its ability to support wide functionality and applications is determined initially by its resolution, which is based on two key factors: bandwidth and number of channels. The wider the bandwidth and the more channels the radar supports, the more accurate the data received. Imagine the difference between a 1990s television model and a 4K 2018 television model - As the resolution is ever improving, the sharper and more detailed is the image. When looking at the short-range radar sensor market, prominent companies such as Texas Instruments and NXP are offering radar-on-chip solutions supporting 2\3 transmitters (Tx) and 3\4 receivers (Rx), mainly utilising frequency bands of 77-81GHz, as they target mostly automotive and autonomous driving applications. Another company that develops such radar-on-chip solution is Vayyar Imaging, an Israeli start-up, founded in 2011, that developed a radar sensor for 3D imaging. Vayyar Imaging directly targets the smart home and security markets with its radar-on-chip, developing modules and products for intruder detection, automation and elderly care (fall detection). Providing not only chips, but complete systems, the new model makes radar technology highly available and accessible. The radar-on-chip technology opens the door to installation of security and well-being devices in locations where privacy or environmental conditions pose an issue Radar-on-chip solution The radar-on-chip solution supports 72 full transceivers, an integrated DSP and radar bands between 3-81GHz. The resolution provided by this type of specification is high enough to provide subtle information about people’s real time location posture (lying down\falling\sitting\walking), and breathing, and enables to classify pets from humans, but it is low enough as to not compromise privacy. This type of technology opens the door to installation of security and well-being devices in locations where privacy or environmental conditions pose an issue, such as in bathrooms or heavily lit environments. Moreover, utilisation of this technology allows to dramatically minimise the numbers of sensors installed in the home, as it provides full home coverage with just one or two sensors and enables using the same HW to support additional capabilities such as breath monitoring, fall detection and highly accurate automation. Using AI and machine learning, the data derived by these sensors can be leveraged to provide smarter, verified alerts on the one hand and whole new insights on the on the other. The sensor can be tuned to learn the location of the house entrances or boundaries, where the inhabitants are expected to be at night, or where they should be expected to enter from into the home, adding new logics to the traditional yes\no decision making. Home security is widely regarded as a necessity, provides peace of mind to people and is integral to people's day to day lives Additional smart home services Among the evolving home technology verticals, security is by far the most relevant and integral to people’s day to day lives. Home security is widely regarded as a necessity and provides peace of mind to people. Being a legacy industry with many well-known and well-trusted brands, security players are well positioned to introduce new technology into the home and have the ability and credibility to expand their offerings to additional smart home services by utilising existing infrastructure and channels. With technology giants entering the security arena through the smart home door the DIY security solution market expected to explode with a CAGR of 22.4% (according to a report by Persistence Market Research). Now that new pricing and service models offer minimal commitment, traditional security players will need to step up. Security companies will need to explore new technologies and expand their offering if they intend to stay relevant and competitive in a market trending on functionality converge and minimisation of maintenance and installation costs.

With the ever-growing availability of video data thanks to the low cost of high-resolution video cameras and storage, artificial intelligence (AI) and deep learning analytics now have become a necessity for the physical security industry, including access control and intrusion detection. Minimising human error and false positives are the key motivations for applying AI technologies in the security industry. What is artificial intelligence? Artificial intelligence is the ability of machines to learn from experience using a multi-layer neural network, which mimics the human brain, in order to recognise items and patterns and make decisions without human interference. The human brain is estimated to have 86 billion neurons; in comparison, the newest Nvidia GPU Volta has 21 billion transistors (the equivalence of a neuron), which offers the performance of hundreds of CPUs for deep learning.AI can learn continuously 24 hours per day every day, constantly acquiring, retaining and improving its knowledge In addition, unlike humans, AI can learn continuously 24 hours per day every day, constantly acquiring, retaining and improving its knowledge. With such enormous processing power, machines using Nvidia GPU and similar chips can now distinguish faces, animals, vehicles, languages, parts of speech, etc. Depending on the required complexity, level of details, acceptable error margin, and learning data quality, AI can learn new objects within as fast as a few seconds using Spiking Neural Network (SNN) to a few weeks using Convolution Neural Network (CNN). While both SNN and CNN offer advantages and drawbacks, they outperform tradition security systems without AI in terms of efficiency and accuracy. According to the research reports of MarketsandMarkets, the market size of perimeter intrusion detection systems is projected to increase from 4.12 billion USD in 2016 to 5.82 billion USD in 2021 at a Compound Annual Growth Rate (CAGR) of 7.1%. Meanwhile, the predicted market of AI in security (both cyber security and physical security) will grow from 3.92 billion USD in 2017 to 34.81 billion USD by 2025, i.e., with an impressive CAGR of 31.38%. Legacy perimeter intrusion detection systems Legacy perimeter intrusion detection systems (PIDSs) are typically set up with the following considerations: Geographical conditions: landscape, flora, fauna, climate (sunrise, sunset, weather conditions, etc.), whether there are undulations in the terrain that would block the field of view of cameras Presence or lack of other layers of physical protection or barriers Integration with other systems in the security network: camera, storage, other defensive lines (door, lock, alarm, etc.) Types of alarm triggers and responses System complexity: intrusion detection with various types of sensors, e.g., microwave sensors, radar sensors, vibration sensors, acoustic sensors, etc. Length of deployment Local regulations: privacy protection, whether the cameras/sensors must be visible/hidden/buried, etc., electromagnetic interferences that may affect other systems such as oil rigs or power plants Human involvement: on-site personnel arrangement, human monitoring, human action in response to alarms AI object detection can easily distinguish different types of people and objects Pain points and benefits of AI The conditions listed above correspond to certain requirements of an intrusion detection systems: minimal false alarm, easy setup and maintenance, easy integration, and stable performance.AI by nature is designed to learn, adapt itself and evolve to work in multiple conditions: it should be integrated with existing video recording systems  Minimal false alarms: False alarms lead to increased cost and inefficiency but are the main problem of PIDSs without AI technology, where animals, trees, shadows, and weather conditions may trigger the sensors. AI object detection can easily distinguish different types of people and objects, e.g., in a region set up to detect people, a car driving by, a cat walking by, or a person’s shadow will not trigger the alarm. Therefore, the amount of false alarms can be reduced by 70% to orders of magnitude. Easy setup and maintenance: Legacy PIDSs without AI must account for terrain, line of sight of cameras, sensor locations; any changes to the system would require manual effort to recalculate such factors and may disturb other components in the system. In contrast, AI PIDSs enable the system administrator to access the entire system or individual cameras from the control room, configure the region and object of interest in the field of view of cameras within minutes, and adjust with ease as often as necessary. Computing knowledge and even specific security training are not required to set up a secured PIDS with AI because AI PIDS is designed to relieve humans from knowing the inner working of machines. Easy integration with complementary technologies: Legacy PIDS without AI relies on physical technology, which are often proprietary and require complete overhaul of systems to function smoothly. On the other hand, AI by nature is designed to learn, adapt itself and evolve to work in multiple conditions, so AI PIDS is easily integrated with existing video recording (camera) and storage (NVR) systems. AI also eliminates the need for physical wireless or fiber-based sensors; instead, it functions based on the videos captured by cameras. Furthermore, AI enables easy and instantaneous combinations of multiple layers of defense, e.g., automatic triggering of door lock, camera movement focusing and access control as soon as a specified object is detected in the region of interest, all set up with a click of a button.  Stable performance and durability: Legacy PIDSs without AI requires complicated setup with multiple components in order to increase detection accuracy. More components mean a higher probability of malfunction in the system, including exposure to damages (e.g., sensors can be destroyed) and delay in detection, while human monitoring is inconsistent due to human fatigue (studies have shown that a person can concentrate in mundane tasks for only up to 20 minutes, and the attention span decreases even more rapidly when humans are faced with multiple items at once, e.g., multiple camera monitoring screens). AI significantly reduces, if not completely eliminates the need for human involvement in the intrusion detection system once it is set up. In addition, AI reduces the risk of system malfunction by simplifying the hardware sensors needed. Minimising human error and false positives are the key motivations for applying AI technologies in the security industry Additional benefits of AI in intrusion detection Artificial Intelligence is undeniably reshaping every business and weaving into every aspect of daily lifeMaximal detection capability: The most advanced AI intrusion detection system today provides an all-in-one solution to distinguish any combination of alarm-triggering criteria beyond perimeter protection. Using AI, the system administrator can configure as many zones with different settings and object of interests as necessary, which include detections for specific colors or attributes (e.g., person not wearing the required uniform or carrying food/drink), numbers and dwell time (e.g., group of more than 5 people loitering), or movements (e.g., cars moving faster than the speed limit). In addition, AI can accurately pinpoint the location of event occurrence by displaying the camera that records the event in near real time, i.e., with few-second delays. Lower security operation cost: By minimising the number of false positives and human involvement while maximising ease of use and stability, AI intrusion detection systems significantly decrease the total cost of ownership. Companies can reduce the large security personnel overhead and cost of complicated and expensive legacy PIDSs systems. McKinsey Global report in June 2017 shows that proactive AI adopters can realize up to 15% increase in profit margin across various industries. Artificial Intelligence is undeniably reshaping every business and weaving into every aspect of daily life. In security, legacy systems are giving way to AI-based systems, and the first enterprises to adopt AI-based systems will soon, if not immediately, benefit from such investment. By Paul Sun, CEO of IronYun, and Mai Truong, Marketing Manager of IronYun