Dahua Technology IR Corner Network Camera
Dahua Technology IR Corner Network Camera

System OverviewWith advanced H.265 encoding technology, Dahua corner network camera has efficient encoding capacity, which helps to save bandwidth and storage space. The camera adopts starlight technology, intelligent IR technology, and intelligent image analysis technology; and has waterproof function, dust-proof function and vandal-proof function, complying to the standards of IP67 and IK10+50J. Functions Smart ( H.265+ & H.264+ )With advanced scene-adaptive rate control algorithm, Dahua smart encoding technology realizes the higher encoding efficiency than H.265 and H.264, provides high-quality video, and reduces the cost of storage and transmission. StarlightDahua Starlight technology mainly applies to the environment of low illuminance, and it can provide clear colorful video. Even in the environment of ultra-low illuminance, the technology can guarantee the good image effect. Perimeter ProtectionWith deep learning algorithm, Dahua Perimeter Protection technology can recognize human and vehicle accurately. In restricted area (such as pedestrian area and vehicle area), the false alarms of intelligent detection based on target type (such as tripwire, intrusion, fast moving, parking detection, loitering detection and gathering detection) are largely reduced. Distortion CorrectionWith advanced distortion correction algorithm, Dahua Distortion Correction corrects the image distortion in both horizontal and vertical directions to be consistent with the actual situation. No IR ExposureWith 94 nm IR LED, the camera will not generate IR exposure. Naked eyes are invisible. Protection (IP67, IK10, wide voltage)IP67: The camera passes a series of strict test on dust and soak. It has dust-proof function, and the enclosure can works normal after soaking in 1 m deep water for 30 minutes. IK10: The enclosure passes strict vandal-proof test, and it can stand the punch of 50J impact energy. Wide voltage: The camera allows ±30% input voltage tolerance (wide voltage range), and it is widely applied to outdoor environment with instable voltage.

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Hikvision Fisheye IP Camera For Retailers
Hikvision Fisheye IP Camera For Retailers

Hikvision has launched a new Fisheye IP camera series (DS-2CD63X5G0) with AI. This 360˚ panoramic camera uses the deep learning technology to deliver a more accurate heat map functionality. It gives an enhanced view of its surroundings – and is especially useful in large retail applications. The cameras’ 360˚ panoramic image of the scene before it, means the user can see a wider area much more clearly. This is enhanced by independent control of a three-way infrared light, which can be separately configured to reduce the amount of ‘reflective’ wall space. This improves image quality, especially when placed in a corner location. The deep learning algorithm focuses only on human targets, improving the accuracy of the heat map functionality. This means users can see ‘hotspots’ in a space, showing areas that people visit, or pass, the most. An added layer to the heat map visualization makes it a lot clearer than previous technologies, presenting more information in a clearer way. Despite the high quality of the images, the cameras boast extremely light bandwidth, saving storage and costs by using H265+ compression technology. They also support Multiple Expansion Modes, with up to 15 live view display modes available, designed for three different mounts. This means they can be more easily adjusted to meet the users’ exact preferences, and improve their browsing experience. Other features include: New Immervision lens (only 12MP, 1.29mm lens model) Up to 12MP resolution 120 dB WDR Up to 15m IR range Built-in microphone and speaker Smart features: 6 behavior analyses, and 3 exception detections IK10/IP66 available. The cameras will be a useful addition to retail solutions, with heat mapping helping owners to understand customers’ psychology and identify which products attract the most attention on the shop floor. They can also be used in other large area applications, like train stations and public squares. The series will also be a boon to installers, with the ability to achieve monitoring which has no ‘dead angles’, making the solution more efficient and reducing installation costs. “We pride ourselves on continually advancing our technology and how it is implemented”, says Peter Guan, Director of Channel Sales and Marketing for Hikvision Europe. “This new Fisheye camera will provide clear flow information that will help users to make the right business decisions to make their spaces much more profitable.”

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Dahua Dual 4MP Starlight Hunter Camera
Dahua Dual 4MP Starlight Hunter Camera

AI series products adopt the most advanced AI technologies, including deep learning algorithms that primarily target people and vehicles, which provides higher flexibility and accuracy for end-users. This enables the Dahua AI series to offer various advanced applications such as Face Recognition, Metadata, traffic data statistics, etc. The complete lineup of Dahua AI includes network (PTZ) cameras, network video recorders, servers, and more devices. Beyond seeing the world, the power of AI allows devices to perceive the environment and understand the world in a better way. System Overview Dahua PTZ AI network camera adopts advanced CNN deep learning algorithms to support face recognition with high accuracy. The Dual 4MP Starlight Smart Capture Camera consists of panoramic camera and PTZ camera. Panoramic camera captures panoramas, and then PTZ camera takes detailed snapshots of objects and keeps tracking objects after rule violations occur. This camera possess wide monitor range and PFA algorithm that can always present a clear, focused image while zooming. Functions Dual PTZ systemPanoramic camera and Detail camera of the dual PTZ system can be adjusted horizontally and vertically. Face RecognitionOnce facial features are extracted from captured faces, they are stored in a database where they can be easily searched and compared against other images. Once a successful match is found, the system outputs the result. The Dahua Face Recognition camera supports a built-in database that stores up to 10,000 facial images, helping the camera achieve realtime face capture and comparison. Starlight TechnologyFor challenging low-light applications, Dahua's Starlight Ultra-low Light Technology offers best-in-class light sensitivity, capturing color details in low light down to 0.001 lux. The camera uses a set of optical features to balance light throughout the scene, resulting in clear images in dark environments. PFA TechnologyPFA technology has innovatively introduced new methods of judgment to ensure the accuracy and predictability of the direction of subject distance adjustment. The result is a set of advanced focusing algorithms. PFA ensures clarity of the image throughout the process of zooming and shortens focus time. The realization of PFA technology substantially improves user experience and increases product value. MetadataMetadata is feature attribute information extracted from a target object which can be used for data retrieval. There are four kinds of metadata supported by Dahua PTZ AI camera: human face, human body, motor vehicle and non-motor vehicle metadata. Facial information includes gender, age, glasses, masks, beards, etc. Human body information includes hat, top, top color, bottom, bottom color, bag, etc. Motor vehicle information includes plate color, type, vehicle color, sunshield, ornament, calling, seatbelt, smoking, annual inspection sticker, etc. Non-motor vehicle information includes type, color, top type, top color, people number, etc. Smart trackingHuman, motor vehicle, and non-motor vehicle, or their combinations can be set as objects. Once the objects selected trigger detection rules (like tripwire and intrusion), the detail camera will track them automatically. Perimeter ProtectionAutomatically filtering out false alarms caused by animals, rustling leaves, bright lights, etc. Enables system to act secondary recognition for the targets. Improving alarm accuracy. InteroperabilityThe camera conforms to the ONVIF (Open Network Video Interface Forum) specifications, ensuring interoperability between network video products regardless of manufacturer.

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Dahua Technology AI WDR Bullet Network Camera
Dahua Technology AI WDR Bullet Network Camera

Dahua AI series products adopt the most advanced AI technologies, including deep learning algorithms that primarily target people and vehicles, which provides higher flexibility and accuracy for end-users. This enables the Dahua AI series to offer various advanced applications such as Face Recognition, ANPR, Metadata, People Counting, traffic data statistics, etc.The complete lineup of Dahua AI includes network (PTZ) cameras, network video recorders, servers, and platform management products. Beyond seeing the world, the power of AI allows devices to perceive the environment and understand the world in a better way. System Overview Pro AI series contains Face Capture, Perimeter Protection and People Counting functions.Powered by deep-learning Artificial Intelligence algorithms, significantly improved accuracy. Meanwhile, the series features starlight and smart IR technology. This series fully protected from dust and water, certified to IP67 standard. Functions Face CaptureFace capture is a software application that automatically captures faces from within a digital image or a video frame from a video source. Dahua cameras use advanced deep learning algorithms and are trained by a large number of face data sources, enabling the camera to locate faces quickly and accurately from the video source and capture facial images. Perimeter ProtectionDahua’s Perimeter Protection functions significantly improved accuracy. Perimeter Protection reduces false alarms and decreases pixel count requirements for object detection. Perimeter Protection features custom tripwires based on object type for automation in limited access areas such as pedestrian or vehicle-only zones. This combination of advanced AI analytics and real-time alerts to a desktop or to a mobile client reduces system requirements and resources resulting in greater surveillance system efficiency. People CountingPeople Counting function uses advanced image processing technology to capture depth information from within images. The camera pairs this information with deep learning algorithms to analyze and detect humanbodies and track target objects in real time. The camera provides statistics for separate individuals’ entrance and exit with up to 95% counting accuracy. Full-color StarlightThe camera adopts F1.6 large aperture lens and 1/1.8" high performance sensor. With higher amount of absorbed light and advanced image processing algorithm, the camera presents an impressive lowlight performance with an exceptional balance between noise reduction and the blur of moving object. Warm Supplemental lightsWith two warm supplemental LED lights, the camera is able to provide a colorful and vivid image even in total darkness. It also provides visible By default, the camera is set to smart light mode, in which the camera can automatically adjust the exposure time and light sensitivity simultaneously to avoid overexposureing of the objects in the image center. Also, the sensitivity and intensity of the LED lights can be remotely controlled by OSD menu. Protection(IP67, wide voltage)The camera allows for ±30% input voltage tolerance, suitable for the most unstable conditions for outdoor applications. Its 6KV lightning rating provides effective protection for both the camera and its structure against lightning. Subjected and certified to rigorous dust and immersion tests (IP67) , the camera is the choice for installation in even the most unforgiving environments.

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IP cameras - Expert commentary

Why Visualization Platforms Are Vital For An Effective Security Operation Center (SOC)
Why Visualization Platforms Are Vital For An Effective Security Operation Center (SOC)

Display solutions play a key role in SOCs in providing the screens needed for individuals and teams to visualize and share the multiple data sources needed in an SOC today. Security Operation Center (SOC) Every SOC has multiple sources and inputs, both physical and virtual, all of which provide numerous data points to operators, in order to provide the highest levels of physical and cyber security, including surveillance camera feeds, access control and alarm systems for physical security, as well as dashboards and web apps for cyber security applications. Today’s advancements in technology and computing power not only have increasingly made security systems much more scalable, by adding hundreds, if not thousands, of more data points to an SOC, but the rate at which the data comes in has significantly increased as well. Accurate monitoring and surveillance This has made monitoring and surveillance much more accurate and effective, but also more challenging for operators, as they can’t realistically monitor the hundreds, even thousands of cameras, dashboards, calls, etc. in a reactive manner. Lacking situational awareness is often one of the primary factors in poor decision making In order for operators in SOC’s to be able to mitigate incidents in a less reactive way and take meaningful action, streamlined actionable data is needed. This is what will ensure operators in SOC truly have situational awareness. Situational awareness is a key foundation of effective decision making. In its simplest form, ‘It is knowing what is going on’. Lacking situational awareness is often one of the primary factors in poor decision making and in accidents attributed to human error. Achieving ‘true’ situational awareness Situational awareness isn’t just what has already happened, but what is likely to happen next and to achieve ‘true’ situational awareness, a combination of actionable data and the ability to deliver that information or data to the right people, at the right time. This is where visualization platforms (known as visual networking platforms) that provide both the situational real estate, as well as support for computer vision and AI, can help SOCs achieve true situational awareness Role of computer vision and AI technologies Proactive situational awareness is when the data coming into the SOC is analyzed in real time and then, brought forward to operators who are decision makers and key stakeholders in near real time for actionable visualization. Computer vision is a field of Artificial Intelligence that trains computers to interpret and understand digital images and videos. It is a way to automate tasks that the human visual system can also carry out, the automatic extraction, analysis and understanding of useful information from a single image or a sequence of images. There are numerous potential value adds that computer vision can provide to operation centers of different kinds. Here are some examples: Face Recognition: Face detection algorithms can be applied to filter and identify an individual. Biometric Systems: AI can be applied to biometric descriptions such as fingerprint, iris, and face matching. Surveillance: Computer vision supports IoT cameras used to monitor activities and movements of just about any kind that might be related to security and safety, whether that's on the job safety or physical security. Smart Cities: AI and computer vision can be used to improve mobility through quantitative, objective and automated management of resource use (car parks, roads, public squares, etc.) based on the analysis of CCTV data. Event Recognition: Improve the visualization and the decision-making process of human operators or existing video surveillance solutions, by integrating real-time video data analysis algorithms to understand the content of the filmed scene and to extract the relevant information from it. Monitoring: Responding to specific tasks in terms of continuous monitoring and surveillance in many different application frameworks: improved management of logistics in storage warehouses, counting of people during event gatherings, monitoring of subway stations, coastal areas, etc. Computer Vision applications When considering a Computer Vision application, it’s important to ensure that the rest of the infrastructure in the Operation Center, for example the solution that drives the displays and video walls, will connect and work well with the computer vision application. The best way to do this of course is to use a software-driven approach to displaying information and data, rather than a traditional AV hardware approach, which may present incompatibilities. Software-defined and open technology solutions Software-defined and open technology solutions provide a wider support for any type of application the SOC may need Software-defined and open technology solutions provide a wider support for any type of application the SOC may need, including computer vision. In the modern world, with everything going digital, all security services and applications have become networked, and as such, they belong to IT. AV applications and services have increasingly become an integral part of an organization’s IT infrastructure. Software-defined approach to AV IT teams responsible for data protection are more in favor of a software-defined approach to AV that allow virtualised, open technologies as opposed to traditional hardware-based solutions. Software’s flexibility allows for more efficient refreshment cycles, expansions and upgrades. The rise of AV-over-IP technologies have enabled IT teams in SOC’s to effectively integrate AV solutions into their existing stack, greatly reducing overhead costs, when it comes to technology investments, staff training, maintenance, and even physical infrastructure. AV-over-IP software platforms Moreover, with AV-over-IP, software-defined AV platforms, IT teams can more easily integrate AI and Computer Vision applications within the SOC, and have better control of the data coming in, while achieving true situational awareness. Situational awareness is all about actionable data delivered to the right people, at the right time, in order to address security incidents and challenges. Situational awareness is all about actionable data delivered to the right people Often, the people who need to know about security risks or breaches are not physically present in the operation centers, so having the data and information locked up within the four walls of the SOC does not provide true situational awareness. hyper-scalable visual platforms Instead there is a need to be able to deliver the video stream, the dashboard of the data and information to any screen anywhere, at any time — including desktops, tablets phones — for the right people to see, whether that is an executive in a different office or working from home, or security guards walking the halls or streets. New technologies are continuing to extend the reach and the benefits of security operation centers. However, interoperability plays a key role in bringing together AI, machine learning and computer vision technologies, in order to ensure data is turned into actionable data, which is delivered to the right people to provide ‘true’ situational awareness. Software-defined, AV-over-IP platforms are the perfect medium to facilitate this for any organizations with physical and cyber security needs.

We Need To Talk About Intelligent Enclosure Protection
We Need To Talk About Intelligent Enclosure Protection

Enclosures containing electronics, communications or cabling infrastructure offer a simple attack point for cyber breaches and an opportunity for a physical attack on the hardware. Yet, many of these assets are housed within enclosures that provide minimal security features to offer a deterrent to any would-be attacker. This has always just been a pet hate. Walking down the high street of a town anywhere in the United Kingdom, you can often see open street communication cabinets. You can actually look directly inside at the equipment. And if I was a bad guy, I could quite easily just put my foot into their enclosure and quite quickly take out their infrastructure. Charged service for enclosures This seems crazy when a US$ 2 magnetic contact on a door can quickly tell you whether your enclosure is open or shut, and can be vital in keeping your network alive. Moreover, the operators of these systems, whether it is telecoms or internet providers, are providing a charged service to their customers, so they should really be protecting their enclosures. Why has that security level not been so readily taken into the outside world, into the unprotected environment? More sobering, if you contrast this security approach to the approach taken in the data center world, an environment that already has multiple stringent security protocols in place, you get a very different picture. For instance, security devices can capture snapshots of anyone who opens a cabinet door in a data room, so it is recorded who has opened that door. While that is just one simple example, it begs the question. Why has that security level not been so readily taken into the outside world, into the unprotected environment? In my mind, a lot of it boils down simply to education. Network connection, easy point of cyber attacks Our preconceived idea about cyber security is some big corporation being knocked out or held to ransom by, again in our mind, someone sitting at a laptop, probably with their hood up over their head, typing away in the darkness, attacking us through the internet. But how the would-be criminal is going to come at us is just like in sport. They attack at the weakest point. Networks can be deployed in the outside world in many ways, such as cameras monitoring the highways. That means those locations will have a network connection. And that can be a point of attack in a non-secure outside world. Enclosures can be broken into by attackers Many people think, ‘That is okay because I’m going to take that ethernet device that my cameras are connected to and I’m going to put it inside an enclosure.’ However, what people do not realize is that the only thing that the enclosure is doing is protecting the ethernet device from Mother Nature. Because, without proper security, those enclosures can be broken into pretty easily. Many of them are just a single key that is not in any way coded to the device. Twofold cyber security People need to realize that cyber security is twofold. It can be carried out by hacking the network or physically breaking Therein lays the problem. People need to realize that cyber security is twofold. It can be carried out by hacking the network or physically breaking into the weakest physical point. And so, a simple boot through the open door of an enclosure can vandalise the devices inside and take down a small or large part of a network. And by definition, this meets the criteria for a cyber-attack. So, how do we go about tackling this problem? Well, security is a reaction marketplace. And for enclosures, there’s not, at present, a plethora of solutions out there for to counter these types of attacks. It can be challenging to find what you’re looking for through a quick Google search compared to searching for more traditional security protection measures. Deploying smart sensors and detectors But, under Vanderbilt and ComNet, we are currently taking our knowledge and experience from system installation and compiling it together. We’re bringing different products from different parts of our business to make a true solution. For instance, we have sensors for enclosures that detect anything from gas or smoke to open doors, detectors that will tell you if someone is trying to smash open your enclosure with a sledgehammer, or that someone is trying to lift your enclosure off of its mount. More importantly, as is not really a one-size-fits-all solution, we have developed a menu structure available that allows customers to pick and choose the ones that will best fit their own requirements.

We Have The Technology To Make Society Safer – How Long Can We Justify Not Using It?
We Have The Technology To Make Society Safer – How Long Can We Justify Not Using It?

While the application of facial recognition within both public and private spheres continues to draw criticism from those who see it as a threat to civil rights, this technology has become extremely commonplace in the lives of iPhone users. It is so prevalent, in fact, that by 2024 it is predicted that 90% of smartphones will use biometric facial recognition hardware. CCTV surveillance cameras  Similarly, CCTV is a well-established security measure that many of us are familiar with, whether through spotting images displayed on screens in shops, hotels and offices, or noticing cameras on the side of buildings. It is therefore necessary we ask the question of why, when facial recognition is integrated with security surveillance technology, does it become such a source of contention? It is not uncommon for concerns to be voiced against innovation. History has taught us that it is human nature to fear the unknown, especially if it seems that it may change life as we know it. Yet technology is an ever-changing, progressive part of the 21st century and it is important we start to shift the narrative away from privacy threats, to the force for good that LFR (Live Facial Recognition) represents. Live Facial Recognition (LFR) We understand the arguments from those that fear the ethics of AI and the data collection within facial recognition Across recent weeks, we have seen pleas from UK organizations to allow better police access to facial recognition technology in order to fight crime. In the US, there are reports that LAPD is the latest police force to be properly regulating its use of facial recognition to aid criminal investigations, which is certainly a step in the right direction. While it is understandable that society fears technology that they do not yet understand, this lack of knowledge is exactly why the narrative needs to shift. We understand the arguments from those that fear the ethics of AI and the data collection within facial recognition, we respect these anxieties. However, it is time to level the playing field of the facial recognition debate and communicate the plethora of benefits it offers society. Facial recognition technology - A force for good Facial recognition technology has already reached such a level of maturity and sophistication that there are huge opportunities for it to be leveraged as a force for good in real-world scenarios. As well as making society safer and more secure, I would go as far to say that LFR is able to save lives. One usage that could have a dramatic effect on reducing stress in people with mental conditions is the ability for facial recognition to identify those with Alzheimer’s. If an older individual is seemingly confused, lost or distressed, cameras could alert local medical centers or police stations of their identity, condition and where they need to go (a home address or a next of kin contact). Granted, this usage would be one that does incorporate a fair bit of personal data, although this information would only be gathered with consent from each individual. Vulnerable people could volunteer their personal data to local watchlists in order to ensure their safety when out in society, as well as to allow quicker resolutions of typically stressful situations. Tracking and finding missing persons Another possibility for real world positives to be drawn from facial recognition is to leverage the technology to help track or find missing persons, a lost child for instance. The most advanced forms of LFR in the market are now able to recognize individuals even if up to 50% of their face is covered and from challenging or oblique angles. Therefore, there is a significant opportunity not only to return people home safely, more quickly, but also reduce police hours spent on analyzing CCTV footage. Rapid scanning of images Facial recognition technology can rapidly scan images for a potential match Facial recognition technology can rapidly scan images for a potential match, as a more reliable and less time-consuming option than the human alternative. Freed-up officers could also then work more proactively on the ground, patrolling their local areas and increasing community safety and security twofold. It is important to understand that these facial recognition solutions should not be applied to every criminal case, and the technology must be used responsibly. However, these opportunities to use LFR as force for good are undeniable.   Debunking the myths One of the central concerns around LFR is the breach of privacy that is associated with ‘watchlists’. There is a common misconception, however, that the data of every individual that passes a camera is processed and then stored. The reality is that watch lists are compiled with focus on known criminals, while the general public can continue life as normal. The very best facial recognition will effectively view a stream of blurred faces, until it detects one that it has been programmed to recognize. For example, an individual that has previously shoplifted from a local supermarket may have their biometric data stored, so when they return to that location the employees are alerted to a risk of further crimes being committed. Considering that the cost of crime prevention to retailers in recent years has been around £1 billion, which therefore impacts consumer prices and employee wages, security measures to tackle this issue are very much in the public interest. Most importantly, the average citizen has no need to fear being ‘followed’ by LFR cameras. If data is stored, it is for a maximum of 0.6 seconds before being deleted. Privacy Privacy is ingrained in facial recognition solutions, yet it seems the debate often ignores this side of the story Privacy is ingrained in facial recognition solutions, yet it seems the debate often ignores this side of the story. It is essential we spend more time and effort communicating exactly why watchlists are made, who they are made for and how they are being used, if we want to de-bunk myths and change the narrative. As science and technology professionals, heading up this exciting innovation, we must put transparency and accountability at the center of what we do. Tony Porter, former Surveillance Camera Commissioner and current CPO at Corsight AI, has previously worked on developing processes that audit and review watch lists. Such restrictions are imperative in order for AI and LFR to be used legally, as well as ethically and responsibly. Biometrics, mask detection and contactless payments Nevertheless, the risks do not outweigh the benefits. Facial recognition should and can be used for good in so many more ways than listed above, including biometric, contactless payments, detecting whether an individual is wearing a facemask and is therefore, safe to enter a building, identifying a domestic abuse perpetrator returning to the scene of a crime and alerting police. There are even opportunities for good that we have not thought of yet. It is therefore not only a waste not to use this technology where we can, prioritising making society a safer place, it is immoral to stand by and let crimes continue while we have effective, reliable mitigation solutions.  

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