Fujifilm CCTV Network / IP Cameras  (1)

Display solutions play a key role in SOCs in providing the screens needed for individuals and teams to visualise and share the multiple data sources needed in an SOC today. Security Operation Centre (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 visualisation 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 analysed in real time and then, brought forward to operators who are decision makers and key stakeholders in near real time for actionable visualisation. 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 centres 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 visualisation 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 Centre, 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 organisation’s IT infrastructure. Software-defined approach to AV IT teams responsible for data protection are more in favour 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 centres, 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 centres. 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 organisations with physical and cyber security needs.

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 centre 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 realise that cyber security is twofold. It can be carried out by hacking the network or physically breaking Therein lays the problem. People need to realise 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.

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 organisations 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 centres 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 recognise 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 analysing 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 recognise. 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 centre 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.  

Fujifilm and Videotec announce a new collaboration, integrating top-performance products to supply an innovative solution for accurate long-range surveillance. This solution is ideal for protecting critical infrastructure and transportation networks, including airports, harbours, highways, borders and the environment. The combined system incorporates Fujifilm’s new high-end SX800 camera into Videotec’s ULISSE MAXI PTZ. Integrating the SX800 camera into the robust and precise ULISSE MAXI positioning unit is simple and fast, resulting in a first-class PTZ IP camera system for monitoring perimeters and extensive outdoor areas. Maximum resistance motors ULISSE MAXI is a powerful Full-IP PTZ for outdoor IP video surveillance, which can manage IP cameras with large-size lenses, with easy integration into a network system via ONVIF protocol. The sturdy mechanical structure and the powerful motors of the ULISSE MAXI PTZ are designed to guarantee maximum resistance to high operating stress, vibrations and to withstand harsh weather conditions. The unit is equipped with a wiper for removing rain and dust from the front glass. The SX800 camera lens offers a 40x optical zoom that covers a broad range of focal lengths from 20 mm on the wide-angle end to 800mm on the telephoto end, constantly providing sharp images and detailed closeups. It is complemented with 1.25x digital zoom to achieve long-range surveillance equivalent to 1000mm in focal length. The built-in image stabiliser accurately compensates for camera movement, typically caused by gusts of wind or structure vibrations. The system is particularly effective when shooting in the ultra-telephoto range, which is susceptible to even the smallest movement. Advanced de-fog function With a highly sensitive sensor and advanced noise reduction, the SX800 can shoot clear footage with minimal noise even in low-light conditions. The advanced de-fog function brings vivid clarity to hazy images caused by light diffusion due to mist and dust. Alessio Grotto, President of Videotec said: “Our ULISSE MAXI coupled with Fujifilm’s SX800 is the perfect solution when operating cameras in the most challenging environments, and to get the best possible image quality while meeting the needs of the most demanding long-range surveillance applications.”

Fujifilm announces the update of its popular DF/HF-HA-1B series lenses to ruggedised versions equipped with the unique Fujinon ‘Anti-shock and Vibration’ technology. Demand for quality optics in ruggedised versions continues to increase and the designated DF/HF-HA-1S is designed to meet that demand. The Fujinon HF-HA-1B series lenses are already in wide use across a variety of manufacturing environments, from automotive to electronics to pharmaceutical. These applications often have strict space constraints, making the external diameter of only 29.8 mm an attractive feature. Reliable performance The Fujinon HF-HA-1S upgrade provides vibration mitigation and shock absorption within the existing design, so the compact form factor remains. “A ruggedised Fujinon HF-HA-1S provides mechanical robustness for reliable performance in machine vision applications such as automated assembly, quality inspection, and industrial robots. It expands the base to where quality optics are required but where ruggedised design is also a significant factor, such as unmanned aerial vehicles and mobile applications”, says Nina Kürten, Sales Manager at Fujifilm. These lenses are compatible with image sensors up to 2/3’ in a broad selection of focal lengths (6, 9, 12.5, 16, 25, 35, 50, and 75mm). The optical performance of the upgraded series is identical to that of the Fujinon HF-HA-1B. The Fujinon HF-HA-1S will be available from January and will become the new standard version, eventually replacing the Fujinon HF-HA-1B as current stocks are depleted. Pricing will remain the same.

Industrial imaging systems are frequently subject to strong accelerations, shocks, and vibrations. This is especially true for mobile systems, like robot-guided 3D scanners, but also for fixed installations. Fujifilm has investigated the impact of shocks and vibrations on industrial fixed focal lenses via a dedicated test procedure. In many cases, the procedure leads to a significant reduction of the resolution and to a shift of the optical axis. However, the intensity of the effects depends heavily on the mechanical design of a camera lens—a widely underestimated aspect at the selection of fixed focal lenses. Modern robot arms are so powerful they can move major loads with a multiple of the gravitational acceleration (unit G, 1 G = 9.81 m/s²). Robot-guided machine vision systems, as they are used with welding and assembly robots as well as with 3D scanning stations, need to withstand such accelerations. Additionally, they are exposed to the vibrations at the tip of the robot arms just like camera-lens setups at large machines with rotating elements, e.g. in large offset printing systems.Fujifilm has developed a testing procedure for such lenses to measure their robustness against shocks and vibrations. Shock testing on machine vision cameras Most industrial machine vision solutions utilise industrial cameras and c-mount lenses with fixed focal length, which need to provide constant image quality irrespective of harsh conditions. Therefore, Fujifilm has developed a testing procedure for such lenses to measure their robustness against shocks and vibrations. At first, 10 G shocks impact the lenses from 6 different directions orthogonal to the optical axis. Next, a special vibrating table exposes the lenses to various sinusoidal vibrations according to IEC 60068-2-6 (up to 500 Hz and 100 m/s²). Finally, the shock test is repeated. The results show a shift in the optical axis of a conventional lens by up to 26 µm which corresponds to approx. 7 pixels at Sony Pregius sensors of the second generation. Their resolution power, measured using a contrast chart, deteriorates dramatically (see false colour rendering). For most machine vision applications, where fast accelerations and strong vibrations may occur, these lenses are not suitable. On the other hand, all lenses of the Fujinon HF-12M series, as well as the lenses of the HF-5M series with 6 and 50 mm focal length, withstand the shocks and vibrations showing a shift of the optical axis of just between 4 and 10 µm. This is enabled by the Fujinon Anti-Shock & Vibration design, an elastic and patent pending fixation of the internal lens arrangement.The Anti-Shock & Vibration design of the Fujinon lenses minimises the dependency on adhesives and ensures a constant performance and image quality in the long run. Towards high image quality At conventional camera objectives, the lenses are fixed with adhesives, which does not withstand shocks and vibrations plus it is sensitive to changes in humidity and temperature. The Anti-Shock & Vibration design of the Fujinon lenses, however, minimises the dependency on adhesives and ensures a constant performance and image quality in the long run. Beyond the optical format, resolution power, and focal length, developers of mechanically stressed imaging systems should consider the robustness of their camera objectives against shocks and vibrations. The following lenses are already equipped with the Fujinon Anti-Shock & Vibration design: HF-12M series for pixel sizes from 2.1 µm and sensors up to 1“ HF-5M series for pixel sizes from 3.45 µm and sensors up to 1.1 (focal length: 6 and 50 mm)