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If you’re responsible for a medium or large-sized office, it’s more important than ever that you have access to a means of ensuring people’s safety, managing risks and fraud, and protecting property. Any security system that you employ must therefore meet the most demanding commercial requirements of today’s offices, and tomorrow’s. This means thinking beyond a basic intrusion system and specifying a comprehensive solution that integrates smart features like access control, video management and intelligent video analytics. Because only then will you have security you can trust, and detection you can depend on. Reliable Entry Management Access control systems have been developed that guarantee reliable entry management for indoors and outdoors Access control is becoming increasingly important for ensuring the security of office buildings, but as the modern workplace evolves you’re unlikely to find a one-size-fits-all solution. Today, it’s commonplace to control entry to individual rooms or restricted areas and cater to more flexible working hours that extend beyond 9 to 5, so a modern and reliable access control system that exceeds the limitations of standard mechanical locks is indispensable. Access control systems have been developed that guarantee reliable entry management for indoors and outdoors. They use state-of-the-art readers and controllers to restrict access to certain areas, ensuring only authorized individuals can get in. With video cameras located within close proximity you can then monitor and record any unauthorized access attempts. The system can also undertake a people-count to ensure only one person has entered using a single pass. Scalable Hardware Components As previously mentioned, there is no one-size-fits-all system, but thanks to the scalability of the hardware components, systems can adapt to changing security requirements. For example, you can install Bosch’s Access Professional Edition (APE) software for small to medium-sized offices, then switch to the more comprehensive Access Engine (ACE) of the Building Integration System (BIS) when your security requirements grow. And, because the hardware stays the same, any adaptations are simple. APE’s ‘permanent open’ functionality allows employees and guests to enter designated areas easily and conveniently The APE software administers up to 512 readers, 10,000 cardholders and 128 cameras, making it suitable for small to medium-sized buildings. With functions like badge enrollment, entrance control monitoring and alarm management with video verification it provides a high level of security and ensures only authorized employees and visitors are able to enter certain rooms and areas. Of course, there will always be situations when, for convenience, you need certain doors to be permanently open, such as events and open days. APE’s ‘permanent open’ functionality allows employees and guests to enter designated areas easily and conveniently. Growing Security Needs You switch to the Bosch Building Integration System (BIS), without having to switch hardware (it stays the same, remember?). This is a software solution that manages subsystems like access control, video surveillance, fire alarm, public address or intrusion systems, all on a single platform. It is designed for offices with multiple sites and for large companies with a global presence. Bosch Building Integration System (BIS) manages subsystems like access control, video surveillance, fire alarm, public address or intrusion systems, all on a single platform The BIS Access Engine (ACE) administers up to 10,000 readers and 80 concurrent workplace clients per server, and 200,000 cardholders per AMC. An additional benefit to security officers is the ability to oversee cardholders and authorizations through the central cardholder management functionality and monitor all access events and alarms from every connected site. For consistency, multi-site cardholder information and access authorizations can be created on a central server and replicated across all connected site servers, which means the cardholder information is always up to date and available in every location. Intrusion Alarm Systems Bosch B Series and G Series intrusion control panels can also send personal notifications via text or email Securing all perimeter doors is vital when protecting employees, visitors and intellectual property. Doors are opened and closed countless times during business hours, and when intentionally left open, your office is vulnerable to theft, and the safety of your employees is compromised. For this reason, intrusion control panels have been developed with advanced features to ensure all perimeter doors are properly closed, even when the system is not armed. If a door remains open for a period of time (you can specify anything from one second to 60 minutes), the system can be programmed to automatically take action. For example, it can activate an audible alert at the keypad to give employees time to close the door. Then, if it is still not closed, it will send a report to a monitoring center or a text directly to the office manager, and when integrated with video it can even send an image of the incident to a mobile device. Customized Intrusion Systems What about people who need to access your building outside of working hours, like cleaning crews? Your intruder system allows you to customize the way it operates with a press of a button or swipe of a card. This level of control enables you to disarm specific areas, bypass points and unlock doors for cleaning crews or after-hours staff, whilst keeping server rooms, stock rooms and executive offices safe and secure. Bosch B Series and G Series intrusion control panels can also send personal notifications via text or email. You can program the panel to send you opening, closing, and other event alerts, which means you don’t have to be on-site to keep track of movements in and around your facility. Video Management System A video management system will add a next level of security to your access control system Every office building has different video security requirements depending on the location, size and nature of the business. Some offices may only need basic functions such as recording and playback, whereas others may need full alarm functionalities and access to different sites. A video management system will add a next level of security to your access control system. For example, the video system can provide seamless management of digital video, audio and data across IP networks for small to large office buildings. It is fully integrated and can be scaled according to your specific requirements. The entry-level BVMS Viewer is suitable for small offices that need to access live and archived video from their recording solutions. With forensic search it enables you to access a huge recording database and scan quickly for a specific security event. For larger offices, embellished security functions for the BVMS Professional version can manage up to 2,000 cameras and offers full alarm and event management Full Alarm And Event Management For larger offices, embellished security functions for the BVMS Professional version can manage up to 2,000 cameras and offers full alarm and event management. It’s also resilient enough to remain operative should both Management and Recording Servers fail. Large multi-national companies often need access to video surveillance systems at numerous sites, which is why BVMS Professional allows you to access live and archived video from over 10,000 sites across multiple time zones from a single BVMS server. When integrated with the BVMS Enterprise version multiple BVMS Professional systems can be connected so every office in the network can be viewed from one security center, which provides the opportunity to monitor up to 200,000 cameras, regardless of their location. Essential Video Analytics Video analytics acts as the brain of your security system, using metadata to add sense and structure to any video footage you capture If your strategy is to significantly improve levels of security, video analytics is an essential part of the plan. It acts as the brain of your security system, using metadata to add sense and structure to any video footage you capture. In effect, each video camera in your network becomes smart to the degree that it can understand and interpret what it is seeing. You simply set certain alarm rules, such as when someone approaches a perimeter fence, and video analytics alerts security personnel the moment a rule is breached. Smart analytics have been developed in two formats. Essential Video Analytics is ideal for small and medium-sized commercial buildings and can be used for advanced intrusion detection, such as loitering alarms, and identifying a person or object entering a pre-defined field. It also enables you to instantly retrieve the right footage from hours of stored video, so you can deal with potential threats the moment they happen. Essential Video Analytics also goes beyond security to help you enforce health and safety regulations such as enforcing no parking zones, detecting blocked emergency exits or ensuring no one enters or leaves a building via an emergency exit; all measures that can increase the safety of employees and visitors inside the building. Intelligent Video Analytics Intelligent Video Analytics have the unique capability of analyzing video content over large distances Intelligent Video Analytics have the unique capability of analyzing video content over large distances, which makes it ideally suited to more expansive office grounds or securing a perimeter fence. It can also differentiate between genuine security events and known false triggers such as snow, rain, hail and moving tree branches that can make video data far more difficult to interpret. The final piece in your security jigsaw is an intelligent camera. The latest range of Bosch ’i’ cameras have the image quality, data security measures, and bitrate reduction of <80%. And, video analytics is standard. Be prepared for what can’t be predicted. Although no-one can fully predict what kind of security-related event is around the corner, experience and expertise will help make sure you’re always fully prepared.
The term “smart city” gets thrown around a lot nowadays, but as different technologies that strive to be defined in this way are adopted by different countries globally, the meaning of this phrase gets lost in translation. The simplest way to define a “smart city” is that it is an urban area that uses different types of data collecting sensors to manage assets and resources efficiently. One of the most obvious types of “data collecting sensor” is the video camera, whether that camera is part of a city’s existing CCTV infrastructure, a camera in a shopping mall or even a police car’s dash camera. The information gathered by video cameras can be used with two purposes in mind, firstly: making people’s lives more efficient, for example by managing traffic, and secondly (and arguably more importantly): making people’s lives safer. Live Streaming Video All The Time, Everywhere In the smart and safe city, traditional record-only video cameras are of limited use. Yes, they can be used to collect video which can be used for evidence after a crime has taken place, but there is no way that this technology could help divert cars away from an accident to avoid traffic building up, or prevent a crime from taking place in the first place. However, streaming live video from a camera that isn’t connected to an infrastructure via costly fiber optic cabling has proven challenging for security professionals, law enforcement and city planners alike. This is because it isn’t viable to transmit video reliably over cellular networks, in contrast to simply receiving it. Video Transmission Challenges Transmitting video normally results in freezing and buffering issues which can hinder efforts to fight crime and enable flow within a city, as these services require real-time, zero latency video without delays. Therefore, special technology is required that copes with poor and varying bandwidths to allow a real-time view of any scene where cameras are present to support immediate decision making and smart city processes. The information gatheredby video cameras can beused to make people’s lives more efficient, and to make people’s lives safer There are many approaches to transmitting video over cellular. We’ve developed a specialist codec (encoding and decoding algorithm) that can provide secure and reliable video over ultra-low bandwidths and can therefore cope when networks become constrained. Another technique, which is particularly useful if streaming video from police body worn cameras or dash cams that move around, is to create a local wireless “bubble” at the scene, using Wi-Fi or mesh radio systems to provide local high-bandwidth communications that can communicate with a central location via cellular or even satellite communications. Enhanced City Surveillance Live video streaming within the smart and safe city’s infrastructure means that video’s capabilities can go beyond simple evidence recording and evolve into a tool that allows operations teams to monitor and remediate against incidents as they are happening. This can be taken one step further with the deployment of facial recognition via live streaming video. Facial recognition technology can be added on to any video surveillance camera that is recording at a high enough quality to identify faces. The technology works by capturing video, streaming the live video back to a control center and matching faces against any watch lists that the control center owns. Importantly, the data of people who aren’t on watch lists is not stored by the technology. Identifying Known Criminals This technology can work to make the city safer in a number of ways. For example, facial recognition could spot a known drug dealer in a city center where they weren’t supposed to be, or facial recognition could identify if a group of known terror suspects were visiting the same location at the same time, and this would send an alert to the police. Facial recognition technology captures and streams live back to a controll center, matching faces against any watch lists that the control center owns In an ideal world where the police had an automated, electronic workflow, the police officer nearest to the location of the incident would be identified by GPS and would be told by the control room where to go and what to do. Most police forces aren’t quite at this technological level yet, and would probably rely on communicating via radio in order to send the nearest response team to the scene. As well as this, shopping malls could create a database from analog records of known shoplifters to identify criminals as soon as they entered the building. This would be even more effective if run co-operatively between all shopping malls and local businesses in an area, and would not only catch any known shoplifters acting suspiciously, but would act as a deterrent from shoplifting in the first place. Live Streaming For Law Enforcement As mentioned above, live streaming video from CCTV cameras can help the police fight crime more proactively rather than reactively. This can be enhanced even further if combined with live streaming video from police car dash cams and police body worn cameras. If video was streamed from all of these sources to a central HQ, such as a police operations center, the force would be able to have full situational awareness throughout an incident. This would mean that, if need be, officers could be advised on the best course of action, and additional police or other emergency services could be deployed instantly if needed. Incorporated with facial recognition, this would also mean that police could instantly identify if they were dealing with known criminals or terrorists. While they would still have to confirm the identity of the person with questioning or by checking their identification, this is still more streamlined than describing what a person looks like over a radio and then ops trying to manually identify if the person is on a watch list. The smart, safe city is possible today – for one, if live video streaming capabilities are deployed they can enable new levels of flow in the city. With the addition of facial recognition, cities will be safer than ever before and law enforcement and security teams will be able to proactively stop crime before it happens by deterring criminal activity from taking place at all.
The use of drones has increased dramatically in the last few years. Indeed, by 2021, the FAA says the number of small hobbyist drones in the U.S. will triple to about 3.55 million. With that growth, drone capabilities have increased while costs have decreased. For example, the DJI Phantom 4 can deliver a 2-pound payload to a target with 1.5m accuracy from 20 miles away for the less than $1000.00. This is an unprecedented capability accessible to anyone. This new technology has created an entirely new security risk for businesses and governments. Drone Security Risks Already, rogue groups such as ISIS have used low cost drones to carry explosives in targeted attacks. Using this same method, targeting high profile locations within our borders to create terror and panic is very possible. Security professionals and technologists are working furiously to address the gaps in drone defense. Currently, the most common technologies in use for drone detection are video, acoustic sensors, radio, and air surveillance radar. Each of these has advantages, but they also have flaws that make it difficult to detect drones in all conditions. Both optical and thermal cameras, as well as acoustic sensors, do not operate in severe weather such as fog and snow. And while radio and air surveillance radar cover a wide area of detection, they suffer from high installation costs and limiting technical challenges, such as being unable to detect low flying drones on autopilot. Compact Surveillance Radar (CSR) Compact Surveillance Radar (CSR) is a security technology addressing the problems with other types of detection. CSR, like traditional radar, has the benefit of being able to detect and track foreign objects in all weather conditions, but at a fraction of the size and cost. The compact size allows the radar to be mounted on existing structures or even trees, providing extensive perimeter defense almost anywhere that you can imagine. CSR can also filter out clutter such as birds by using an advanced algorithm reducing the number of false alarms. While the use of CSR and the other detection technologies are legal in the US and in most locations throughout the world, the response mechanisms are generally not. Current regulations in the US prohibit the use of jamming or GPS spoofing in all cases except for a few federal agencies Regulations Limiting Drones Current regulations in the US prohibit the use of jamming or GPS spoofing in all cases except for a few federal agencies. This makes it difficult to stop the damage that drones can cause. The FAA has put into place new regulations that limit some uses of drones. However, in most cases it is still illegal for even state or local governments to stop or interfere with drones other than to locate the operator and have them land the drone. In 2016 the first law to neutralize a drone in the United States was passed in Utah to respond to drones in wildfire areas because of their interference with airborne firefighting. This law may very well provide a model for other states dealing with drones in situations where people’s lives are being put at risk by drones. At the federal level, much effort is being put into evaluating the regulations and technology surrounding the misuse of drones. In the 2016 reauthorization bill for the FAA, Section 2135 included a pilot program for the investigation of methods to mitigate the threat of unmanned aircraft around airports and other critical infrastructure. There are many federal agencies that are evaluating the use of a variety of technologies to respond to this threat. Both optical and thermal cameras, as well as acoustic sensors, do not operate in severe weather such as fog and snow Effective Countermeasure Technologies The most effective countermeasure for drones is jamming, currently off-limits to the private sector. This includes stadiums, convention centers, and other large gathering areas. A number of companies are developing new response technologies that do not require the use of jammers or hacking. Several companies have developed net guns that shoot a net at an approaching drone. These are only effective at less than 100m and frequently miss the target, especially when the drone is approaching at high speed. Several other companies have taken this method a step further, with drones that capture other drones. Once a radar detects a drone, another defense drone is launched and flies to the point of detection. Then, using video analytics it homes in on the drone and fires a net to disable the drone and take it to a safe location. While this drone capturing technique is still in its infancy, it shows a great deal of promise and will not be restricted in the same fashion as jamming. However, even this solution is difficult under current regulations, as all commercial drones in the US must be under direct control of a human operator within their line of sight. This effectively means that a drone operator is required to be on-site at all times to protect a facility, event, or persons. One thing is for certain, technology will continue to adapt and security companies will continue to invent new methods to protect their facilities and the people they are sworn to protect.
Artificial Intelligence. You’ve heard the words in just about every facet of our lives, just two words, and they’re quite possibly the most moving, life-changing words employed in everyday conversations. So what exactly is AI, who currently uses it and should be using it? What is AI? AI is a powerful way of collecting, qualifying and quantifying data toward a meaningful conclusion to help us reach decisions more quickly or automate processes which could be considered mundane or repetitive. AI in its previous state was known as “machine learning” or “machine processing” which has evolved into “deep learning” or, here in the present, Artificial Intelligence. AI as it applies to the security and surveillance industry provides us the ability to discover and process meaningful information more quickly than at any other time in modern history. Flashback - VCR tapes, blurred images, fast-forward, rewind and repeat. This process became digital, though continued to be very time-consuming. Today’s surveillance video management systems have automated many of these processes with features like “museum search” seeking an object removed from a camera view or “motion detection” to create alerts when objects move through a selected viewpoint. These features are often confused with AI, and are really supportive analytics of the Artificial Intelligence, not AI themselves. Machine Learning Fully appreciating AI means employment of a machine or series of machines to collect, process and produce information obtained from basic video features or analytics. What the machines learn depends on what is asked of them. The truth is, the only way the AI can become meaningful is if there is enough information learned to provide the results desired. If there isn’t enough info, then we must dig deeper for information or learn more, properly described as “deep-learning” AI. Translated, this means that we need to learn more on a deeper level in order to obtain the collaborative combined information necessary to produce the desired result. Deep learning AI Deep learning AI can afford us the ability to understand more about person characteristic traits & behaviors. Applying this information can then further be applied to understand how to interpret patterns of behavior with the end goal of predictable behavior. This prediction requires some degree of human interpretation so that we are able to position ourselves to disrupt patterns of negative behavior or simply look for persons of interest based on these patterns of behavior. These same patterns evolve into intelligence which over time increases the machine’s ability to more accurately predict patterns that could allow for actions to be taken as a result. This intelligence which is now actionable could translate to life safety such as stopping a production manufacturing process, if a person were to move into an area where they shouldn’t be which might put them in danger. Useful applications of intelligence Informative knowledge or intelligence gathered could be useful in retail applications as well by simply collecting traffic patterns as patrons enter a showroom. This is often displayed in the form of heat mapping of the most commonly traveled paths or determining choke points that detract from a shopper’s experience within the retail establishment. It could also mean relocating signage to more heavily traveled foot-paths to gain the highest possible exposure to communicating a sale or similar notice, perhaps lending itself to driving higher interest to a sale or product capability. Some of this signage or direction could even translate to increased revenues by realigning the customer engagement and purchasing points. Actionable Intelligence From a surveillance perspective, AI could be retranslated to actionable intelligence by providing behavioral data to allow law enforcement to engage individuals with malicious intent earlier, thus preventing crimes in whole or in part based on previously learned data. The data collection points now begin to depart from a more benign, passive role into an actionable role. As a result, new questions are being asked regarding the cameras intended purpose or role of its viewpoint such as detection, observation, recognition or identification. Detecting human presence By way of example, a camera or data collector may need to detect human presence, as well as positively identify who the person is. So the analytic trip line is crossed or motion box activated or counter-flow is detected which then creates an alert for a guard or observer to take action. Further up the food chain, a supervisor is also notified and the facial characteristics are captured. These remain camera analytics, but now we feed this collected facial information to a graphic processing unit (GPU) which could be employed to compare captured characteristics with pre-loaded facial characteristics. When the two sources are compared and a match produced, an alert could be generated which results in an intervention or other similar action with the effort of preventing a further action. This process- detect, disrupt, deter or detain could be considered life-saving by predictably displaying possible outcomes in advance of the intended actions. The next level is deep-learning AI which employs the same characteristics to determine where else within the CCTV ecosystem the individual may have been previously by comparatively analyzing other collected video data. This becomes deep-learning AI when the GPU machine is able to learn from user-tagged positive identification, which the machine learns and begins to further reprocess its own data to further understand where else the person of interest (POI) may have existed on the ecosystem and more correctly improve its own predictive capabilities, thus becoming faster at displaying alerts and better at the discovery of previously archived video data. The future In conclusion, the future of these “predictables” wholly rests in the hands of the purchasing end-user. Our job is to help everyone understand the capabilities and theirs is to continue to make the investment so that the research perpetuates upon itself. Just think where we’d be if purchasers didn’t invest in the smartphone?
Edge devices (and edge computing) are the future. Although, this does seem a little cliché, it is the truth. The edge computing industry is growing as quickly as technology can support it and it looks like we will need it to. IoT Global Market The IoT (Internet of Things) industry alone will have put 15 billion new IoT devices into operation by the year 2020 according to a recent Forbes article titled, “10 Charts That Will Challenge Your Perspective of IoT’s growth”. IoT devices are not the only edge devices we have to deal with as the total number of connected edge devices includes the likes of devices like security devices, phones, sensors, retail sales devices, and industrial and home automation devices. The IoT (Internet of Things) industry alone will have put 15 billion new IoT devices into operation by the year 2020 The sheer number of devices begins to bring thoughts of possible security and bandwidth implications into perspective. The amount of data that will need to be passed and processed with all of these devices will be massive. There needs to be consideration taken by all business owners and automation engineers into how this amount of data and processing will be conducted. Ever-Expanding Edge Devices Market As the number of edge devices in the marketplace and their use among consumers and businesses rises, the need to be able to handle the data from all of these devices is no longer going to be suitable for central server architectures. We are talking about hundreds of billions and even trillions of devices. According to IHS Markit researchers’ study, there were 245 million CCTV cameras worldwide. One has to imagine there are at least 25% of that many access control devices (61.25 million devices) based on a $344 million market cap also calculated by IHS Markit’s researchers. If all the other edge devices mentioned earlier are considered then one can see that trying to route them all through servers for processing is going to start to become difficult if it hasn’t already, -which arguably it already has, as is evidenced by the popularity of cloud-based solutions amongst those businesses that already use a lot of edge devices or are processing a lot of information on a constant basis. Cloud Computing The question is whether cloud computing the most effective and efficient solution as the IoT industry grows The question is this; is cloud computing the most effective and efficient solution as the IoT industry grows and the amount of edge devices becomes so numerous? My belief is that it is not. Taking the example of a $399 USD device that is just larger than the size of a pack of cards and runs a CPU benchmarked at the same level as a mid-size desktop. This device has 8GB RAM and 64GB EMMC built-in and a GPU that can comfortably support a 4K signal at 60Hz with support for NVMe SSDs for add-on storage. This would have been unbelievable five years ago. As the price of edge computing goes down, which it has done in a dramatic way over the last 10 years (as can be seen with my recent purchase), the price to maintain a central server that can perform the processing required for all of the new devices being introduced to the world (due to the low cost of entry for edge device manufacturers) becomes more expensive. This introduces the guarantee that there will be a point where it will be less expensive for businesses, and consumers alike, to do the bulk of their processing at the edge as opposed to in central server architectures. Cloud computing is now being overtaken by edge computing, the method of processing data at the edge of the network in the devices themselves Edge Computing There are a plethora of articles discussing and detailing the opposition between the two sides of the computing technology coin, cloud computing and edge computing. The gist of it is that “cloud computing” was the hot new buzzword three years ago and is now being overtaken by “edge computing.” The truth is that cloud computing is a central server architecture hosted at someone else’s location. Edge computing is going to be a necessary development in the technology industry Edge computing is the method of processing data at the edge of the network (in the devices themselves) and allowing for less resources required at a central location. There is certainly a use case for both, however the shift to edge computing amongst the general public and small to mid-sized businesses will not be a surprise to those players, who have been paying attention. One article titled, “Next Big Thing In Cloud Computing Puts Amazon And Its Peers On The Edge” by Investor’s Business Daily takes the stance that edge computing is going to completely displace centralized cloud computing and even coins the phrase, “Cloud computing, decentralized” to explain edge computing. It speaks for the stance that most experts in technology seem to be taking, including Amazon Web Services’ VP of Technology, Marco Argenti according to the same article. We know that edge computing is going to be a necessary development in the technology industry, and it is happening as I write this, and quickly at that. Cost Efficiency Of Edge Processing As time goes on, the intersection between the prices of network bandwidth, edge processing and maintaining super powerful central servers will cause edge processing to be the most efficient and cost-effective way to maintain a scalable network in any environment, including datacenters. Owning a central server or utilizing edge computing become the better options As it currently stands, most residential users can only achieve a 1Gbps WAN (internet) connection, and small to medium-sized business can’t get much more but seem to get much less, based on my personal experience. When more than 1Gbps needs to be processed, cloud computing becomes very expensive at which point, owning a central server or utilizing edge computing become the better options. Then you look a total cost of ownership and when the cost of edge computing is less expensive than the cost of maintaining central server architectures, edge computing becomes the single best option. So, I’ll say it again, edge devices (and edge computing) are the future.
Paul Smith brings over 10 years of experience of managing sales teams in the IP video sector IndigoVision is delighted to announce the addition of Paul Smith, as Senior Vice President, United States, to its executive team. Paul, who was previously responsible as Vice President of Sales and Marketing at DVTel, comes with over 10 years experience of managing sales teams in the IP Video sector. "I have known Paul since 2004 and am delighted that he is joining us to lead our American sales team" commented Marcus Kneen, IndigoVision CEO, "Paul brings extensive sales leadership experience in the US market, particularly in our focused sectors. We have high ambitions to grow revenue significantly in the US and by bringing Paul on board, I believe we have the right person to lead the team." Paul Smith added: "I have been following IndigoVision for a number of years and have had high regard for their strong reputation for innovative products. The US market has shown an ever strengthening commitment to IP Video Security and I’m excited to join IndigoVision’s growing team in North America to help capture more of that business". Before joining DVTel, Paul was a founder and Chief Operating Officer of DSET Corporation, a leader in network management development software, and led annual sales revenue from start up to $50m. The addition of Paul to the US team follows on from several new recruits to the IndigoVision Sales and Support team in North America, where the IP Video Security market is expected to grow strongly in the coming years.
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