Dr. Rustom Kanga
With recently signed MoU, iOmniscient and Ajilon exhibited together for first time at 2015 Asia Pacific Cities Summit in Brisbane iOmniscient, the leader in providing intelligent analytics solutions, is proud to announce our partnership with Ajilon, a leading Australian IT consultancy firm. iOmniscient's smart solutions are offered hand-in-hand with Ajilon's excellence in deployment of such solutions to ensure successful implementation of Smart Video, Sound and Smell Analytics Systems. Improving Public Safety With Innovative Solutions Supported by Microsoft, the organizations are working together to develop solutions for safer and smarter communities by utilizing iOmniscient’s unique, patented and comprehensive analytics (video, sound and smell) offerings and Ajilon’s significant experience in this market, particularly their award-winning work in the law enforcement and justice, and public sector fields. Nichole Whyte, Microsoft Australia’s Public Safety & National Security Industry Market Development Manager said: “We were delighted to introduce these leading companies to each other with the unified mission of making Australian cities safer by improving public safety with their innovative solutions to reduce crime, decrease costs and improve operational effectiveness for our cities. Combining iOmniscient’s proven analytics solutions with Ajilon’s domain knowledge, expertise and agile delivery capability, provides a unique partnership to proactively address some of the everyday challenges faced by law enforcement and emergency responders in the Australian market to increase the safety of our citizens”. Deliver services and a safer environment to communities Commenting on the partnership, Dr. Rustom Kanga, CEO, iOmniscient said, “We are an Australian company and have installed our systems in over 40 countries. We are very excited to partner with Ajilon and use their wide expertise to deploy our Smart City Systems in Australia. “The integrated multi-sensor analytics (video, sound and smell) combined with our Automated Response capabilities has already helped major cities around the world become safer and more efficient. There are an incredible array of uses for the technology from optimizing traffic systems to detecting unsafe or suspicious behaviors in crowds; from recognizing criminals to keeping the city clean and graffiti free. Working with Ajilon we expect to share our international experience with Australian Cities that wish to become more efficient in the way they deliver services and a safer environment to their communities," he added. Managing Director at Ajilon, Ger Doyle, said "Our experience in developing systems that link multiple law enforcement and justice agencies to enhance their real-time communications and information sharing has shown us that utilizing technology has a real and significant impact on the ability of frontline officers and first responders to do their jobs more effectively and efficiently. By placing more ‘eyes’ and ‘ears’ on the streets and better informing the public in times of crisis we will have the ability to greatly increase the effectiveness of our defense, law enforcement, justice and local government safety initiatives. Our work across the Australian law enforcement and justice system has given us a great insight into what this market needs and we are confident we have the right partners to deliver that.” With recently signed Memorandum of Understandings, iOmniscient and Ajilon exhibited together for the first time at the 2015 Asia Pacific Cities Summit in Brisbane from 5 – 8 July.
Improvements in the technology have lowered – but not eliminated – concerns about false alarms False alarms have plagued the video analytics market since the beginning. Improvements in the technology have lowered – but not eliminated – concerns about false alarms. Companies providing video analytics systems say the question isn’t whether false alarms can be eliminated, but rather how they can be managed. “We’re still very far away from a day of zero false alarms,” says Zvika Ashani, chief technology officer (CTO), Agent Video Intelligence (Agent Vi). “Maybe someday when enough computing power is available and algorithms are at the level of sophistication of humans, but we’re still not there.” However, significant strides have been made in the last half dozen or so years, Ashani adds. Today when customers install the Agent Vi system and configure it, they can quickly reach a working state with mostly “true positives,” he says. In other words, false positives can be managed. The ability to achieve a workable level of false positives is “the difference between robust, high-end analytics and what you can get inside a camera at a low cost,” he adds. “People realize they can’t work with [in-camera analytics], so they come to us for a more reliable solution.” iOmniscient’s Nuisance Alarm Minimization System (NAMS) uses artificial intelligence to analyze what is or isn’t a threat – what’s a man or what’s a dog or what’s just a light changing? The system also helps to deal with the “noise” in a video image. “You never get to zero (false alarms), but if you reduce it several levels of magnitude, it’s tolerable,” says Dr. Rustom Kanga, CEO of iOmniscient. For example, if false alarms can be reduced from 20 a day to one every few days, it’s more manageable. "You never get to zero (false alarms), but if you reduce it several levels of magnitude, it’s tolerable" says Dr. Rustom Kanga, CEO of iOmniscient Kanga also contends there are times when false alarms are more tolerable because of the environment. For example, a face recognition analytic looking for shoplifters in the totally uncontrolled environment of a shopping mall might only be 70 percent accurate. However, identifying seven out of 10 in a crowd of 30,000 is better than 0 (and 3 out of 10 false positives is manageable). In markets that require perimeter protection and real-time alerting, there is still a lot of wariness about the success of video analytics, concedes Brian Lane, director of marketing, 3VR. In these markets, analytics need to be nearly 100 percent accurate for them to be useful; otherwise, security directors tire of all the false alarms and eventually turn the analytics off. In markets that require less accuracy, analytics are gaining ground, Lane says. For example, in business intelligence, analytics require less accuracy than, for example, identifying a former employee entering a building. Business intelligence relies on trends, not a single data point.
Retail has the greatest potential for analytics because it can be used both for security and for marketing & operations Video analytics isn’t just for security. In general, the ability to leverage data from video provides a new wealth of information and “intelligence” about all aspects of the business. The retail vertical is leading the way in reaping the benefits of video analytics beyond the security function. There are two reasons retailers have taken advantage of video analytics far more than other vertical markets. First, retailers generally face more theft than any other vertical market, says Brian Lane, director of marketing, 3VR. Analytics can help catch suspects by alerting in real-time. After the fact, analytics used for search purposes are far more effective to identify a theft than rewinding and fast-forwarding through video. Secondly, analytics can be used in retail to track customers, understand their age and gender, manage queue lines, know how long people dwell at an end cap, provide heat maps, etc. In short, retail has the greatest potential for analytics because it can be used both for security and for marketing and operations, says Lane. 3VR’s Customer Insights business is used by retailers, banks, food service, hospitality and other markets to track customers and understand buying habits. Through an interactive dashboard, retailers and others can harness 3VR analytics to provide business intelligence they can use to help increase sales or improve operations. Most of 3VR’s loss prevention and security products use some form of video analytics for forensic search capabilities, even if they only use a motion analytic. Using analytics for search greatly reduces the amount of time needed to find a suspect. Video analytics for POS & in-store operations management The latest security analytic at 3VR is aimed at any market where there is a point of sale or teller transaction. 3VR’s Customer Not Present analytic is integrated with the customer’s POS or teller system and requires a camera placed above the POS/teller. Each time a transaction takes place, 3VR’s VisionPoint VMS creates an event card with information about the transaction, such as items purchased, dollar amount, time/date, transaction number, account number, and other customizable data. The event card, when clicked-on, plays video of the event. If a transaction takes place without a customer present, the analytic will create a special event card marked as “Customer Not Present.” A manager can then search for all transactions in which a customer was not present to see if money is being stolen from the till, there are false returns, or other forms of employee theft. Analytics can be used in retail to track customers, understand their age and gender, manage queue lines and provide heat maps For the Customer Insights business, 3VR’s VisionPoint Queue Management software has added new features to detect average wait time, customer flow rate, and average queue size. There is also a customisable real-time dashboard that can notify store managers how many cashiers are needed now and how many cashiers will be needed in 30 minutes (or other customer time limit). For 3VR’s Customer Insights business, traffic is counted at the edge using 3VR’s People Counter, which results in far greater accuracy and less bandwidth, since video does not need to be sent to the server for processing. Only the metadata is sent, which requires very little bandwidth. Because of this, the data can be sent directly into the cloud where the data is parsed and available online at any time using a web browser to access 3VR’s VisionPoint Dashboard. The advantage to this method is that only the metadata is required.Analytics aids traffic and liability management in retail stores Other video analytics providers are also active in the retail environment. Agent Vi’s system can count people and measure foot traffic in a retail store, then aggregate the information and analyze the data. Even for retailers with multiple branches, Agent Vi provides a way to visualize traffic patterns in a store, to determine product placement, analyze how a change in store configuration might impact sales. Being able to respond immediately can help to promote return on investment (ROI) in the retail environment, especially related to managing liability. Dr. Rustom Kanga, CEO of iOmniscient, gives an example of someone who slips and falls in a shopping mall. “Now you can respond to the person immediately, ask if they’re OK, offer them a cup of tea,” says Kanga. “If somebody falls, and they think someone is taking care of them, they are much less likely to sue.” Responding immediately might mean the number of times people decide to sue would go down 80 percent, which reduces insurance costs. He notes the example of a shopping center owner with 200 malls that might have five slip-and-fall claims per week at each location, and many would just be “paid off” at $1,000 or $2,000 each. Responding quickly and with caring can lower the number to one claim per week, so it’s easy to do the math in terms of economic benefit – and ROI.
"The better the sensors, the better a human can see," agrees Dr Rustom Kanga, CEO of iOmniscient. "However high resolution cameras require more computing power, bandwidth and storage”. His company has therefore ensured they can do very comprehensive analytics with very low resolution cameras using higher resolution selectively only when it is necessary for automated recognition. For instance if a bag is abandoned in a very busy location where it is significantly obscured by passersby, iOmniscient's system can detect it with a very low resolution camera. Their system would automatically jump back to the start of the event to see who brought the bag into the scene. It would then focus in on the face of the person and extract that particular portion at high resolution (note that you do not need to see his shoes in high-res to recognize him) and then track him on different cameras till he is apprehended. This entire process can be automatic with no human intervention. This patented ability to extract, store and use high-res for important parts of the image such as faces, number plates and other things of interest while leaving the rest of the image in low resolution enables iOmniscient to reduce the storage and bandwidth requirements by around 90%. "Our system can dynamically look at an image in low resolution while still seeing the important features (eg faces and number plates) in high resolution", says Kanga, "This is how humans see. They have a wide field of view but only have a focussed view of a very small area. The difference in our system is that one can have multiple high-res views. So if there are 10 people and 5 cars in the scene the system can see all the faces and number plates in high-res while leaving all the rest of the image in low-res. Our customers can see that the saving in storage is so significant that it will usually pay for the intelligent software and more."
The better the sensors, the better the analytics Garbage in, garbage out. The familiar cliché is just as applicable to the area of video analytics as any other field of computing. You simply must have a high-quality image in order to achieve a high-functioning analytics system. The good news is that video cameras, which are the sensors in video analytics systems, are providing images that are better than ever, offering higher quality – and more data – for use by video analytics. For analytics that require a higher resolution to achieve superior results, megapixel cameras provide video that allows for better face recognition, clearer license plate numbers, reliable age and gender of customers, and other uses. These help prevent false positives and increase reliability in forensic searches, says Brian Lane, director of marketing, 3VR. When Ipsotek considers a video analytics-based solution, 50 percent of that solution is reliant on the selection of the appropriate sensor (camera). With the emerging technologies of thermal, megapixel and advances in camera processing, this half of the solution is more readily achieved, says Dr. Boghos Boghossian, CTO, Ipsotek. In some areas like face recognition, the illumination of the face in challenging environmental conditions is key to the success of the solution. Therefore, Ipsotek has been evaluating cutting edge camera technology provided by Ipsotek’s technology partners to assist consultants and solution partners to design successful solutions for every growing video analytics market. The better the sensors, the better the analytics, agrees Dr. Rustom Kanga, CEO of iOmniscient, and lower costs of thermal cameras make them a good choice. However, cameras that provide higher-resolution images require more computing power, bandwidth, and storage, which complicates their use with analytics. In general, the resolution is downgraded to the least resolution possible to detect the activity the analytics system is looking for. For analytics that require a higher resolution to achieve superior results, megapixel cameras provide video that allows for better face recognition, clearer licence plate numbers, reliable age and gender of customers, and other uses iOmniscient has a new technology called IQ Hawk that “pulls out of the image what is important,” says Kanga. It accesses higher resolution only for areas of interest in the photo – such as using higher resolution of a face or licenseplate viewed from a distance to enable facial or license plate recognition. The rest of the image is used at lower resolution. If there are three people in a video frame, IQ Hawk presents all three faces in high-res to enable identification. “With IQ Hawk, we can dynamically look at an image at high and low resolution, based on what’s important,” says Kanga. In terms of using higher-resolution cameras with analytics, Zvika Ashani, chief technology officer (CTO), Agent Video Intelligence (Agent Vi), says it is important to consider the “lowest common denominator” in terms of usable resolution. For example, a megapixel camera might have a clearer image in good sunlight; but at nighttime, the image will suffer, and could be worse than a low-resolution image. “More pixels don’t mean more detection quality,” he says. “The more pixels you have, the more processing power you need inside the camera.” Therefore, high-resolution images may even be “downscaled” to a lower resolution for analysis to minimize the amount of data to be managed. Higher resolution can also introduce additional noise in many cases. Some higher-resolution cameras have video analytics built in. DVTEL’s new ioimage HD Analytic IP cameras provide HD broadcast-quality IP video coupled with built-in military-grade analytics. These high-resolution, low-bandwidth cameras, available in both HD 1080p and 720p, are optimized for outdoor conditions and available with predictable storage. The cameras have enhanced low-light and no-light capabilities, high sensitivity, and true wide dynamic range. A new analytics feature provides a reduced false alarm rate for people standing upright, which benefits applications that don’t need sophisticated detection of camouflaged or crawling intruders. ioimage analytics now have improved detection distance, which allows for fewer cameras needed to cover the same area.
Video analytics allow users to automate the use of video and extract more value Almost anyone in the video analytics market will admit that the capabilities of the technology were initially oversold. The first generation of analytics simply didn’t work as promised, and an undercurrent of distrust of the technology in general still haunts the market. Ironically, video analytics capabilities have now matured into a robust and dependable option for a variety of applications. Suppliers are eager to get the word out. “Since video analytics were introduced to the security market, we have learned enough about customer needs and the technology to offer fully robust solutions that can provide significant value to the end customer,” says Maor Mishkin, director, Video Analytics Product Champion, DVTEL. DVTEL’s focus today is on the analytics that provide the most value such as people counting, loitering and directional, he adds. Processing power has increased to allow analytics to be pushed out to the edge, increasing use cases and reliability, adds Mishkin. DVTEL’s ioimage video analytics line is a comprehensive portfolio for outdoor perimeter protection. DVTEL’s HD cameras feature built-in analytics, enabling both edge-based and server-based flexibility. Serving a range of vertical markets, ioimage cameras help to increase the probability of detection and reduce the false alarm rate. Site View, a web-based remote live viewing and playback feature, enables operators to respond quickly in real-time and also investigate incidents after they happen. Ioimage IP analytics are available over H.264 video for the company’s HD and thermal cameras, or as a server-based video analytics solution (SVA) through DVTEL’s Latitude NVMS. DVTEL’s video analytics portfolio includes server-based and edge-based analytics to maximize the advantages of either approach, depending on the application. The smart cameras work independently or as a complement to perimeter intrusion detection sensors and other technologies. Since 2005, ioimage’s team has fine-tuned the advanced algorithm-based technology, which has increased market acceptance. The company has invested significantly in R&D and expanded system reliability and flexibility. Driving Value For The User Generally speaking, video analytics allow users to automate the use of video and extract more value. Without applying analytics, surveillance systems tend to create large amounts of video that isn’t doing anyone any good. It is captured and archived using terabytes of expensive storage, and then it’s deleted after a time, having provided no value. Agent Vi has identified three types of applications for video analytics that can drive value for the user: -- Real-Time Event Detection, allowing the user to transform the video system into a proactive detection system rather than a passive viewing system. -- Forensic Investigations, cutting down on the costs of investigations by making it easier to search video based on video analytics and other parameters. -- Business Analytics, providing data that would otherwise be impossible to collect, such as people-counting, and in-store behavior analysis in the retail environment. The only alternative would be to position a person at a store entrance or throughout the store to observe activity and count customers with a “clicker.” “These days, most of the customers are comfortable that this is actually going to work,” says Zvika Ashani, chief technology officer (CTO), Agent Video Intelligence (Agent Vi). “There’s still an education process. People have heard of video analytics, but they don’t really understand or know what the analytics are. It’s not what they saw on TV. Once their expectations are well defined, they can get a lot of benefit out of it.” DVTEL’s focus is on the analytics that provide the most value such as people counting, loitering and directional Meeting Diverse Operational Needs Verint offers multiple analytics for refining video into “actionable intelligence.” For situations that may be simple or complex, Verint Video Analytics offer a range of capabilities for security, surveillance and business applications. Security analytics are focused on opportunities to identify target individuals or vehicles, based on unique identifiers or simply discerning which video has people or vehicles within the frame of view. Surveillance analytics help in identifying crowding, loitering, or objects left behind. Business analytics seek to support pattern identification for retail merchandising and checkout excellence. Most customers are interested in some mix of these analytics to fit their diverse environments and operational needs. “The first wave of analytics met the harsh realities of customer environments and eroded confidence in all areas of the security advisory community, most notably among security consultants,” says Joshua Phillips, director of product marketing, video and situation intelligence solutions, Verint Systems Inc. Accuracy, processing load, and application guidelines have improved greatly since analytics first burst on the scene over 10 years ago, and it’s time for evolution to take its course, he adds. Video analytics can help a customer move toward a system that is easier or less expensive to operate, says Phillips. A video analytic detecting an anomaly can be programmed to set in motion a security response that has been pre-defined, such as a guard or officer dispatch to the specific area. Without the analytic, the security operations center is relying on the operator to have the appropriate camera view open at the right time, visually discern the breach, and be able to take action to initiate the response. If the problem is clearly understood, and the analytic rules are applied, the customer in this case gets the result they want – expedited response. This simple example may require an additional means of verifying the accuracy of the analytic detection, says Phillips. The customer may have other sensors available through other systems, or cameras, which if triggered could be paired with the video analytic to create an enhanced alarm, he says. Analytics In A Complex World iOmniscient specialises in video and other analytics in practical context situations – such as a crowded scene. For example, it’s easy to find a bag left behind in an empty room, but much more complex to identify that bag if there are 1,000 people in the scene. In face recognition applications, iOmniscient only requires 22 pixels between the eyes to identify a person (while some competitors require up to 300 pixels). Therefore, using iOmniscient, a standard camera can recognize people 50 meters away in an uncontrolled environment, says Dr. Rustom Kanga, CEO of iOmniscient. "Most customers don’t know what to ask for; they get things that don’t work. Where we have well-educated customers, we are the most successful. We spend time educating them about the technology in depth" “It’s a complex world, and we specialize in complex environments,” says Kanga. Many customers try to implement inexpensive systems that are “simple and trivial” to address situations that are complex, which is why many systems fail, he adds. Kanga points to the Boston bombing incident as an example of a situation where iOmniscient’s system would have been helpful. The system would have been able to identify the bag left behind (containing the explosives) amid the crowded scene. It also could have employed face recognition to identify the person who left the bomb, and it could have sent information in real-time to a nearby first responder. An automated response capability is a new development of the iOmniscient system. It locates the nearest police car or other first responder and sends an alert. The capability can reduce response time on street accidents from 25 minutes to under 5 minutes, Kanga says. The feature is also useful for applications when there is no central control room; if there are five security officers, the system can identify and notify the officer nearest the scene. Kanga attributes early problems among video analytics companies to the short attention spans of venture capitalists looking to make a quick profit on the emerging technology. “It took 10 years to develop the technology, so they didn’t have time to wait for it,” Kanga comments. “We raised our own money and built it. The technologies have taken a long time to build, but they are robust and are implemented in many places.” Video analytics keeps improving, based on improving algorithms, says Kanga. One improvement in the iOmniscient system is better people counting accuracy – now 99 percent versus the previous 95 percent. A requirement for successful implementation of video analytics is that customers ask clearly for what they want, says Kanga. If a requirement is to “find a bag,” a lower-cost system might be proposed. However, if the proposal is to “find the bag in a crowded scene if the view of the bag is obscured 50 percent of the time,” lower-cost systems would immediately be ruled out. “Customers are learning to ask for what they actually require,” says Kanga. “Most customers don’t know what to ask for; they get things that don’t work. Where we have well-educated customers, we are the most successful. We spend time educating them about the technology in depth. They become good customers. When implemented properly, the systems give you good results.” iOmniscient also combines video analytics with sound analysis and smell analysis. Sound analysis might include gun shots or people shouting. An example of smell analysis is a recent project in Asia, where the customer wanted to detect the threat of an electrical fire before it starts. The smell sensor alerts to the scent of plastic getting hot. (It’s actually a third-party sensor that enables analysis of a “chemical signature;” iOmniscient has adapted it.) An example of the benefit of multiple types of analysis can be seen in the case of a person falling down. A video analytics system can alert on the incident, and typically a security person would hurry to the scene to help the fallen person. However, if a sound analysis also indicates a gunshot at the same time the person falls down, the response would be very different.
The aviation and transportation industries are using video analytics to provide operational cost savings and performance enhancement Video analytics are now increasingly being used for the critical infrastructure, airports, transportation and city surveillance sectors, among other high-value markets. These markets need robust video analytics solutions that can be integrated into an overall security solution to deliver totally reliable results without any significant level of nuisance alerts. “We expect these markets to continue growing in hand with increasing advances in research and development for video analytics,” says Bill Flind, CEO, Ipsotek. Aviation and transportation industries are good examples where video analytics provide additional benefits including operational cost savings and performance enhancement, Flind says. Security personnel who were previously required to physically man certain areas can now be freed up to enhance security elsewhere on a site. Transportation and city surveillance sectors benefit from improved safety, compliance and business intelligence through early detection of potential hazards as they develop, triggering alerts for action before incidents occur. The market has been generally slow to adopt video analytics, says Flind. “We believe this is due to the historically disappointing results from many of the early technologies (that were over-promised and under-delivered),” he says. A good example is the many times when a “basic” system has been deployed onto what the customer had believed was a simple environment (e.g., perimeter fence of an airport or a power station), and then that system has become unusable because it generates hundreds (in some cases, thousands) of nuisance alarms each day. Flind adds: “The change that we are now seeing is that most potential customers now understand that a far more advanced technology will deliver an excellent solution into these environments – specifically, it is now widely understood that the power of a scenario-based solution like Ipsotek’s is required to deliver a robust solution even in these simple applications.” “What we are seeing now in the marketplace is that video analytics is being specified, but specified in a discerning and intelligent way, where the client and the client’s trusted advisors have an appreciation of the difference in the capability of the different technologies,” Flind says. 3VR’s VisionPoint VMS uses face, license plate, advanced object tracking, loitering and demographics analytics to search for suspects Ipsotek delivers scenario-based video analytics across a wide range of applications in the commercial and public sectors. Deployments include perimeter protection, intrusion detection, investigation and forensics, and the management of traffic, crowds and operations. The patented scenario-based approach creates an exact description of the target behavior, thereby giving dependable real alerts and dramatically reduced false alarms. Ipsotek has received “i-LIDS Primary” accreditation by the UK Home Office, signifying it is “deployable as the sole system for perimeter protection for sterile zone intrusion.” This recognition of quality and reliable video analytics provides assurance that high-security sites and projects will be monitored to the utmost level of protection. Installations include Transport for London (TfL) traffic management, London Eye, the O2 Arena, Network Rail, the Australian Parliament, plus various international airports and other critical buildings and infrastructures around the world. Meeting Stringent Customer Requirements Another video analytics provider, Agent Vi, is strong at the mid- to high-end of the market, where customer requirements are more stringent. Vertical markets include critical infrastructure and transportation hubs (including airports, seaports, train stations and railroad operations), the enterprise market, and retail. Agent Vi’s rules-based system includes some preconfigured types of objects the system can detect and behaviors it can analyze. The integrator can specify the analytics rules needed on a per-camera basis. For example, one camera might alert if a crowd forms and another might alert if a vehicle stops in the area. A user interface allows operators to set the rules, or they can rely on a systems integrator to set the system up. In the enterprise market, applications might include perimeter security, or detecting people where they shouldn’t be, or detecting tailgating through access control points. Analytics can address safety issues, such as detecting if something is blocking an emergency exit or a vehicle is parked in a no-loading zone. “We provide a fairly extensive tool box, and a lot of times we don’t know the exact configuration or application,” says Zvika Ashani, chief technology officer (CTO), Agent Video Intelligence (Agent Vi). “It’s so versatile.” Video analytics company iOmniscient is active is 30 vertical markets, including transportation (airports, railways, seaports), retail banking, hotels, casinos, the Secret Service, Defense Department, etc. The company is also active in Smart City applications, including Singapore and other locations in the Middle East and Asia. In the North American market, iOmniscient supplies the Chicago Transit Authority, the Mexico City airport, prisons in Vancouver, various oil and gas applications, universities, museums, etc. iOmniscient systems can operate centrally or at the edge, depending on the application. However, at the edge, the software is installed in a black box alongside the camera rather than in the camera because chips inside cameras do not have enough computing power. “When we say edge, we mean near the camera not in the camera,” says Dr. Rustom Kanga, CEO of iOmniscient. Consider Overall System Costs In assessing the costs of video analytics, the traditional practice of considering costs “per camera” is no longer relevant. Rather, the cost of the entire system should be considered, and also how it might be offset by cost savings achieved in other areas. Kanga contends one Smart City application was completed at zero incremental cost – the cost of the system was offset completely by a 70 to 80 percent reduction in storage, bandwidth and computing requirements. “The hardware is half the cost of the system, so if you can reduce it by 80 percent, the whole system can come in at zero incremental cost,” he says. “Our system is very cost-competitive.” "If you don’t have video analytics, you are wasting your money putting in cameras" “If you don’t have video analytics, you are wasting your money putting in cameras,” says Kanga. “If you have 1,000 cameras in a large environment, no one will sit and watch them. They are only useful after the event. Video analytics enables systems to become a useful tool to prevent incidents and to allow a fast response. With video analysis, video becomes a tool that you can use in real time.” Analytics are used to solve a specific problem, says Brian Lane, director of marketing, 3VR. For example, when there are bandwidth restraints, cameras can be set up to send only low-bandwidth video until the analytic detects a car or person. The analytic tells the camera to then send a high-resolution stream to the server for the duration of the event. This helps keep bandwidth and storage requirements low. 3VR’s Customer Insights business is used by retailers, banks, food service, hospitality and other markets to track customers and understand buying habits. Through an interactive dashboard, retailers and others can harness 3VR analytics to provide business intelligence they can use to help increase sales or improve operations. 3VR’s VisionPoint VMS loss prevention and security video management software (VMS) uses face, license plate, advanced object tracking, loitering and demographics analytics to search for suspects. The price of analytics is dropping, and many companies are lowering the barrier to entry by allowing customers to pay monthly or yearly, rather than all at once, says Lane. But, while implementing analytics has become easier, many integrators are not trained on how to set up and install analytics, leading to a frustrated customer. 3VR has specific tried-and-true methods for setting up cameras for analytics, and its integrators are trained on analytic implementation through online and on-site classes. 3VR provides the hardware for highly accurate people counting, and customers can pay for retail analytics monthly. Proactive Perimeter Security According to DVTEL, video analytics provide an ideal solution for proactive perimeter security in the critical infrastructure, transportation and commercial/industrial verticals, as well as general security for healthcare, gaming and other facilities. Going beyond the typical forensic video capabilities, analytics can help users catch criminals during a security event. The technology provides the best ratio of false alarm rates to probability of detection, as well as the most reliable and cost-effective solution for intrusion detection, when compared to legacy perimeter and fence sensors, typical surveillance devices and other video content analysis solutions. DVTEL’s Site Viewer eliminates the need to use a Video Management System to monitor and control remote sites. This makes it suitable for remote sites that cannot install a PC (such as power utility installations, solar farms, cellular and communication facilities, and construction sites) and that have limited network bandwidth. Today’s most effective security systems incorporate other sensors, including perimeter intrusion detection, alarms, remote video monitoring thermal imagery and video analytics, says Maor Mishkin, director, Video Analytics Product Champion, DVTEL. In today’s market, end users demand integrated systems that combine intelligent detection systems to specifically fit their business and risk profile, he adds. By streamlining decision-making and even automating some protocols, video analytics enable organizations to respond more quickly to events By streamlining decision-making and even automating some protocols, video analytics enable organizations to respond more quickly to events, using fewer personnel than would be required with traditional surveillance systems. In addition, ioimage video analytics enable more accurate detection and fewer false alarms by reliably differentiating between legitimate threats and other movement, such as tree branches blowing in the wind. Perhaps most compelling, video analytics has the potential to decrease storage costs for many users, since they are able to record at lower resolution until the system detects suspicious movement. Tight Integration at the Edge High-profile perimeter security breaches at critical sites have underscored the risks associated with physical security breaches and the potentially disastrous consequences. Now organizations – some as a result of pending regulations such as NERC CIP for utilities – are seeking reliable and cost-effective solutions using video analytics to detect intruders and send alarms about security incidents in real time. SightLogix SightSensors are smart thermal cameras with embedded video analytics powered by a high degree of video processing. By tightly integrating the imager, analytics and video processing, SightSensors are able to deliver accurate detection in all weather, climates, and conditions. Some verticals adopting video analytics for outdoor intrusion detection include electrical utilities, specifically substations; airports and other transportation organizations, such as bridges and rail applications; datacenters; and ports. These sites require protection and 24/7 detection for large, open areas that are difficult to patrol. Video analytics with thermal detection cameras combine detection with video verification in a single solution, allowing for a fast and precise response. Beyond security, video analytics combined with outdoor thermal cameras opens up a new world of understanding, from early detection scenarios to looking at behavior that increases operational efficiency.