Today’s intelligently-built video solutions provide the integrator with an easy-to-track cost savings over the lifespan of the project
Strategic management of costs is important when considering video storage systems

Costs are at issue when considering any component of a video system. Strategic management of costs is especially important when considering video storage systems because storage accounts for such a large cost component of networked systems.

Gartner’s Total Cost of Ownership (TCO)

As enterprise products begin to dominate the video storage market, more attention needs to be addressed to Gartner’s Total Cost of Ownership (TCO), says Jeff Burgess, president and CEO of BCDVideo. This concept takes it beyond the initial purchase costs, and also factors in management and support, the opportunity cost of downtime, and other productivity losses. “It’s especially true these days as more and more, video data is being analysed for business purposes,” says Burgess. “After all, they are counting on it to run their project. The video doesn’t get recorded if the recorder is not working or continually freezing up.”

‘Cost of power, pipe, and people’

Burgess urges integrators and end users to ask themselves: What is the video recorder really costing me over the course of the five-year project? It’s likely a racked solution, so in IT terminology that “costs power, pipe, and people.”

“Take the people out of the mix,” Burgess says. “You should not need to roll a truck to the site every time there is an issue. Especially after a warranty service call. The system should automatically accept the replacement drive and bring the data over to it within the existing RAID settings, without the integrator’s on-site presence needed. The integrator really needs to look under the hood to see what else the system can provide other than simply being a storage box or a box of parts from multiple brands, not meant to work together.”

Finding the right balance of control, performance, scalability and availability to keep up with and effectively exploit the surveillance data deluge allows organisations to avoid painful and costly upgrades

Today’s intelligently-built video solutions provide the integrator with an easy-to-track cost savings over the lifespan of the project versus buying boxes on the cheap, says Burgess. “Today’s savvy integrator realises it doesn’t take many truck rolls to lose all those front-end savings, which are now eating away at their profits.”

Camera with SD cards

Another cost factor is to focus more on the utilisation of the SD cards in the camera. Utilising cards within the cameras creates a very inexpensive way of adding redundancy to a solution, says Burgess, who notes that most VMS companies can pull the video from the SD cards should there be an interruption in the network or at the head end.

Educate yourself

Veracity recommends asking a lot of questions to guide system design and minimise costs. What retention time do you need? What would you wish? Do you want to relay on video motion detection, or would you prefer to find a system that allows you to record low frame rate 24/7 and then increase frame rate on motion? Does your storage choice allow you to use low cost drives? Does it use a huge amount of power? Is it overly complex? “Educate yourself about the choices,” says Scott Sereboff, CEO of Veracity USA. “Look around. Consider the alternatives. You have a choice that does not include a RAID storage system with an $800-plus per terabyte price tag.”

"Starting with a solution that takes minimal install and tuning, and is proven to scale well beyond current needs, future proofs the system for the short- and long-term for the customer and the integrator", says Jeff Adams, director of sales, surveillance solutions, DDN Storage solutions

Balancing performance, capacity and availability

Finding the right balance of control, performance, scalability and availability to keep up with and effectively exploit the surveillance data deluge allows organisations to avoid painful and costly upgrades, says Jeff Adams, director of sales, surveillance solutions, DataDirects Network (DDN) Storage solutions. “Performance needs to scale to allow for increasingly demanding playback and/or analytics features. Capacity needs to scale non-disruptively as cameras are added, while resolutions and retention periods may increase over time. Availability at scale is tricky; something as simple as slow rebuild times becomes critical in larger systems – endangering availability and system data integrity.”

In addition to new installations, DDN does a healthy business in replacing underpowered infrastructures that deliver on the initial requirements but fail on scaling, says Adams. The most frequent culprits when a video surveillance site fails and needs a significant replacement/upgrade include: single controller architectures, silent data corruption, data loss from secondary failures during drive rebuilds, performance impact of rebuilds, alternates to RAID6 data protection, and lack of experience scaling into the petabyte or multi-petabyte range.

Many mid-range video surveillance storage “solutions” take more than a week to install and tune, and cannot handle significant scale, adds Adams. For end users, this limits the ability to add cameras, capacity and demand (playback, analytics and system consolidation). For integrators, this means a lot of “care and feeding,” and frequent completion delays up front, as well as increased support considerations throughout the life of the project. “Starting with a solution that takes minimal install and tuning, and is proven to scale well beyond current needs, future proofs the system for the short- and long-term for the customer and the integrator,” says Adams. It also keeps costs low.

Download PDF version Download PDF version

In case you missed it

The EU called for a ban on police use of facial recognition but not commercial use. Why?
The EU called for a ban on police use of facial recognition but not commercial use. Why?

Recently, the European Parliament called for a ban on police use of facial recognition. In the US, too, some cities have restricted police use of facial recognition. The first question that comes to mind is - why ban police from using technology that is allowed to private companies? Point of difference The key difference between the way police use facial recognition and the way commercial facial recognition products work is that: The police get a picture of a suspect from a crime scene and want to find out: "Who is the person in the picture?" That requires as wide a database as possible. Optimally - photos and identities of all the people in the world. Commercial facial recognition products such as those used by supermarkets, football stadiums, or casinos answer different questions: "Is the person in the picture on the employees' list? Is the person in the picture on a watch-list of known shoplifters?" To answer these questions doesn't require a broad database but rather a defined list of employees or a watch-list of specific people against whom there is an arrest warrant or a restraining order. Use of facial recognition AnyVision helps organisations leverage facial recognition ethically to identify known persons of interest "Facial Recognition Apps Should Be Provided to the Police with an Empty Database". This is exactly the subject of the open letter sent by AnyVision, to the British Biometrics and Surveillance Camera Commissioner, Prof. Fraser Sampson, titled: "Facial Recognition Apps Should Be Provided to the Police with an Empty Database". AnyVision recently raised $235M from Softbank and another leading VCs is a visual AI platform company that helps organisations across the globe leverage facial recognition ethically to identify known persons of interest, including shoplifters, felons, and security threats. Ethical use of facial recognition AnyVision CEO Avi Golan wrote, "The ethical use of facial recognition is a thorny one and requires a nuanced discussion. Part of that discussion has to explain how facial recognition works, but, just as important, the discussion must also involve how the technology is used by police departments and what checks and balances are built into their processes.” “We recommend building their watchlists from the ground up based on known felons, persons of interest, and missing persons. Some facial recognition solution providers have scrapped billions of photos and identities of people from social networks, usually without their consent." "Unfortunately, this method of facial recognition has justifiably angered privacy groups and data protection agencies around the globe and damaged the public trust in accuracy and reliability of facial recognition systems.” Preventing invasion of citizen’s privacy We believe an unjustified invasion of citizens' privacy can be prevented, false arrests can be reduced" “We believe that lists of suspects should be limited and justified. In this way, unjustified invasion of citizens' privacy can be prevented, false arrests can be reduced and public confidence in technology can be increased.” Golan added: "AnyVision is willing to share its industry insights and best practices from our vast research experience with leading global players, including name-brand retailers, global hospitality and entertainment companies, and law enforcement agencies from around the world.” Balancing public order and crime prevention “If the regulations set forth by Surveillance Camera Code of Practice are committed to the principles outlined above, then law enforcement agencies can strike the right balance between the need to maintain public order and prevent crime with the rights of every person to privacy and non-discrimination before the law." Recently Clearview AI CEO told Wired; the company has scraped 10 billion photos from the web - 3 times more than was previously known.

Dahua Technology shows how intelligent cameras enhance safety in nursing homes
Dahua Technology shows how intelligent cameras enhance safety in nursing homes

Patient falls in nursing homes are a serious problem. In the United States, for example, around 1,800 elderly people, living in nursing facilities, die each year from injuries related to falls, according to the Nursing Home Abuse Center. Those patients who survive their injuries often have a reduced quality of life and suffer some form of permanent disability. Rise in nursing home patient falls Figures show that between 50% and 75% of nursing home residents suffer falls each year, twice the chances of falling when compared to seniors who live in a regular residential community. It has been a prevalent challenge to detect falls quickly and effectively, especially when these occur in residents’ bedrooms. In the United Kingdom, the Care Quality Commission has recognised that the use of CCTV may be one of the best ways to ensure safety and quality of care. However, using video surveillance also brings into question other security issues, such as privacy and data protection. Dahua’s WizMind technologies WizMind embraces human-based AI (Artificial Intelligence), for a whole host of applications across verticals This is where Dahua Technology’s WizMind technologies come into play. WizMind embraces human-based AI (Artificial Intelligence), for a whole host of applications across verticals, such as retail, energy, finance, transportation and of course, health and social care. Specific to the health and social care sector are deep-learning algorithms, to protect the privacy of the face and body in real-time, and stereo analysis, which combines dual-lens cameras with three-dimensional scene analysis, in order to detect sudden physical movement, such as falls. Stereo video analysis The growth of AI applications has enabled the greater availability of 3D scene analysis solutions, thereby enabling objects and people to be analysed in three dimensions. Dahua Technology’s stereo analysis uses two lenses, in order to capture separate images of the same scene. It then computes the ‘optical parallax’ of spatial points in the two images, providing 3D information of the scene. The stereo vision mimics the depth of view that comes from humans having two eyes, known as binocular vision. Combined with deep-learning algorithm Combined with a deep-learning algorithm, stereo analysis can recognise event patterns, such as falls and other movement-based behaviours, such as people approaching, the detection of an abnormal number of people in an area, and violent behaviour. In nursing and care homes, stereo analysis cameras can help staff monitor residents, in case of emergency and respond to residents’ problems, such as tripping and falls. The cameras can view all three dimensions of subjects and together with its deep-learning algorithm, can immediately alert staff to any unusual or sudden movement, such as would be evident in a fall. Cameras in communal areas and bedrooms With cameras situated both in communal areas and in bedrooms, the staff is able to respond quickly to incidents With cameras situated both in communal areas and in bedrooms, the staff is able to respond quickly to incidents, which may otherwise stay undiscovered for hours. An example of such a scenario is a nursing home in Singapore, which has a capacity of around 400 beds and is divided into 14 separate living environments, with each designed to be a home-like living area. Dahua cameras with intelligent fall detection technology Dahua cameras, such as IPC-HDW8341X-BV-3D with intelligent fall detection technology were installed, including the provision of 167 stereo analysis cameras inside each bedroom. These trigger an alarm, in the case of incidents, such as a fall, allowing immediate response by staff. Not only does this enhance the well-being and safety of residents, but it also can reduce the nursing home’s labour costs. In addition, Stereo Analysis can also be applied in other application scenarios. An underground unmanned bicycle parking garage in Amsterdam, for instance, has installed Dahua Technology’s behaviour analysis cameras, to detect abnormal events and prevent accidents, such as people tripping and falling, or suspicious individuals wandering around the area. Privacy Protection 2.0 technology While monitoring their situation inside the nursing home, Dahua also adopts Privacy Protection 2.0 technology that features masking of human face and body, to protect the residents’ privacy. It involves the restriction of what can be seen in video images and applies equally to live, and recorded images. Digital masking takes place on the front-end device (e.g. network camera). Dahua’s Privacy Protection 2.0 provides real-time occlusion of the body and face and enables users to access recorded videos, without having to overlay faces with mosaic masks. It also offers additional occlusion options, such as irregular polygons, mosaics and coloured blocks, and allows code exporting based on specified targets, ensuring the privacy of subjects. Privacy and security in evidence collection Stereo video analysis and privacy protection come into their own in nursing homes and healthcare facilities Benefits offered include non-pixelated human targets, allowing for privacy and security in evidence collection. The technology also allows for face and human attributes analysis, without breaching people’s privacy, making it ideal for nursing homes. Stereo video analysis and privacy protection come into their own in nursing homes and healthcare facilities. It allows the close monitoring of residents or patients to help ensure their well-being and safety, while at the same time protecting the privacy of often vulnerable individuals. Dahua TechMonth As part of the Dahua TechMonth, this blog highlights how Dahua’s stereo analysis technology, combined with privacy protection, can provide a valuable tool to help staff respond to incidents quickly and efficiently, including falls, without infringing on people’s data protection rights. In the next blog, Dahua Technology will be discussing the WizMind application of human metadata, enabling users to maximise situational awareness and analysis of events. 

Eagle Eye’s Uncanny Vision deal highlights value of combining AI and cloud
Eagle Eye’s Uncanny Vision deal highlights value of combining AI and cloud

The trend of video customers moving to the cloud has reached a tipping point. At the same time, artificial intelligence (AI) is being adopted on a massive scale. Combining the two trends adds a higher level of value than either component individually. Merging the power of AI and the cloud is a driving force behind cloud surveillance company Eagle Eye Networks’ acquisition of Uncanny Vision, an AI and video analytics company headquartered in Bangalore, India. Expensive AI resources Cloud systems empower customers to leverage AI without having to install and program complicated and expensive hardware, in effect stripping away the barriers to entry that customers face when seeking to embrace AI. The cloud also enables customers to share expensive AI resources. One of the key components is ease of deployment – click, click and turn on the AI for any camera" Simplicity of implementation is crucial to the combined value proposition of Eagle Eye Networks and Uncanny Vision. “One of the key components is ease of deployment – click, click and turn on the AI for any camera (in a cloud system),” says Dean Drako, Eagle Eye Networks CEO. There is also a benefit of having AI systems networked, enabling 25 banks to perform facial recognition of customers from a single cloud-based system, he adds. A transition is also under way in the perception of AI. Video surveillance applications While previously it was seen as an add-on to surveillance systems, now it is seen as a very desirable feature on any system. “Centralised management of the cloud benefits the AI database,” says Drako. “In a project built around licence plate recognition (LPR), for example, all the data goes up to the cloud into a single database, and the customer can get a mobile view of everything going on across the world. You can’t do that without the cloud. And AI for LPR is more accurate.” Uncanny Vision’s targeted focus on AI for video surveillance applications was one factor that attracted Eagle Eye Networks to make the acquisition, says Drako. In contrast, some other companies have embraced broader applications of video AI. Uncanny Vision also has more customers using their system in real-world applications than competitors. Finally, the acquisition will help to expand Eagle Eye Networks’ presence in the LPR market, where Uncanny Vision is especially strong. Improving business operations The 60 employees at Uncanny Vision are mostly engineers and programmers Uncanny Vision’s deep learning algorithms enable recognition, identification, and prediction, improving business operations, customer service, and site safety. Applications include smart parking, retail, smart cities, ATM monitoring, worker safety and perimeter security. The 60 employees at Uncanny Vision are mostly engineers and programmers. “These guys understand how to translate AI algorithms to run very efficiently on various types of hardware,” says Drako. “They optimise how they get the code to run so we can implement in the cloud cost-effectively. They do it at a modest cost to make it more accessible. They understand how to deploy software for high performance on low-cost hardware.” For Uncanny Vision, the new ownership provides more reach. “We have a huge channel and a huge brand,” says Drako. “They are strong technical guys who need a sales and solution channel.” Video analytics solutions Even in light of the acquisition, Eagle Eye Networks will continue to provide a selection of third-party AI and video analytics solutions to customers. Use of AI and video analytics is specific to the application and business needs of each customer. Use of AI and video analytics is specific to the application and business needs of each customer In addition to AI functionality, systems need a ‘business logic’ component that drives how that capability is integrated into a system. System needs vary widely by vertical market, and many third-party vendors are focused on a specific vertical and how AI can benefit that market. Recurring monthly revenue “Third parties can provide analytics and the business logic, which is different for a factory, an office building or for a drive-thru restaurant,” says Drako. “The market is looking for many solutions, and one company couldn’t own a majority of them.” To ensure flexibility, Eagle Eye Networks will accommodate third party solutions, deploy their own analytics, or leverage analytics embedded in cameras. For Eagle Eye Networks’ dealer and integrator customers, the expansion into AI presents a new opportunity for recurring monthly revenue (RMR) and provides greater value to customers. Drako says the impact of the acquisition will be global as AI applications grow in popularity worldwide.