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Video Surveillance-as-a-Service (VSaaS) and Access-Control-as-a-Service (ACaaS) have continued their strong growth into 2018 as AI Analytics are now being introduced with greater effectiveness. Demand for Analytics will be more pronounced in VSaaS, and this is the focus of our following article.
The main drivers up to 2017 have been initiated by the supply side spending more time, effort and investment into providing VSaaS and ACaaS services. Technology has gradually overcome many limitations and reduced service costs. At the same time, suppliers are winning over system integrators to adopt cloud services and this has also provided a significant boost to growth. Another contributing factor for product manufacturers is that the cloud services route could help to alleviate some of the pressure on margins, as leading Chinese suppliers continue to lower prices.
The second is that the demand side, the existing owners of video surveillance and access control systems, are now automatically investigating “as-a-service” options when they are looking to upgrade their operations. More customers will come into this category over the next 5 years.
Persuading end users to go for VSaaS and ACaaS has taken much longer than analysts predicted but we have now reached the stage where this option is being seriously investigated and services is now much improved.
One financial institution that specializes in investing in the physical security industry, Capital One, is very bullish about the business opportunities to be had in VsaaS and ACaaS. In 2016 they carried out a survey of security system professionals that showed that 85% of respondents expect improved financial performance through Video monitoring and Video Surveillance-as-a-service (VSaaS).
VSaaS was launched in the late 2000’s with predictions that within 5 years it would be a multi-billion market. It failed to deliver against this date. We estimate that the global market size for VSaaS in 2016 was approximately $600m. Most forecasts predict that it will reach $1Bn by 2020 growing at a CAGR of approximately 14% and we can expect it to grow well into the next decade.
So why has VSaaS so far failed to meet market expectations? The first is upstream bandwidth availability and the relative cost of centralized storage. However from the above figures it can seen that some of the roadblocks to VSaaS are gradually being removed. Bandwidth prices are falling, and peak speeds have been increasing, making VSaaS potentially more viable in a larger range of applications.
A bigger help to VSaaS will be the emergence of Smart CODECs and the introduction of H.265. These technologies can help reduce the amount of bandwidth the cameras consume, potentially overcoming bandwidth costs and data cap barriers. This year has seen a major growth in the adoption of Smart Codecs.
The first major plus is that VSaaS is continually monitoring. Because of this systems are quickly fixed in the event of failure, so reliability should improve. This ensures that the quality of video is satisfactory for forensic purposes and that all aspects of usability, like how do I retrieve the video and share it, are taken care of.
Whilst these value propositions are more likely to be critical in large prestige buildings where the consequences of failure would be very costly and detrimental to the operation in them. However some reports show a high rate of resistance here because they have already invested significant sums of money in their own equipment and have the staff on board to operate it. When this equipment becomes outdated (approx. five years in the fast moving video surveillance business) they should become prime candidates to move over to VSaaS.
Most followers of VSaaS believe that the small and medium building sector offers the most attractive proposition for buyers because they would rather pay a monthly fee for the service than the alternative, which is to buy the system and take one big financial hit.
Cloud based services for Video Analytics looks to fit well at both extremes of the range of complexity, with owners / occupiers of small buildings wanting to pay an annual charge with no responsibility to maintain the system and at the top end of the enterprise sector similarly not wanting to take on specialist and expensive staff to operate and maintain the system.
No doubt selling Video Analytics direct to end users will be the major route to market but the complexity of selling this solution does favour VSaaS particularly at this stage of development.
The big advantage of services like Amazon Kinesis Video Stream (KVS) are that they create and maintains ready-to-use video ingestion systems, in which all the infrastructure necessary to manage video streams is already in place. Users do not need to worry about configuration, scalability, available storage and data security as the number of streams grows; instead, they can focus on buying in or building their own artificial intelligence (AI) or machine learning (ML) applications to analyze video data.
KVS can be applied to many different scenarios. For example, in a smart home setting the user can stream videos from a baby monitor to AWS for simple playback on a smartphone or some more advanced tasks such as facial recognition. In a retail store where there are multiple security cameras installed, the owner could stream footage captured in real time to AWS and then analyze live feeds using video analytics applications to understand consumer behavior.
While AWS offers its scalable and cost-effective KVS service to end users, it has also established the AWS Partner Network (APN) program. The program is designed to help customers identify companies with machine learning competency and expertise to support integration and deployment of various solutions. The designation recognizes members who provide solutions that help organizations solve their data challenges and enhance machine learning applications. Both Agent Vi and Veritone are APN partners.
Veritone has developed aiWARE, an AI operating system that leverages AI-based cognitive computing, including facial recognition, transcription, geolocation and sentiment detection to analyze unstructured audio and video data, such as TV broadcasts and surveillance footage.
innoVi, Agent Vi’s cloud-based video analytics software as a service (SaaS), is implemented by deep learning technology and other advanced algorithms that enable detection accuracy. Able to distinguish between people, vehicles and static objects, innoVi can not only detect security incidents in real time but also perform analysis that transforms security cameras into intelligent devices.
With the integration of these systems and Amazon KVS, users are free from the trouble of managing a huge amount of video data while enjoying the advantage of making every frame of video searchable for objects, faces, keywords and more. There are other companies forming strategic alliances to offer similar services because the cloud provides great scalability to process video without having to add capabilities or hardware on-site.
This article is based on information taken from our annual report – The Physical Security Business 2017 to 2022 and our forthcoming report – The Global Market for Intelligent Video Analytics which will be published in late Q2 2018.