Demand for professional video surveillance cameras has been growing quickly and is forecast to continue growing in 2018. It is estimated that less than 10 million surveillance cameras were shipped globally in 2006, which grew to over 100 million in 2016, and is forecast to make over 130 million during 2018.
Despite this increase in demand, the average price of cameras and other video surveillance equipment will continue to fall quickly. As a result, IHS Markit forecasts that in terms of US dollar revenues the world market for video surveillance equipment will grow at an annual rate of less than 6% in 2018.
It will be challenging for vendors to continue to grow revenues and margins, but there will be opportunities for well-placed vendors. For example, both the South East Asian and Indian markets are forecast to grow at higher than average rates. There is also great potential for the next generation of products powered by technologies like deep learning and cloud computing.
So, what will be the big stories during 2018? Deep learning, GDPR compliance and drone detection technologies are just some of the trends discussed in this eighth annual trends IHS white paper. The following articles are designed to provide some guidance on the top trends for 2018 in the video surveillance industry.
Josh Woodhouse
Video Surveillance Fault Tolerance
The ability of a video surveillance system to tolerate faults while maintaining operation with minimal disruption is seldom discussed. No one likes to plan for the worst, yet even though the video surveillance industry is increasingly utilizing enterprise grade IT technology, many video surveillance systems still have fairly limited fault tolerance and failover capability. When compared with what is common in the IT industry, the video surveillance industry is often thought of as having a relaxed approach to many aspects of failover and redundancy. However, as the multiple uses and perceived value of video surveillance data are increasing we may see increased demands for greater failover, redundancy and backups from end-users.
Surveillance systems which do have a high level of fault tolerance tend to focus on mitigating failure after video is captured by a surveillance camera. This is due to a higher impact of failure from the ‘back-end’ rather than at an individual camera. For example, if an individual camera fails, the impact is smaller than if the recording server or storage system fails which may cause the loss of all past and future video recordings.
As video surveillance is being leveraged for multiple uses beyond just security the perceived value of video surveillance data is increasing. This value can sometimes be measured with incurred costs if data becomes unavailable. This may be a direct cost (e.g., a fine from an authority) or an indirect cost (e.g., lack of data for business operations, hampering productivity). Cost analysis can form the basis for evaluating potential investment into additional levels of failover, redundancy and backups for video surveillance systems such as:
Additional hardware costs (e.g., redundant servers/ storage).
Additional software costs (e.g., virtualization or mirroring software licenses).
An interesting example of where we’ve observed increased levels of failover and redundancy is in legalized marijuana supply in the USA. Here, facility owners are investing more in higher levels of failover in their surveillance systems to ensure they do not fall foul of stringent legislation in some states. This legislation focuses on the ability to retain and produce past video recordings when demanded by authorities. Failure to comply can have dire consequences including loss of business licenses. In other industries, for example manufacturing, as video becomes more ingrained in business operations we are likely to see similar patterns of investment for greater failover in video surveillance systems.
IHS Analyses
The A to I of Video Surveillance Terminology By – Jon Cropley
Big Differences between the Chinese Market and the Rest of the World By – Jon Cropley
General Data Protection Regulation (GDPR) By – Josh Woodhouse
Forensic Video Analytics as a Service By – Josh Woodhouse
The Evolution of Deep Learning in Video Surveillance By – Monica Wang
