Software packages across the Physical Security industry are numerous covering many different functions; Many overlapping each other causing confusion for end users and resulting in a fragmented business.
There is a need to rationalize this business in order to meet the needs of clients, and fit into the World of the Internet of Things (IoT) and Artificial Intelligence (AI), ultimately delivering the high growth that is forecast.
Whilst software has made a significant contribution to the growth of the Physical Security business over the last 10 years it is a relatively small part of the business accounting for no more than 10% of the total annual value, but growing its market share every year.
Software has been delivered through security hardware manufactures for the most part and software companies that have specialized in the physical security business, unlike other Building Automation Services (BAS) where software companies external to the business have had a major influence on the business and shaping its future. However as our latest report shows this is changing as deep learning and video analytics is being introduced into initially the video surveillance industry with the major thrust coming through independent specialist software companies.
Software packages that extend across the business include Video Management Software (VMS), Intelligent Video Software, Physical Identity Access Management (PIAM), Access Control Management Software, Physical Security Information Management (PSIM), which is now often termed Converged Security and Information Management (CISM). In addition there are software platforms to integrate across all 3 branches of the physical security business and beyond into other BAS services.
Whilst almost all of these packages overlap one another, there are few suppliers that offer more than one service. There has been some rationalization over the last 5 years within these services and more importantly between them, particularly PIAM and Access Control Management and VMS and Intelligent Video through merger and acquisition and strategic alliance.
Physical Identity Access Management (PIAM) is a software product that can weld together Physical Access Management with Identity Management and makes the system much more secure, delivering many other valuable features. Now that IP is becoming standard in Access Control it’s relatively simple to link these services together. Almost all Fortunes top 500 have installed PIAM systems. The key benefit from PIAM solutions is operational cost reduction that can be delivered through this platform, providing a bridge between the disparate systems, without stripping out and starting again.
However connectivity between PIAM and Physical Access Control in the mainstream market has been a relatively slow process but developments this year are moving this along. HID Global one of the leading PIAM suppliers and acquired Mercury Security this year. This strategic acquisition will put them in a strong position to provide this service to the mainstream business.
Physical Security Information Management (PISM) is a category of software that provides a platform and applications created by middleware developers, designed to integrate multiple unconnected security applications and devices and control them through one comprehensive user interface.
A decade ago, PSIM was the ‘next big thing’, but demand has been restricted to large complex sites, most in public ownership where safety is critical. Whilst the cost and complexity of installing a PSIM has improved it is still too high for most commercial buildings and for this reason PSIM will remain a niche offering. Given time the IoT will deliver a much more eloquent solution and a cheaper one. But the push to go for Smart Cities right across the globe could open up a window of opportunity for PSIM to extend its life.
However much of the security industry believe the principal of joining all the different services through a top-end software solution through bespoke software is proving to be fragile causing high maintenance and does not deliver all the intelligence that is available. Big Data and IoT could solve these problems, be a better proposition but its probably 3 years away from commercial acceptance.
In the last 2 years we have witnessed some significant changes in the structure and product performance of the physical security software business and much of this has come through merger and acquisition. In particular PIAM, Access Control Software and VMS have been in the top 5 places when benchmarked on number of acquisitions and this year 5 deals involved the acquisition of Artificial Intelligence Software companies.
While deep learning is rapidly becoming the new star of video analytics actual commercial implementations are rare and there are only a few commercial products with deep learning that are available today in the field of video surveillance.
Machine learning encompasses a range of algorithms to enable a trend or pattern recognition over time. It can be supervised, i.e. with expert training, or unsupervised, with no inputs from humans. Deep learning is a subset of machine learning and has applications in today’s world, from speech recognition to image recognition to even biomedical informatics. In general, one can think of it as a cascade, many layers of nonlinear processing units for feature extraction and transformation. Each successive layer, uses the output from the previous layer as input. Deep learning when perfected should be much more accurate tool than traditional video analytics.
Neural networks are loosely designed based on the biology of our brain. It tries to simulate how humans think. All the interconnects between the neurons, where the neurons can connect to any other neurons within certain physical distance. So artificial neural networks have several layers of connections and directions of data propagations. Their applications include pattern analysis, classification etc. which are all based on the learning of multiple layers of features or representations of data. The higher level features are divided from the lower layer features to form hierarchical representations.
Nvidia and Neurala are relatively new starts chip manufacturers developing deep neural network frameworks designed for use in low-power GPU’s. Their aim was to give devices like drones, security cameras, and consumer electronics some decision-making capabilities previously unavailable in these categories due to size, cost, or power restraints.
Motorola is among Neurala’s investors and has invested an undisclosed sum in Neurala’s $14M Series A as part of the partnership between the two companies. Motorola’s Si500 Advanced Bodycam was designed to take advantage of AI/DNN technologies, enabling Neurala’s software to run within their bodycam.
While Neurala also offers edge-based analytics capabilities for object classification, a number of manufacturers such as Avigilon, Axis Communications, Hanwha, Hikvision, and others, have already begun releasing products with edge-based analytics, making Neurala’s offering in this regard of lower interest for the surveillance market.
The analytics market today is processed in the cloud but it will move to the edge of the network as advances in compute capabilities and lower cost of communications hardware make it cost effective to apply analytics closer to where data is generated or collected. Various predictions forecasts that the volume of data captured by IoT connected devices will grow nearly six-fold and top over 2,000 exabytes (2.0 zettabytes) in 2021.
Having previously had its fingers burned, the security industry in general is a little skeptical that new deep learning products are as practical and robust as manufacturers say they are. However analytics in general is becoming an important driver and deep learning will add more momentum to its importance.
This article has been taken from our report The Physical Security Business 2017 – 2022 which is available to buy NOW for only $1,500 USD for a single user license.