We have once again reached the time of year when we look ahead to some technology trends that will affect the security sector over the coming 12 months. The pace of change is as fast as ever.
Some of the trends are evolutions of those we have seen in previous years. An obvious one is the continued interest in how AI will be applied in our sector, and we have highlighted some of the new considerations that need to be addressed moving forward. Others are new, or even a resurgence of topics we may not have focused on for a while.
National and regional legislators will once again try to keep pace with technological innovation. AI, cybersecurity, privacy, and the need for resilience in critical entities. All these (and more) will be the focus of proposed and new regulations. We have not highlighted this as a specific trend, but it is no less a priority and something every organisation will need to respond to.
Within all of these trends lies significant opportunity for the sector. For our customers, that means enhanced capabilities, more flexibility, greater efficiency and increased value.
Hybrid solutions
In previous years, we have highlighted how hybrid architectures – those that best use edge, cloud, and on-premises technologies – have become the de facto choice for security solutions.
Every organisation’s drivers for choosing architecture will be unique, taking into account technological, legal, ethical, and governance concerns and requirements. The environment is evolving quickly, and therefore, freedom of choice is imperative.
Hybrid solutions give you the freedom to store video, view video, manage devices, etc. Either by combining edge, cloud, and on-premises technologies to get an optimal total system solution or utilising its flexibility, choose the instance you prefer.
Whether demanded by emerging local and regional regulations or concerns over control of data, cost, or energy efficiency, hybrid solutions will continue to offer the greatest flexibility in creating architectures that best suit specific organisational needs and allow a system to be scaled.
AI evolution alongside AI efficiency
Development within the field of AI continues to race ahead. Deep learning technologies are the bread and butter of most analytics solutions within the security sector, while newer generative AI technologies are rapidly maturing. There is still a lot of hype in certain areas, but real applications of generative AI in the security sector are becoming available. Each step of evolution brings with it a new set of opportunities, as well as ethical, legal, and corporate considerations.
Generative AI models are large and require a lot of computing capacity to execute, which creates a debate about how to balance the cost of AI (both in terms of financial investment and energy use, and environmental impact) with its value. A lot of effort is being put into reducing the size of the models, while maintaining the quality of results. The increased use of AI technologies only reinforces hybrid architectures as the standard.
The various ‘flavours’ of AI – from deep learning-based object recognition to generative AI – either demand or benefit
from being applied at different places in the value chain and in specific environments. Generative AI can assist operators in interacting with security solutions in natural language but, for the foreseeable future, requires significant processing power. Conversely, deep learning-based analytics, such as enhanced object recognition, can be performed within surveillance cameras themselves.
Eventually, this will enable generative models to be run on cameras, at least partly, with high-quality results. At the same time, the models are improving in quality regarding ethical aspects, bias, hallucinations, and the risk of making the wrong decisions.
Over time, there is a big opportunity to change the efficiency and effectiveness of security operations dramatically. Algorithms will be able to understand what is happening in a scene and react to anomalies based on the analysis of different types of input data, including but not limited to visual information. Input data will come from radar, audio, and numerous other sensors. This will create solutions that enable increasingly proactive capabilities and generate valuable insights into security scenarios for long-term planning.
Beyond safety and security becomes real
The application of increasingly advanced computer vision, audio, access control and other connected technologies continues to serve security and safety use cases. Greater accuracy of analytics through the application of AI – particularly in object recognition – means that incidents can be responded to more quickly and effectively than ever before.
What is also clear is that the data generated by sensors of all types – video, audio, environmental, and more – can benefit numerous use cases beyond the traditional. While still a relatively small part of the market, we expect an acceleration of applications aligned to operational efficiency and business intelligence.
This trend highlights the opportunities for increased collaboration across customer organisations. Technology being sourced or specified for one use case could well be used in another area of a business’s operations. For instance, data being created by video cameras employed principally for security purposes can be analysed over time to improve customer or employee experience, sustainability, or process efficiency.
The pace of development and innovation is astounding, thanks to the high-quality hardware platforms available. Hardware vendors that foster an open and collaborative ecosystem of application developers and system integrators will bring the greatest value to customers most quickly.
The ‘rebirth’ of image quality
It may be counterintuitive to suggest that a focus on image quality is a trend in the sector, where many would assume it has always been a priority (which, of course, it has). The trend is in how the images from visual sensors are being used, and with that the increased opportunities better image quality bring.
The paradigm shifts when we consider that images are now often initially viewed and analysed by computers rather than humans and are viewed continuously rather than when an incident of interest has taken place.
Advances in analytics and AI mean that a higher-resolution image will inevitably lead to a better result, whatever the use case. Object recognition will be more accurate, and more detailed data (and metadata) will be created. The drive towards even better image quality has been reignited.
This has come with opportunities for efficiency and effectiveness. A single camera producing much higher image quality can cover as large an area as multiple cameras would have been needed previously. Higher resolution images also support analytics, for instance, in large crowds, busy traffic intersections, or fast-moving production lines.
As the saying goes, the human is still very much ‘in the loop’. Operators will be automatically alerted to scenes they need to pay attention to, increasing the efficiency and effectiveness of a response. Image quality as a focus will also place keen attention on the maintenance of surveillance cameras – still often a manual task – as small obstructions can have a significant impact on analysis.
The long-term value of software support
At the higher end of the security sector, the quality of hardware has been improving year-on-year. Today, hardware devices can be of such high quality – particularly in terms of performance and capabilities – that expectations about their lifetime are greater than ever.
However, while quality hardware can last for many years – as illustrated by the length of warranties – the defining factor in a camera’s functionality, including cybersecurity and lifetime value, comes through ongoing software support.
Vendor commitments to support software that continues to enhance and build on the camera’s capabilities and keep it as secure as possible throughout the expected lifetime of the hardware are essential. This also underpins the total cost of ownership of hardware. Investing in a better quality camera, with comprehensive software support throughout its lifecycle, will ultimately be a more effective and efficient solution.
Technology autonomy to the customer’s benefit
The role of Axis, and that of our partner ecosystem, is ultimately to focus on meeting the needs of customers. Technology, for technology’s sake, serves nobody’s purpose – innovations must be aligned to the priorities of the end user.
This clearly means supporting customers’ goals in safety and security, operational efficiency, and business intelligence. However, it also means supporting their cybersecurity posture, commitment to sustainability through energy-efficient solutions, and flexibility and freedom of choice via open standards-based technologies and platforms.
Technology vendors with more autonomy over their core technologies are clearly best placed to support these customer requirements. Greater control over foundational technology, from the silicon upwards, will allow a vendor to design specific capabilities and functionality
aligned to customer needs into its products. Such an approach to core technology ownership will also allow a vendor to stand by its commitment to being secure by design.
Furthermore, greater control of technology – at a component or even material level – is an important prerequisite to more effectively mitigate the risks of broader disruption to global supply chains. This enhances the ability to meet customers’ requirements when they are needed.
We are already seeing companies that would have traditionally been seen as software vendors, designing their own semiconductors to gain more control over their service delivery – particularly in the area of AI – and we foresee this trend continuing in all sectors. Core technology independence is a trend we are proud to say w are some way ahead of, having developed our system-on-chip, ARTPEC, for the last 25 years.
For more information, contact Axis Communications,
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www: | www.axis.com |
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