How a new model is changing the video intelligence landscape, according to Matt Powell, Managing Director, North America, ISS.
With the constantly evolving nature of security and the rise of smart city applications, the role of analytics in amplifying safety measures is essential.
Video analytics, propelled by advanced algorithms and AI, continue to be at the forefront of this transformation because of their capacity to extract specific details from surveillance footage and empower security teams to be more proactive.
Historically, the adoption of such cutting-edge technologies has been primarily saved for organizations with significant budgets to spend, leaving many others grappling with the challenge of enhancing security while addressing resource constraints.
However, recent advancements in processing capabilities have given rise to a new type of offering: service-based analytics.
As video analytics use advanced algorithms to analyze video footage from surveillance cameras, these applications enable security teams to enhance security measures through intelligence-gathering features like object detection, tracking and facial recognition technologies.
This not only identifies individuals, vehicles and objects of interest, but also enhances access control and threat identification.
Behavioral analysis and crowd management capabilities empower security personnel to respond effectively to potential security threats and ensure public safety in crowded environments.
While video analytics have long been considered an essential part of a comprehensive security program, there are significant changes being seen in the functional use of AI-driven decision-making that is cost-prohibitive for organizations.
The use of terms like AI, deep learning, machine learning, neural networks and more are all associated with the current crop of video analytics that have revolutionized how the market approaches public safety.
These technological advances have fundamentally changed the value proposition of video analytics for today’s end users.
Rather than specifying a system that records and archives footage for retrieval in the event of an incident, modern, high-trust analytics enable organizations to have a proactive security posture, responding to threats as they arise.
In addition to bolstering security, AI-enabled video analytics can also help end users improve business operations or even comply with certain safety and regulatory requirements.
However, for many companies, analytics-driven decisions have been out of reach, hindered by lack of budget, resource allocation or the inability to comprehend the value of such investments.
This has given rise to the idea of service-based analytics offerings.
X-as-a-service (XaaS) is an umbrella term for delivering products and solutions in a service-oriented manner and encompasses all cloud-enabled services.
XaaS, covering a range of systems from access control to video surveillance, has enabled users to access advanced functionality and scalability beyond what traditional methods offer.
Over the last several years, the physical security industry has seen a large shift from “manufacturer” to “service provider” based on the rise and prevalence of the “as-a-service” model growth.
It represents a fundamental shift across the industry toward software-based sales and support from these providers to end users.
The benefit to end users is also a huge factor in its continued growth and success.
End users benefit from shifting investment from a capital expenditure to a more operational expenditure, resulting in a smaller incremental cost footprint that can be a lot easier for security leaders to gain approval for.
Additionally, the ability to layer software that enables other security investments to work better – like analytics – fundamentally changes the way existing solutions work to better deliver data-driven results.
As analytics continue to advance, the cost of investing in solutions that leverage this technology grows to encompass all of the nuanced insights being gained.
This creates a large swath of companies that are unable to leverage the actionable data being collected.
The rise of something service-based analytics on demand might be the answer.
So, what happens when traditional rules-based analytics fall short? Enter: analytics-as-a-service (AaaS).
Leveraging machine learning and neural networks to deliver insights, AaaS allows users to upload video footage to receive tailored reports that detect anomalies and trends, spotlighting crucial datapoints that can make the reports actionable for security teams.
Examples of this might include the following:
The benefits of the AaaS model are several-fold. It allows security teams to leverage powerful data-driven insights without investing in long-term, permanent solutions that can be costly to maintain and operate.
With budgets tightening – or in many cases, staying the same – this ability opens up a world of possibilities for security teams to garner critical insights without significant investment.
From transportation hubs dealing with the balance between efficiency and vigilance to urban centers navigating the complexities of public safety, AaaS has the potential to provide much-needed innovation while balancing the nature of shrinking budgets and cost-cutting measures.
Harnessing the power of machine learning and neural networks, organizations are entering an era of being able to derive actionable insights from video data without long-term investments.
Service-based analytics might be the tip of the iceberg for both public and private organizations looking to leverage their incoming data to make better decisions about the way they approach new initiatives for public safety.
From ensuring compliance with safety regulations to providing invaluable datapoints on security operations and everything in between, the transformative potential of AaaS knows no bounds, guided only by the visionary imagination of the customer and the cutting-edge capabilities of the analytics provider.
Securing the transportation sector is complex due to its vast infrastructure, high volume of people and cargo, and interconnected nature.
The challenge lies in implementing effective security measures without impeding the flow of goods and people.
Additionally, international considerations, emerging threats like cyber-attacks and the criticality of transportation infrastructure further complicate security efforts.
Addressing these challenges requires a layered approach involving collaboration between government agencies, transportation operators and technology.
More specifically, the sheer amount of data points present across transportation-related entities makes analysis without layering intelligence and advanced analytics that much more complicated.
The unique challenges that each entity faces provides security leadership with the flexibility and opportunity to customize results based on specific needs.
Whether the organization is focused on traffic flow optimization, turning movement counts or urban planning, aligning objectives and tailoring results means more data-driven decision-making.
More specific analytics that can be leveraged to paint a specific picture that allows security leadership to make more informed decisions about resource allocation and streamlined response might include:
Matt Powell is Managing Director for North America at ISS (Intelligent Security Systems).
He has over two decades of experience in security and transportation technologies having formerly served as Principal-Infrastructure Markets at systems integrator Convergint and as a developer of transportation market strategies for Videolarm and Moog prior to that.
He can be reached at [email protected].
This article was originally published in the June edition of Security Journal Americas. To read your FREE digital edition, click here.