Page 18 - Security Today, March/April 2025

A R T I F I C I A L I N T E L L I G E N C E
“These “new tricks” mark a significant
milestone in the field of professional
security, emphasizing flexibility,
intelligence and collaboration.”
specifi c truck logos or monitor pallet movements at a loading dock.
This adaptability has implications far beyond security. By us-
ing on-site learning, data-hungry businesses can generate valu-
able operational metrics and key performance indicators (KPIs).
For instance, monitoring forklift activity in a warehouse can
provide insights into workfl ow effi ciency, while counting vehicles
can support predictive maintenance or resource allocation. By
embedding this intelligence at the edge — directly within the cam-
era — organizations can reduce the need for centralized process-
ing, ensuring real-time responsiveness and cost effi ciency.
HOSTING SPECIALIZED APPLICATIONS
WITH OPEN PLATFORMS
Another innovation transforming use cases for security cameras is
its ability to host third-party applications through an open-plat-
form architecture. This approach gives developers and integrators
the freedom to create bespoke solutions that address unique chal-
lenges.
For example, a camera could host an application designed to
detect individuals who have fallen — identifying a horizontal hu-
man form in a space where people are expected to remain upright.
Similarly, applications can be developed for detecting smoke or
leaks in outdoor environments where traditional sensors might fail.
Key to this fl exibility is the use of standardized container
technologies, such as Docker, which enable modular, secure and
scalable application development. Containers encapsulate appli-
cations within a protective layer, preventing unauthorized access
to the camera’s core functions while facilitating seamless integra-
tion with cloud services. Developers can design and deploy their
applications in cloud environments and then run them on any
compatible device, whether on the edge or in the cloud.
By using containerized architectures, security professionals
gain the fl exibility to customize their systems for specifi c use cases
while maintaining cybersecurity standards. Modular containers
also simplify updates, enabling users to implement new features
or improvements without disrupting existing operations. This ca-
pability aligns with broader digital transformation efforts, making
AI-enabled cameras more than just security tools — they become
essential IoT devices supporting a range of business functions.
EXTENDING THE LIFE OF LEGACY SYSTEMS
The ability to integrate AI capabilities into existing infrastruc-
ture is another key development in the evolution of AI-enabled
cameras. By processing AI analytics at the edge, newer systems
can enhance the functionality of legacy devices, such as older
network cameras. This approach reduces the need for full-scale
replacements, which can be both costly and disruptive.
1 8 For instance, edge devices can add AI metadata to non-AI
cameras, enabling features like object recognition or event detec-
tion without requiring physical upgrades. This is particularly ben-
efi cial in scenarios where cameras are in hard-to-reach areas, such
as industrial facilities or large campuses.
Extending the lifespan of existing hardware not only maxi-
mizes return on investment but also minimizes waste, and reduces
downtime, all while aligning with sustainability goals.
THE OPEN-PLATFORM ADVANTAGE
In an industry often divided between closed and open systems,
open-platform architectures are emerging as a clear winner for
organizations seeking adaptability and long-term value. Closed
systems, while straightforward to deploy, often lock users into
proprietary ecosystems, limiting their ability to adopt new tech-
nologies or integrate third-party solutions.
Open platforms, on the other hand, encourage collaboration
and innovation by providing developers with access to tools like
software development kits (SDKs), application programming
interfaces (APIs), and open development platforms like Docker.
These tools allow users to integrate a wide range of applications,
ensuring their systems remain future-proof and capable of adapt-
ing to evolving needs.
For example, cameras built on open platforms can host ap-
plications from various developers, much like a smartphone
runs multiple apps. By embracing open-platform technologies,
organizations avoid the constraints of one-size-fi ts-all solutions
and gain the ability to build tailor-made systems that meet their
unique requirements.
THE FUTURE OF AI-ENABLED SECURITY CAMERAS
As AI-enabled security cameras continue to evolve, their role is
expanding beyond traditional surveillance. On-site learning and
open platforms are transforming these devices into versatile tools
that contribute to both security and operational effi ciency.
By allowing cameras to learn from their environments and host
specialized applications, organizations can address challenges that
were previously beyond the scope of traditional security systems.
This shift highlights the growing importance of edge intelli-
gence and modular design in the security industry. By leveraging
these advancements, businesses can not only improve their security
posture but also gain valuable insights that support broader or-
ganizational goals. Whether it is tracking assets, enhancing safety
protocols, or generating actionable data, the potential applications
for AI-enabled cameras are virtually limitless.
For security professionals, the message is clear: the future of
AI in security lies in adaptability and collabora-
tion. By embracing open platforms and evolving
capabilities at the speed of innovation, we can
teach AI new tricks that uniquely benefi t every
organization.
Adam Lowenstein is the Americas Product
Director at i-PRO.
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