Ken Francis, CEO of Actuate reveals how hybrid edge AI surveillance represents the future of security management.
AI and edge computing
In the rapidly evolving landscape of security technology, the integration of AI with edge computing has revolutionized how surveillance systems are deployed and managed.
Traditional security setups relied heavily on centralized hardware and manual monitoring, which often led to delays, blind spots and false alarms that drained resources and compromised safety.
Today, the emergence of hybrid AI solutions, combining cloud and edge processing, offers a powerful, flexible approach that addresses these challenges head-on.
A hybrid system
At its core, hybrid AI in surveillance systems leverages the strengths of both cloud computing and on-site edge devices.
Cloud platforms enable centralized data storage, large-scale processing and advanced analytics, accessible from anywhere at any time.
Meanwhile, edge devices, such as cameras with integrated AI capabilities, handle real-time processing locally, minimizing latency and reducing strain on network bandwidth.
The synergy between the two ensures rapid response times for critical events while maintaining the ability to analyze massive volumes of video data efficiently.
Implementing such hybrid systems provides significant benefits.
By processing certain analytics at the edge, surveillance systems can instantly eliminate a considerable amount of video data which would otherwise slow the process and identify specific threat types that require further processing with more powerful cloud resources like weapons or suspicious behaviors.
AI models are just that: models – mathematical algorithms trained for narrow tasks.
A single model rarely delivers the functionality required in a physical security application. Instead, multiple or many models are combined into a series of algorithms built for specific use cases.
When designed properly, hybrid applications enable the technology owner to leave the edge analytics in place and constantly update the more power-hungry algorithms in the cloud, resulting in a great quality of service.
This division of compute not only enhances operational efficiency but also ensures that security responses are both swift and informed.
A key advantage of this hybrid approach lies in its ability to seamlessly integrate with existing infrastructure.
Many organizations have invested heavily in cameras, cabling and management systems, making hardware replacement costly and disruptive.
Hybrid edge AI solutions can often operate alongside these legacy systems without requiring substantial upgrades.
For instance, analytics can be deployed directly on edge modules, enabling organizations to upgrade their security posture incrementally.
This integration is complemented by centralized cloud platforms that unify data streams, manage alerts and provide insights without the need for extensive hardware overhaul.
Reducing false alarms
One of the critical challenges in surveillance is balancing the need for comprehensive monitoring with the risk of false alarms.
Conventional systems often generate numerous unnecessary alerts caused by weather, animals or environmental factors – wasting valuable operational resources.
Advanced AI-powered systems mitigate this problem through multi-model processing and deep learning techniques that finely distinguish between genuine threats and benign activities.
For example, they can identify unauthorized persons, detect weapons with high accuracy or monitor crowded environments to flag unusual behavior – all while drastically reducing false positives.
This smarter filtering allows security personnel to focus on real incidents, improving safety and response times.
Another significant benefit of hybrid AI systems is their scalability and deployment flexibility.
As organizations expand their facilities or operational footprint, adding new cameras or sensors becomes straightforward without massive infrastructure investments.
Low-bandwidth optimization ensures that even remote locations or bandwidth-constrained environments can support high-quality video analytics.
Centralized management platforms facilitate rapid deployment across multiple sites, providing unified control and monitoring, which simplifies the complexities of managing large-scale security operations.
In complex environments, such as sprawling campuses or multi-location facilities, the hybrid system’s ability to provide comprehensive coverage is essential.
AI algorithms at the edge continuously analyze video feeds locally, flagging critical events, while centralized systems aggregate data across sites, providing a macro view of security status worldwide.
This distributed yet connected architecture enables security teams to respond effectively across borders, whether investigating localized incidents or coordinating responses to threats.
The transformative potential of hybrid AI in surveillance extends beyond mere threat detection.
It enhances operational efficiency, supports compliance requirements and improves resource allocation – all while helping organizations adapt swiftly to new security challenges.
From reducing false alarms to enabling real-time responses and facilitating long-term strategic planning, this approach provides a resilient, scalable and intelligent framework for modern security needs.
In summary, the integration of AI with edge and cloud technologies in surveillance systems represents a paradigm shift in security management.
It combines the immediacy of local processing with the analytical depth of centralized systems, resulting in smarter, faster and more reliable security solutions.
As threats become more sophisticated and environments more complex, adopting hybrid edge AI technology will be essential for ensuring proactive, effective and scalable security operations.
About the author
Ken Francis joined Actuate as the CEO in November 2024 after serving as the President of Eagle Eye Networks for eight years.
Before joining Eagle Eye Networks in 2016, Ken launched ADT Security Services back into the commercial marketplace following the spinoff and IPO of ADT by Tyco International in 2012.
Previously, Ken served as the Vice President of Sales and Marketing for UTC’s Global Security Products Business Unit, led the GE Security, Integrated Systems Program as the Global Product GM and co-founded AMAG Technology.
In all three roles, Ken was responsible for the growth of software-based access control and video technologies through the leadership of international product management teams and the expansion of global channels.
He earned a Bachelor of Business Administration from Florida State University and a Master of Business Administration from American University.
He currently serves as Chair of the Executive Advisory Board of the Security Industry Association.
This article was originally published in the October edition of Security Journal Americas. To read your FREE digital edition, click here.