How AI is Transforming Alarm Monitoring

Over the past decade, AI machine learning and deep learning have greatly improved alarm monitoring through faster, more reliable alarm verification; yet, in practice, AI has often fallen short of its expected impact.

The general advancement of AI is not in and of itself transformative; thus, the potential of recent AI breakthroughs will not automatically transform alarm monitoring. It requires innovative engineering approaches to translate that potential into real operational value.

“When video analytics software first entered the market – and later also became embedded in cameras, there was widespread optimism that what the industry called ‘intelligent video’ would finally overcome the longstanding shortcomings of alarm monitoring,” explains Ken Francis, CEO of Actuate, a provider of a cloud-based AI-enabled alarm monitoring solution. “Each generation of analytics brought worthwhile improvements, but none fully resolved the core issues. Instead, these tools primarily enabled systems to scale by supporting larger numbers of cameras. The fundamental nature of alarm monitoring remained unchanged.”

Francis adds that across decades of alarm monitoring, four persistent shortcomings have challenged the security monitoring industry:

• High false alarm rates (not a real incident) – false positives;
• Missed real incidents due to limited incident detection capabilities – false negatives;
• Limited or no contextual understanding of the alarm event; and
• Operator stress and fatigue from total (true and false) alarm volume and time-critical response pressure.

Alarm Monitoring Breakthrough

Fortunately, new AI models have emerged that can be used to fundamentally change the nature of alarm monitoring. Properly applied, advanced AI-enabled video analytics can transform monitoring centers into high-tech command centers and remote guarding services into AI-augmented services.

Historical shortcomings are pushing remote monitoring beyond alarm verification, toward proactive solutions, where not only fast response but contextual awareness of the incident can be critical. New AI monitoring capabilities enhance incident response in a variety of ways:

• Alerting with rich contextual alarm data;
• Automated security system responses;
• Human-in-the-Loop enablement and engagement;
• Adherence to critical response protocols; and
• Audit trails that document not only the manual and automated actions taken but also the situational rationale behind them.

Video-verified alarms not only meet emerging legal mandates but often ensure faster police response as departments prioritize calls with visual or audio confirmation of criminal activity.

AI is transforming alarm monitoring from a reactive process into a proactive, intelligence-driven service. By dramatically reducing false alarms, accelerating response times, and providing real-time situational awareness, AI is addressing the core challenges that have long plagued the industry. AI-enabled alarm monitoring is emerging as the new industry standard – reshaping expectations for both security providers and the clients they serve.

Most importantly, for the first time in the history of the physical security industry, high-caliber security monitoring is now feasibly available to all properties that desire it, not just Fortune 500 sites.

Analytics for False Alarm Reduction: Two Technology Options in the Spotlight

Actuate (actuate.ai): This cloud-based AI video analytics platform transforms monitoring centers into high-tech command centers and remote guarding into AI-augmented services. It detects intruders, weapons (99% accuracy), fires (earlier than sensors), critical crowd formations, and more – integrating with most cameras, NVRs, VMS products, and monitoring platforms.

Typical object classification analytics (detecting, people or vehicles) must be tuned to prioritize the avoidance of missed threats, which results in high false alarm rates (false positives). Actuate’s AI models and scenario-focused AI model training excel in context-aware event processing, reducing false positives by 95%+ while maintaining virtually no missed threats, backed by a $10,000 reimbursement policy for missed detections.

This reliability allows staff to manage more sites with less stress and focus on real threats. The result is improved job satisfaction, lower turnover, and the ability for existing staff to manage more accounts without sacrificing quality. One monitoring center reported a 57% reduction in per-site alerts—over 400,000 fewer per month—thanks to highly accurate false alarm suppression.

Actuate developed and trained its own AI models using more than 1.5 million images captured from security scenario videos. No third-party training or external processing is involved. Ultra-fast event confirmation is achieved by analyzing each video frame and routing it to the most appropriate AI models, selected based on the event scenario, camera type (e.g., high-res, low-res, infrared), and image content. Additional speed and precision come from an approach called “slicing,” where high-resolution images are intelligently divided into smaller segments for parallel and specialized processing. This allows for early detection of events at long distances—particularly valuable at sites like car dealerships, campus perimeters, logistics yards, and construction zones.

Actuate’s detection pipeline uses multiple sequential layers, each combining AI models and machine learning processes. These layers work like overlapping slices of Swiss cheese: if a detection slips past one layer, it is caught by the next. This layered architecture supports Actuate’s high-performance guarantee, backed by a $10,000 reimbursement policy for missed slicing detections.

Actuate also performs proactive Camera Health Monitoring—designed to ensure consistent reliability and operational integrity of video systems. It continuously checks the health of each camera and provides insights enabling fixes before issues affect performance. This includes detecting outages, image degradation, misalignment, and obstructed views that may otherwise go unnoticed.

Uniquely for a monitoring platform, Actuate accommodates both live video streaming from cameras and NVR/VMS setups, as well as workflows where edge AI in cameras or recorders sends images via email—using Simple Mail Transfer Protocol (SMTP)—based on scene or object motion detection. Supporting both streaming and edge AI email alerts is crucial because some sites cannot stream video due to bandwidth limitations, and some have workflows built around email alerts. Actuate’s AI models apply the same stringent processing to video images, clips, and continuous streams, achieving uniform accuracy across all monitoring station customers.

Deep Sentinel (www.deepsentinel.com): This service delivers AI-powered remote guarding capabilities, coupled with site surveillance and response technology, that were once only practical for Fortune 500 companies. Their unique approach overcomes the cost and complexity barriers of earlier high-end systems while avoiding the design and capability constraints that have often limited small business and residential solutions. Their remote guarding service is tailored for residential homes, apartments, small-to-medium businesses, and commercial and retail environments.

At its core is an on-premises edge computing and connectivity Hub built using an AMD or Intel NUC mini-computer, a small form factor computer that represents a significant advancement in compact, high-performance computing. The Hub connects cameras and other devices and is a point of device integration. It runs all the AI at the edge – analyzing live video feeds from cameras in real time.

Once a potential threat is identified, the system streams the event to a live specially-trained security guard who can engage directly – using two-way audio, activating built-in sirens, or even deploying FlashBang deterrent options (e.g., smoke bombs, pepper spray, strobe lights) to actively stop intruders.

Deep Sentinel also offers physical duress buttons as part of its SentinelNow service. If an employee feels unsafe, notices suspicious activity, or wants an extra set of eyes – such as before heading to the dumpster or parking lot – they can press the button to instantly connect with a Deep Sentinel guard. Within seconds, the guard reviews the live camera feed, provides verbal support when appropriate, and escalates to emergency services if needed. In such cases, the guard can relay real-time details to first responders, including suspect descriptions, visible weapons, crime information, and known medical needs.

The Deep Sentinel Gen V Hub typically supports up to 20 cameras, providing flexibility for both residential and small enterprise deployments. This design prioritizes low latency, proactive deterrence, and consistent operation even in smaller-scale settings.

Deep Sentinel’s stated objective is to deliver real-time intervention at the highest standard in the industry. Underscoring that commitment is the response time profile defined in its business and residential Service Level Agreements (SLAs):

1.       AI detection: ~5–7 seconds

2.       Streaming to guard: ~2–8 seconds

3.       Guard viewing & intervention onset:

a.       Business: within 30 seconds from event start for 10 common business events, and 60 seconds after hours for Trespasser, Auto-loitering and Door loitering

b.       Residential: within 30 seconds from event start for 10 common residential events, and 60 seconds after hours for Auto-loitering and Door loitering

Although Deep Sentinel offers its own small line of affordable cameras, it also provides a third-party camera partner program, called a Bring Your Own Camera (BYOC), enabling customers to connect existing IP or PoE cameras, ensuring seamless integration with current systems.