As technology within the security industry evolves, monitoring centers are under increasing pressure to improve operational efficiency, reduce false alarms, and deliver faster, more accurate responses. A key driver of this transformation is the rapid advancement of video analytics — an AI-powered suite of tools that interprets video streams in real time to distinguish signals from noise.

During The Monitoring Association’s session “Improving Operations: Video Analytics in Action (2025 Update),” moderator Anthony Iannone, director of innovation and industry relations at Affiliated Monitoring, led a panel discussion exploring how video analytics technologies are reshaping monitoring center workflows, staffing models, and client outcomes — ushering in a new era of proactive, intelligent video surveillance. The panel featured three leading voices in the industry: Wes Usie, owner and president, Guardian Alarm Systems, and president, CHeKT Visual Security; Nicole Pitts, North America sales director, Calipsa, a Motorola Company; and Brian Karas, director of marketing and Eastern Region sales, Actuate.AI.

A long-time supporter of TMA, Usie has served on numerous committees and work groups. His dual leadership roles give him deep insight into both monitoring center operations and the application of advanced video analytics technologies. Pitts brings extensive experience helping customers improve operational efficiency in the video space. At Calipsa, a leading provider of AI-based video analytics, she is deeply engaged with real-time video processing and client enablement. Karas leads Actuate’s efforts to expand its footprint in the video analytics market, focusing on transforming existing security cameras into smart detection tools using advanced AI.

From Passive Watching to Proactive Intelligence

Historically, monitoring centers have relied on human operators to receive signals from intrusion systems — simple binary data indicating a door had opened, glass had broken, or motion was detected. The response was relatively straightforward: call the customer, attempt to verify the cause, and, if unsuccessful, dispatch the police. This model, while effective for decades, was limited by its lack of context and reliance on guesswork.

Video has changed that equation entirely. Instead of reacting to a signal with little insight, operators are now presented with real-time visuals of what’s occurring at the site. But with this new visibility comes a dramatic shift in responsibility. Operators are no longer simply verifying alarms — they are interpreting human behavior. They must decide, often within seconds, whether a person seen on the property is a threat or not. What was once a task driven by scripted calls has evolved into a judgment-based process.

“This adds a new dynamic to the monitoring center that’s actually very challenging,” Usie said. “Customers expect a high level of service, but operators are facing a wide range of unpredictable human behavior. What sounds straightforward is actually very difficult.”

This evolution underscores the importance of consistent training, clear protocols, and advanced tools to help agents maintain performance standards across countless scenarios.

Reducing False Alarms & Increasing Actionable Events

False alarms remain one of the most persistent and costly problems in the monitoring industry. They not only strain internal resources but also reduce credibility with law enforcement and clients. AI-powered video analytics address this problem head-on by applying contextual intelligence to video feeds. These systems can detect the difference between innocuous activity — like a gust of wind moving a tree branch — and actual threats such as a person loitering near a restricted entrance.

“Smart filtering is one of the biggest operational gains,” Pitts said. “We’re seeing a drop in false dispatches and a significant increase in verified events that lead to actionable responses.”

Real-World Results from Advanced Integration

The panelists shared real-world examples of analytics deployments driving measurable results: smart perimeter detection that automates incident tagging, cloud-based systems that push high-confidence alerts to operators instantly, and intelligent workflows that generate clips and pre-fill reports automatically.

Karas highlighted how cloud-based platforms provide significant scalability benefits. “Centralized updates, easy deployment, and lower labor costs — it all adds up to much faster resolution times,” he said.

By integrating analytics directly into monitoring software platforms through APIs and dashboards, operators are empowered to move from detection to response in record time.

The Human Element: Training & Empowerment

Rather than replacing operators, AI analytics elevate their capabilities. Usie and Pitts emphasized that monitoring professionals now need to interpret data-rich alerts, make nuanced decisions, and communicate effectively with customers and authorities.

“Operators aren’t being replaced — they’re being upgraded,” Usie noted. With AI handling basic detection, human staff can focus on high-value decisions and coordination.

To meet this new standard, monitoring centers must invest in ongoing training and develop standard operating procedures tailored to analytics-driven environments. Understanding camera placement, system limitations, and customer expectations is just as important as understanding the technology itself.

Implementation Insights: Crawl, Walk, Run

Adopting video analytics is not a one-size-fits-all deployment. The panelists offered several best practices for successful rollouts:

• Start Small: Begin with limited use cases like line crossing or vehicle detection.
• Test and Tune: Environmental variables — lighting, weather, camera quality—require calibration.
• Set Expectations: Clients must understand what the system can and cannot interpret.
• Vet Vendors Carefully: Strong technical support and responsiveness are essential.

This measured approach helps avoid over-promising and under-delivering, preserving trust as the technology scales.

Looking Ahead: Innovation & Ethics

As the session wrapped up, the conversation turned toward the future. Predictive analytics, privacy-conscious facial recognition, and cross-platform threat intelligence were cited as upcoming innovations. However, panelists warned that with greater capability comes greater responsibility.

Monitoring centers will need to strike a balance between innovation, ethical use, and regulatory compliance.

Why It Matters

Video monitoring is evolving from passive observation to proactive decision-making. AI-powered analytics offer the tools to transform noisy, high-volume environments into streamlined, intelligent operations. But with that power comes complexity — both technological and human.

As operators transition from verifying simple binary signals to interpreting human behavior on video, the stakes are higher, and the margin for error is smaller. Customers expect clarity, consistency, and speed — and delivering that requires the right combination of AI tools and trained human judgment.

In an industry where seconds and certainty matter, video analytics are no longer just a nice-to-have — they’re essential.