It’s this simple: AI is driving the future of physical security technology, and organizations that don’t become adopters will get left behind.
An array of AI-enabled technologies have flooded the market in recent years, including AI video analytics. These solutions changed the landscape, making it possible to automate video surveillance monitoring, more accurately detect threats, fortify the overall security posture, and much more.
But any user of the average AI video analytics tool will tell you that while it has strengths, it has weaknesses. This is where computer vision intelligence enters the picture.
Where AI video analytics falters, computer vision intelligence soars, empowering teams to achieve the strongest, most proactive security posture possible and prevent incidents before they happen.
We’re here to share all you must know about AI-based video analytics and the latest technology that enables physical security teams to solve what was previously unsolvable.
Table of Contents
- AI video analytics explained
- Where AI video analytics software falls short
- Computer vision intelligence, going beyond AI video analytics
- Computer vision intelligence vs. traditional video analytics
- How computer vision intelligence solves physical security challenges
- Computer vision intelligence success stories
- Ambient.ai achieves what your AI video analytics solution can’t
AI video analytics explained
AI video analytics leverages AI and machine learning to analyze video footage and supply end users with key patterns and insights. For physical security teams, AI emerges as a powerful force multiplier to achieve greater accuracy, efficiency, and responsiveness.
With AI, security teams are better equipped to detect suspicious activity — such as loitering, tailgating, trespassing, and theft — before incidents escalate, reduce false alarms by verifying threats, and conduct more efficient investigations, among other use cases.
But not all AI-based physical security technologies are created equal. As AI has evolved, security tools have become increasingly sophisticated, capable of providing more accurate and actionable insights. Meanwhile, other AI-driven solutions have lagged behind, opening up organizations to vulnerabilities.
Where AI video analytics software falls short
Some AI video analytics are smart, but not intelligent. Notably, it’s difficult for the typical AI video analytics tool to distinguish between threats and normal activity. That’s because most AI models lack the near-human-level understanding of a scene that’s required to identify genuine incidents.
When AI fails to improve security operations, it’s often due to this lack of contextual insights. In turn, this limits the situational awareness that’s necessary to detect threats. Physical security teams need more advanced AI-driven technology to overcome these shortcomings.
Enter: computer vision intelligence.
Computer vision intelligence, going beyond AI video analytics
If you’re not familiar with computer vision intelligence (CVI), it’s time to get acquainted with the future of physical security. CVI monitors surveillance video in the way that a human would. Human perception is all about context, and context is crucial in security. The AI takes in the context of a scene, such as the location and interactions between objects, to accurately evaluate security threats and automatically trigger actions.
Think of it this way: someone holding a knife in your workplace’s kitchen isn’t unusual, but someone with a knife in your lobby is cause for concern. Computer vision intelligence understands this and would automatically alert your team so that they could respond immediately. No nuisance alarms, only real, verified threats.
All of this creates massive benefits for your physical security operations:
- Liberate security personnel from constant video surveillance
- Act proactively with real-time situational awareness
- Reduce alarm noise and unearth genuine alerts
- Prevent incidents from escalating by detecting early threat indicators
- Make smarter operational decisions
Computer vision intelligence vs. traditional video analytics
Computer vision intelligence surpasses what is possible with today’s video analytics. At the core of this differentiation is computer vision intelligence’s advanced detection.
Computer vision intelligence’s ability to understand contextualized activity and contrast it from the normal patterns of life reduces false positive alarms and allows your security team to focus on genuine threats in a way that traditional video analytics can’t.
Plus, where most video analytics tools struggle to identify partially obscured persons and objects, computer vision intelligence infers exactly what’s in a scene — all without needing 4k cameras. There’s no need to pull out and replace your surveillance system; computer vision intelligence is just as effective with lower-resolution cameras as it is with higher-resolution cameras.
How computer vision intelligence solves physical security challenges
You can think of computer vision intelligence as the central hub of your security program: constantly monitoring all cameras and alarm endpoints, identifying threats with maximum accuracy, uncovering key insights, and reducing the cognitive demands on your team.
It acts as a powerful force multiplier for physical security programs by solving these common challenges:
1. Challenge: Moving away from reactive security
It’s a frustrating reality and one of the biggest struggles facing security teams today. Manual video surveillance monitoring, alarms that generate thousands of false positives daily, and the inability to have security officers everywhere at the same time leave teams in a reactive posture.
Instead of stopping threats in their tracks and addressing vulnerabilities, teams find themselves stuck in a cycle of responding to incidents after the fact.
Solution: An “always on” AI brain
Computer vision intelligence AI extends the human capabilities of your security team, equipping them with the foresight and tools to preempt security incidents.
This advanced AI enables proactive security by continuously monitoring your security systems, from your security video footage to your access control infrastructure. AI never sleeps; any deviations from the norm are promptly detected and addressed without the possibility of human error or oversight.
AI also automates threat detection and response. As your computer vision intelligence solution monitors your site, it rapidly identifies and alerts your operators of threats in real-time. Plus, since CVI processes images similar to human perception, it’s able to send alerts with all of the contextual information you’d need to respond appropriately.
In this manner, leveraging an AI brain prevents early threats and alarms from escalating into full-blown incidents and allows teams to focus on proactive security measures.
2. Challenge: Overwhelming alarm volumes
The average operator spends countless hours verifying alarms, a majority of which — roughly 99% or more — turn out to be false positives. In light of these staggering alarm frequencies, many operators either overlook or mask the endless stream of “door forced open,” “door held open,” and “invalid badge” notifications.
Thorough human verification becomes nearly impractical with such alarm volumes. But at the same time, a lack of vigilance puts organizations in danger of exposing vulnerabilities and missing crucial alerts. The takeaway is clear: security teams urgently need a more effective approach to alarm management.
Solution: Reduce false alarms with contextual analysis
A computer vision intelligence solution enables you to automatically verify and clear nuisance alarms with complete accuracy. The result: a drastic reduction in noise, smarter alarm prioritization, and more time spent intervening in actual incidents.
CVI’s ability to understand the context of a scene is key to its success in distinguishing false alerts from real threats. From there, it can send operators actionable alerts with all of the situational context that they’d need to conduct an appropriate response.
When operators spend less time dispositioning false alerts and more time dispatching on legitimate threats, they directly create a safer, more secure environment for all employees.
3. Challenge: Time-intensive investigations
Today’s security video investigations are flat-out time-consuming. Depending on the complexity and the severity of a given incident, conducting a video review with traditional tools takes hours — even days — to complete a single investigation.
Once someone reports an incident, what follows is a long process of searching one stream at a time through thousands of hours of footage. Operators must pin down the correct time frame of the incident and the cameras that captured it take place. It’s a painful cycle of verifying time frame after time frame, camera after camera, and manually searching for specific people and objects.
Solution: Speed up forensic investigations with AI
Investigations demand prompt action. This is exactly what computer vision intelligence delivers. What sets computer vision intelligence apart from other video investigation technologies is its ability to detect complex behaviors and patterns. This empowers investigators to directly search for events of interest, rather than person and object search.
For instance, computer vision intelligence allows investigators to search for specific behaviors, like a person carrying a bag, to locate a desired scene in minutes. Conversely, technology that enables just person and object detection restricts investigators to searching for simply a person and a bag somewhere in camera view.
CVI’s big results: faster investigations increase the odds of apprehending perpetrators and recovering valuable assets. Plus, accelerated resolutions free up valuable time and resources for more strategic pursuits.
4. Challenge: Lack of insights for operational decision-making
For your physical security team to establish effective security measures, they need to understand the behavior of people and the behavioral patterns that are unique to your organization. But that’s precisely the problem.
Each day, teams filter through mass amounts of data generated from security cameras, access control systems, and sensors. Yet this data doesn’t provide actual insights on behavior — just a lot of noise.
Without deeper site-level intelligence and greater visibility into alerts, it’s nearly impossible to make informed operational decisions. Then, when it comes time to decide where to post guards or mount a camera, you’re stuck relying on assumptions and best practices.
Solution: Leverage AI-powered insights
No security team can afford to fly blind. Fortunately, computer vision intelligence can unearth the crucial operational insights you’ve been missing.
By correlating the signals provided by security cameras and access control systems, operators receive contextual alerts that cue them into the behaviors prevalent at their organization and where these behaviors tend to concentrate.
With these deeper insights, security teams better understand where to optimize security measures and allocate additional resources. For instance, if you receive constant tailgating alerts from your lobby door, this area might require greater security measures.
Plus, with more visibility into the volume of genuine incidents versus alerts meant for situational awareness, teams can filter out the noise to clearly see where their true vulnerabilities lie.
Computer vision intelligence success stories
From real-time responses to threats, to reductions in access control alarms, to faster forensic investigations, industry leaders that use computer vision intelligence see major results.
For VMware and NorCal Cannabis, Ambient.ai, the physical security industry’s first computer vision intelligence product, helped them achieve success.
VMware decreased alarms by over 93%
Before implementing Ambient.ai, the physical access control system (PACS) at VMware’s Palo Alto campus would generate about a million false alerts per year. The vast majority of alerts were false positives, but operators still had to respond to each one as if it were an actual breach.
Responding to the false alerts burdened their resources and detracted attention from higher-value activities. But with Ambient.ai, the team can automatically verify alerts, filter out the noise, and measure the complete lifecycle of an incident. As a result, VMware reduced false positives and decreased alarms by over 93%.
NorCal Cannabis cut down investigations to under one hour
With the risk of theft and their strict regulatory environment, NorCal Cannabis needed to find a way to investigate incidents and provide footage to regulators as fast as possible. But even after investing in cameras and thorough processes, video analysis and forensics still took too long for the team.
That all changed after they used Ambient.ai. The platform both decreased the burden of monitoring hundreds of cameras and streamlined investigations. With Ambient’s ability to quickly search for specific scenes in video footage, NorCal Cannabis reduced investigation times from days to under one hour.
Ambient.ai achieves what your AI video analytics solution can’t
The Ambient.ai platform transforms enterprise security operations like no other tool can. Ambient applies AI and computer vision intelligence to existing sensor and camera infrastructure to deliver continuous physical security monitoring and automate the immediate dispatch of human resources.
The system proactively alerts on real threats, 24x7x365, so your physical security team can prevent incidents before they happen. In short, we’re making the impossible possible for physical security teams.
With Ambient.ai, our customers experience:
- 90%+ reduction in access control alarms
- Real-time responses to incidents
- 20x faster forensic investigations
Discover how Ambient.ai’s computer vision intelligence platform helps Fortune 500 companies and cutting-edge industry leaders see real results from their security operations.
