In an era where safety and efficiency are desired and expected, AI video surveillance is becoming an essential tool in today’s modern enterprises. According to IBM’s AI Global Adoption Index, over half of leading organizations are looking for ways to implement AI. This can range from project management tools to sales intelligence platforms and even video security. However, most of today's video security systems are slow to adopt or fail to effectively integrate AI into their products.

AI is transforming how we work, and the benefits it can deliver within the security landscape are still largely undiscovered. This article will share real-world applications and considerations for organizations looking to use AI video surveillance.

Understanding the Shift Toward AI Video Surveillance

Many organizations are concerned with improving the visibility, safety, and proactivity of their video security. Technology without these qualities can leave you feeling uncomfortable, frustrated, and stressed. AI video surveillance aims to solve this by enhancing all aspects of traditional security, including monitoring, management, and response.

We’ve seen video security evolve from DVR and NVR to cloud and hybrid cloud—now we’re witnessing a shift to true AI video security. AI empowers companies to accomplish more with fewer resources, pushing many organizations to find ways to integrate AI into their tech stack. Not only does AI video security improve efficiency, but it can also help interpret video to resolve incidents before they escalate. When incidents occur, AI can understand what’s happening with human-like perception and trigger real-time alerts for immediate response.

Most video security vendors market some level of AI, but those capabilities vary wildly among products and are often limited to basic face and license plate recognition or some variation of appearance search. There are a multitude of different AI security options, but finding the right one largely depends on your needs and requirements. We’ll explain the options available to you in the “How to Implement AI Video Surveillance” section later in this article.

How Different Industries Can Use AI Video Surveillance

Video security has historically been used solely to record footage. Even with recent technological advancements, video security is still used this way—as a video recording tool that is reactive and used only after an event has already occurred. By implementing AI, organizations can turn video security into a proactive solution to identify abnormal events and unlock new possibilities.

AI video surveillance provides tailored advantages over traditional systems to reflect the unique needs of various industries. Below are a few practical examples of how organizations can leverage AI video security.

• Manufacturing: AI video surveillance can be used to monitor assembly lines, ensure safety protocols are followed, and detect unauthorized personnel or dangerous behaviors to create safer, more productive work environments.
• Schools: AI video surveillance can be used to protect campus perimeter zones and off-limits areas and issue real-time alerts to school safety staff when suspicious faces, vehicles, or behaviors are identified.
• Commercial Real Estate: AI video surveillance not only provides enhanced visibility but can also be used to supply real-time insight into foot traffic, occupancy, vandalism, loitering, theft, and tampering of building equipment.

How to Implement AI Video Surveillance

Selecting the proper method for AI video surveillance is critical to your success. Choosing the wrong method can drain resources, lead to low adoption, or provide a subpar user experience. Organizations looking to implement AI video security generally have four avenues: in-camera AI, AI analytic add-ons, cloud video security, or unified AI video security.

In-Camera AI

Many leading camera brands incorporate in-camera AI technology. This approach is often the most cost-efficient way to begin using AI. However, built-in AI capabilities are typically limited in scope and accuracy. This limitation is primarily due to the constrained AI resources in these devices and the use of generic models, which receive infrequent updates.

AI Analytic Add-Ons

AI analytic add-ons layer onto your existing video security system. With this option, you can keep your existing camera system and add additional AI capabilities as needed. Analytic add-ons vary in ease of implementation and typically require additional hardware or software, resulting in higher costs. Additionally, this method often delivers a poor user experience as it works alongside your primary video management system (VMS) and does not effectively manage the entire end-to-end experience that organizations require. 

Cloud Video Security

The next option is a recent advancement within the video security space. Cloud video security systems have more modern features and some AI capabilities to simplify security management compared to legacy on-premise systems. While system architecture is more contemporary, the AI technology is limited due to the cost of processing and the bandwidth required to send video to the cloud. Additionally, due to bandwidth limitations, cloud AI analytics deliver lower resolution and frames-per-second (FPS), which result in lower detection accuracy. Cloud video security systems focus primarily on providing a better video security experience, not necessarily a smarter one that leverages advanced AI models.

Unified AI Video Security

The last option, unified AI video security, provides an all-in-one experience that seamlessly integrates video security with advanced AI. Unlike the other three options, this solution is constructed with AI at its core. Then, a complete video security system is built around the AI to ensure an optimal end-user experience. Unified AI video security is typically camera-agnostic, meaning it can work with any device. It also features hybrid-cloud architecture to provide modern cloud features with significant processing power to run complex AI models at high FPS and resolution.

Unified AI video security is the best way to merge AI analytic providers and cloud video security systems with no potential drawbacks. The choice ultimately depends on your organization’s needs, readiness, and long-term security vision. If AI video surveillance is part of that vision, then adopting a unified solution will ensure success both now and in the future.

Key Considerations for an Effective AI Video Surveillance Strategy

Consider how a vendor solves and handles the following points when implementing an AI video surveillance solution.

Future Proofing

AI is progressing rapidly, with new and impressive applications emerging daily. Selecting an AI solution that is dynamic and continually evolving, rather than stagnant, is crucial. Choose a solution that consistently offers state-of-the-art capabilities and regular system updates, ensuring it always remains modern and up-to-date.

Technical Compatibility

Assess how compatible your existing infrastructure is with AI demands. Not all organizations are ready for a complete system overhaul; some may want to take their time to transition. Before researching viable solutions, it’s always best to ask if you are solving for one specific use case or looking to implement AI broadly to transform how you manage security, safety, and operations.

Data Handling and Privacy

The right solution for your organization should always handle your data responsibly and in a privacy-sensitive manner. Enterprise-grade encryption, pen tests, SOC 2 compliance, MFA, and automatic firmware updates should be standard with any solution you are looking into.

Cost Implications

Ensure you understand the financial nuances such as up-front costs, total cost of ownership, and potential savings due to increased efficiency or prevented incidents. Many organizations look only at up-front expenses, but when evaluating AI solutions, it’s essential to factor in the intangible benefits your organization will gain by implementing AI. These benefits could include preventing safety incidents, saving money by responding immediately to an event, or saving time on general system maintenance.

Considering these details will ensure a smooth and successful adoption of advanced AI video security technologies.‍

How AI is Transforming Anomaly Detection and Physical Security

With rapid digitalization, evolving risks, and the growing complexity of operational management, traditional video security methods are no longer enough. By leveraging AI video security, organizations can configure custom alert triggers, define what type of event is anomalous or unwanted, and receive immediate alerts when incidents need attention. These triggers can be expanded upon to address unique business problems, providing new and innovative possibilities.

AI within video surveillance has revolutionized how we perceive and interact with our environment, allowing us to automatically detect anomalies, pinpoint objects of interest, sift through countless hours of footage quickly, and even enhance video using generative AI techniques. Beyond physical security, AI offers unprecedented clarity and insight into our surroundings and will become a cornerstone in managing our spaces for years to come.