A Watchful Eye

Addressing these challenges demands a strategic approach that leverages technology, fosters collaboration across departments, and prioritizes sustainability, safety and occupant well-being. Technology should intertwine with architecture, making visibility into the activities and health of buildings easier than before.

The smart building industry continues to grow, and with it, technologies like sensors, lighting, building management systems and IoT devices are evolving. One incredibly fast-growing segment is video monitoring. The size of the video monitoring market in the U.S. is estimated at US$12.3 billion in 2024, and is projected to reach US$22 billion in five years, according to Mordor Intelligence. That is a compound annual growth rate of 12.3 percent.

Advancements in data gathering and artificial intelligence (AI) have supercharged growth in video monitoring, as video analytics can now be applied to video data. By using machine learning and computer vision, these technologies can constantly monitor and analyze video content, providing usable information and insights. AI-powered video analytics software can quickly detect suspicious or abnormal activities, and distinguish between people, vehicles, animals and other objects.

The largest applications for video analytics involve security. Effectively monitoring and managing crowded spaces is a formidable challenge for FMs. Data annotation tools enable AI algorithms to count the number of heads or people in real time. This is accomplished by training AI models on meticulously labeled images and videos, which allows them to learn the visual characteristics of people. Once trained, these models can be deployed to manage crowd movement, detect suspicious activity and prevent potential accidents. These systems can provide updates on crowd density and movement patterns, helping security personnel identify potential bottlenecks and take necessary measures to ensure safety.

The evolution of video monitoring

Video technology has come a long way since its inception. The widespread commercial use of surveillance cameras began in the early 1970s, thanks to the combination of increasingly sophisticated closed-circuit television systems and video recorders. Facilities could finally record security footage, review it later; then save it or record over it. Over the years, the camera quality got better, and the size got smaller.

Monitoring still relied on CCTV networks and VCRs until the digital revolution began in the 1990s. Digital cameras could record video footage on hard drives and flash storage rather than magnetic tape. The first Internet Protocol (IP) camera arrived in 1996, which removed the need for a closed-circuit system.

Fast forward to today, and AI and cloud computing have disrupted the market. The migration of video monitoring to the cloud represents a convergence of two powerful forces: the growing demand for enhanced security and business intelligence and the need for scalable, flexible and accessible solutions. With cloud video surveillance, facility owners and managers can easily add or remove cameras, add storage capacity and expand coverage without the need for significant hardware investments. The cloud enables remote access and monitoring of video feeds from anywhere, anytime.

Authorized personnel can securely view live video streams and access recorded footage using various devices, such as smartphones, tablets or laptops. Having greater access to video footage empowers FMs to monitor multiple locations and respond to incidents faster even when physically distant from the surveillance site.

Cloud computing is not a strict requirement for AI-driven video analytics. Many AI algorithms can run directly on local devices, such as cameras or on-premises servers. Cameras with powerful processors can do more video data processing than ever before. This approach, often called edge computing, has benefits, including reduced latency, enhanced privacy and security, and the ability to operate in environments with limited or no internet connectivity.

Enhanced edge processing can also make cloud-based systems efficient and less costly to operate. Cloud computing can boost the capabilities of AI by providing the infrastructure, resources and services to enable FMs to efficiently deploy and scale AI applications. In addition, AI algorithms, especially deep learning models, benefit from large cloud-accessible datasets for training purposes. Cloud-based systems are making AI features attainable for businesses of any size because of the economies of scale. However, keep in mind that the volumes of video data are quickly growing thanks to the adoption of ultra-high-definition and 4K cameras. The growth necessitates investments in robust storage infrastructure and bandwidth.

Video analytics elevated by data and AI

The accuracy of surveillance systems has improved due to advancements in object and facial recognition, behavior analysis and anomaly detection. The heightened precision enables:

• Reduced false positives/negatives: Data and AI can reduce false alarms by distinguishing between normal activities and potential security threats. Similarly, data and AI can minimize false negatives by detecting and alerting operators to events that might have been missed by human operators or traditional surveillance systems.

• Increased detection rates: Smart video surveillance systems can achieve higher detection rates for specific objects, behaviors or individuals than traditional methods. AI filtering can differentiate types of motion detected and alert users to vehicles or persons, while eliminating other motions, such as a tree blowing in the wind.

• Faster response times: AI enables real-time video data analysis, allowing for immediate alerts to enable quicker responses to security incidents.

• Improved operational efficiency: By automating the analysis of video data, AI can reduce the burden on human operators and shrink error rates, enabling higher productivity and more efficient use of resources.

Advancements in video analytics are shaping the future of the alarm monitoring industry. Many facilities rely on central station alarm monitoring to help give them peace of mind. Professional video monitoring can allow facilities to have continuous site visibility without additional personnel or payroll. However, in previous generations of video motion detection technology, false alarms were often a problem, triggered by everything from animals to wind-blown branches. More than 90 percent of sensor-based alerts are false positives, according to Eagle Eye Network’s 2024 Video Surveillance Trends report. Investigating each alarm has the potential to drive up customer costs. In addition, the process of manually watching video can be tedious, ineffective and oftentimes expensive.

However, newer AI-powered features mean alarm-monitoring companies can use cameras as sensors that generate intrusion alarms, providing action-based intelligence for central stations in real time. The technology is different than video verification, in which cameras are commonly used in tandem with alarm sensors to corroborate an alarm. The security industry calls this new service “proactive video monitoring” or “smart surveillance.” AI now “watches the video” and provides alerts and content-based search capabilities, helping to make video monitoring and the investigative process scalable and effective.

Beyond security, video analytics has the potential to improve workplace health and safety, a growing priority as more workers return to the office. The same cameras that are used to detect loitering and intrusion can also alert workers entering restricted or high-risk areas. They can also recognize early signs of smoke and fire and can be used to track the flow of evacuation through the facility and support rescue teams. The benefit of video-based monitoring is that the safety systems are always-on, enabling facilities to monitor compliance with workplace health and safety regulations. For example, certain video surveillance could detect if employees wear appropriate personal protective equipment and help identify potential hazards, such as spills, equipment malfunctions or unsafe behaviors, to prevent accidents. AI solutions are also helping to make parking lots smarter and more secure by controlling access through license plate recognition and analyzing utilization to help drivers find available spaces.

One of the common requests from facility managers, according to the above-mentioned Eagle Eye Networks report, is integrated video monitoring and access control. An integrated system can help security managers better control access to designated facilities and areas and deliver immediate visibility and tracking capabilities. Open video monitoring platforms enable easier integration and customization with access control and other security applications.

Accessible video application programming interfaces promote collaboration, innovation and flexibility — traits that are essential to anticipating the future needs of smart buildings. By opening access to video data and functionalities, developers can experiment with different ideas and build new solutions to address specific challenges, as well as provide users with a more personalized and tailored experience. Interoperability helps foster the growth of a vibrant ecosystem of developers, partners and third-party vendors. A diverse ecosystem leads to the availability of a wide range of video-related applications, services and integrations, giving end users more choices and opportunities.

The role of FMs has become more intricate than ever, as they continue to grapple with myriad challenges. Modern video and video analytics are powerful tools in navigating this world, and its rapid growth marks a transformative era in security, business intelligence and public safety. The integration of AI, machine learning and computer vision has propelled the evolution of video analytics. As technological advancements accelerate, intelligent video solutions expand beyond traditional surveillance to modernize industries and enhance human experiences. With its ability to extract valuable insights from vast amounts of visual data in real time, video analytics empowers facilities to make informed decisions, mitigate risks and unlock new opportunities for innovation.