As of 2025, the IoT landscape predicted back in 2020 has largely materialised and expanded significantly. The number of enterprise and automotive Internet of Things (IoT) endpoints has grown substantially, far surpassing earlier forecasts. A considerable portion of this expansive network consists of physical security devices, particularly advanced video surveillance IP cameras. These cameras are pivotal in gathering vast amounts of data, extending well beyond traditional security monitoring and facial recognition to encompass a wide array of operational and analytical applications.
The historical focus on using cameras primarily for post-event analysis of security incidents has firmly shifted. Today, in 2025, the deployment of IoT-driven applications like AI-powered people counting, dwell time analysis, and sophisticated object recognition and classification is standard practice. These capabilities are routinely used to optimise operations, enhance customer service, and provide end-users with real-time business intelligence through comprehensive analytics dashboards, enabling better resource allocation.
A smart, IoT-centric approach, often featuring tight integration with diverse physical IoT sensors, continues to be highly effective in reducing the high volume of false alarms historically generated by simpler sensors. Modern cameras, equipped with advanced AI software capable of accurately distinguishing between humans, animals, vehicles, and other objects, allow security personnel to triage alerts efficiently, confirming or dismissing them rapidly and thereby mitigating alarm fatigue.
Furthermore, the integration capabilities of surveillance cameras within the broader IoT ecosystem have matured. Beyond their standalone data-gathering and analytical functions, cameras are commonly combined with other physical security systems, such as IoT-enabled access control and intrusion detection systems. This synergy unlocks advanced security functionalities. For instance, leveraging video analytics combined with card readers for enhanced identity verification at critical access points is a widely adopted practice, adding a crucial layer of security through real-time facial recognition cross-referencing.
Organisations are also effectively utilising integrated camera and sensor solutions to combat persistent issues like tailgating, especially in areas where traditional barriers like turnstiles are impractical. Access readers paired with AI-powered cameras provide immediate alerts upon detecting unauthorised entries, allowing for swift incident response. Given ongoing threats like active shooters and data theft, such integrated capabilities are considered essential for organisations of all sizes in 2025.
The value proposition of IoT applications is significantly amplified when incorporating video analytics. For example, while location data from beacons connected to customer smartphones in retail environments provides basic insights, integrating this data with video analytics yields far richer information, detailing shopper demographics like gender and age groups, thus adding substantial value.
Embedded sensors on buildings, vehicles, personnel, and equipment continuously generate data. This data is processed either locally at the edge for immediate action or sent to the cloud for in-depth analysis, providing critical insights into the real security posture. Based on these insights, decisions are made to activate alarms or dispatch personnel. The seamless integration between IoT platforms, their analytics layers, and sophisticated Video Analytics systems is now fundamental to delivering an optimised end-user experience, characterised by minimised false alarms and maximised actionable intelligence.
