How Edge Analytics and AI Transform CCTV into Visual Intelligence

In a world where the need for flexible and intelligent security infrastructure is ever more apparent, businesses and organizations are seeking innovative solutions to ensure the safety and efficiency of their operations. The evolution of the security landscape is relentless, driven by the exponential growth of data generated by CCTV cameras and the ever-changing nature of security requirements. Edge analytics emerges as a pivotal paradigm that promises to transform the way we approach surveillance, analysis, and decision-making based on business insights generated through AI.

According to the SIA (Security Industry Association) 2024 Megatrends report, AI is the overarching megatrend, with the security of AI as one main focus and with the transformation of video surveillance into visual intelligence as the megatrend that describes the development of cameras to the ultimate sensors. “The camera is rapidly becoming the ‘everything tool’ in our industry – moving beyond its early capacity as a recording device and creating the opportunity for exponential value,” states the report.

Edge analytics is a specific approach that involves real-time data analysis at the source of data generation. AI, on the other hand, is a broader field encompassing various techniques for data analysis and decision-making, which can be applied both locally and in centralized systems, with a focus on adaptability and handling complex data. Tailored for real-time processing at the edge, edge analytics is a subset of AI that witnessed the biggest market growth globally. It allows for the immediate detection of events and incidents, which is crucial for quick responses to security threats. By processing data at the source, close to the field, organizations can significantly reduce latency, ensuring rapid decision-making and timely action.

The Exponential Growth of Video Data

The growth of the CCTV industry has been staggering over the past few decades. Cameras have become ever present, recording vast amounts of video data that serve as critical input for security operations. The sheer volume of data generated by these cameras is beyond what humans can reasonably handle, making it increasingly clear that the reliance on technology is not an option but a necessity.

From identifying security threats in real-time to extracting valuable insights from historical footage, the need for advanced analytics is greater than ever before. AI and edge analytics applied together make the cameras so much more valuable to end users, especially when you compare unmonitored cameras with modern 24/7 monitoring and alerts in real time.

The combination of artificial intelligence and modern camera technology elevates video surveillance to a new level, requiring high-quality and clear images for accurate data analysis. The need for surveillance in public and private environments has steadily increased. Video surveillance no longer just secures an area visually; AI-based deep learning analyses allow for full utilization of video surveillance’s potential. The surveillance cameras act not only as a video device but also as a sensor that detects suspicious activities or behavior patterns. This enables security personnel to be notified proactively and instantly to take timely action.

For example, edge analytics combined with AI can be used in traffic management. Traffic cameras equipped with AI can monitor traffic flow in real-time, identify accidents or traffic jams, and optimize traffic signal timings accordingly. This proactive approach not only improves traffic efficiency, but also enhances road safety.

Evolving Safety Requirements

Edge analytics and AI make security systems future proof. Safety requirements are constantly evolving, driven by changes in technology, threats, and regulations. The question that security professionals face is how to ensure that investments in security infrastructure deliver a tangible return on investment, even as circumstances and demands change. The way forward lies in adopting flexible and intelligent security systems that can evolve and adapt to the shifting landscape of safety and technology.

Consider the security requirements at airports. Today’s security standards have evolved beyond traditional metal detectors and X-ray machines. Threats have become more sophisticated, and regulations have changed. Edge analytics enables airport security systems to rapidly adapt to these evolving needs. For instance, an AI-powered camera can detect anomalies in passenger behavior, triggering immediate alerts to security personnel while also monitoring abnormal crowd movements.

Edge Analytics and the Role of Artificial Intelligence (AI)

Rather than relying on centralized servers or cloud-based processing, edge analytics takes place directly on the camera or at the network’s edge. This approach offers real-time analysis, without the need for extensive network bandwidth or delays associated with cloud processing.

Artificial intelligence plays a pivotal role in the advancement of edge analytics. Deep learning-based analysis empowers cameras with the ability to detect suspicious changes in scenes, automatically adjust image settings, and optimize video compression. These AI-driven capabilities enhance the efficiency of edge analytics.

Edge analytics, coupled with AI, opens up new possibilities for security professionals. It ensures that data generated by security cameras is not just a passive recording but also a source of proactive intelligence. Security systems can now respond to potential threats in real-time, providing a level of protection and operational efficiency that was previously unattainable.

i-Pro’s AI-enabled security cameras are designed for edge analytics and come with a powerful built-in AI processor that enables integrated AI functions directly within the camera. This allows video and image data to be processed and analyzed on the cameras themselves. The cameras structure, filter, and categorize their data, then transfer the metadata via i-Pro Active Guard to the video management system (VMS). The software captures, filters, and classifies the best shots and metadata based on deep learning, matching them with the database. Since the video stream is not fully transmitted to the VMS, only a small amount of data volume is required.

The Future of Security

In a rapidly changing world, where security requirements are evolving, and the amount of video data generated is overwhelming, edge analytics and AI offer a promising path forward. These technologies enable flexible, intelligent, and responsive security solutions that can adapt to changing circumstances and demands, and they can improve the return on invest (ROI) of security installations, another megatrend in the industry. Security professionals can keep their focus on protecting people and assets, but now they are also able to show operational ROI that benefits other departments.

As the security industry continues to embrace edge analytics and AI, surveillance will evolve from passive monitoring to active intelligence and insights, making our environments not just safer but also more efficient. At the same time, the ethical use of AI is crucial to ensure fairness, transparency, accountability, privacy, and security, fostering trust and widespread adoption while aligning with societal values. i-Pro plays a significant role in promoting ethical AI by developing standards that uphold these principles, protecting personal data, and creating responsible AI solutions for public safety.

i-Pro is leading the way in edge analytics and AI, and the launch of the new X-series range shows its dedication to real-time, adaptable security hardware, improving safety and efficiency. This innovative line of cameras extends the capabilities of edge analytics and AI to a previously unattainable level. These cameras not only have learning capabilities but can also analyze their own video stream as well as video streams from other non-AI cameras already installed within a video surveillance system. The X-series marks a significant advancement in AI accessibility.