Video surveillance camera company Hanwha Vision has unveiled its key trend forecast for the video surveillance industry in 2025.
The company says the industry is poised to enter an era of super-intelligent video surveillance, transcending basic detection and search capabilities and moving towards autonomous decision-making based on comprehensive understanding and analysis.
Generative AI is propelling the advancement of edge AI devices, while cloud technology is unlocking the full potential of data utilization. Simultaneously, key factors are emerging that will reshape the video surveillance landscape, including the growth of an open AI ecosystem, better efficiency through integrated solutions, and reinforced privacy protection.
Generative AI is transforming numerous industries, and the video surveillance industry is no exception. Some cloud-based video management systems are already leveraging generative AI to enhance event search efficiency through intuitive natural language interfaces.
Hanwha Vision anticipates that generative AI, currently limited to cloud-based solutions, will permeate both on-premise systems and edge AI cameras by 2025.
Currently, generative AI is primarily used in management solutions like VSaaS (video surveillance as a service). This technology allows users to effortlessly retrieve specific video footage by simply describing the scene in natural language. For example, a user could request, “Show me footage of a person wearing red clothing meeting with someone in the lobby around 3 p.m. yesterday.” The system would then intelligently analyse the stored video data and deliver relevant results. It’s like giving a task to an AI assistant.
Looking ahead, edge AI cameras are predicted to evolve into intelligent AI agents capable of independently understanding and assessing situations, generating events, and providing real-time alerts.
For example, intrusion detection will transcend the limitations of conventional systems by analysing human behavioral patterns, such as running, loitering, or climbing fences, to determine intent, rather than simply detecting movement within predefined zones.
Similarly, fire detection will move beyond merely detecting smoke or flames. By analysing a broader context, including evacuation behavior and fire extinguisher use, these advanced systems will assess the likelihood of a fire and facilitate rapid response. This transformation will empower edge AI cameras to act autonomously on behalf of users, significantly enhancing security and efficiency.
Furthermore, Hanwha Vision predicts that security systems will be able to track a series of events or objects through multiple cameras using generative AI that understands the flow of time and the connectivity of events.
“The integration of generative AI and advanced Re-ID (Re-Identification) technology enables the development of more accurate and efficient object tracking systems,” said Hanwha Vision’s Chief Product Officer Andy Ryu, Chief Product Officer.
“This technology has far-reaching applications beyond criminal investigations and missing person searches,” he adds. “It can revolutionise traffic management and disaster response and even provide valuable insights into visitor behavior for optimizing operational efficiency and gathering marketing intelligence. This significantly enhances the utility of video surveillance systems across diverse industries.”
Re-ID technology excels at identifying the same person or object across images or videos captured at different times and locations.
The Rise of Collaborative AI Ecosystems
In 2025, the video surveillance market is poised for a transformative shift with the expansion of the AI ecosystem, ushering in an era of innovative change.
The days of individual companies competing to develop their own proprietary AI technologies are fading. Now, building and expanding an AI ecosystem through openness and collaboration has emerged as a key factor determining market competitiveness, promising limitless scalability and rapid innovation for the video surveillance market.
First, the AI ecosystem allows for easy expansion of functionality by integrating various AI solutions into video surveillance systems as needed. For instance, Hanwha Vision AI Box allows users to add sophisticated AI features, such as object detection/classification and advanced video analytics, to conventional security cameras without replacing existing infrastructure.
Another advantage of the AI ecosystem is its ability to meet diverse customer needs by providing customised solutions. Similar to adding apps to a smartphone, users can selectively deploy AI solutions optimized for their specific environment and objectives.
This flexibility allows for the creation of bespoke systems, such as integrating customer behavior analysis AI in retail stores or implementing production line monitoring solutions within smart factories.
Harnessing the Power of Cloud and Data
Cloud computing, with its ability to maximise data utilisation, has become indispensable for enhancing competitiveness in the video surveillance industry. A significant portion of the industry is embracing cloud adoption, leveraging various approaches like hybrid cloud and cloud-native architectures tailored to specific organisational needs and industry verticals.
As AI and cloud technologies become increasingly crucial for gaining a competitive edge through data utilisation, the demand for cloud migration in 2025 is expected to surge within data-intensive industries.
“With the growing need for AI solutions in the city, retail, logistics, and manufacturing sectors, the demand for cloud-based systems to efficiently process and analyse massive video datasets will intensify,” said Hanwha’s Head of R&D Solutions Seung In Noh
Integrating vast amounts of data from city, retail, and manufacturing sectors with cloud-based security systems unlocks a multitude of powerful capabilities.
Firstly, in urban environments, high-performance cloud computing enables efficient storage and processing of massive video data streams. This facilitates real-time analysis of traffic flow, enabling dynamic adjustment of signal cycles to optimise traffic management during peak hours. By analysing city-wide CCTV data, the system can also detect urban issues like illegal dumping and road damage in real-time, enabling rapid response and urban environment improvement.
In the retail sector, analysing customer behavior, including movement patterns, product interactions, and dwell times, optimises product placement and identifies high-potential buyers, maximizing marketing effectiveness. Cloud-based systems enable integrated management and analysis of data from multiple stores, revealing valuable insights into customer purchase patterns and trends for developing targeted marketing strategies.
In the manufacturing sector, integrating and analysing diverse sensor data, including temperature, pressure, and vibration, with video feeds in the cloud enhances production line efficiency and safety. For instance, if temperature sensor data exceeds a critical threshold and the system simultaneously detects smoke or flames in the video feed, it can assess the likelihood of a fire and instantly alert administrators, enabling rapid response.
Achieving True Efficiency
The rapid evolution of AI and cloud technologies has unlocked unprecedented capabilities in video surveillance systems. Paradoxically, this increased sophistication is driving a new paradigm focused on simplicity and efficiency.
Increasingly, the security market is shifting towards end-to-end solutions that seamlessly integrate various systems and services, expanding the scope of security. This transcends the traditional role of video capture and storage, encompassing integration with access control, fire detection, data analytics, and environmental sensors to create a comprehensive security framework.
However, building such end-to-end solutions presents challenges, including ensuring interoperability between disparate systems, managing integration costs, and mitigating potential functionality issues. To address this, there is a growing trend towards one-stop solutions where a manufacturer provides all necessary products and services for streamlined deployment. One-stop solutions ensure optimal compatibility between systems and enhance operational efficiency through unified management.
Alongside end-to-end solutions, another prominent trend is SPOG (Single Pane of Glass). SPOG provides a unified interface for managing and monitoring diverse systems and data, much like a single window offering a comprehensive view instead of fragmented perspectives.
Organisations can leverage SPOG, which supports standard protocols like ONVIF, to integrate and manage cameras, NVRs/DVRs, access control systems, and other components from various manufacturers within a single platform. With features such as data visualization, search, and filtering, SPOG facilitates real-time situational awareness and data-driven decision-making, enabling organizations to extract valuable insights for optimizing business operations.
By easily integrating heterogeneous systems, SPOG allows organisations to transform security centers into efficient business operation hubs. Video surveillance systems, once considered merely a form of insurance, are now evolving into strategic investments that directly contribute to profitability through concepts like SPOG.
The New Imperative in Video Surveillance
With technological advancements, increasing security threats, and growing demands for corporate social responsibility, the video surveillance market has entered a new phase.
Transparency has emerged as a crucial factor determining market competitiveness. The rise in cyberattacks, increasing public concern for personal data protection, and the growing complexity of software supply chains have intensified the demand for transparency in security systems. Consequently, companies are prioritizing initiatives that ensure transparency to bolster personal information protection and cybersecurity.
Companies are striving to achieve transparency in the following key areas:
Firstly, the increasing complexity of software supply chains, particularly with the widespread use of open-source software in video surveillance systems, necessitates greater transparency. A key solution gaining traction is the Software Bill of Materials (SBOM).
SBOMs enhance transparency by providing a comprehensive inventory of software components. While not yet mandatory in the video surveillance industry, the growing emphasis on SBOMs suggests potential future regulations. Some leading manufacturers are already adopting SBOMs, and Hanwha Vision will proactively begin issuing SBOMs for its products by the end of 2024.
Protecting personal information is also paramount in the industry. Privacy by Design (PbD), a philosophy that prioritises privacy from the initial design stage, is increasingly critical. Companies are actively developing data anonymisation technologies, such as privacy masking and mosaics, to implement PbD.
They are also enhancing data protection by incorporating encryption and ensuring data is processed only for specific, intended purposes. To this end, Hanwha Vision is integrating Dynamic Privacy Masking (DPM) as a built-in feature in its products, starting from the Q series AI cameras launching soon.
Recently, trustworthiness has become a critical factor in the video surveillance industry, extending beyond product safety to encompass a company’s entire operation. Customers and global evaluation agencies now scrutinize not only the safety of products but also the reliability of the companies that produce them, assessing their operational methods, processes, data management practices, and social responsibility.
