On-site learning for AI systems set to change up the surveillance industry
In the rapidly evolving landscape of artificial intelligence, 2024 is poised to witness a significant surge in AI adoption within the physical security market. While AI has already made substantial contributions to security through advanced monitoring features like human and vehicle detection, Missing Object alerts and more, the next leap forward lies in the realm of customisable on-site learning for AI systems. This advancement is expected to revolutionise how businesses utilise data for security and operational purposes.
The current generation of AI-based security cameras has demonstrated their ability to reduce errors and enhance surveillance capabilities by reliably identifying humans and vehicles. However, the true potential of AI in security is yet to be fully harnessed. The forthcoming wave of AI adoption will be driven by the integration of on-site learning capabilities, allowing businesses to tailor AI analytics to recognise specific and unique objects relevant to their operations.
One of the key advantages of on-site AI training is the ability to recognise and track objects that are crucial for business intelligence. Traditional AI models may struggle to discern specialised items such as logos on vehicles or uniforms, count various objects like planes, forklifts, or even baby prams accurately. The on-site training of edge devices, such as security cameras, enables a more personalised and nuanced understanding of the unique elements that matter to a particular business.
The customisation of AI analytics on-site opens up new avenues for businesses to extract valuable insights from security camera data. For example, the ability to recognise logos on vehicles can aid in brand monitoring and asset tracking. Counting forklifts or other specific objects in a warehouse or logistics facility can contribute to inventory management and workflow optimisation. This granular level of data collection and analysis, directly harvested through edge processing within security cameras, promises to be a game-changer in the realm of business intelligence.
The implications of this on-site AI training extend beyond security measures, which changes the capital expense of setting up a surveillance network into more of an operational expense. The newfound stream of business intelligence data can be leveraged to enhance operational efficiency and service quality, thereby bringing new measures of productivity into the business. Automated workflows can be fine-tuned based on real-time insights from the AI systems, streamlining processes and reducing the need for manual intervention. This not only saves time but also minimises the likelihood of errors associated with human oversight.
Moreover, the integration of on-site AI training introduces the potential for AI-based systems to move beyond passive surveillance to proactive assistance. For instance, these systems could detect when individuals require assistance, whether due to a security threat or a medical emergency. The ability to notify about potential hazards, such as a wet floor, can prevent accidents and injuries, showcasing the broader societal impact of AI in physical security.
The shift towards on-site AI learning signifies a paradigm shift in how businesses approach and benefit from artificial intelligence. It aligns with the growing demand for personalised and adaptable solutions that cater to the unique needs of each organisation. As businesses increasingly recognise the importance of harnessing AI for a competitive edge, the ability to train AI models on-site will become a crucial differentiator.
In conclusion, 2024 is poised to witness the ascent of on-site AI learning as the next frontier in AI adoption within the physical security market. The customisable nature of this technology empowers businesses to train AI analytics to recognise specific objects, leading to a wealth of business intelligence data. This data, harvested through edge processing within security cameras, not only enhances security measures but also contributes to operational efficiency and service quality. As AI-based systems evolve to provide proactive assistance, the impact of on-site AI learning will extend beyond security, shaping a future where AI plays a pivotal role in optimising various aspects of business and societal well-being.
