Edge Generative AI Solutions for Industrial Security
A. Alangari, F. Alsumail, Al Dajani, Ahmad A Alkhabbaz, Abdulaziz Mohammed Alanazi · 2025
As computing chips become smaller and more efficient, the amount of compute that can be processed by smaller devices are getting increasing exponentially. This, coupled with the industrial need to enhance security, safety, and operational efficiency through Artificial Intelligence (AI) in remote areas where there are limited connectivity options have created unforeseen opportunities at the edge, minimizing the dependence on highspeed connectivity. This white paper presents a comprehensive analysis of the industrial security applications of Edge Generative AI (Gen AI), a novel technology that enables real-time processing of AI models at the edge of industrial networks where users, and data points are close to each other. The industrial security sector is particularly well-suited to benefit from Edge Gen AI due to its reliance on complex, distributed systems and high-stakes decision-making that require real-time data. By deploying AI models closer to the source of the data, Edge Gen AI enables faster processing, reduced latency, and improved real-time insights – all of which are critical for enhancing security, detecting potential threats, and responding to incidents. Furthermore, the integration of Edge GenAI with Internet of Things devices and sensors can unlock new levels of monitoring, automation, efficiency in areas such as threat detection, incident response, and security analytics. This white paper provides an in-depth examination of the technical architecture, methodology, and performance results of Edge Gen AI in industrial security applications, including Gen-AI enabled Security and Surveillance, Autonomous Drones, and Emergency Response. Our goal is to share the knowledge gained from this pioneering technology and provide valuable insights for other organizations seeking to harness the power of Edge Gen AI to enhance their industrial security posture.