The integration of Artificial Intelligence (AI), Robotics, and Computer Vision is revolutionizing industrial monitoring by automating traditionally manual and time-consuming tasks, increasing both efficiency and safety. This thesis explores the integration of these technologies into a proprietary AI framework, to enhance industrial visual analysis through Autonomous Mobile Robots (AMRs), focusing on two key tasks: Automated Gauge Reading and Autonomous Surveillance in Restricted Areas. The first task addresses the challenge of continuously monitoring pressure gauges in large-scale industrial environments, a process traditionally performed by human operators and prone to errors and inefficiencies. To overcome these limitations, this study employs Boston Dynamics' Spot, a quadruped robot functioning as a mobile Internet of Things (IoT) platform capable of executing pre-configured inspection missions.