AI Inspection Model Library

Analog Gauge Reading Asset Maintenance InFlightAI’s Analog Gauge Reading model uses computer vision AI to automatically read analog pressure, temperature and flow gauges, as well as tap counters. Trained on thousands of gauges across hundreds of industrial types, it accurately interprets readings from varied angles using parallax correction and supports complex configurations, including multi-needle and side, bottom and center-pivot designs. Bags and Packages Physical Security Patrol InFlightAI's Unexpected Object Detection model uses computer vision AI to identify unattended bags, backpacks, and packages. It supports real-time security monitoring and flags potential threats or anomalies in operational areas. Corrosion Detection Asset Maintenance InFlightAI's Corrosion Detection model uses computer vision AI to identify rust, oxidation, and material degradation on equipment and infrastructure. It enables early intervention and extends asset lifespan by supporting proactive maintenance strategies. Crack Detection Asset Maintenance InFlightAI's Crack Detection model uses high-resolution computer vision AI to identify surface cracks in structures such as walls, foundations, and equipment. It detects fine and large-scale defects, supporting structural integrity assessments and maintenance planning. Cross Arm Condition Asset Maintenance InFlightAI’s Cross Arm Inspection model uses computer vision AI to assess cross arm alignment and structural condition. It detects tilt, warping, and material degradation such as wood splitting or rot, helping identify stability risks and prioritize maintenance. Digital Panel Reading Asset Maintenance InFlightAI’s Digital Panel Reading model uses AI-powered OCR and image processing to automatically read digital panels. It supports both pre-trained and custom OCR, identifies and reads multiple panels within a single image, and allows targeted text selection when multiple readings are present. The model accurately interprets seven-segment displays and screen-based readouts for monitoring temperature, pressure, and voltage. Encampment Detection Physical Security Patrol InFlightAI’s Encampment Detection model uses computer vision AI to identify unauthorized encampments on or near monitored properties, including tents, makeshift shelters, and clusters of personal belongings. It supports proactive site management and helps security and facilities teams respond consistently and appropriately. Equipment Tag Reading Asset Maintenance InFlightAI's Equipment Tag Reading model uses AI-powered OCR and image processing to automatically detect and extract asset identifiers from labels, tags, and nameplates. It supports varied formats, orientations, and lighting conditions, enabling accurate asset tracking, inventory management, and inspection workflows. Fuse Status Inspection Asset Maintenance InFlightAI’s Fuse Condition Inspection model uses computer vision AI to determine fuse state and condition, including open and closed positions as well as visible damage. It enables automated inspection of protective devices to ensure proper operation and reduce the risk of electrical faults. Gate Open/Close Physical Security Patrol InFlightAI's Gate Monitoring model uses real-time computer vision AI to detect gate position and state changes. It enables automated tracking of access points and improves perimeter security and compliance. Graffiti Detection Physical Security Patrol InFlightAI’s Graffiti Detection model uses computer vision AI to identify graffiti, tagging, and unauthorized markings on walls, equipment, and infrastructure. It supports rapid remediation workflows, helps maintain property appearance, and reduces the long-term visibility and cost of vandalism. Hotspot Detection Asset Maintenance InFlightAI's Hotspot Detection model uses real-time thermal analysis to identify localized high-temperature areas on equipment, wiring, infrastructure and ground surfaces. Designed for live monitoring workflows, it highlights critical risk zones that may indicate imminent failure or the risk of wildfire, enabling rapid response and improved operational safety. Insulator Condition Inspection Asset Maintenance InFlightAI's Insulator Assessment model uses computer vision AI to detect damage, flashing, contamination, and degradation in electrical insulators. It identifies cracks, chips, and buildup that may impact performance, supporting preventative maintenance and reducing the risk of outages. Liquid Spill Detection Asset Maintenance InFlightAI's Liquid Spill Detection model uses computer vision AI to identify equipment leaks, spilled liquids, and chemical releases on surfaces and floors. It focuses on operational hazards from equipment failure or handling errors, supporting rapid containment response and safety compliance. Perimeter Inspection: Climbing Aid Physical Security Patrol InFlightAI's Climbing Aid Detection model uses computer vision AI to identify objects near fences that could enable unauthorized access, such as ladders, stacked materials, or equipment. It helps proactively mitigate security vulnerabilities. Perimeter Inspection: Fence Anomaly Physical Security Patrol InFlightAI's Fence Anomaly model uses computer vision AI to detect irregularities along perimeter fencing, including damage, missing sections, attached objects, and obstructions. It supports automated inspection workflows to maintain secure boundaries. Perimeter Inspection: Vegetation Physical Security Patrol InFlightAI's Vegetation Monitoring model uses computer vision AI to detect overgrowth near fences and critical infrastructure. It identifies areas where vegetation may obscure visibility or create security and maintenance risks. Person Detection Physical Security Patrol InFlightAI's Person Detection model uses real-time computer vision AI to identify and count individuals within a scene. It supports live monitoring, occupancy tracking, and security workflows across facilities and perimeters. Powerline Splice Detection Asset Maintenance InFlightAI's Splice Detection model uses computer vision AI to identify and localize splices along powerlines. It enables inspection teams to verify splice integrity, monitor wear, and ensure compliance with maintenance standards. Powerline Wire Status Asset Maintenance InFlightAI's Powerline Wire Status model uses computer vision AI to monitor the condition of overhead wires. It detects sagging, breaks, and abnormal positioning, helping identify safety risks and maintain system integrity across transmission and distribution networks. PPE Detection Asset Maintenance InFlightAI's PPE Detection model uses computer vision AI to automatically verify the presence of required personal protective equipment, including safety vests, hard hats, and gloves. It supports safety compliance monitoring across industrial environments and flags violations to reduce risk and improve adherence to safety protocols. Security Door Open/Close Physical Security Patrol InFlightAI's Door Monitoring model uses real-time computer vision AI to determine door state (open or closed). It supports security and operational workflows by identifying unauthorized access or improper closures. Sight Glass Reading Asset Maintenance InFlightAI’s Sight Glass model uses AI to automatically read liquid levels in cylindrical and glass tube sight glasses, including circular “bullseye” gauges. It ensures oil levels remain within defined operational thresholds and supports horizontal level detection for accurate monitoring. Smoke Detection Asset Maintenance InFlightAI's Smoke Detection model uses computer vision AI to identify visible smoke in industrial and outdoor environments. It enables early warning of fire-related incidents and supports rapid response to reduce damage and safety risks. Thermal Anomaly Detection Asset Maintenance InFlightAI's Thermal Anomaly Detection model uses computer vision and thermal imaging AI to automatically identify abnormal heat signatures across equipment and infrastructure. It detects early indicators of overheating, electrical faults, and mechanical failure, enabling proactive maintenance and reducing unplanned downtime. Thermal Person Detection Physical Security Patrol InFlightAI's Thermal Person Detection model uses thermal imaging AI to detect human presence in low-light or no-light conditions. It enhances security coverage and reliability in challenging environments where traditional vision systems are limited. Trailer Contents Monitoring Physical Security Patrol InFlightAI’s Trailer Contents Monitoring model uses real-time computer vision AI to detect open trailer doors with visible contents inside. It supports loading dock efficiency and theft prevention by flagging trailers that require attention—whether closing up an unattended load or completing a pending delivery, or flagging doors that are left open or improperly secured. Trailer Detection Physical Security Patrol InFlightAI’s Trailer Detection model uses real-time computer vision AI to identify and count trailers across distribution centers, yards, and staging areas. It supports inventory visibility, dock utilization, and logistics planning by providing accurate counts and locations of trailers in monitored zones. Trailer Door Tag Detection Physical Security Patrol InFlightAI’s Trailer Tag Detection model uses AI-powered OCR and computer vision to identify and read trailer door tags, seals, and identifiers. It supports tracking, audit, and compliance workflows across distribution centers and logistics operations. Trash and Debris Physical Security Patrol InFlightAI's Debris Detection model uses computer vision AI to identify foreign objects, trash, and clutter in monitored environments. It helps maintain operational cleanliness, safety, and compliance. Unexpected Water Detection Asset Maintenance InFlightAI’s Water Detection model uses computer vision AI to identify unexpected water presence and accumulation across operational environments. It detects flooded areas, pooling water, and abnormal moisture conditions that may indicate drainage issues and safety hazards. Utility Pole Status Asset Maintenance InFlightAI's Utility Pole Status model uses computer vision AI to assess the structural condition of utility poles. It detects issues such as leaning, cracking, rot, and physical damage, providing actionable insights for maintenance prioritization and infrastructure reliability. Utility Pole Vegetation Encroachment Asset Maintenance InFlightAI’s Vegetation Encroachment model uses computer vision AI to detect vegetation growing too close to utility poles and associated infrastructure. It identifies clearance violations that may pose safety risks or interfere with operations, supporting proactive vegetation management. Valve Positioning Monitoring Asset Maintenance InFlightAI's Valve Monitoring model uses computer vision AI to determine valve position states (open, closed, partially open) across industrial systems. It supports remote verification of operational status and helps prevent process disruptions or safety incidents. Vehicle Identification (LPR & VIN) Physical Security Patrol InFlightAI's Vehicle Identification model uses AI-powered OCR and computer vision to read license plates and vehicle identification numbers. It supports access control, tracking, and audit workflows across facilities. Weapons Detection Physical Security Patrol InFlightAI's Weapons Detection model uses computer vision AI to identify visible weapons such as firearms and other threats in monitored environments. It supports security teams with early detection and rapid escalation workflows. Wildlife Detection Physical Security Patrol InFlightAI’s Wildlife Detection model uses computer vision AI to identify the presence of animals in monitored environments, including birds, mammals, and other wildlife near critical infrastructure. It supports safety, operational continuity, and risk mitigation by flagging incursions that may impact equipment, perimeters, or personnel.