Computer Vision

Computer Vision for Inspection and Monitoring of Industrial Infrastructure

Large-scale industrial operations manage infrastructure networks spanning hundreds of miles. An energy company, for example, needs to maintain vast networks of electrical wires, distribution poles, transmission towers, electrical substations, and other critical assets. Because these assets are often located in remote and dangerous locations, inspecting them for maintenance issues demands high-risk expeditions, skilled labor, and an enormous amount of time and financial resources.

Detecting Rusty Pipe

Today, computer vision technology empowers industrial companies to achieve safer, more accurate, and more cost-effective inspections of key infrastructure components. Whether the computer vision inspection strategy involves IoT-connected smart cameras installed in remote locations, drones collecting visual data by air – or satellite imagery – a well-trained visual AI system can detect maintenance problems, environmental hazards, and safety concerns with higher degrees of accuracy than traditional methods of infrastructure inspection.

Get a demo of AI for infrastructure inspection with Industrial AI.

Traditional Methods of Infrastructure Inspection

The inspection and maintenance of critical infrastructure components is a necessary part of nearly every large-scale industry. Some common infrastructure types requiring inspections include:

  • Power lines
  • Utility infrastructure
  • Construction sites
  • Cell towers
  • Coastal shoreline erosion
  • Bridges
  • Roads and interstates
  • Hydroelectric dams
  • Wind turbines
  • Solar farms
  • Industrial agriculture
  • Wastewater and effluent

Each of the above use cases has developed its own standards and procedures for infrastructure inspection and maintenance – including inspections for compliance with environmental statutes. Traditional methods for performing these inspections may include the use of:

  • Human visual inspectors
  • Photogrammetry
  • Orthomosaics
  • 3D models
  • Geospatial information services
  • Aerial inspections by helicopter
  • Drone-based aerial photography
  • Satellite imagery
  • LiDAR
  • Ultrasound
  • Liquid penetration inspection (LPI)
  • Radiography
  • Infrared camera footage
  • Surveillance cameras installed at various inspection sites

Aside from using advanced technology, trained and experienced professionals are an integral part of most inspection processes. These inspectors frequently endure dangerous conditions to perform in-person evaluations using the human eye alone with no special instrumentation. Often traveling to remote areas by helicopter, working out of bucket trucks – or climbing up towers, wind turbines, bridges, and electrical distribution poles – human inspectors need to evaluate the condition of key assets to answer a host of questions.

Infrastructure inspectors may need to consider questions such as:

  • Is it rusty?
  • Is it structurally sound?
  • Are trees growing over a transformer box?
  • Are guy-wires intact?
  • Are key actions happening on schedule?
  • Is wastewater flowing properly through drain pipes?
  • Is it overheating?
  • Is it the wrong color?
  • Are power lines broken or hanging too low?
  • Is it leaking?

The Challenges of Traditional Infrastructure Inspections

Large-scale industrial operations spend millions of dollars each year to conduct visual inspections that rely on human eyes and human understanding without any special equipment. Until the recent introduction of computer vision technology, the use of human inspectors for these visual evaluations was a necessity. However, the following challenges continue to plague any inspection activities that rely on human eyes:

  • Slow and laborious: Getting human workers on-site to perform inspections at thousands of sites across hundreds of miles of distance is difficult, costly, and time-consuming – resulting in infrequent inspections and detection delays. For example, a wastewater treatment facility could be dumping contaminated effluent into a river for days – even months – before a human inspector detects the problem. Similarly, the infrequent inspection of hydroelectric facilities, cell towers, wind turbines, and other infrastructure components means that an inexpensive problem could grow into a devastating catastrophe.
  • Risky and dangerous: The process of sending human workers to remote sites to climb cell towers and key pieces of infrastructure is fraught with dangers. For example, workers climbing cell towers face the risk of electrocution, inclement weather (excessive wind, rain, lightning, hail, and snow), objects falling at high speeds, and protective equipment failures. The remoteness of inspection sites – combined with dangerous inspection tasks and safety training failures – elevates the chances and severity of injuries.
  • Error-prone: Whether they are performing inspections on-site, or remotely while viewing visual data collected by cameras, drones, and other detection equipment, inspectors can only achieve certain levels of accuracy due to the inherent limitations of their human faculties. Human inspectors are commonly overworked, lacking adequate rest, bored, inadequately trained, or without sufficient experience and expertise. These challenges result in errors, mistakes, and inconsistent inspection results.
  • Expensive: Hiring, training, and employing skilled human inspectors is costly – so is transporting inspectors to and from remote inspection sites. Utility companies pay as much as $1,000 per mile for aerial inspections by helicopter. Insurance costs related to these often dangerous inspection activities are another significant expense.

Consider the simple inspection task of monitoring for tree overgrowth around power lines. It’s not uncommon for tree branches to break through power lines, destabilize distribution poles, and short-circuit transformers. Early detection and trimming of trees is essential to prevent blackouts, fires, and electrocution hazards. However, it’s costly, time-consuming – and virtually impossible – to detect all instances of tree overgrowth. Invariably, an undetected branch could grow in such a way that leads to an expensive or catastrophic problem.

Another simple yet problematic inspection task relates to monitoring wastewater effluent for signs of particles, discharges, and discoloration. Human inspectors need to continually check discharge pipes to ensure that wastewater is running clean and on schedule. If not, the problem could represent a costly violation of Environmental, Social, and Governance (ESG) criteria or Socially Responsible Investing (SRI) standards. However, due to the limited number of human inspectors – and logistical challenges associated with constant monitoring – it’s not uncommon for factories, plants, and wastewater treatment facilities to unknowingly discharge untreated water directly into the ocean – sometimes for weeks or months before they detect it.

Leveraging Computer Vision for Better Infrastructure Inspections

Computer vision technology provides a cost-effective solution for conducting accurate and timely inspections of industrial infrastructure assets. In addition to achieving more accurate and consistent results than human-led inspections, visual AI for infrastructure inspection is dramatically safer and more affordable.

Computer vision strategies for infrastructure inspection leverage the following features:

  • High-definition IoT-connected cameras – including infrared cameras – mounted in remote locations that observe site conditions.
  • Deployment of drones for aerial footage, visual measurements, and automatic identification of potential problems.
  • High-resolution satellite topography imagery to show the current condition and status of assets on the ground.
  • Edge servers running sophisticated AI models that analyze and interpret visual data, identify maintenance issues, detect environmental hazards, and spot instances of fire and overheating.
  • Instant alerts, reports, and metrics sent to decision-makers for immediate action on potential problems.

With Chooch, companies that manage large infrastructure networks can rapidly train computer vision models to detect all types of visually perceivable problems and maintenance concerns. Through the use of drones, on-site surveillance cameras, and satellite imagery, Chooch AI systems can monitor critical infrastructure assets without the time, risk, and cost of transporting human inspectors to remote locations – and do so faster and more accurately.

Chooch offers industrial companies immediate access to a wide library of pre-built visual AI models for the most common inspection use cases. For more unique scenarios, operators can add layers of training to existing models – or train entirely new models – depending on the inspection needs. Armed with these tools and the Chooch AI platform, customers can develop visual AI models that instantly detect the following concerns:

  • Tree overgrowth
  • Rusty, damaged, or defective structures
  • Overheating, smoke, flares, and fire
  • Leaks in pipes
  • Wastewater effluent and discharges
  • Retention pond and drainage problems
  • Low-hanging or broken power lines
  • Virtually any other visually detectable inspection issue

At the end of the day, the ROI benefit of computer vision for industrial inspections is clear. Whether it’s a large-scale industrial operation, utility company, or governmental organization, computer vision technology empowers faster and more accurate detection of maintenance and environmental concerns – orders of magnitude more affordable than relying on human inspectors alone. Even better, Chooch AI can design and deploy a custom visual AI inspection strategy in only 6 to 9 days.

Get a demo of AI for infrastructure inspection with Industrial AI.