The role of computer vision software in field operations

How does computer vision impact field services?

Computer vision systems provide real-time feedback on work quality when analysing visual data, whether in telecommunications, manufacturing, construction, or utility inspections, allowing teams to address issues promptly and maintain high standards. This capability greatly reduces site visits as tasks are verified on the first attempt, saving time and resources. Moreover, computer vision automates inspections and monitoring processes in industries where regulatory compliance is crucial – like utilities and transportation.

Understanding computer vision

Computer vision is a branch of Artificial Intelligence (AI) that empowers machines to interpret and understand visual data. It employs machine learning and neural networks to enable computers to extract meaningful information from digital images, videos, and other visual inputs.

In essence, if AI equips computers with the capacity to think, computer vision allows them to see, observe and comprehend. It aims to replicate and improve the human visual system's ability to perceive and make sense of the surrounding environment through images and videos.

Computer vision involves developing algorithms and techniques to extract meaningful insights, identify patterns, recognise objects or scenes, and make decisions based on visual data.

Beyond telecom: utilities, construction, and EV-charging

While the telecoms industry has been an early adopter of computer vision technology, its benefits are now being recognised by other sectors as well. Industries like utilities, construction, and green/electric vehicle infrastructure deployment are increasingly using computer vision software for various field operations.

Utilities

As part of the utilities sector, computer vision is crucial for monitoring and managing critical infrastructure. It enables companies to conduct efficient inspections of power lines, substations, and pipelines using drones or cameras equipped with advanced imaging capabilities.

Using computer vision systems, utility services can detect anomalies, identify faults, and prioritise maintenance activities, improving reliability and resilience. Additionally, computer vision optimises grid management, automates meter reading processes, improves safety and security measures, and drives overall operational efficiency within the utility sector.

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Use case examples:

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Power grid monitoring – computer vision can monitor power lines and infrastructure for potential vegetation encroachment or equipment failures. For example, drones can inspect power lines to detect anomalies.
Water management – utilities use computer vision to monitor water reservoirs, detect pipeline leaks, and optimise water usage. AI-powered systems can analyse images from cameras installed in water treatment plants or along pipelines to identify leaks or measure water levels.

Construction

Construction is beginning see significant benefits with the introduction of computer vision. It's used in automated machinery which can identify and sort materials, operate in hazardous areas, and perform repetitive tasks more efficiently than human workers.

Other areas include monitoring construction sites, identifying potential safety hazards and ensuring that work is being carried out according to plans. Furthermore, it aids in surveying and mapping construction sites, providing precise measurements and detailed site analysis. In essence, computer vision is becoming an indispensable tool in the construction industry for boosting productivity while ensuring safety.

Use case examples:

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Progress monitoring – computer vision can monitor construction sites and track progress automatically. Cameras placed on-site capture images or videos that are analysed to assess construction milestones, detect delays, and optimise resource allocation.
Safety monitoring – computer vision-powered systems can enhance construction site safety by detecting hazards such as workers in unsafe zones, equipment malfunctions, or unauthorised personnel accessing restricted areas. These systems can trigger alerts or automated safety protocols.

EV-Charging

Computer vision technology is used to automatically recognise Electric Vehicles (EVs), helping to monitor the charging process and even manage the parking spaces around charging stations.

Advanced algorithms can identify the type of vehicle and its charging port type and execute an automated charging process. This improves the efficiency of EV charging stations and enhances the customer experience by reducing human errors and providing a seamless charging experience. Hence, computer vision significantly contributes to the growth and sophistication of EV charging infrastructure.

Use case examples:

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Vehicle detection and management – cameras or sensors can recognize license plates or unique vehicle identifiers to associate charging sessions with specific users or vehicles.
Queue management – AI algorithms can analyse real-time footage to prioritise charging slots or dynamically adjust pricing based on usage patterns.

Inveniam’s unique approach to computer vision

Inveniam AI is an end-to-end computer vision solution that helps enterprises across telecommunications, utilities, and complex infrastructure industries enhance Right First Time operations, improve operational efficiencies and eliminate costly rework. Transforming visual data into actionable insights, our software can quickly detect objects, patterns and anomalies faster than a traditional workforce ever could.

With every lifecycle stage covered, we build, deploy and manage transformative computer vision solutions that our customers can rely upon. Moreover, our solution can learn to recognise different types of equipment, detect faults, and suggest appropriate solutions. This improves the speed and accuracy of field operations and enables field technicians to focus on more complex tasks. As a result, companies can streamline their operations, improve coordination among departments, and enhance customer service.

Tailored computer vision solutions for diverse field challenges

Inveniam's computer vision solutions are designed to meet the specific needs of different industries. Whether it's telecom, utilities, or EV charging, Inveniam's solutions can be customised to address unique field challenges. For instance, in the telecoms industry, our computer vision technology can be tailored to automate network infrastructure management – from installation to maintenance.

Additionally, it can be customised to monitor and maintain infrastructure, detect faults, and ensure safety regulations are met in the utility sector. However, our use cases span more than what we covered above. Our strength lies in the quality and adaptability of our AI models. Thanks to our in-house expert data science team, we don’t just offer ready-made models, we also create custom models for unique needs and custom cases.

Superior quality control through automation & optimisation

A key benefit of Inveniam's computer vision software is its ability to automate quality control in the field. Our technology uses AI and machine learning algorithms to detect and rectify defects in real-time, ensuring high-quality standards are consistently met. This improves the efficiency and effectiveness of field operations and reduces the chances of human error. It leads to increased customer satisfaction and lower operational costs for companies.

Case study: Axione

Axione is a leading telecommunications infrastructure provider in France, specialising in the design, construction, and operation of digital networks. With a focus on delivering high-performance solutions, Axione supports the connectivity needs of businesses, government agencies, and communities across various sectors.

The company's expertise spans fibre optic networks, wireless communication systems, and innovative technologies, enabling reliable and efficient connectivity solutions tailored to the specific requirements of its clients.

Axione oversees more than 6M FTTH premises and 25 public initiative networks, connecting over 175 municipalities. However, despite being experts in addressing the complexities of nationwide cabling and wiring, the manual reviewing process proved to be extremely time-consuming and inefficient.

However, once we partnered up, the situation quickly changed, and we were able to reach amazing results:

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EFFICIENCY – 10K image analysis in under 1 hour
MAINTENANCE – 46% drop in incident tickets
SCALE – 4M+ images analysed in 2 years
NETWORK COVERAGE – 100% coverage in 6 months
CARBON EMISSIONS – 15+ metric tons saved per year
WORKLOAD – 20K+ engineer hours saved per year

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Wrapping up

Whether it's telecoms, utilities, construction, or EV charging, companies are increasingly relying on computer vision to automate tasks, improve quality control, and enhance efficiency. With these developments, more sophisticated applications will become possible, including autonomous vehicles, smart surveillance, and personalised shopping. The role of computer vision technology in driving innovation and creating sustainable solutions will increase as we move toward a more connected world.