How AI visual automation solutions reduce Telco infrastructure costs

4 Minutes Read

The arrival of Artificial Intelligence (AI) has sparked a new wave of innovation in the quickly changing telecom sector, changing how businesses operate, manage data, and provide services. AI has made deep inroads into the day-to-day operations of Telcos, proving to be an inevitable part of efficiency, automation of procedures, and resource optimization. Those who are hesitating to use AI are not really deciding "if", but "when".


The application of AI in the telecommunication sector has enabled companies to reduce costs while improving the quality of service they provide to their customers. Telecommunications infrastructure owners save costs by using visual automation  in several ways, including:


  • Quality control of daily on-field operations
  • Network infrastructure maintenance
  • Network monitoring over time
  • Network energy consumption and carbon footprint reduction


Quality control of daily on-field operations


Infrastructure operators and Internet Service Providers face the challenge of ensuring that all the company's field service employees and contractors provide high-quality service and adhere to the same standards. This can be difficult when multiple contractors are involved, and a lack of quality control can be the reason for the network downtime.


Based on industry surveys, the cost of network downtime is typically over 5,300 Eur/minute. Another market estimate is that nearly 70% of connection failures are due to the human factor and only 30% are due to network failures. The latter statement makes it clear that day-to-day field operations and their quality should be the focus of rapid improvements to reduce associated costs.


The solution is here. Telco infrastructure owners use AI visual automation to monitor daily on-field operations in real time. Field technicians upload infrastructure images into the internal informational system while on-site, before and after the work is done. They immediately receive real-time feedback and analysis of deviations and anomalies, which allows them to immediately address the problem while on site. This eliminates repetitive visits and the cost of rework, as any corrections are made by the same field engineer during the same visit.


The cost of maintaining the infrastructure network is huge, and addressing small infrastructure issues in a timely manner can help identify problems before they become critical and schedule maintenance accordingly, avoiding massive repair and replacement costs. By controlling the quality of daily operations, Telcos can improve the reliability of their services and reduce the risk of costly downtime.


Daily image analysis allows anomalies and poor-quality operations to be detected in real-time, preventing rework. Human operators can detect failures in an image in about 2 minutes. Eygles solution by INVENIAM can analyze more than 1000 images per minute, without losing focus regardless of the number of focus points.




Network infrastructure maintenance 


A Telco company has many infrastructure units spread across a vast geographical area. Maintaining these units is essential to ensure they function optimally and provide reliable network coverage. 

In the past, Telcos relied on manual inspections to identify problems with their infrastructure units. These inspections were time-consuming, and it was difficult to detect problems that weren't immediately visible. By using visual automation AI solutions, Telcos can monitor the health of their infrastructure networks and identify problems in a timely manner. The latter scenario means relying on the processing of visual information (images) from day-to-day operations, rather than relying on scheduled and often late maintenance checks.

Infrastructure owners can also benefit from harnessing the power of predictive maintenance. Field service employees and contractors may ignore minor problems and anomalies that the algorithm would never miss. Addressing small infrastructure issues in a timely manner can help identify problems before they become critical and schedule maintenance accordingly, avoiding massive repair and replacement costs.






The Inveniam solution serves as a perfect combination of AI and Business Intelligence, ensuring continuous monitoring of the infrastructure. The AI engine allows continuous monitoring of the flow of images from day-to-day operations, while Business Intelligence provides a system of triggers and red flags to facilitate timely maintenance checks.



Network monitoring over time


As fiber networks are deployed and assets are put into service, they begin to depreciate, which can lead to higher operating expenses in the form of maintenance, repair and replacement costs. Analyzing the images of each infrastructure unit and the entire network over time with AI allows Infrastructure owners and Internet Service Providers to monitor how the network performs and evolves. This analysis of deviations and anomalies not only eliminates repeat visits and rework costs, but also contributes to the long-term health of the overall network, preventing its deterioration and degradation.


The result of the continuous monitoring of infrastructure images over time is a Business Intelligence module that helps to evaluate every single operation performed on a given device and the health of the entire network. Business Intelligence provides a clear view of figures, KPIs and a network health scoring system. This allows infrastructure units, operations within them and their impact on the dynamic change of the score to be compared, helping to estimate the level of long-term deterioration and degradation of the network.


A combination of Eygles and Business Intelligence modules allows to track the health and evolution of each infrastructure unit and the overall network over time. This ensures full control of asset value and provides a tool and information to prevent excessive depreciation of infrastructure assets.


Optimize energy consumption and reduce carbon footprint


Telco infrastructure owners can also use visual automation AI solutions to monitor and manage energy consumption in their facilities. By identifying areas of high energy consumption, telcos can optimize energy usage and potentially save on utility costs. It goes without saying that this positively impacts the carbon footprint.


To set an example, AI can be used to optimize the cooling systems in Data centers. This can be done by analyzing the temperature and humidity of the air in the data center using thermal imagery and adjusting the cooling system accordingly. By using AI, data center operators can ensure that cooling systems are only used when they are needed, reducing overall energy usage. This process is commonly called “Smart Cooling”. Using an AI energy optimization solution can reduce the annual energy consumption of Data centers by nearly 40%.


Another example of carbon emission reduction comes from fiber optic network daily operations. AI visual control detects early signs of network degradation or damage, which can be easily repaired before they become significant problems. This reduces the need for extensive repairs or replacements, which in turn reduces the number of carbon emissions associated with the manufacturing and transportation of new equipment.


The same goes for day-to-day operations and reducing rework. Eliminating repetitive visits and getting each job right the first time not only reduces rework costs. It also makes a significant contribution to reducing the carbon footprint through reduced fuel consumption.





Using Eygles energy optimization solution can reduce energy consumption and carbon emission in Data centers and fiber optic network daily operations.



Telecoms using AI technology are more competitive


The telecom sector is undergoing a rapid transformation, and the use of AI is completely changing how businesses function, manage data and provide services. The ability for businesses to automate operations, optimize resources, and make revenue-boosting decisions is one of the most important advantages of AI.


Telecom firms that use AI technology are more competitive because they can provide better services, enhance customer satisfaction, and boost revenue while lowering operating expenses. As AI technology develops further, it will become even more important for the telecom sector and help businesses stay competitive.



Do you have issues related to quality control in your telecom infrastructures?
Do you have questions about the deployment of artificial intelligence in your organization?


Book an online appointment with an Inveniam consultant specialized in artificial intelligence solutions!


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Picture of Mathias ZIMMER

Mathias ZIMMER

DIgital Marketing