AI & fibre network design

AI & fibre network design

AI & fibre network design

AI can enable more efficient network design and management, reducing costs, while improving service and flexibility – providing certain preconditions are met…

How is AI changing FTTH network design?

The global FTTH network design market is expected to grow from $1.3 billion in 2020 to $3.5 billion by 2025, with a Compound Annual Growth Rate (CAGR) of 18.5%, according to a recent MarketsandMarkets report. This growth is significantly driven by the increasing adoption of Artificial Intelligence (AI) in FTTH network design.

AI is transforming FTTH network designs in key areas, including Network Planning and Optimization, Fault Detection, Predictive Maintenance, Troubleshooting, and Customer Demand & Service Management, including forecasting. AI can create detailed, interactive 3D models of network infrastructure, making it easier to visualize and analyse complex networks. It can gather and analyse historical data on designs, identify patterns, and predict and plan network elements based on existing topologies and geographical information. This input can be used to configure network elements and optimise performance and planning. Generated reports on network performance, usage trends, and maintenance activities, can save time and reduce manual errors.

AI's ability to analyse large amounts of related information and find patterns offers advantages that may be hard for humans to match. It can detect faults and anomalies in real-time, send alerts to maintenance teams and enable swift resolution. They can also ensure efficient use of network resources and continuously analyse network performance, identifying issues and optimizing configurations in real-time. Other areas in which AI can have an edge include capacity planning, workforce deployment and scheduling, and risk assessment.

The use of AI can support extra efficient, customer-focused network design and management, resulting in lower costs, improved service delivery, and the ability to adapt to future technological advancements. If reliable, recent data is available, AI-generated designs may outperform human designs due to their ability to process large amounts of information quickly and accurately. However, AI-generated designs have their limitations, and their reliability and accuracy depend on the quality of the data used. If data is incomplete, inaccurate, or outdated, AI-generated designs and advice may be flawed. Human activities such as site surveys and ‘sanity checks’ are often needed to confirm the accuracy of the outcome.

Hybrid approach

Furthermore, generated designs may lack transparency, making it difficult to understand how decisions were made and why certain design choices were made. While AI can process large amounts of data quickly and accurately, it may not always be able to fully understand the nuances and complexities of a fibre network. Local conditions such as environmental factors, infrastructure constraints, safety regulations, and regulatory requirements often require a fair amount of interpretation in order to be used in a planning project. A hybrid approach that combines the strengths of AI and human expertise is the most effective, using AI to support and augment human decision-making rather than replace it entirely.

Benefits of AI-assisted FTTH network design

  1. Improved accuracy and efficiency in network planning and design;
  2. Enhanced predictive maintenance and reduced downtime;
  3. Optimization of network configuration and resource allocation; 
  4. Better management of network complexity and scalability.