Fiber networks have revolutionized connectivity, uniting people across the globe with high-speed internet and fostering collaboration. But not everyone is benefiting. Rural areas have been largely left out of the broadband expansion. In fact, more than 30 million Americans are in areas without broadband infrastructure, making it impossible to access affordable and reliable high-speed Internet. The cost to reach these targeted homes and communities is expensive, time-consuming, labor-intensive, and prone to human errors. However, recently passed US laws changed the outlook toward fiber networks in unserved and underserved communities.
New federal grant programs aim to get all Americans online by funding partnerships between states or territories, communities, and stakeholders to build infrastructure to provide high-speed internet to everyone. With many providers seeking to expand their reach into underserved areas, there is a significant first-mover advantage for those able to secure subsidies. Most ISPs use traditional and highly manual methods of fiber network deployment, complete with challenges. However, the game-changing capabilities of artificial intelligence (AI) are transforming fiber network deployment and management, providing a valuable first-mover advantage. AI-powered fiber deployments significantly ease the effort in broadband expansion, allowing underserved communities and residents to receive the economic, educational and healthcare benefits usually reserved for urban or suburban areas.
Operators Face Obstacles Designing Fiber Networks
Fiber planning and design are essential in extending broadband. However, available trained workers are limited. As a result, operators pay more daily for design services and construction. Inconsistent engineering standards result in variability, leading to design and operational flaws. Time-consuming and labor-intensive manual processes negatively impact speed and create high-cost results. The lack of automated workflow lengthens intervals and reduces first-movers' advantage. The consequences of these obstacles include budget depletion, corrections and mistakes that erode possible profits, postponed implementations, delayed income recognition, failure to adapt to market fluctuations, and loss of first-mover advantage.
How AI Improves Outside Plant (OSP) Design
AI can improve outside plant (OSP) design in three areas: route planning, fiber test planning, and bandwidth capacity management. For route planning improvements, AI can assist in the planning and design stages of fiber network deployment by analyzing data sets like population density, terrain, existing infrastructure, and projected demand. AI algorithms can help identify the most efficient routes for fiber deployment, predict and anticipate future demand, and optimize fiber network deployment. By analyzing historical data, AI algorithms can identify patterns and trends that allow operators to allocate resources more effectively and deploy fiber infrastructure in areas with high predicted demand to prevent overbuilding or underserving specific regions.
Fiber test planning can also benefit from AI. Completing the Link Loss Budget Analysis is a critical element in design. Properly laying out the route, cables, and components ensures all customers have adequate capacity. Traditional fiber testing is a labor-intensive and time-consuming process. AI-powered automated testing systems can expedite and simplify this process. AI algorithms can quickly analyze fiber quality, detect faults, and assess performance metrics, making the testing process more efficient and accurate.
Finally, bandwidth capacity management improves with AI-infused software. AI can optimize the allocation of network resources, based on dynamic demand patterns. AI algorithms can dynamically adjust resource allocation to maximize network efficiency by analyzing usage patterns and predict demand fluctuations to minimize network congestion.
The Impact AI Has on OSP Design
Using AI-driven automation, manual tasks, corrections, and mistakes can be reduced, speeding up the design process. The manual design process takes about 45-60 days. The challenges include a lack of transparency, rework and repeat follow-ups, and overly manual processes. The AI-automated fiber design process takes about 25 days. High-level design (HLD) can automate on-field surveys and validation (existing and new details, homes, sketch design per standards, and create HLD in GIS systems. Micro-level design (LLD) can automate the creation of prints, schematics, straight-line diagrams, and supporting documents, including splitter information, permits, BOM, etc. Digitalization in fiber design operations minimizes manual work and reworks, ensuring a right-first approach.
AI Will Help Connect Everyone
America runs on high-speed internet. Broadband internet powers our economy, supports education, fosters better public health, connects loved ones, and strengthens social ties. But not everyone is connected. Too many Americans don’t have access to the opportunities that high-speed internet makes possible. The November 2021 Infrastructure Deal’s $65 billion investment aims to ensure every American has access to reliable high-speed internet, like the federal government’s historic effort to provide electricity to every American nearly one hundred years ago.
Currently, many cable providers still utilize manual fiber network deployments that are expensive, time-consuming, and labor-intensive. CSPs should pivot to an AI-led deployment to save money, effort and time and capture first-mover advantage.
Wipro is helping Telcos and CSPs use AI to build last-mile connectivity. As an established player in the market, Wipro has proven its proficiency in network deployment through its defined processes and workflow-based tools (automation, software-based architecture, and so on) for effective network deployment. By fusing technology with purpose, we can help extend broadband infrastructure to provide high-speed connections for everyone.