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Artificial Intelligence makes network deployments faster, safer and smarter

Artificial Intelligence makes network deployments faster, safer and smarter

The rapid advancement of Artificial Intelligence (AI) has revolutionized many industries and processes. AI-powered systems and Machine Learning (ML) algorithms are being increasingly deployed to enhance the accuracy, efficiency, and safety of field operations across diverse sectors.

At Nokia, we have a deep commitment to the health and safety of our employees and those who work with us. The aim is simple: we want everyone to go home safely at the end of the day. AI and ML play a big role in transforming the way we monitor and ensure the safety of everyone in the field. In addition, they make our quality verification process faster and more accurate right from the start, while helping optimize network performance. Artificial intelligence is a true game-changer for network deployments.

In this blog, I will explore the applications and benefits of AI in quality verification and how it can help ensure the health and safety of those working in field activities of mobile network deployments.

Embracing AI and ML for deployment services

The validation of site quality as well as ensuring compliance with health and safety regulations are of critical importance in network deployments. Both are prone to human error and subjectivity, which can lead to rework, site revisits, increased cycle time and increased risk of operational hazards.

Embracing artificial intelligence and moving away from manual work helps minimize human error and enhance the accuracy of the verification processes.

At the same time, we have to acknowledge that the adoption of AI and ML in our operations is not without its obstacles. This is true with all disruptive technologies. In my experience, these four aspects can greatly contribute to a positive result:

  • Applying standard processes everywhere 
    A uniform way to work on all site deployments helps optimize operations and establish important routines. If processes vary between different sites, it may lead to oversights, which can then result in unfortunate safety hazards.

  • Ramping up expertise in data analytics 
    When adopting new digital tools, it is important to provide the users with appropriate competence development and opportunities to ramp up their skills. Otherwise, the benefits of the new technologies are left unexploited. 

  • Adopting a positive mindset 
    There can be resistance to digitalization especially when the old manual-intensive tasks are proven to work well enough. However, AI can take away the repetitious and the most time-consuming part of the workload, letting human personnel concentrate on more motivating and value-adding tasks.

  • Ensuring data security and legislative compliance 
    Data security is a valid concern, and we embed security thinking in all our products and solutions. In some regions, AI-related legislation designed to protect personal privacy may limit the extent to which AI can be leveraged when processing data. We help our customers find the best solution in compliance with local regulations.

Achieving enhanced quality with First Time Right approach

We have seen great results when utilizing AI and ML for RAN deployments in Europe: an increase of 30 percent in our First Time Right achievements. I’m convinced that with the further enhancements of our digital platform and the increasing expertise in leveraging artificial intelligence, we will do even better. Our First Time Right approach means, for example, that the amount of site re-visits decreases, resulting in concrete cost savings.

Another finding from our projects was that with AI, our quality verification was completed in 33 minutes whereas with traditional methods, it took 43 minutes – a reduction of 25 percent. The beauty of AI is that it can achieve time savings across the entire deployment process, making the deployments much faster and more cost-effective.

Artificial intelligence has allowed us to institutionalize a new and improved way of working. In short, we leverage AI and ML for these five critical tasks:

  • Technical site surveys

  • Site quality self-assessments conducted by the field crew

  • Site quality audits conducted by a Nokia supervisor

  • Customer acceptance checks for site quality

  • Health and safety checks prior to starting field activities

AI/ML-based automation is essential for the safety and quality of modern field operations

Our industry-first approach to using AI and ML helps enhance the safety, speed and quality of deployments for our customers and partners.

The benefits are multifold: Artificial intelligence enables automated inspections by analyzing vast amounts of data collected from field activities. Machine learning algorithms can identify defects, anomalies, or deviations from desired quality standards and customer-specific checklists. AI-powered systems can monitor compliance with health and safety regulations such as the use of personal protective equipment as well as hazard recognition in real-time.

As Artificial Intelligence continues to evolve, I believe that it has an ever-growing potential to transform critical processes in network deployments. Leveraging AI and ML technologies in field activities can drive efficiency, reduce costs, and most importantly, protect the well-being of workers.

Find out more on our Deployment Services webpage.

Deepak Harie

About Deepak Harie

With more than 25 years in the telecommunications industry, Deepak is a dynamic senior executive who is passionate about using business transformation, digitalization, and innovation to drive superior customer experience. He currently leads Nokia's largest network technical support and deploy business, where he is responsible for the strategy, portfolio, delivery model and business performance across deployment, software and hardware support, and customer training. He has most recently prior to that also led the Cloud and SI professional services unit for Nokia.

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