Smarter energy use in telecom with machine learning

Mobile base stations are crucial for connectivity, but they also account for a substantial portion of electricity consumption in the telecom industry. With approximately 25,000 masts in Norway alone, even small improvements in efficiency can have a significant impact. Together with a large telecom operator, we developed an AI-based solution that reduces energy consumption at mobile towers—by adapting power usage to actual traffic patterns, seasons, and context.

Challenge: Base stations for mobile communications consume a significant portion of electricity in the telecom industry. In Norway, there are around 25,000 such masts, and globally over 13 million. Each station uses between 2,000 and 6,000 kWh of energy per year. More efficient use of the base stations saves electricity, money, and the environment. In total, the telecom industry uses 2–3 percent of global electricity consumption.

Solution: We developed a machine learning-based prototype that analyzes the power consumption of base stations and identifies savings potential. The project focuses on adapting power consumption to actual mobile usage. The solution takes into account factors such as traffic volume, weather, location, consumption patterns, and several other factors that influence whether the base station is used as efficiently as possible. For example, base stations at winter sports venues have large variations in mobile traffic throughout the year. By analyzing and predicting needs, energy use can be reduced without compromising coverage or capacity.

Result: The solution has demonstrated that it is possible to almost halve the power consumption in the base stations. This enables the optimization of operations both economically and environmentally, without compromising customer experience or safety.

Antire has completed several hundred AI and machine learning projects for our customers. What the projects have in common is that they can be developed and implemented in a short time, while providing outstanding value to customers. Here you can read about four of the projects.

Antire has been working with machine learning and artificial intelligence (AI) since 2013. Over the years, we have completed several hundred projects across various industries and with some of the leading enterprises in the Nordic region. 

What most of the projects have in common is that they involve few people and take a short time. It usually takes 1–2 months from start to implementation and production. The projects typically last no more than six months. The AI solutions solve specific tasks, providing excellent value and paying off quickly. 

Machine learning and AI have followed Moore's Law in terms of development, with capacity doubling approximately every 18 months. In the last couple of years, however, growth has accelerated, with capacity doubling every 3–4 months. This means that the AI ​​solutions we deliver do more and have greater value for customers.

The projects can be made available in several ways, for example, as independent apps, dashboards, and solutions that are integrated into the customers' ERP systems. The value depends on use. It is therefore essential that they have a good interface and are easily accessible to everyone who will use them. If customers wish, they can add their factors afterwards. 

We present four concrete AI and machine learning projects that we have recently developed and implemented:

• Predicting power market imbalances with AI.
• Keep the fraudsters out - AI that stops SMS fraud in real time.
• Where to produce hydrogen and wind? AI finds the optimal locations.

If you’re curious about what AI and machine learning can do for your energy efficiency, let’s talk.

Get in contact with Øyvind Spørck—our Head of Tailored AI and a leading expert in applied machine learning.