Recently I blogged about how Deutsche Telekom is using AI for variety of things. The most interesting being (from this blog point of view), fiber-optic roll-out. According to their press release (shortened for easy reading):
"The shortest route to the customer is not always the most economical. By using artificial intelligence in the planning phase we can speed up our fiber-optic roll-out. This enables us to offer our customers broadband lines faster and, above all, more efficiently," says Walter Goldenits, head of Technology at Telekom Deutschland. It is often more economical to lay a few extra feet of cable. That is what the new software-based technology evaluates using digitally-collected environmental data. Where would cobblestones have to be dug up and laid again? Where is there a risk of damaging tree roots?
The effort and thus costs involved in laying cable depend on the existing structure. First, civil engineers open the ground and lay the conduits and fiber-optic cables. Then they have to restore the surface to its previous condition. Of course, the process takes longer with large paving stones than with dirt roads.
"Such huge amounts of data are both a blessing and a curse," says Prof. Dr. Alexander Reiterer, who heads the project at the Fraunhofer IPM. "We need as many details as possible. At the same time, the whole endeavour is only efficient if you can avoid laboriously combing through the data to find the information you need. For the planning process to be efficient the evaluation of these enormous amounts of data must be automated." Fraunhofer IPM has developed software that automatically recognizes, localizes and classifies relevant objects in the measurement data.
The neural network used for this recognizes a total of approximately 30 different categories through deep learning algorithms. This includes trees, street lights, asphalt and cobblestones. Right down to the smallest detail: Do the pavements feature large pavement slabs or small cobblestones? Are the trees deciduous or coniferous? The trees' root structure also has a decisive impact on civil engineering decisions.
Once the data has been collected, a specially-trained artificial intelligence is used to make all vehicles and individuals unidentifiable. The automated preparation phase then follows in a number of stages. The existing infrastructure is assessed to determine the optimal route. A Deutsche Telekom planner then double-checks and approves it.
In the recent TIP Summit 2018, Facebook talked about ‘Building Better Networks with Analytics’ and showed off their analytics platform. Vincent Gonguet, Product Manager, Connectivity Analytics, Facebook talked about how Facebook is using a three-pronged approach of accelerating fiber deployment, expanding 4G coverage and planning 5G networks. The video from the summit as follows:
TIP Summit 2018 Day 1 Presentation - Building Better Networks with Analytics from Telecom Infra Project on Vimeo.
Some of the points highlighted in the video:
“It is very encouraging that DT and Facebook are seeing the benefits of data and automation for design. I think that is the only way we’re going to be able to plan modern communication networks. We approach it from the RAN planning perspective: 8 years ago our clients could already reduce cost by automatically selecting locations with good RF performance and close to fibre nodes, alternatively locations close to existing fibre routes or from particular providers. Now the range of variables that we are capable of computing is vast and it includes aspects such as accessibility rules, available spectrum, regulations, etc. This could be easily extended to account for capability/cost of deploying fibre per type of road.
But also, we believe in the benefit of a holistic business strategy, and over the years our algorithms have evolved to prioritise cost and consumers more precisely. For example, based on the deployment needs we can identify areas where it would be beneficial to deploy fibre: the study presented at CWTEC showed a 5G Fixed Wireless analysis per address, allowing fibre deployments to be prioritised for those addresses characterised by poor RF connectivity.”
There is no doubt in my mind that more and more of these kinds of tools that relies on Analytics and Artificial Intelligence (AI) will be required to design and plan the networks. By this I don’t just mean 5G and other future networks but also the existing 2G, 3G & 4G networks and Hetnets. We will have to wait and see what’s next.
Related Blog Posts:
"The shortest route to the customer is not always the most economical. By using artificial intelligence in the planning phase we can speed up our fiber-optic roll-out. This enables us to offer our customers broadband lines faster and, above all, more efficiently," says Walter Goldenits, head of Technology at Telekom Deutschland. It is often more economical to lay a few extra feet of cable. That is what the new software-based technology evaluates using digitally-collected environmental data. Where would cobblestones have to be dug up and laid again? Where is there a risk of damaging tree roots?
The effort and thus costs involved in laying cable depend on the existing structure. First, civil engineers open the ground and lay the conduits and fiber-optic cables. Then they have to restore the surface to its previous condition. Of course, the process takes longer with large paving stones than with dirt roads.
"Such huge amounts of data are both a blessing and a curse," says Prof. Dr. Alexander Reiterer, who heads the project at the Fraunhofer IPM. "We need as many details as possible. At the same time, the whole endeavour is only efficient if you can avoid laboriously combing through the data to find the information you need. For the planning process to be efficient the evaluation of these enormous amounts of data must be automated." Fraunhofer IPM has developed software that automatically recognizes, localizes and classifies relevant objects in the measurement data.
The neural network used for this recognizes a total of approximately 30 different categories through deep learning algorithms. This includes trees, street lights, asphalt and cobblestones. Right down to the smallest detail: Do the pavements feature large pavement slabs or small cobblestones? Are the trees deciduous or coniferous? The trees' root structure also has a decisive impact on civil engineering decisions.
Once the data has been collected, a specially-trained artificial intelligence is used to make all vehicles and individuals unidentifiable. The automated preparation phase then follows in a number of stages. The existing infrastructure is assessed to determine the optimal route. A Deutsche Telekom planner then double-checks and approves it.
In the recent TIP Summit 2018, Facebook talked about ‘Building Better Networks with Analytics’ and showed off their analytics platform. Vincent Gonguet, Product Manager, Connectivity Analytics, Facebook talked about how Facebook is using a three-pronged approach of accelerating fiber deployment, expanding 4G coverage and planning 5G networks. The video from the summit as follows:
Some of the points highlighted in the video:
- Educating people to connect requires three main focus areas, Access, Affordability and Awareness – One of the main focus areas of TIP is access.
- 4G coverage went from 20% to 80% of world population in the last 5 years. The coverage growth is plateauing because the last 20% is becoming more and more uneconomical to connect.
- Demand is outpacing supply is many parts of the world (indicating that networks has to be designed for capacity, not just coverage)
- 19% of 4G traffic can’t support high quality videos today at about 1.5 Mbps
- Facebook has a nice aggregated map of percentage of Facebook traffic across the world that is experiencing very low speeds, less than 0.5 Mbps
- Talk looks at three approaches in which Facebook works with TIP members to accelerate fiber deployment, expand 4G coverage and plan 5G networks.
- A joint fiber deployment project with Airtel and BCS in Uganda was announced at MWC 2018
- 700 km of fiber deployment was planned to serve over 3 million people (Uganda’s population is roughly 43 million)
- The real challenge was not just collecting data about roads, infrastructure, etc. New cities would emerge over the period of months with tens of thousands of people
- In such situations it would be difficult for human planners to go through all the roads and select the most economical route. Also, different human planners do thing in different ways and hence there is no consistency. In addition, its very hard to iterate.
- To make deployments simpler and easier, it was decided to first provide coverage to people who need less km of fiber. The savings from finding optimal path for these people can go in connecting more people.
- It is also important for the fiber networks to have redundancy but it’s difficult to do this at scale
- An example and simulation of how fiber networks are created is available in the video from 07:45 – 11:00.
- Another example is that of prioritizing 4G deployments based on user experience, current network availability and presence of 4G capable devices in partnership with XL Axiata is available in the video from 11:00 – 14:13. Over 1000 sites were deployed and more than 2 million people experienced significant improvement in their speeds and the quality of videos.
- The final example is planning of 5G mmWave networks. This was done in partnership with Deutsche Telekom, trying to bring high speeds to 25,000 apartment homes in a sq. km in the center of Berlin. The goal was to achieve over 1Gbps connection using a mixture of fiber and wireless. The video looks at the simulation of Lidar data where the wireless infrastructure can be deployed. Relevant part is from 14:13 – 20:25.
“It is very encouraging that DT and Facebook are seeing the benefits of data and automation for design. I think that is the only way we’re going to be able to plan modern communication networks. We approach it from the RAN planning perspective: 8 years ago our clients could already reduce cost by automatically selecting locations with good RF performance and close to fibre nodes, alternatively locations close to existing fibre routes or from particular providers. Now the range of variables that we are capable of computing is vast and it includes aspects such as accessibility rules, available spectrum, regulations, etc. This could be easily extended to account for capability/cost of deploying fibre per type of road.
But also, we believe in the benefit of a holistic business strategy, and over the years our algorithms have evolved to prioritise cost and consumers more precisely. For example, based on the deployment needs we can identify areas where it would be beneficial to deploy fibre: the study presented at CWTEC showed a 5G Fixed Wireless analysis per address, allowing fibre deployments to be prioritised for those addresses characterised by poor RF connectivity.”
There is no doubt in my mind that more and more of these kinds of tools that relies on Analytics and Artificial Intelligence (AI) will be required to design and plan the networks. By this I don’t just mean 5G and other future networks but also the existing 2G, 3G & 4G networks and Hetnets. We will have to wait and see what’s next.
Related Blog Posts:
- The 3G4G Blog: Telefonica, Mayutel, Facebook & Parallel Wireless: Connecting the Unconnected in Peru (#InternetParaTodos)
- 3G4G Small Cells Blog: MTN sees future in 3G
- 3G4G Small Cells Blog: Ultimate Guide to the Telecom Infra Project (TIP)
- Operator Watch Blog: Disruptive Reliance Jio on the road to 4G leadership
- The 3G4G Blog: Automated 4G / 5G HetNet Design
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