"People think digital twins require significant capex investment but it’s really part of the opex cost"

tower

This is my 28th year at Bentley Systems, a world-leading provider of software solutions for the global infrastructure industry, with offices in over 100 countries. As a global leader in the provision of interoperable digital twin cloud services, Bentley Systems is used by engineers, architects, and operators from around the world to build, operate, and advance the world’s infrastructure.

OpenTower iQ is a newer division in Bentley to focus our digital twin offerings in the telecom sector. I help to manage this group. Bentley’s digital twin platform, known as iTwin is offered as a PaaS (platform as a service) solution allowing our users and partners to develop and customize products to suit their needs and requirements. OpenTower iQ is an iTwin product organically developed within Bentley to serve Towercos, MNOs, as well as service providers, like engineering service providers, drone service providers, etc. As a part of Bentley’s Acceleration wing, OpenTower iQ is committed to bringing new innovations and services to meet the unprecedented demand for modernization and automation.

As we understand, one of the biggest challenges in the telecom space is about the ‘known source of truth.’ This industry is constantly challenged by a lack of good quality data; there’s just too much data out there and no one knows what to rely on. The Telecom sector primarily uses mapping or inspection services, predominantly field surveys performed by tower climbers, spending millions of dollars every year for data that isn’t always reliable or correct. Sometimes, it’s done just to check a box to close the project

As you can imagine, field inspections are a very manual process that can be impacted by many factors, including the quality of training of staff or types of equipment used to assess the site, time, budget, etc. It’s difficult to get reliable, consistent field data. Climbing towers is risky along with other health hazards. So why not use available technology to empower field inspectors to deliver their services faster and cheaper while significantly lowering their safety hazards?

Drones are now being adopted for everyday scenarios and can capture images to build a tower ‘reality model’. However, this is just a model and it must be contextualized to get a fully functional digital twin. This is why I describe the space as murky as these datasets can vary depending on the hardware as well as the ability of the pilot. The outcome and the usability can vary significantly depending on the use cases and the persona.

To solve this, we developed an extensive set of AI algorithms that can automatically provide context and create consistency in how this data is gathered, contextualized, and displayed. We created the best practices guidelines to automate flight planning software along with geo-correction techniques, such as GCP (Ground Control Points) and RTK (Real-Time Kinematic), to get precise geolocated models. Without geo-correction, the accuracy can be significantly off.

To go one step further, we developed a special algorithm so that even with not-so-good data we can guarantee good results. We published a recent whitepaper that proved how accurate the data can be if it is scaled properly using a good algorithm. Ultimately, it’s about automating as much of the process as possible, and our priority is to innovate and ensure technology is available to get consistently good outcomes.

There are many examples we can use across the globe where companies have used our program to extract inventory data automatically resulting in better than any manually extracted measurements.

For example, here in the US, the highest point of a tower is usually the lightning rod. To comply with the FAA regulations, tower owners must know the highest point of the tower. Using OpenTower iQ, our users could consistently and automatically get that measurement along with full equipment inventory. While it’s necessary to have climbers for certain aspects of maintenance and new installations, the existing technology can automate regular inspections, reducing time and improving accuracy.

Most of our successes have come through our partners, like engineering, service providers, and drone service providers. We help them to deliver their services faster and cheaper. While digital twins are still in the early stages of adoption by MNOs and towercos, it’s the service providers who are already applying them to optimise their existing processes and seeing great success.

Digitisation is more than just digital twins which is why this topic can become a bit convoluted. The reality model, as I mentioned earlier is just one part of a digital twin. We can break the digital twin into three major categories. Part one is the ‘information twin’ making up all of the data that is coming in from various sources. Part two is the ‘operational twin’ making up day-to-day operational activities including the reality model, and part three is the ‘engineering twin.’ The combination of all of these is what makes a ‘digital twin’ effective, meaning having just the model and measuring different attributes of the tower isn’t exactly the utilisation of the technology in its full scope.

Without digitisation it would be almost impossible to know how towercos can increase colocations or monitor the performance of their systems. Accurate and reliable data is a core pillar for a towerco to evaluate how they are serving their customers while maximizing revenue generation. For example, towers having multiple tenants can leverage just one capture for the towerco as well as all the tenants, reducing multiple site visits.

Digitisation technology is here to stay and as the industry invests slowly but surely these datasets will unlock many other use cases, further cutting operational costs, by as much as 50% by our best guess. But, here is the key, they must invest in the right platform, create one source of truth, share the platform, and interact with all the stakeholders to take full advantage of the technology.

The market’s understanding of digital twins varies largely depending on whom you’re talking to. Digital twins can be very low-cost especially compared to any traditional inspection method. The biggest cost remains to send people to the site. In many markets including the US and Europe the data-gathering drone service costs between $400-$500. Adding a fraction of that into OpenTower iQ, you can unlock most of the value you are looking for in an inspection. And you can use this data multiple times. In contrast, just one traditional inspection costs around $2,000 in Europe or in the USA, even though it typically serves just one tenant.

Either way, someone needs to go to the site, so the human cost doesn’t make it any more expensive, in fact, you are able to send fewer people who can do the job quicker with drones and even capture multiple sites in the same amount of time. While you still need tower climbers for various reasons, you can mitigate the insurance costs and risks by limiting the amount of necessary tower climbs. People think digital twins require significant capex investment but it’s really part of the opex cost. Towercos and MNOs can start right away without really any up-front cost, and we are always happy to provide this and willing to show the industry that there is no need for massive technology investments.

Everyone is looking at the same information for their use cases, and having digital integration gives people a much better visual of the site pretty much instantly. Satellite data doesn’t have the required granularity, so site visits are still needed. As you start using a singular source of information on the same platform, even if connected to different tools, it cuts down extra time and removes that uncertainty factor to help field teams get started right away.

There is also a real opportunity for towercos and MNOs to monetise this data. Particularly when it comes to small cells, having this data allows them to sell this as some form of data-as-a-service. There could be partnerships among utility and telco companies. For outside stakeholders, take for example a solar company that wants to install solar panels on the roof of a building. If the towerco or MNO has a rooftop there, they may have all the information on dimensions and structure which can be sold to the solar company. Towercos and MNOs can also sell data to each other, and data sharing and data monetisation is a large by-product of digitisation.

If MNOs and towercos know what is available at each site location and how each small cell is performing, you can assess the quality of the network as it is being rolled out. This is incredibly useful for telling whether enough small cells have been deployed and if you have enough capacity. With digitisation, MNOs and towercos can see everything in real-time and avoid either over or under-investing in the network. This is more relevant to the operators but if towercos continue to make strides towards managing RAN sharing they will need to improve visibility as well.

We need to invest more of our time in educating MNOs about this technology. Sometimes, I feel, they don’t fully understand its value and have a lot of legacy systems and processes in place. MNOs are ultimately paying the money that feeds the tower ecosystem through vendors, suppliers, and towercos. Service providers should work more closely with MNOs to prove the value of digitisation.

Throughout the next year or so we will be focussing on education, but the service provider should be seeing the value of digital twins now. I ask towercos and MNOs to give us the chance to show you the value of this technology and we are always willing to work on proof of concepts to show how the initial investment is well worth the significant long-term opex savings and benefits to both performance and efficiency. A PoC on just 50 or 100 towers is enough to provide an educational platform that demonstrates that value digital twins can bring to their towers.

The market is still very slow in embracing this technology and has been reacting even slow this year. There is a lot of uncertainty over the cost of adoption as there aren’t enough case studies to convince ROI. This is why I believe, service providers should be at the forefront of proving its value, why it works, and why it should be adopted.