Digital twins are all the rage for the Internet of Things and have regularly been named as a strategic technology trend in recent years. Indeed, the benefits of virtual technologies are tremendous, and many industries such as agriculture, government, transportation and retail have reported significant Return on Investment (ROI) from the use of these technologies —including minimized testing and production costs, less defective products, etc. Deutsche Telekom have found that digital twin technologies enable IoT developers to reduce their time to market by 1.2 years and avoid 40% of the short and long terms issues that may otherwise have arisen.
Digital twins are real time digitalized versions of physical objects (an IoT device, a vehicle, a machine, etc.) that can be used to assess, test and alter the robustness, viability and suitability of a system without having to build it, or even interact with it in the real world, thereby avoiding any negative consequences. The simulations that are produced help to identify how to optimize the system’s performance and avoid potential future issues through the analysis of data and monitoring.
So we couldn’t continue our quest of “How to create a successful ecosystem for your IoT project”, and talk about prototyping and testing without addressing this subject. We asked Miguel Rodriguez - Senior Manager IoT Device Verification & Engineering at Deutsche Telekom to tell us all about the IoT Solution Optimizer, a powerful virtual twin modeling platform that allows customers to assess different implementation options for their IoT devices.
Deutsche Telekom is a German telecommunications company, the largest telecommunications provider in Europe by revenue. The company provides fixed-network/broadband, mobile communications, Internet, and IPTV products and services for consumers, and information and communication technology (ICT) solutions for business and corporate customers. Over the past few years, DT has developed a range of integrated solutions for IoT business customers, including network, tools, platforms, consultancy, testing and support services to help developers of all sizes along every stage of their project. A key focus area has been to enable Mobile IoT customers using the standardized and secure 3GPP™ low power wide area (LPWA) technologies operating in licensed spectrum: NarrowBand IoT (NB-IoT) and LTE-M.
One of these solutions, the IoT Solution Optimizer, was launched in 2019. This online device planning tool enables IoT developers to model and optimize the performance of their battery-powered, constrained Mobile IoT applications. Not only does it help accelerate the product design stage, reducing time to market by 1.2 years on average, but it serves as a powerful support tool which can guide lifecycle decision-making in product maintenance. In just a few minutes, users can assemble a “virtual twin” of their IoT application, by specifying the deployment markets and the access technology of choice, configuring their hardware implementation, be it the radio module, antenna and battery, and defining the communication and power efficiency profiles of the application, including payload, protocols and power saving features. The IoT Solution Optimizer even considers the impact of coverage quality, of antenna inefficiency due to improper placement of components on the PCB, as well as the effects of mobility and environmental temperature. From there, they can model reliable results of expected battery life on the selected operator networks and find out whether their IoT project will work as planned, if it is efficient and how its performance can be further optimized. This gives customers a solid basis for their decisions and a means to improve their planning and business case – even before they invest in an implementation.
A few years ago, we realized that the complexity of IoT productization was increasing for companies of all backgrounds. A lack of industry best-practice and know-how when moving from legacy technologies towards highly specialized, emerging protocols were essentially a paradigm shift. Designing devices for low-bandwidth, battery-powered use cases in deep indoor coverage presented many with new and unforeseen challenges.
Take the clouds and protocols that developers commonly use. We take for granted that they will always work. Yet, many well-established hyperscaler solutions are optimized for communication over Wi-Fi, 2G, 3G or 4G, using standard protocols like MQTT or HTTP. When implementing such TCP-based protocols over NB-IoT or LTE-M, developers suddenly began encountering power consumption challenges, as these protocols require a regular data exchange to maintain their active sessions. Tearing down the session also brings drawbacks, for it would require renegotiations and the set-up of encrypted transport, including a heavy certificate exchange. Although developers were building highly efficient hardware, the software was not adapted to the system’s smaller available bandwidth, and a regular interruption of the Mobile IoT power saving features meant that these were less effective in delivering the desired battery lives.
Another example is the hesitancy to perform firmware updates, fearing that these may drain the battery. But what happens if your devices need an urgent security patch? In the case of some applications like parking sensors, it may be impossible to replace a battery without damaging the device. Service providers needed new tools to model the impact of such updates over the air and compare these to the effect of more frequently transmitted messages, in this case, those reporting parking events.
The lack of professional tools that can shed light on these challenges continue affecting significant parts of the IoT value chain. Device manufacturers are confronted with multiple, costly prototyping cycles and field tests. Procurement companies generally have few tools to benchmark components and devices, identify feature gaps, or simply to scout for suppliers. Operators and service providers in turn also face a whole new set of challenges. Under the legacy technologies, the changing of network configurations could be done with relatively little impact on the performance of customers’ solutions. But now, such decisions cannot be made independently. Service providers must understand what their customers have deployed, and capabilities to forecast which potential impacts configuration changes may have on the install base are becoming mission critical.
To address these new challenges, Deutsche Telekom needed a new capability. To these means, we patented and developed a cloud-based service that can perform virtual twin modeling of battery-powered IoT devices. It is a platform that allows our customers to do what other industries have already mastered. Take the automobile or aviation industry, for instance. It would be cost-prohibitive to create dozens of different prototypes before they settle on a product design. Instead, they leverage virtual twin technology to model subsystems of their proposed product, identifying which designs hold the most promising outcomes. We brought this concept to the world of IoT, in the form of the IoT Solution Optimizer application, a planning tool that our customers can leverage to make virtual twins of their IoT applications.
The way that it works is that once you’ve identified what kind of a vertical your device belongs to – and we have about two dozen categories, from asset trackers, predictive maintenance, wearables, to parking devices, the first step is to configure a network. We have integrated all the European networks of Deutsche Telekom, T-Mobile US, and participating mobile network operators around the globe. When you select one or more of these networks, all the network configurations affecting battery life are automatically taken into account.
Then you choose the technology. Our focus is to help customers understand how to optimize for battery life and for coverage. Currently, the IoT Solution Optimizer offers customers the option to build NB-IoT and LTE-M projects, including multimode operation.
You will then need to specify how the product is deployed. Not only is the Coverage Enhancement level important (representing performance in good, moderate and poor coverage), but also whether the device is static or moving and roaming internationally. Finally, the deployment temperature range is critical, for it affects the battery capacity.
The IoT Solution Optimizer allows you to model and benchmark commercially available products. We integrate these together with the suppliers and place them on the shelf for our customers to discover.
In the event that you want to build your own solution instead, you must first configure the hardware design. Deutsche Telekom offers one of the largest portfolios of operator certified Mobile IoT modules in the world and the list is constantly growing. For each certified module, there are over 1,000 measurements which we take, allowing us to accurately characterize over one hundred 3GPP™ procedures. These measurements allow the IoT Solution Optimizer to model the module’s power consumption accurately, something which the supplier in turn review and confirm before we publish the component on the shelf. Altogether, this may be the largest database of performance measurements for NB-IoT and LTE-M models in the industry, cutting across almost a dozen chipset ecosystems. If the user has difficulty in choosing their module, selection guides are available to help in refining their choice based on supported features.
What follows are screens that allow customers to select and configure the operating mode of certified GNSS solutions for positioning, if applicable. Here again, we systematically take measurements to properly characterize the performance of the component. Together with our worldwide partners, we implemented an antenna modeling feature that predicts the impact to coverage performance and battery life caused by improper placement of antennas. We observe, as IoT devices get smaller and the frequency drops to 800 MHz – 900 MHz, the handling of the antenna component becomes ever more critical. Specific placements of the component may lead to inefficiencies that cancel the Maximum Coupling Loss benefits of Mobile IoT technologies.
Then the next step is the software.
This is where you configure the payload and protocols that the application exchanges between the device and server. The IoT Solution Optimizer allows users to visualize how protocols like CoAP, MQTT, MQTT-SN, HTTP and oneM2M work, and their pros and cons. It helps you understand which choice is the right one for your solution. Recently we even integrated a feature that allows you to model hyperscaler and mobile network operator clouds. This is essential in evaluating which is the right provider for your business case.
The last step in this application configuration stage is the configuration of 3GPP™ power saving features. This is where many developers may make a mistake. The fact is that only certain power saving features are suitable for specific use cases. The IoT Solution Optimizer recommends the best combination of power saving features, based on your application’s characteristics, whether your communication is Uplink- or Downlink-centric, and aligned with what the network and selected module support. This ensures that you won't make an error. You can also learn how the network is configured by default and it allows the IoT application to override the settings for specific features.
Finally, you arrive at the battery configuration. We chose Saft to be our exclusive partner for lithium technology. We leveraged Saft’s expertise to develop the battery modeling algorithms, and directly integrated power measurements from their laboratories which model the impact of temperature on the capacity. If a customer doesn't want to use Saft batteries, they can define their own battery profile, but with the risk of less accuracy.
Once the project configuration is completed, you can get your results within seconds. We calculate the performance KPIs for the project and present the customer with information which graphically shows where power consumption is taking place and the expected battery life in different coverage conditions. We also run hundreds of what-if scenarios in the cloud, allowing us to present multiple optimization suggestions that the user can use to create a superior product. The user also gets access to an AT Command checklist and documentation for the components they chose. Contact links to the suppliers are generated, as well as webshop links to place an order, often via a distributor.
Once they’ve built their digital twin, users are also notified of new measurements or settings are available for components and networks, so they can track what's happening in their own supply chain. It’s future proof!
Finally, there’s a lot of great consultancy packed into the user interface. In case customers want to learn more, we've integrated about 300 different “Technology Cards” and supporting documentation. So if you want to learn about how power saving features work, or want to know what is the difference between a chipset and a module, or understand more about battery technologies, you can actually find out information in this in-built encyclopedia.
The best way to wrap it up would be to say that if you want to be successful, you need to engage the IoT ecosystem and be open to collaborate with and learn from others. That's the whole overarching story of the IoT Solution Optimizer. IoT is very fragmented, but by offering such an interactive, collaborative platform, we can make amazing things happen! Not only does our service enable partners worldwide to come into contact with many new customers, but the same customers can also find and model great products from these partners. And once those customers finish building their own solution, we’re also interested to showcase it on the IoT Solution Optimizer’s product shelves.
What makes our platform a powerful enabler is the large ecosystem of partner companies that stand behind it – over sixty world-leading companies representing numerous industries across the value chain. We work closely with them to develop new features, integrate their know-how, and make complex topics more tangible for end-customers. Our mission from day one has been to connect enterprises to the opportunities of today and tomorrow.
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