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Look in the Mirror and Foresee the Future of Telecommunications

By Martin Laesch, Chief Technology Officer, Neural Technologies

The adoption of 5G will unleash the full potential of augmented and virtual reality, Smart Cities, and the Internet of Things (IoT); this will present opportunities for Communications Service Providers (CSPs) to strengthen current revenue sources or create entirely new revenue streams. Consumers continue to display an insatiable appetite for data and with the consumption of data-hungry applications securing a place in consumers’ daily lives, data usage is set to continue increasing exponentially into the future.

CSPs currently face the ever-increasing challenges of leveraging 5G networks and offering customers new types of services. To overcome these challenges, new digital technologies are required to automate complex business processes to provide customers with the personalized service they have come to expect in a fast-evolving, digital world.

By 2025, CSPs should already be leveraging 5G networks to offer new types of services to various customer segments. The challenges of this endeavor will lie in the ability to scale telecom platforms, automate lifecycle management of network slices, and incorporate predictive demand and maintenance – all while ensuring operational efficiency and a behind-the-scenes workforce to support platform optimization.

Using automation to improve customer services

To address these challenges, an Analytical Data Model (Artificial Intelligence [AI] Data Model) and Machine Learning (ML) were used to develop the Digital Twins technology and tested as part of the 2019 TM Forum Digital Twins catalyst project. The technology serves as a virtual representation of a real-world entity or system, which acts as a mirror to provide a means to simulate, predict, and forecast behavior in the digital world. As part of the catalyst project, the Digital Twins technology was applied to various use cases, such as networks, individuals, organizations, and processes, to determine their effectiveness for telecom industry applications in order to address the aforementioned challenges predicted for 2025.

For the Digital Twins technology to be possible, a common data model is essential. All data needs to be classified and structured in the same way for the digital technology to perform. Digital Integration is the first step to making this possible.

One example of a Digital Twin is that of a customer. A customer’s Digital Twin will be represented in a heatmap with icons to help visualize aspects of their digital lifestyle, such as whether they spend a lot of time gaming, have high mobile usage, or are physically inactive. This twin can then be used by the CSP to tailor messages to that individual. For example, the Digital Twin may show that the customer has a low step count, which could trigger a notification to the individual to be more active.

Using a Digital Twin, operators can also determine where there will be a significant increase in latency within the network, and then share that information with the customer’s Digital Twin to find out what is going to be affected and determine the next best action.

The Digital Twin can also speed up product development cycles, save time and money, and create new business models based on intelligent outcomes. This allows enterprises to personalize the customer experience and meet their precise demands, thereby enabling the enterprises to grow and improve their customer base through targeted campaigns, tailored services, and promotions. In turn, this generates greater customer loyalty and retention as well as customer spending through personalization with timely, individually tailored offers.

Proven methods for the future

The TM Forum Digital Twins catalyst project proved that Digital Twins not only work for the manufacturing industry, but for the telecommunications space as well. As part of the project, Neural Technologies successfully created a Customer Twin alongside the collaborative development of a Mobile Network Twin and an Enterprise IP Network Twin, all originating from the core AI Data Model.

In addition, the catalyst project also demonstrated real-time communication between the twins. Using the proposed TM Forum Open Application Program Interfaces (APIs), Neural Technologies was able to share such simulated, forecasted, and predicted outcomes so that each individual twin was able to recommend a more informed action, instead of a siloed view.

Ultimately through using Digital Twin technologies in the telecommunications industry, a more holistic view across the whole of the operator’s network will be achievable, making it possible to not only make more informed recommended actions, but also make equally fast decisions. As a result, all such “what if” scenarios could now be done in the virtual world without affecting the real world.

Next to the challenges the telecommunications industry will face with the ever-growing volumes of usage data, software vendors like Neural Technologies need to provide solutions that are able to exchange data with any kind of connected system. Information exchange between systems will be key. and the usage of real time APIs will grow. Industry standards for these APIs, like those specified through the TM Forum Open APIs, will help to standardize the exchange of information which Neural Technologies fully supports already today.

With more data becoming available through the Internet of Things and 5G in the future, operators need to prepare themselves to leverage this data. Data is every operator’s asset, and using AI and ML, these assets can be mobilized to enable CSPs to strengthen current revenue sources by creating entirely new revenue streams. Ready to help CSPs achieve these goals, Neural Technologies’ state-of-the-art digital transformation and analytical technologies can help CSPs leverage this data and create new revenue streams.

Bio

Martin Laesch joined Neural Technologies in October 2015 as Senior Vice President of Professional Services and is now the Chief Technology Officer. Martin is responsible for the global Strategy and Products, Solutions development as well as the Consultancy Services to customers. Martin has more than 20 years’ experience in telecommunications services and the software industry, filling roles from Project Manager to Managing Director. Martin joined Neural Technologies in October 2015 by acquisition of Enterest GmbH, which he co-founded in 2003. Martin holds a Master of Computer Science degree.

 

Customizable Cloud-Computing Ensures Successful Commercial Drone Missions

By Barry Alexander, Founder and CEO, Aquiline Drones

Although awareness of and appreciation for commercial drone systems is growing, many businesses remain unaware of the opportunities drones offer to achieve better business results, help streamline business solutions, and elevate profitability. Drones are unique aerial vehicles and are ideal for providing crucial aerial perspectives to assess emergency situations like the recent Australian wildfires, and for delivering critical medical supplies to those in need. Drones are even being used to deliver information to the public, as in the current coronavirus pandemic.

However, most businesses do not realize the intrinsic benefit of integrating drones into their day-to-day operations, whether it be for asset inspection and management, perimeter security, precision farming, aerial ranching, video production, or surveying and mapping. The list continues! But a point of note is this: A drone is just mechanical hardware unless used optimally to gather information. Such reconnaissance activity allows users to capture, analyze, manage, model, and share data insights – usually in real-time. This level of application calls for a robust computing platform that supports complex drone operations and the footage they generate. This is facilitated with cloud computing technology.

According to a recent survey by RedLock, only 7% of businesses firmly believe they have decent visibility over all important company information from drone usage in a well-structured and well-secured enterprise cloud. To address their inadequacies, companies are now seeking out unique, customizable, technical platforms such as the AD Cloud. These platforms offer everything involved in completing commercial drone operations in one centralized setting. The AD Cloud in particular provides a variety of salient features ideal for building highly customizable and large-scale solutions.

Building a Cloud from the Ground Up

Core features and services offered by some of the nation’s most notable cloud companies that have mastered and integrated artificial intelligence (AI) and the Internet-of-Things (IoT) include:

  • Modularity – Scalability for high-density drone operations across industries requires a modular cloud design, in which services can be added a la carte, allowing businesses to start small, then scale up as needed.
  • Unmanned Aerial Vehicle (UAV) Specific – It is important for cloud environments to cater to the industries for which they are being used. Specialized cloud platforms such as the AD Cloud provide algorithms for UAV operations, manufacturing, and maintenance, making the AD Cloud more valuable and more desirable for businesses that want to integrate UAVs into their operations.
  • Aviation Compliance – Drones are aircraft. Accordingly, they must operate and should be held to the same or similar standards as manned aircraft. These standards should be established and regulated by the Federal Aviation Administration (FAA) or the International Civil Aviation Organization (ICAO). A drone-specific cloud should maintain built-in compliance rules to ensure that connected devices remain safe and compliant with regulations and the law.
  • True Autonomy – Allows for autonomous UAV operations with plug-and-play mission capabilities.
  • Data Insights – Specialized algorithms can be created for flight control, traffic management, enhanced awareness, terrain modeling, and image recognition, along with specific additions for more sophisticated scenarios.
  • Full Lifecycle Governance – This includes providing connectivity and insights across the drone lifecycle – from product development, to manufacturing, to UAV operations and MRO – resulting in greater efficiencies and reduced downtime.
  • Dynamic Dashboard – A full-capability digital dashboard accessible on any device delivers a comprehensive, standardized, and flexible user experience (UX) with the power of the cloud at one’s fingertips. Users can plan, collaborate, and execute missions, livestream data and video, and obtain real-time data insights – all from within a single and customizable enterprise asset management (EAM) system.

Further, a comprehensive cloud system such as AD Cloud can also aggregate data, which enables companies to make statistical forecasts and logical inferences for future resource planning and allocations.

A Bright and Lofty Future

Despite its extreme growth within the past decade, the global cloud computing market is forecast to exceed $623 billion by 2023 as 80% of organizations – many using drone technology – migrate to the cloud by 2025.

One key projection is that cloud computing will change the hardware architecture of drones by simplifying these flying robots. With low latency, higher bandwidth, and a highly reliable connection to the cloud, a drone only needs to carry sensors, without requiring any additional power.

Drones and edge computing technology will continue to grow exponentially, allowing for more resolution, more sensor types, and more flight capabilities, while supporting demand for higher frequency and more data. In fact, drone fleets and swarms will have the ability to launch from edge computing hubs to further automate the process.

Another major highlight will be the quick creation and activation of a comprehensive cloud computing-drone infrastructure as directed and overseen by the FAA, the regulatory agency for all UAVs – ensuring safety remains paramount.

Lastly, the recent introduction of a bipartisan bill in Congress entitled, The American Security Drone Act of 2019 essentially bans the use of foreign drones – mainly Chinese drones – and other unmanned aerial systems that have been purchased with federal dollars.

The drone industry continues to gain in purpose and popularity, empowering companies that use them with powerful, customized cloud computing capabilities. Cloud-enabled drone technology increases these companies’ operating efficiency, efficacy, safety, and ultimately, their bottom line. As more of these cloud computer-connected devices take to the sky, we’ll see a world that is truly interconnected within the technological atmosphere.

Bio

A veteran pilot, serial entrepreneur, and visionary leader, Barry Alexander is founder and CEO of Aquiline Drones, a full-service, US-based commercial drone company that boasts an integrated manufacturing and supply chain, world-class MRO services, and real-time data insights to improve ROI across a variety of industries. Barry’s ultimate goal is to revolutionize the entire American drone market through innovative technology and key community and governmental partnerships to create a world in which humans and drones live and operate in harmony for the betterment of society.