Airports: The roles of 5G & private networks

A deep dive into private networks for the aviation vertical

This report is intended to be both a specific examination of an important sector of opportunity for Private 5G (P5G) and an example of the complexity of major industrial sectors and campus-based environments. It also covers opportunities for MNOs.

Airports have been among the earliest sites for private cellular and remain a major focus for vendors and service providers, as solutions mature and spectrum options proliferate. They already generate huge investments into public cellular (indoor and outdoor) as well as being headline sites for Wi-Fi deployment and use. They also employ dozens of other wireless technologies, from radar to critical voice communications.

In the case of airports, the largest are so large and diverse that they actually resemble cities, with “private” networks serving an environment actually quite similar to a small national operator or regional MNO. For example, Dallas Fort-Worth airport spans 27 square miles – larger than the island of Manhattan or the principality of San Marino. They may have 100s of companies as tenants, and 10000s of employees – as well as passengers, vehicles and IoT devices. This may mean that they end up with multiple private wireless networks in different parts of the airfield – from the passenger terminal to maintenance hangars to hotels, to the car-rental facility.

They are also intensive Coordination Age ecosystems. Their effective operation involves the safe and secure management of millions of physical and digital assets across multiple parties, billions of dollars, and many lives.

Often technology product and marketing executives think of industry sectors as monolithic (“finance”, “retail”, “oil and gas” etc), typically aligning with familiar industry classification codes. The truth is that each industry has multiple sub-sectors and varied site types, numerous applications, several user-groups, arrays of legacy systems and technology vendors, and differing attitudes and affordability of wireless solutions.

STL Partners hopes that this exercise examining airports will prompt suppliers and operators to drill into other vertical sectors in similar depth. Depending on the response to this type of document, we may well write up other areas in similar fashion in future. (We are also available for private analysis projects).

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Sector trends and drivers affecting private 5G networks

This report is not the appropriate venue for a full analysis of the aviation and airport industry. However, a number of top-level trends are important to understand, as there is a fairly direct link to the deployment of cellular technologies and private 4G/5G.

Trends for airlines

Before the pandemic, there was a sustained growth in worldwide air-passenger traffic, fuelled by the growth of Chinese and Indian middle-classes, as well as inter-regional and long-haul flights in and between Europe, Asia, the Americas and the Middle East. Forecasts were continued for growth, with air-freight also increasing alongside passenger numbers.

This growth resulted in numerous impacts on aviation more broadly:

  • Construction of many entirely new airports, along with extra terminals and refurbishments at established sites. Examples have included immense new airports at Beijing, Doha and Istanbul. These developments typically include huge focus on efficiency, IoT and safety – all heavily reliant on connectivity.
  • Low-cost and “basic” airlines such as Southwest, EasyJet, AirAsia and others have grown rapidly (at least pre-pandemic). Some have built dedicated terminals. Many have a huge focus on fast “turns” of aircraft between arrival and departure. This needs enhanced coordination and communications between multiple ground-service providers to manage 50+ tasks, from baggage unloading to cleaning and refuelling.
  • Established airlines focusing on greater efficiency, novel route choices, new hub airports, better customer satisfaction via information and interactivity throughout their journeys, as well as pushing ancillary services such as contract maintenance. Again, connectivity plays a variety of roles, from hangars to in-flight wireless.
  • Major warehousing and logistics centres built at airports for companies such as Fedex and UPS, as well as eCommerce players such as Amazon starting to build fleets of planes and on- or near-airport facilities. These typically feature high levels of automation and wide use of robotics.
Long-term air passenger growth (pre-pandemic)

Long-term air passenger growth (pre-pandemic)

Airports as “hubs” for multiple businesses

Many airports now operate on-site business centres, hotels, large retail facilities – as well as growing sophistication of air-freight, contract maintenance services and aircraft refits. Each is often a business in its own right, with separate buildings – but must also coordinate with the central airport authority in terms of security, traffic, signage and vehicle movements.

As well as their own internal connectivity requirements for employees and a growing range of IoT systems, the site-owners are also responsible for wired and wireless links for stakeholders such as:

  • Transportation companies
    • Airlines, both within the terminals and at hangars / warehouses and nearby offices.
    • Shipping agents and freight forwarders
    • Logistics and package-delivery firms
  • Services providers
    • National mobile network operators
    • Retailers and other concessions
    • Vehicle rental agencies
    • Bus, rail, taxi & tour companies
    • Caterers
    • Fuel companies
    • Security firms
    • On-site hotels, warehouses and business parks
    • Insurance and finance organisations
  • Operations and public safety
    • Police and firefighters
    • Medical services
    • Air / port traffic control
    • Power and lighting providers
    • Construction contractors

Many of these groups could potentially justify their own investments in private cellular networks (as well as indoor coverage and Wi-Fi if they have dedicated buildings). An open question is whether airport authorities will try to deploy fully campus-wide networks, or whether a diverse array of separate infrastructures will emerge organically.

Industry transformation, automation and IoT-led innovation

As well as the airlines, the airport authorities have become ever-more focused on technology of the site overall. They are aware of operational efficiency, security and safety – and increasing the potential to earn extra revenues from passengers. A very broad array of existing and new use-cases are leaning on improved connectivity, such as:

  • In-building coverage (and huge capacity) for passengers and workers, all of whom expect both multi-network cellular and ubiquitous Wi-Fi availability
  • Prolific use of digital sign-boards for passengers, staff, plane/ship crews etc
  • Freight-tracking, including details about pallets and containers
  • Security cameras and sensors
  • Smart lighting for runways, loading areas and local roadways
  • Support of complex and mission-critical baggage-handling systems
  • Border and customs functions, including automated passport scanners with video analytics
  • “Smart building” technology ensuring optimal use of ventilation, heating, lighting and safety sensors
  • Robotic and remote-controlled vehicles, such as tugs or drones
  • Voice communications systems, now evolving from 2-way radios to cellular-based systems
  • Maintenance systems for aircraft in hangars – increasingly with high-definition video inspections, augmented reality for engineers, and strict requirements on documentation and record-keeping.

Security and safety concerns

Airports have always had to contend with security issues, from immigration to fire-safety, anti-terrorism, theft and smuggling operations. This has required continued evolution of screening systems, cameras, staff access control and multiple layers of analytics software.

This translates to private cellular in a number of ways:

  • Desire to update legacy critical communications systems (e.g. TETRA radios) to more-capable LTE or 5G equivalents, to enable data, video and other applications.
  • Requirement for networks with a bias towards data uplink rather than downlink, especially for HD video and other security  This may mean a preference for separate frequencies to the public networks, in order to accommodate a different mix of up/down traffic.
  • Involvement of a wide range of systems integrators and critical communications specialists with a long history of deploying reliable wireless  Many are adopting 4G and 5G skill-sets internally.
  • Requirement for 100% coverage of the airport environment, both indoors and outdoors as far as the perimeter fence. This may be outside the coverage of many public networks, especially for higher-frequency 5G

Complex wireless environment

It is important to recognise that airfields have a huge array of different technology systems, many of which depend on radio communications or other electromagnetic use-cases. Some of these – such as radars – can occupy frequency bands quite close to those used for 4G or 5G mobile. There are also assorted niche applications, for air traffic control, critical communications among ground workers and emergency services, satellite connectivity for aircraft, scientific instruments for weather forecasting and many others. Wi-Fi is used intensively, both inside the terminal and across some outdoor areas. Some airports have sections used by the military as well as civil aviation, with yet another group of radio types and frequencies employed.

This has several implications:

  • Unlike many other sites, cellular communications is not the most important use of spectrum  Mobile networks – whether public or private – need to fit alongside a huge variety of other services and functions.
  • Some frequency bands that are offered by regulators on a local basis for private 4G/5G may not be available for licensing at airports, as there may be important incumbent users.
  • Airports take increasing interest in overall spectrum management tools, as well as site surveys and the ability to intervene rapidly in case of problems.
  • The aviation industry has a large number of wireless and RF specialists, some of whom are likely to be cross-trained in cellular  This makes it more capable than many sectors to adopt private networks rather than always relying on public MNO service.

Covid-19 Pandemic

Since early 2020, the aviation and airline sector has been decimated by travel restrictions imposed because of the pandemic. Traffic and passenger levels at many airports fell to 20% of pre-pandemic levels or lower. However, as vaccination programs enable the re-opening of travel, growth is starting to occur again.

Various after-effects of the pandemic will increase the need for automation, connectivity and communications. There are new security-checks on vaccination and testing status, more cameras for fever-detection and mask-compliance, automated sanitising of surfaces and much more. Many airports have needed to reconfigure the layouts of their terminals to accommodate testing centres, facilitate social distancing, or sometimes close areas in order to reduce costs. This puts a premium on wireless connectivity that can be adapt to new circumstances rapidly.

Another impact of the last 2 years has been growth in the importance of cargo shipments, from both dedicated freight terminals and in commercial airliners. This has led to new warehouse facilities being constructed, as well as different types of asset tracking and loading vehicles being employed. Again, this has driven the need for better connectivity.

Table of content

  • Executive Summary
    • Overview
    • Recommendations for Airport Operators & Airlines
    • Recommendations for Mobile Operators
    • Recommendations for Regulators & Policymakers
    • Recommendations for Vendors
  • Introduction
    • Sector trends and drivers affecting private networks
  • Evolving airport use-cases for 4G/5G
    • Understanding airports’ layout
    • Background: Public cellular at airports
    • From public to private connectivity: growth in B2B wireless
    • Specific use-cases for private 4G / 5G at airports
  • Airports – a subset of “campus” networks
    • Characteristics of campus networks
    • Adjacent trends
    • Campus networks: who is responsible?
  • Building & operating airport private networks
    • Supply-side evolution for airport networks
    • Airport stakeholders
    • Monetisation opportunities
    • Airport private network case studies
    • Can public 5G network slicing work instead of private 5G?
    • Where does Wi-Fi & other wireless technology fit?

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A3 for enterprise: Where should telcos focus?

A3 capabilities operators can offer enterprise customers

In this research we explore the potential enterprise solutions leveraging analytics, AI and automation (A3) that telcos can offer their enterprise customers. Our research builds on a previous STL Partners report Telco data monetisation: What’s it worth? which modelled the financial opportunity for telco data monetisation – i.e. purely the machine learning (ML) and analytics component of A3 – for 200+ use cases across 13 verticals.

In this report, we expand our analysis to include the importance of different types of AI and automation in implementing the 200+ use cases for enterprises and assess the feasibility for telcos to acquire and integrate those capabilities into their enterprise services.

We identified eight different types of A3 capabilities required to implement our 200+ use cases.

These capability types are organised below roughly in order of the number of use cases for which they are relevant (i.e. people analytics is required in the most use cases, and human learning is needed in the fewest).

The ninth category, Data provision, does not actually require any AI or automation skills beyond ML for data management, so we include it in the list primarily because it remains an opportunity for telcos that do not develop additional A3 capabilities for enterprise.

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Most relevant A3 capabilities across 200+ use cases

9-types-of-A3-analytics-AI-automation

Most relevant A3 capabilities for leveraging enterprise solutions

People analytics: This is the strongest opportunity for telcos as it uses their comprehensive customer data. Analytics and machine learning are required for segmentation and personalisation of messaging or action. Any telco with a statistically-relevant market share can create products – although specialist sales capabilities are still essential.

IoT analytics: Although telcos offering IoT products do not immediately have access to the payload data from devices, the largest telcos are offering a range of products which use analytics/ML to detect patterns or spot anomalies from connected sensors and other devices.

Other analytics: Similar to IoT, the majority of other analytics A3 use cases are around pattern or anomaly detection, where integration of telco data can increase the accuracy and success of A3 solutions. Many of the use cases here are very specific to the vertical. For example, risk management in financial services or tracking of electronic prescriptions in healthcare – which means that a telco will need to have existing products and sales capability in these verticals to make it worthwhile adding in new analytics or ML capabilities.

Real time: These use cases mainly need A3 to understand and act on triggers coming from customer behaviour and have mixed appeal to telcos. Telcos already play a significant role in a small number of uses cases, such as mobile marketing. Some telcos are also active in less mature use cases such as patient messaging in healthcare settings (e.g. real-time reminders to take medication or remote monitoring of vulnerable adults). Of the rest of the use cases that require real time automation, a subset could be enhanced with messaging. This would primarily be attractive to mobile operators, especially if they offer broader relevant enterprise solutions – for example, if a telco was involved in a connected public transport solution, then it could also offer passenger messaging.

Remote monitoring/control: Solutions track both things and people and use A3 to spot issues, do diagnostic analysis and prescribe solutions to the problems identified. The larger telcos already have solutions in some verticals, and 5G may bring more opportunities, such as monitoring of remote sites or traffic congestion monitoring.

Video analytics: Where telcos have CCTV implementations or video, there is opportunity to add in analytics solutions (potentially at the edge).

Human interactions: The majority of telco opportunities here relate to the provision of chatbots into enterprise contact centres.

Human learning: A group of low feasibility use cases around training (for example, an engineer on a manufacturing floor who uses a heads-up augmented/virtual reality (AR/VR) display to understand the resolution to a problem in front of them) or information provision (for example, providing retail customers with information via AR applications).

 

Table of Contents

  • Executive Summary
    • Which A3 capabilities should telcos prioritise?
    • What makes an investment worthwhile?
    • Next steps
  • Introduction
  • Vertical opportunities
    • Key takeaways
  • A3 technology: Where should telcos focus?
    • Key takeaways
    • Assessing the telco opportunity for nine A3 capabilities
  • Verizon case study
  • Details of vertical opportunities
  • Conclusion
  • Appendix 1 – full list of 200 use cases

 

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Telco data monetisation: What is it worth?

Data revenue opportunities are variable

Monetisation of telco data has been an area of activity for the last six years. However, telcos’ interest levels have varied over time due to the complexity of delivering and selling such a diverse range of products, as well as highly variable revenue opportunities depending on the vertical. Telcos’ appetite to pursue data monetisation has also been heavily impacted by the fortunes of other new telco products, in particular IoT, owing to the link between many data/analytics products and IoT solutions.

This report assesses the opportunity for telcos to monetise their data and provide associated data analytics products in two parts:

  1. First, we look at the range of products and services a telco needs to create in order to deliver financial value.
  2. Then, we explore the main use cases and actual financial value of telco data analytics products across 12 verticals, plus horizontal solutions that apply to multiple verticals.

Telco data monetisation: Calculation methodology

The methodology used to model the financial value of telco data analytics is outlined in the figure below.

  • The starting point for this analysis is 210 data or data analytics use cases, spread across 12 verticals and the horizontal solutions applicable to multiple verticals.
  • We then assess how difficult it is for a telco to address each use case, based on pre-requisite supporting platforms and solutions, regulatory constraints, etc. (shown in red). This evaluation enables us to assess how likely telcos are to develop products for each use case.
  • Thirdly, we assess which types of telco are able to develop the use case (in yellow). For example, telcos in a market with particularly restrictive regulation around use of personal data are simply not able to create certain products.
  • Finally, it is necessary to understand whether the data/analytics products created for a use case can be offered as an independent, standalone product, or more likely to be provided as a bolt-on service to another, pre-existing solution. This question is primarily pertinent in the IoT space where basic data/analytics are likely to be included in the price of the IoT service.
    • For products that we expect to be sold independently, we calculate the potential revenue based on estimated pricing for the type of data product, where known, and likely volumes that a telco will sell in a year.
    • For data analytics products closely linked to IoT, we attach no monetary value.

Calculation methodology for the feasibility and value of telco data monetisation use cases

Rationale behind data monetisation potential

Source: STL Partners, Charlotte Patrick Consult

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Viewing the data

Underlying the analysis in this report is a database tool including a detailed assessment of each of the 210 data monetisation use cases we have identified, with numerical analysis and charting capabilities. We know many of our readers will be interested to explore the detailed data, and so have made it available for download on the website in the form of an Excel spreadsheet.

Full use case database and analysis available on our website

Source: STL Partners

Table of Contents

  • Executive Summary
  • Introduction
    • Calculation methodology
  • What is this market worth to telcos?
  • Creating products for data monetisation
    • Telco products for the ecosystem
    • Data and analytics for IoT
    • Use of location in data monetisation
  • Maximising value in different verticals
    • Advertising and market research
    • Agriculture
    • Finance
    • Government
    • Insurance
    • Healthcare
    • Manufacturing
    • Real estate and construction
    • Retail
    • Telecom, media and technology
    • Transportation
    • Utilities
    • Horizontal solutions for all verticals
  • Conclusion and recommendations
    • How to pick a winning project
  • Index

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The IoT money problem: 3 options

Introduction

IoT has been a hot topic since 2010, but despite countless IoT initiatives being launched questions remain about how to monetise the opportunity.

This report presents:

  • A top-level summary of our thinking on IoT so far
  • Examples of 12 IoT verticals and over 40 use-cases
  • Case-studies of four telcos’ experimentation in IoT
  • Three potential roles that could help telcos monetise IoT

Overview

In the early days of the IoT (about five years ago) cellular connectivity was expected to play a major role – Ericsson predicted 50 billion connected devices by 2020, 20 billion of which would be cellular.

However, many IoT products have evolved without cellular connectivity, and lower cost connectivity solutions – such as SIGFOX – have had a considerable impact on the market.

Ericsson now forecasts that, although the headline number of around 50 billion connected devices by 2020 will remain the same, just over 1 billion will use cellular.

Despite these changes IoT is still a significant opportunity for telcos, but they need to change their IoT strategy to become more than connectivity providers as the value of this role in the ecosystem is likely to be modest.

Mapping the IoT ecosystem

The term IoT describes a diverse ecosystem covering a wide range of different connectivity types and use-cases. Therefore, to understand IoT better it is necessary to break it down into horizontal layers and vertical segments (see Figure 1).

Figure 1: A simplified map of the IoT ecosystem

Source: STL Partners

We are seeking input from our clients to shape our IoT research and have put together a short survey asking for your thoughts on:

  • What role telcos can play in the IoT ecosystem
  • Which verticals telcos can be successful in
  • What challenges telcos facing in IoT
  • How can STL support telcos developing their IoT strategy

To thank you for your time we will send you a summary of the survey results at the end of June 2017.

…to access the other 28 pages of this 31 page Telco 2.0 Report, including…

  • Introduction
  • Mapping the IoT ecosystem
  • Overview
  • Mapping the IoT ecosystem
  • IoT: A complicated and evolving market
  • Telcos are moving beyond connectivity
  • And use cases are increasing in complexity
  • IoT verticals – different end-customers with different needs
  • 12 examples of IoT verticals
  • What connectivity should telcos provide?
  • Four examples of IoT experimentation
  • Case study 1: AT&T: Vertically-integrated ecosystem architect
  • Case study 2: Vodafone: a ‘connectivity plus’ approach
  • Case study 3: SK Telecom: ecnouraging innovation through interoperability
  • Case study 4: Deutsche Telekom AG: the open platform integrator
  • Three potential monetisation strategies
  • Ecosystem orchestrator
  • Vertical champion
  • Trust broker
  • Conclusions

…and the following figures…   

  • Figure 1: A simplified map of the IoT ecosystem
  • Figure 2: Telcos moving beyond connectivity
  • Figure 3: IoT use cases are increasing in complexity
  • Figure 4: Use cases in manufacturing
  • Figure 5: Use cases in transportation
  • Figure 6: Use cases in utilities
  • Figure 7: Use cases in surveillance
  • Figure 8: Use cases in smart cities
  • Figure 9: Use cases in health & care
  • Figure 10: Use cases in agriculture
  • Figure 11: Use cases in extractive industries
  • Figure 12: Use cases in retail
  • Figure 13: Use cases in finance
  • Figure 14: Use cases in logistics
  • Figure 15: Use cases in smart home / building
  • Figure 16: Connectivity complexity profile for pay-as-you-drive insurance and rental services
  • Figure 17: Telco opportunity for deep learning pay-as-you-drive insurance and rental services