IoT for Tourism and Travel

Tourism is not the same thing as “travel,” but internet of things use cases will be found in both. Think of travel as “getting from one place to another,” while tourism is “travel to a destination for fun or work.” You may think of travel as a component of tourism, or tourism as a subset of reasons to travel. 

Either way, the ecosystem involves airlines, ground transport, hotels and accommodation, restaurants, food and beverage, attractions, entertainment and shopping. IoT applications can improve traveler or tourist experience, create more sustainable and pleasurable tourism and improve the effectiveness and efficiency of all support infrastructures and services underpinning travel and tourism. 

About 86 percent of airline industry information technology professionals believed the internet of things will provide benefits “within three years,” a 2015 survey conducted by SITA suggested. That arguably proved true if one considers a consumer smartphone, tablet or smart watch an IoT device. Personalization of the passenger experience was an early initiative.  

Flight status updates are one example of the passenger use case, while check-in personnel, baggage handlers and ramp staff provide examples of employee use cases. 

By the time of the 2019 survey, artificial intelligence had become a stated area of concern. The 2020 report on passenger use of airline travel technology showed widespread use of personal devices for booking, checkin and dwell time functions. Again, some might quibble about whether tablets and smartphones--though connected devices--represent “IoT” use cases.  

Many would argue use of IoT is part of the larger digital transformation of airline travel, including smart luggage and use of beacons to support travelers. Many of us would argue the coming important IoT innovations will come from use of sensors (not consumer devices) applied to the other passenger operations sides of the business, such as analytics on food and beverage consumption, seat pitch, seat belt condition (on or off), seat wear and tear, restroom monitoring and other elements of the actual in-flight experience.  

Of more immediate and obvious value are the use of sensors to detect mechanical issues before they happen. Equipment monitoring has been found to reduce delays by about 20 percent, for example.  

 

Expected use cases include in-room tablets that enable guests to personalize and adjust room temperature, control TV, elevators, and heaters, turn lighting on and off, schedule wake up calls. 

Electronic key cards on guest smartphones, allowing them to check-in without anyone’s assistance, as well as smart locks also are expected use cases.

 Real-time information already is a use case, but IoT applications will help travellers change flights and make connecting flights. Directions to gates at the airport, instructions on how to board a flight and information security checks will be IoT-enabled.  

In flight, sensors might be embedded in the seats inside the aircraft that can measure the anxiety level, heart rate, body temperature, hydration level of travellers, allowing the cabin staff to react to passenger needs. 

 

IoT will streamline the day-to-day operations of airports in areas such as baggage handling and personalization. 

 

IoT will support automation of many crucial business functions of travel and hotel businesses, including everything connected with supply chains and back-end support operations, such as maintenance. 

Tourist experience, probably based on apps available on their smartphones, also are likely to become common.

IoT and Edge are Virtually Inseparable

It is almost impossible to clearly separate the value of internet of things from the value of edge computing, as the one generally drives the other. The value of sensor data, though, mostly hinges on the analytics. 

Insights gleaned by analytics is the driver of value produced by internet of things sensors, but a fraction of the data is likely to  produce most of the value. Alarms and control of processes are the common use cases. 

By perhaps 2028, the greatest single area of edge infrastructure investment will have been made to support mobile customers and residential consumers. 

source: State of the Edge 

Key applications include infotainment. In fact, infotainment might represent between 29 percent and 47 percent of the global edge footprint between 2019 and 2028, the report says. 

Smart appliances might represent 19 percent of the edge footprint between 2019 and 2028. Security with an edge footprint will increase from 10 to 16 percent. 

The footprint for energy management is forecast to increase from 10 to 16 percent. Edge computing facilities also will play a role in assisted living, at two to five percent of the total edge capability, between 2019 and 2028.

“For example, on an oil rig that has 30,000 sensors, only one percent of the data are examined,” McKinsey consultants say. Most of the data is used to detect and control anomalies--a valuable function, to be sure. 

source: State of the Edge 

On the other hand, optimization and prediction might provide the greatest value, say James Manyika, Jonathan Woetzel, and Richard Dobbs McKinsey Global Institute directors; Michael Chui, partner; Peter Bisson, director in McKinsey’s Stamford office; Jacques Bughin, director in the Brussels office and Dan Aharon, consultant in the New York office.

 source: State of the Edge 

Mobile Operator Virtualization and Edge Computing are Inseparable

One big change telecom operator core networks are making is virtualization: the functional separation of applications and software from hardware platforms. At the same time, 5G core network virtualization requires use of edge computing. At this point, virtualization and edge computing require each other.

That allows use of commercial, off the shelf hardware, which provides capital investment and operating cost advantages and sometimes greater simplicity. Increasingly, it also is possible to abstract the hardware platforms as well, using cloud computing supplied by third parties. 

Since March 2020, Google Cloud has been developing a 5G strategy for mobile operator networks, aiming to sell Google Cloud computing as the fabric for virtualized 5G network operations. 

Google Cloud and Intel now have announced they have a platform for supporting virtual radio access networks or open RAN operations. 

 

You might think of this as one way edge computing is going to develop with 5G, or a way virtualized network processes will be supported, computationally. 

One might also see this as another example of telco or enterprise computing virtualization, open network standards and use of commercial off-the-shelf hardware, open source and abstracted functions using application programming interfaces. 

The collaboration uses Google Cloud's Anthos application platform and Intel cloud-native platforms and solutions, including Intel's cloud-native Open Network Edge Service Software (OpenNESS) deployment model. 

Google already had created mechanisms to support application operation at the edge, using Anthos.

Such abstraction of the computing functions supporting core networks illustrates the way telcos themselves will be potential customers of cloud computing service providers. 

But it also is, at the same time, part of the adoption of edge computing.

Who Wins from Private 5G?

In most cases, edge computing and private network growth will go hand-in-hand. The point of the private networks (often using either 4G or 5G) will be to reduce the latency of sensor data and allow faster processing of raw data to glean insights. That will often also be directly related to process control and use of internet of things sensors.  

Faster process control response will typically also require local processing, which means more edge computing, either onboard devices, on the premises or at some close external location. The more latency-dependent the use case, the more likely the computation and analysis will occur on premises. 

And in many industry verticals, the more-predictable response from private 5G  is one reason why 5G enterprise use cases are expected to drive a disproportionate share of incremental 5G revenues from new use cases. 

Many in the edge computing, cloud computing, internet of things and 5G ecosystems will gain revenue. 

So private 5G networks are expected to be a growth industry, but the issue remains “who gains” and “how much?” As with past private networks, such as local area networks, revenue gained by connectivity service providers is one thing; revenue for others in the ecosystem is quite another matter. 

Private networks create direct markets for devices, Wi-Fi chipset suppliers and router suppliers; system integrators and distributors. Connectivity providers gain indirectly, from some positive impact on broadband access accounts or the spending on such accounts.

source: 5G Americas 

In the case of 5G private networks, much of the revenue will be gained by infrastructure suppliers, though some incremental revenue also will be earned by suppliers of 5G public network connections or broadband access services. 

Much of the connectivity revenue is possibly going to be earned by dedicated low-power-wide-area service providers, as well. Some 5G service providers will be more active as system integrators. 

And it remains possible that some 5G service providers will be significant application providers in a few industry verticals, such as the automotive industry and autonomous vehicles, terrestrial and aerial.  

It also will be nearly impossible to separate the value--and spending on--edge computing from spending on 5G private networks.

The Cloud Without the Wait: Mobile Edge Computing and 5G

Intelligence Close to IoT sensors is One 5G Role

Data Gravity and the Edge

Data gravity is the observation that data and applications are attracted to each other, perhaps in the same way that population, economic activity and firms tend to cluster in a small number of metro areas. 

source: Digital Realty 

One explanation for why data gravity exists is that extremely large data sets tend to attract applications intended to glean insights from that data. 

Another reason is that colocation of many servers used by many entities reduces latency and therefore improves performance, while also minimizing wide area network costs and bandwidth. That also causes a clustering of apps, data and firms in a single physical location. 

In one sense, edge computing is an effort to counter data gravity, processing at the edge without storing or processing much data in centralized locations.

How Much IoT and Edge Computing Activity by Top Mobile Operators?

It always is a bit tricky to figure out what the internet of things means for retail connectivity and edge services providers. Much of the total IoT revenue will be earned by suppliers of computing infrastructure or devices, applications or system integration and consulting services, not “new connectivity” or “edge computing as a service” revenue.

“Connected devices” do mean some potential upside for sales of more connectivity accounts. The issue is “how much?” Likewise, use of more IoT sensors also increases demand for edge computing, and the issue there is how much incremental revenue exists for computing on premises or remote servers, as opposed to “onboard” processing. 

According to Berg Insight, the top ten mobile operators reported a combined active base of 1.33 billion cellular IoT connections at the end of 2019, accounting for 85 percent of total industry connections. 

China Mobile was at that point the world’s largest provider of cellular IoT connectivity services with an estimated 683 million cellular IoT connections. China Unicom and China Telecom ranked second and third with 190 million and 157 million connections respectively.

Vodafone reported 97 million connections, AT&T with 66 million, while Verizon, Deutsche Telekom and Telefónica had in the range 24 million to 46 million cellular IoT connections. 

Orange and Telenor had 17 million and 16 million connections respectively. Year-on-year growth rates for the Western operators were in the range of 10 percent to 30 percent.

 But not every connected sensor requires a wide area network connection of its own, and might use a local communications link of some kind, such as Bluetooth or Wi-Fi. On the other hand, it is likely going to be more common that IoT sensors will use edge computing, onboard, on a nearby device, a premises server or a nearby off-premises server. 

Also, not all connected devices are necessarily IoT devices. Some connectivity supplies might count tablet or PC connections in the same category as sensor connections. Not all would agree that is the right classification, though in the long term it should not matter, as such cases will be a small fraction of total IoT connections. 

source: IoT5.net 

In the recent past, devices such as smartphones, tablets, PCs and workstations were counted as connected devices by some analysts. That perhaps matters for the Wi-Fi ecosystem and its suppliers, but has not direct revenue implications for connectivity service providers. 

In other words, among the things that matter when looking at IoT revenue upside for connectivity providers is the new demand for wide area network connections. Also important are any related moves by mobile and other connectivity providers into edge computing as a service or other edge computing roles. 

source: IoT Analytics 

“Mobile operators looking to increase IoT revenues increasingly focus on adding cloud services and security capabilities on top of their connectivity offering,” Berg Insight noted.

That said, it is doubtful that IoT revenues are much more than one percent to two percent of any mobile operator's total revenue, at the moment. Many observers expect that to change over time, as IoT devices become far more numerous than phones and other connected devices.

Hyperscale Cloud Computing Market is Not Yet Stable, But Getting Close

The hyperscale cloud computing business now is a market share battle between just four firms globally, according to Wikibon: Amazon Web Services, Microsoft Azure, Alibaba and Google Cloud Platform. 

source: Wikibon 

Significantly, the market share structure is approaching a distribution that historically suggests a stable. The stable but competitive market structure has a 4:2:1 pattern. The leader has twice the share of the number-two provider, which in turn has twice the share of number three. 

source: Wikibon 

That is not exactly what we see for hyperscale cloud computing suppliers in the infrastructure and platform segments of the market, but is getting close to the predicted pattern.

AWS, at 53 percent share, has not double the share of Azure, but is within the general pattern. Azure has more than twice the share of Alibaba. 

That suggests the number-two provider will eventually lose some share, while either the present number-three or number-four providers will gain share. 

The share amounts and positions change if hosted private cloud services are added.

Edge Computing Value Includes Lower WAN Spending

The business advantage of edge computing is partly latency performance and partly bandwidth efficiency, the same rationale that drove content delivery networks to edge computing (storage, primarily). 

Video consumption patterns typically have 80 percent of customers consuming 20 percent or less of the available content on a streaming platform, for example. 

By edge caching 20 percent of the catalog, content providers have 80 percent of traffic being pulled from edge data centers, and not across the wide area network backbone.

That improves user experience, but also means less spending on WAN facilities. 

source: Openstack

The theory is that applications and use cases that require lots of processing--including those apps requiring use of artificial intelligence--can do much of the heavy lifting locally. The same goes for use cases involving process control, which needs to happen in real time, or nearly in real time. 

Customers Often Buy for Reasons Not Directly Related to Supplier Messaging

The practical reasons information technology or communications technology get deployed often are different from the reasons suppliers suggest. Edge computing, for example, is “supposed” to be about support for ultra-low latency applications. 

But a survey of 800 enterprise IT decision makers by IDC suggests the practical reasons have more to do with bandwidth costs or security than latency. 

Nearly 30 percent reported that the “cost of bandwidth” was a reason for using edge computing. Some 27 percent said security was the reason for edge computing deployment. About 19 percent cited latency as a primary motivation for edge computing. 

source: IDC, Lumen Technologies 

On the other hand, latency below 5 milliseconds also was cited as a primary requirement for edge applications. 

There arguably are more prosaic rationales, on the supplier side of the business. Consider 5G, for example. “Periodically the telecom industry needs a buzz-worthy topic to engage potential customers,” says Matt Bramson, founder of consultancy Advantary. “It starts conversations” that allow firms to sell something to a customer, even if it is not 5G. 

Basically, 5G drives interactions with customers and prospects that can result in sales, Bramson notes. Granted, that is not why global standards bodies, service providers and infrastructure suppliers support 5G.

But the actual value can be distinct from the formal justifications. IoT, 5G and edge computing give service providers and infrastructure suppliers a reason to talk to their potential customers and prospects. 

The same sort of process often happens with gigabit internet access. Even when the marketing message is “gigabit,” prospects often wind up buying some level of service other than gigabit internet access. The point is that the marketing message creates a selling opportunity, even when the specific messaging and specific products are not, in the end, what the customer buys.