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Internet of Things May 2019 Viewpoints

Technology Analyst: Guy Garrud

5G Hardware Developments

Why is this topic significant?

Hardware manufacturers are choosing their strategies for emerging 5G markets.

Description

In April 2019, Apple and Qualcomm announced an agreement to "dismiss all litigation between the two companies worldwide." The announcement came during the first day of a trial between Apple and Qualcomm about a range of intellectual-property disputes. Analysts interpreted the dismissal as indicating that the companies are now prepared to return to a normal business footing—in particular, that Qualcomm may begin supplying 5G components for use in Apple's smartphones. Shortly after the dismissal of actions between Apple and Qualcomm, Intel (which had, for a time, become the sole supplier of 4G chips for Apple's smartphones) announced that it was canceling a planned line of 5G smartphone components.

Also in April 2019, Samsung announced that it had begun mass production of 5G modems and radio-frequency receivers. The Samsung products include both dedicated 5G modems and a modem that supports both 5G and legacy network communications.

Implications

5G is an umbrella term that covers a broad range of next-generation communications technologies. Smartphone 5G hardware is a hotly contested early application because of the high market demand and large established user base. Samsung, in particular, will be keen to carve out a significant market share. The company had to issue a profit warning for the first quarter of 2019 because of a combination of declining demand for smartphones and smartphone components including memory chips and display panels. Samsung Electronics is in a potentially perilous position, because a substantial part of its operations comes from supplying components to other device manufacturers.

However, smartphone 5G hardware is less important for some IoT applications than for the smartphone industry. Smartphones benefit from high-performance components for handling large amounts of data, whereas many IoT applications will instead benefit from systems such as NB-IoT and LTE-M that focus on low-energy long-distance transmission of small amounts of data.

Another important development will be hardware manufacturers' beginning to produce network hardware and device components that use mmWave (millimeter-wave) signals, which form another part of next-generation 5G networks. However, cellular carriers will likely not deploy mmWave infrastructure widely for at least another year because the short communication range of the technology requires a substantial investment in new cell-tower infrastructure.

Impacts/Disruptions

Hardware manufacturers face two broad approaches to 5G hardware: direct competition with other top-level producers and diversification. At present, Qualcomm and Samsung seem set to compete for market share in the first generation of 5G smartphones. Price will be important, but so will device ecosystems. Qualcomm's long-standing relationship with Apple will likely see its hardware in use in 5G iPhones, whereas Samsung components will almost certainly be in future generations of Samsung Galaxy smartphones. Both companies will also see competition from Chinese electronics giant Huawei.

Scale of Impact

  • Low
  • Medium
  • High
The scale of impact for this topic is: High

Time of Impact

  • Now
  • 5 Years
  • 10 Years
  • 15 Years
The time of impact for this topic is: 5 Years

Opportunities in the following industry areas:

Smartphone manufacturing, electronic-component manufacturing, telecoms

Relevant to the following Explorer Technology Areas:

Big Oil and Big Tech Team Up

By David Strachan-Olson
Strachan-Olson is a consultant with Strategic Business Insights.

Why is this topic significant?

Major cloud providers are developing new IoT and AI tools specifically targeting the oil-and-gas industry.

Description

Amazon, Microsoft, and Google are major players in cloud-computing services. These companies are increasingly targeting cloud services for industrial organizations, especially in the oil-and-gas industry.

In March 2019, IHS Markit hosted CERAWeek, a major oil-and-gas conference in Houston, Texas. At this conference, Amazon, Microsoft, and Google made larger appearances than they did in previous years. During an interview, CEO of Amazon Web Services (AWS), Andrew Jassy, highlighted how machine learning, the Internet of Things, and automation will affect the oil-and-gas industry and how AWS could provide solutions for the industry's needs. Jassy mentioned that Shell is using AWS's service to store and process data from seismic images and well logs in order to develop machine-learning tools to identify wells with the best potential. AWS is working with a number of other players, including BP, Shell, Woodside Energy, and Baker Hughes.

In November 2018, Microsoft highlighted Azure's capabilities for oil and gas at the Abu Dhabi International Petroleum Exhibition and Conference. Microsoft focused on Azure IoT Edge, which enables companies to extend cloud intelligence and analytics to edge devices in the field. In 2017, Microsoft announced a seven-year partnership with Chevron to provide data-center services. Since then, Microsoft has also begun to partner with other energy companies, including Exxon Mobil, Equinor, and Schlumberger.

In 2018, Google and Total, a French oil company, signed an agreement to jointly develop artificial-intelligence technology for subsurface-data analysis for oil-and-gas exploration. Google has also partnered with Anadarko Petroleum to develop AI for analyzing large volumes of seismic and operational data to help find oil deposits, maximize output, and increase efficiency.

Implications

Cloud platforms can provide numerous services for the oil-and-gas industry. Basic services include cloud infrastructure to host internal information-technology applications, store data, and provide scalable high-performance computing resources. Cloud companies can also provide solutions for managing vast IoT networks and deploying data pipelines and trained machine-learning algorithms to make the best use of remote assets. Advanced cloud services offer data-analytics and machine-learning tools that enable companies to analyze big data in new ways in order to gain actionable insights. For oil and gas, the biggest applications of machine learning will likely be for predictive maintenance and analyzing oil-field-exploration data.

Impacts/Disruptions

Partnerships between the oil-and-gas sector and big tech companies highlight one of the most significant challenges companies face when undergoing a digital transformation. For many companies, adding sensors, connecting devices, and collecting data are easy, but cleaning data, interpreting data, and using data to improve operations or increase revenue are the challenge. An estimate by Accenture says that an oil well produces 1 to 2 terabytes of data a day. Darryl Willis, a former oil geoscientist now selling Google Cloud to oil companies, estimates that oil companies use only 1% to 4% of the data available to them.

The field of machine learning is still in its infancy, and many companies do not have employees with machine-learning expertise, so they must rely on technology companies to cover this skills gap. Cloud providers are leveraging their cloud-infrastructure capabilities to expand into higher-value services such as IoT administration platforms and machine-learning solutions.

Scale of Impact

  • Low
  • Medium
  • High
The scale of impact for this topic is: High

Time of Impact

  • Now
  • 5 Years
  • 10 Years
  • 15 Years
The time of impact for this topic is: Now to 5 Years

Opportunities in the following industry areas:

Cloud infrastructure, cloud services, machine learning, IoT networks, oil exploration, oil extraction, oil processing

Relevant to the following Explorer Technology Areas: