The Future of IoT

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The Future of IoT

The pace of Massive IoT roll-outs is expected to be slower throughout 2020 compared to 2019 due to the COVID-19 crisis. However, the number of Massive IoT connections is projected to continue growing throughout the 2019-2025 forecast period.

Impact of 5G on IoT

(i) Increase in Data Speed

  • According to Ericsson, 5G technology forms the main foundation for the full realization of IoT's potential. According to their June 2020 mobility report, a total of 190 million 5G subscriptions are expected by the end of the year and around 2.8 billion by 2025.
  • Thales Group reports that 5G technology is 10-100 times faster than the current 4G LTE and is expected to benefit nearly all IoT devices with increased communication speeds across various applications, including healthcare, industrial and critical communications.
  • The increase in speed offered by 5G technology will enable real-time communications within IoT applications, with an extremely low tolerance for error, such as smart vehicles and other connected transport infrastructure, including trucks, buses, and cars, where a split-second obstruction could imply a 4-way crash at an intersection or disruption in the flow of traffic.

(ii) Decrease in Latency

  • The latency rate of 5G technology is extremely low, recorded at one-millisecond compared to 4G, which offers a 200-millisecond latency rate.
  • Latency majorly impacts the response time following stimulation or request for data, with 5G technology's low latency allowing real-time interactivity within IoT applications, including services that use the cloud, therefore, enabling such concepts as autonomous vehicles.

(iii) Support of Larger Device Volumes

  • 5G technology supports over 100 times more connected devices per unit area than 4G technology, equivalent to 1 million devices per 1 square km or 0.386 miles.
  • The technology's ability to support a massive IoT ecosystem involving both static and mobile devices with varying speed and bandwidth requirements enables more efficiency in data management, communication, and data intelligence.

Challenges in the IoT Market

  • According to Microsoft's July 2019 signals report, the top three challenges in the IoT market, as reported by companies both at the proof of concept (POC) stage and after initial roll-out, include technical and complexity issues, security concerns, and lack of knowledge, training, or talent.
  • These challenges are important because, despite the growing success in IoT adoption, they act as a barrier to companies seeking more IoT utilization.
  • The graph below illustrates the top IoT challenges reported as per the report.
  • A full 38% of companies indicated that the complexities and technical issues surrounding IoT implementation were their major barriers to adoption, while 19% indicated security as their major concern.
  • Additionally, 29% of the companies cited the lack of staff resources, including training budgets. In comparison, lack of knowledge and difficulty finding suitable IoT solutions were cited by 29% and 28% of the companies, respectively.
  • Finding experienced workers or those with the right skills in the IoT field is a major challenge cited by 47% of companies that have already adopted IoT, likely due to its relative newness. Additionally, 44% of them lack the resources to provide sufficient training to their unskilled workers to execute IoT applications successfully.
  • A full 97% of companies that have adopted IoT cited security as a major concern during implementation, with 34% concerned about the management of software and firmware, including encryption protocols, 32% citing hardware/software testing, and 31% concerned about the update of software and firmware.
  • The graph below illustrates the various security concerns cited by companies as part of their IoT implementation considerations.
  • A full 38% of companies reported management of IoT devices as their major security concern, particularly the tracking, management, and creation of device security endpoints to enable IoT communications.
  • Additionally, 32% of companies whose IoT projects stalled at the trial stage cited high scaling costs as the leading cause, with undefined business benefits. In comparison, 28% cited an unclear demonstration of investment returns or business value from the pilot projects.
  • The graph below illustrates the reasons cited for the failure of IoT in the proof of concept stage.

Future of IoT Statistics and Projections

  • According to Ericsson's June 2020 mobility report, the pace of Massive IoT roll-outs is expected to be slower throughout 2020 due to the COVID-19 crisis, compared to 2019, where the connections multiplied by a factor of 3, reaching about 100 million by the end of the year.
  • Wide-area IoT connections, which amounted to 1.6 billion in 2019, are projected to grow at a CAGR of 23% within the 2019-2025 forecast period to reach 5.5 billion by 2025.
  • On the other hand, short-range IoT connections, which totaled 9.1 billion in 2019, are projected to grow at a CAGR of 13% within the 2019-2025 forecast period to reach 19.1 billion connections by 2025.
  • Additionally, cellular IoT connections, which totaled 1.5 billion in 2019, are projected to grow at a CAGR of 23% within the 2019-2025 period to reach 5.2 billion by 2025.
  • The graph below illustrates the number of cellular IoT connections globally in billions, by segment and technology, between 2015-2019 and projections for 2020-2025.
  • Massive IoT technologies, specifically narrow-band IoT and Cat-M, which can retain the same bands in 5G as those currently deployed, are projected to make up 52% of all cellular IoT connections by the end of 2025. Some commercial devices for Massive IoT, which include low-complexity devices requiring relatively low communication frequencies, include the various types of sensors, wearables, meters, and trackers.
  • Broadband IoT technologies, which require larger data volumes, higher throughput, and lower latency than Massive IoT, are projected to make up 34% of cellular IoT connections, the majority of which will be 4G-supported.
  • Critical IoT, which mainly supports time-critical use cases requiring guaranteed time, latency, and data delivery targets, is projected to have their first module deployment in 2021 supported by 5G new radio network capabilities. Some typical use cases for this segment include real-time machine and process control and coordination, cloud-based AR/VR, advanced cloud gaming, cloud robotics, and autonomous vehicles.
  • North-East Asia, which has the highest number of cellular IoT connections, is projected to have a 67% market share by 2025, growing from its current market share of 54% as of 2019.
  • According to Microsoft, 94% of enterprises will be using IoT by 2021, 85% of which are currently running at least one IoT project in the learning, purchase, trial, or use phase.
  • Mckinsey projects that investments in IoT technology will continue growing at 13.6% per year until 2022, with revenue pools from connectivity platforms growing at a CAGR of 24% to reach $38 billion (£30.2 billion) in 2023 from $13 billion (£10.3 billion) in 2018.

Microsoft Azure

  • Azure IoT is a comprehensive portfolio of cloud-based managed and platform services offered by Microsoft for building, deploying, connecting, monitoring, and controlling IoT assets.
  • With a 15.5% market share in the cloud computing services market, according to Gartner, IoT forms part of the leading solutions offered by Microsoft Azure, some of which include blockchain, SAP, backup and archive, business intelligence, cloud-scale analytics, gaming, knowledge mining, AI platform, and digital marketing solutions.
  • Azure IoT's value proposition includes the decade-old experience of the Microsoft enterprise on which it is built, enabling it to offer scalable security capabilities, tools, data analytics, and devices across various client business sizes and industries.
  • The industries operated by Azure IoT include automotive, discrete and process manufacturing, transportation and logistics, energy, healthcare, and retail.
  • Azure IoT solutions include accelerating the creation of IoT assets, reducing the cost and burden of IoT development and management operations, use case templates for building customized IoT solutions for various industry verticals, connecting, managing, scaling and transferring IoT assets between the edge and the cloud, building IoT spatial intelligence solutions, and supporting maps and mobility solutions.
  • The IoT product solutions offered by Azure IoT include Azure IoT Central, Azure IoT Solution Accelerators, Azure IoT Edge, Azure IoT Hub, Azure Digital Twins, Azure Sphere, Azure Time Series Insights, and Azure Maps.
  • According to their official website, Microsoft has committed to making investments in IoT alone amounting to $5 billion for the research and addition of new services and features for the Azure IoT products.
  • The table below illustrates some technologies and solutions offered by Microsoft Azure.

IoT Applications and Use Cases for Autonomous Vehicles

  • The IoT technology empowers autonomous vehicles to execute independent actions without driver support through various features and smart options, including machine learning, lidars, and radars, leading to a hierarchy of driving automation based on the extent of the IoT technology applied.
  • The table below illustrates the various levels of autonomous driving based on the extent of IoT technology applied, including company names for each case.
  • Levels 0-2 include basic driver support features that, however, still require the supervision of human drivers, with level 1 involving automated driver assistance features such as vibrating steering wheels or indicator lights giving off signals to the driver, for instance, during unsignaled lane departures.
  • Level 2, on the other hand, involves the partial automation of driving functions such as accelerating, decelerating, and steering. Examples of autonomous vehicles in this segment include Tesla's Autopilot and Nissan's ProPilot Assist models.
  • Level 3-5 includes highly automated driving functions, with level 3 including IoT features that control most of the navigation but still require human intervention in edge-case scenarios. An example of an autonomous vehicle in this segment includes Uber's self-driving car.
  • Level 4 includes fully automated driving functions where the vehicle operates independently, requiring the driver to at least remain able to drive in cases of rare scenarios where the vehicle may not have prior operational programming. Google's Waymo is an example of a company in this segment.
  • Level 5 is a full automation scenario where no driver intervention is required at all. This level of IoT roll-out is still a work-in-progress.
  • Other key players in the IoT use cases for the autonomous vehicle market include GM Motors' Chevrolet Cruise AV, which is a fully autonomous car, Waymo, which is running tests for their autonomous vehicle products at Phoenix, Arizona, Yandex, and Argo AI.
  • Some top IoT applications in the autonomous vehicle market include lane control, adaptive cruise control (ACC), automatic emergency braking system (AEBS), Light Detection and Ranging (LIDAR), street sign recognition, vehicle-to-vehicle (V2V) communication, and object or collision avoidance system (CAS).
  • Lane control involves the monitoring of distances to adjacent vehicles, lane markers, and road edges using cameras and the global positioning system (GPS) to stay safely within the right lane.
  • The ACC is a safety feature used to maintain safe distances between the autonomous vehicle and the vehicle ahead.
  • The AEBS is a safety feature used in automatically stopping the autonomous vehicle, therefore, avoiding collisions.
  • LIDAR is a perception tool in autonomous vehicles used to measure distance and identify surrounding objects using laser-emitting sensors.
  • The street sign recognition feature is used in the processing of sensor data to identify road signs.
  • V2V communication enables the exchange of information between connected vehicles, therefore, improving road safety.
  • The CAS helps avoid collisions through the integration of various features, including object detection and AEBS.

Recent News

(i) Project OWL: Wireless Mesh Network-Configured IoT Devices to be Deployed

  • A link to the article posted on July 6, 2020, can be found here.
  • The article discusses an organization, whereabouts, and logistics (OWL) project triggered by the 2017 and 2018 hurricanes. The open-source project combines IoT, LoRa connectivity, and mesh networking to configure devices that can be quickly and easily deployed during crises to provide communication, following the resultant unavailability of traditional communication protocols.

(ii) IoT: The Fight Against COVID-19

  • A link to the article posted on July 10, 2020, can be found here.
  • The article discusses the various ways that IoT has been deployed during the COVID-19 crisis to help alleviate its impact, including the deployment of low power network devices, including those running on bespoke mesh networks. The devices are worn by workers and are used to emit alarms when the workers are too close to each other, therefore, reminding them to observe social distancing.

(iii) On Semiconductor Bluetooth Low Energy Mesh Networking Innovation

  • A link to the article posted on June 23, 2020, can be found here.
  • The article discusses a Bluetooth Low Energy mesh networking innovation developed by On Semiconductor optimized for various applications, among them industrial IoT, which is gaining recognition across multiple sectors, including smart cities, industrial, logistics, agricultural, and enterprise.

(iv) Silicon Labs and Wi-SUN Partnership

  • A link to the article posted on 1 July 2020, can be found here.
  • The article discusses Silicon Labs' commitment to and partnership with Wi-SUN, a key mesh networking solutions player for the smart, connected IoT applications, which is expected to drive the advancement of the IEEE and the LPWAN connectivity through global standards-based and interoperable solutions.

(v) Scalability using AI, IoT, and Mesh Networks

  • A link to the article posted on 11, July 2020, can be found here.
  • This article by Forbes discusses the need for mesh networks and artificial intelligence (AI) to manage the complex and growing IoT device networking environments and sustain connections at scale.

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