40+ Emerging IoT Technologies you should have on your radar

Updated April 2022: IoT Analytics published a more recent blog on: 55+ emerging IoT technologies you should have on your radar (2022 update)

There are hundreds of software, hardware and connectivity technologies that are relevant for IoT-type projects.

As part of the “State of the IoT – Summer 2019 Update”, the analyst team at IoT Analytics handpicked 43 of the most promising technologies that are relevant to IoT projects around the globe. The team ranked the IoT technologies according to their perceived maturity (based on expert interviews, vendor briefings, secondary research, and conference attendances).

The resulting Emerging IoT Technologies Radar serves as a guide for anyone working in IoT-type environments and projects to understand what technologies they should be watching, evaluating, and perhaps deploying. Many of the topics highlighted on the radar are discussed in much more depth in the State of the IoT 2019 Q1/Q2 Update report.

Emerging IoT Technologies Radar 2019

Here is the complete list of all software, hardware, and connectivity IoT technologies (each ranked by maturity):

A. IoT Software Technologies

#TechnologyDescriptionClassificationTypical vendor(s) or solutions
1Cloud computingUsing a network of remote servers to store, manage, and process data.Fairly MatureAWS, Microsoft Azure, Alibaba Aliyun
2IoT PlatformsForm of modular software that allow easy connection of various IoT devices & other value-added functionality (e.g., remote device management, application enablement, analytics)Nearing maturityAWS IoT, Microsoft Azure IoT, PTC Thingworx
3Edge analyticsCollection and analysis of data at the sensor, device, gateway or edge data center rather than waiting for the data to be sent back to a remote cloud.Nearing maturityAWS IoT Greengrass, Microsoft IoT Edge, Foghorn, Crosser
4IoT-based streaming analyticsReal time processing of streaming of data from IoT devicesNearing maturityCloud vendor solutions, Hortonworks Dataflow, SAS, Software AG
5Supervised machine learningML method where training data for the algorithm includes desired outputs.Nearing maturityUptake, Sparkcognition, Senseye
6Unsupervised machine learningML method where training data for the algorithm does not include the desired outputs.Nearing maturityUptake, Sparkcognition, Darktrace
7ContainersContainers are processes with their own virtual resources and filesystems (memory, CPU, disk, etc.), isolated from other applications and containersNearing maturityDocker, Kubernetes, OpenShift
8IoT MarketplacesA one-stop click-and-buy-store, offering complete Internet of Things solutions ready to deploy smart applications including hardware, software and cloud connection.Coming upPTC, Siemens, ABB, Schneider Electric, Inductive Automation
9Digital TwinsDigital representation of physical assets, processes, systems and devicesComing upGE, Azure, Siemens, Honeywell, Emerson
10Container SecuritySolutions that protect the integrity of containersComing upCloud Vendor Solutions, Palo Alto Networks
11IoT Security platformsPlatform offering security solutions for any IoT device classComing upMocana, Bayshore Networks, Device Authority
12Real-time databaseDatabase that uses real-time processing to handle constantly changing workloadsComing upMongoDB, Counchbase
13Serverless / FaaSDeveloping, running, and managing application functionalities without the complexity of building and maintaining the infrastructure associated with developing and launching an applicationComing upAWS Lamda, IBM OpenWhisk, Google Cloud Functions
14Deep LearningPart of a broader family of machine learning methods based on artificial neural networksComing upTensorFlow, Apache Mahout, Caffe, Deepmind, CuriousAI

B. IoT Hardware Technologies

#TechnologyDescriptionClassificationTypical vendor(s) or solutions
1CPUCentral processing unitFairly matureIntel, HPE, AMD
2Security chipsSecurity-enhancing low-powered modules, include various security-sensitive functionsFairly matureApple, Alphabet
3Edge gatewaysPhysical devices that serve as the connection point between the cloud and controllers, sensors and intelligent devicesFairly matureDell, HPE
4GPUsGraphic processing unitComing upNVIDIA, AMD, Asus, Intel
5NANDNon-volatile flesh memoryComing upMicron, Samsung, Toshiba
6ASICApplication-specific integrated circuitComing upFujitsu, Honeywell, Advanced Linear Devices
7DRAMDynamic random-access memoryComing upSamsung, Micron, SK Hynics
8FPGAField programmable gate arrayComing upXilinx, Intel, Altera
9Neuro-synaptic chipBrain-inspired computer chip, in which transistors simulate neurons and synapsesComing upIBM
10Smart sensorsSensors that take some predefined action when they sense the appropriate inputYears outTexas Instruments, TE Connectivity, Broadcom
11ML-optimized gatewaysControllers that are optimized for ML algorithmsYears outAdlink, Intel
12Energy harvesting for LPDSupplying electricity to LPDs from one or several forms of available energy from the ambient environment instead of using disposable batteries or a connection to the electricity gridYears outSTMicroelectronics, ABB
13Cloud-connected sensorsSensors that are sending data directly to the cloudYears outSchneider Electric
14Quantum computingComputation using quantum-mechanical phenomena e.g., superposition entanglementFar on the horizonIBM, Microsoft, Rigetti

C. IoT Connectivity Technologies

#TechnologyDescriptionClassificationTypical vendor(s) or solutions
1WLANWireless Local Area Networks, includes Wi-Fi and its different versionsFairly matureCisco, Aruba, Extreme Networks
2WPANWireless Personal Area Networks, incl. very short-range (up to ~100 m) connectivity technologies (e.g. BLE, Zigbee)Fairly matureDiGi Int., NXP Semiconductors, Silicon Labs
3Cellular IoT (2G/3G/4G)Provides connectivity to IoT applications via traditional cellular networksFairly matureChina Mobile, Vodafone, Orange
4WNANWireless Neighborhood Area Networks, includes medium-range (~500-2,000 km) mesh connectivity technologies based on the IEEE 802.15.4 standard (e.g. Wi-SUN)Fairly matureItron/Silver Spring Networks, Wirepas
5LPWANLow-Power Wide-Area connectivity for IoT applications (e.g. Sigfox, LoRa, NB-IoT, LTE-M)Nearing maturitySemtech, Sigfox
6Pub/SubForm of asynchronous service-to-service comm. used in IoT messaging protocols e.g. MQTT, XMPPNearing maturityAWS, Google Cloud, PubNub
7eSIMA SIM-card embedded into mobile devices that enables remote SIM provisioning, allowing storing of multiple operator profiles simultaneously and switching between them remotely.Coming upST Microelectronics, Gemalto, Giesecke & Devrient, ARM
8Network VirtualizationAbstracts network elements & resources into a logical virtual network that runs independently on top of a physical networkComing upOracle, VMWare, Juniper Networks
95GThe fifth generation of cellular networks, commercially launched in 2019Coming upHuawei, Ericsson, Nokia
10Wifi 6The newest version of the Wi-Fi protocol, also known as IEE 802.11axComing upQualcomm, Cisco, Huawei
11TSNTime-Sensitive Networking is a set of standards defined by IEEE for the time-sensitive transmission of data over deterministic Ethernet networksComing upABB, Bosch, Cisco, Siemens
12LifiWireless communication technology that uses light to transmit data.Years outPanasonic, Oledcomm, Philips
13Satellite IoTProvides connectivity to IoT applications via satellite networksYears outIridium, Inmarsat, Eutelsat
14APL (Advanced Physical Layer)Developing industrial Ethernet standard that seeks to leverage the work of the IEEE 802.3cg (10BASE-T1L) task force to achieve a single twisted-pair industrial Ethernet standard for hazardous areasYears outPepperl+Fuchs, Endress+Hauser, Analog Devices
156GThe sixth generation of cellular networksFar on the horizonHuawei, Ericsson, Nokia

What the radar measures and what it does not measure?

Technology maturity. The radar shows a subjective measure of maturity as put together by the analyst team at IoT Analytics. The maturity scores are developed based on expert interviews, vendor briefings, secondary research, and conference attendances. The radar is targeted at IoT practitioners that deploy IoT.

The Internet of Things. IoT Analytics defines the Internet of Things as a network of internet-enabled physical objects. Objects that become internet-enabled (IoT devices) typically interact via embedded systems, some form of network communications, as well as a combination of edge and cloud computing. The data from IoT-connected devices is often (but not exclusively) used to create novel end-user applications. Connected personal computers, tablets, and smartphones are not considered IoT, although these may be part of the solution setup. Devices connected via extremely simple connectivity methods such as RFID or QR-codes are not considered IoT devices.

Relevance of individual technologies. Not every technology is relevant for a given IoT context. Some technologies may be purely used in specific IoT settings (e.g., LPWAN for remote, low-power applications), others are used in a variety of settings and IoT only plays a minor role (e.g., Cloud computing which is also used in many non-IoT scenarios).  IoT Analytics is aware that there are many more technologies out there that could be highlighted in such a radar.

Other selected research findings

In addition to the 2019 Emerging Technologies Radar, the 96-page “State of the IoT” report presents 67 current insights on the IoT market, including market breakdowns by industry, region and tech stack. The report also includes an IoT-focused investment and M&A analysis, a look at adjacent technologies, and gives insights from major IoT-focused conferences. This is a small selection of other insights:

  • IoT technologies often take more than a decade to move towards the center of the emerging technologies radar. The typical technologies depicted here take roughly 12 years to move from being “far on the horizon” to becoming so mature and widely adopted that IoT Analytics considers them “mainstream” (in case a technology does become mainstream which is not always the case). Cloud computing, for example, took ~12 years from being far on the horizon to being considered “mainstream” for IoT settings (Note: AWS was first launched in 2006). Research on 5G was initiated in 2012 and was considered far on the horizon at that time. It has moved to the “Coming up” level now and is expected to hit mainstream for IoT applications in the 2024-2025 timeframe (~also 12 years later). One should note though that some technologies do mature quicker than others. Research on 6G started in 2019, by the way.
  • Digital/IoT markets are currently affected by the global slowdown. IoT vendors are lowering their outlook while technology users are (partially) reducing CAPEX. At the same time, shifting supply chains and skill shortages are becoming key inhibitors to further growth in IoT.
  • Lower growth going forward. IoT Analytics expects IoT markets to grow 30% in the medium-run (next 2 years) and 32% in long-run (5 years thereafter). The market is expected to cross the $1trillion mark in 2025.
  • Manufacturing/Industrial hit the hardest. The global slowdown is currently mostly a manufacturing slowdown with Automotive and Machinery hit the hardest and with weakest outlook. Chemicals/Pharma and Food&Beverages are holding up the best.
  • Analytics/AI driving the market. Companies are doubling down on their Analytics/AI investments which is why we expect this area of the tech stack to be the only one that will see a growth increase. 
  • US startups dominate large IoT funding rounds. Top recent IoT investments focus on cybersecurity (13%) and IoT connectivity (13%) – mostly in the US (45%), followed by Israel (10%) and China (10%).

Further reading

The Emerging IoT Technologies Radar discussed in this article is explored in further depth, in the 96-page State of the IoT 2019 Q1/Q2 Update report. The report takes a deeper look at the IoT market and provides 67 insights across the IoT tech stack, adjacent technologies, investments and M&A, and conference highlights.  

A sample of the report and the database can be downloaded here.

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<a href="https://iot-analytics.com/author/knud-lasse-lueth/" target="_self">Knud Lasse Lueth</a>

Knud Lasse Lueth

Since founding IoT Analytics in 2014, my focus has been to build a team that produces high-quality research in areas such as IoT, AI, Cloud, and smart manufacturing. Throughout my journey, I have authored or co-authored over 100 reports, always with a commitment to delivering analyses that are not only trustworthy but also rich in insight and uniqueness.

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