Theme briefing

The digital ecosystem of the IoT

Credit: Bert van Dijk/Getty images.

Powered by

There are four key technologies that intersect with today’s IoT ecosystems: artificial intelligence, cloud computing, cybersecurity, and connectivity. Here we take a closer look at how these four technologies play into the digital ecosystem of the IoT.

Artificial intelligence

Artificial intelligence (AI) refers to software-based systems that use data inputs to make decisions on their own. Machine learning (ML), one of the sub-segments of AI, gives machines (embedded with sensors and computing chips) the ability to learn and improve from data and is considered one of IoT's primary enablers. 

Sensors on connected IoT devices provide real-time data feeds to ML algorithms. These ML algorithms digest the data, meaningfully interpret it, analyse it, and send instructions back to the devices in a virtuous circle of continual improvement.  

The more data that is collected, the better the ML algorithms can interact with the connected device, whether for routine maintenance (for example, detection of faulty parts), predictive analytics (for example, telling a driver they are about to enter congested traffic) or smart robotics (for example, telling a robot how to move, based on cloud-based control centres analysing data from onboard computer vision sensors). 

The emergence of generative AI has added a new dimension to the combination of AI and IoT. While generative AI is a nascent technology, a few use cases are already emerging within IoT. For instance, it can be used to improve the user experience around IoT devices such as wearables. Furthermore, it can also help enhance the accuracy of ML models used in network operations automation by generating new data similar to the input data, a technique called synthetic data.

Cloud computing

Cloud computing involves the provision of IT infrastructure, operating software, middleware, and applications hosted within a data centre and accessed by the end user via the internet. Cloud is a foundational technology for an IoT ecosystem. At the connectivity layer, it provides the infrastructure that delivers flexible, on-demand access to computing resources. 

It facilitates the process of storing, managing, and analysing data. It also enables the disaggregation of physical technology hardware from end-users by allowing the virtualisation and sharing of computing resources such as central processing units and graphics processing units, storage, networking, and software. 

In conjunction with cloud, edge computing helps shift compute, storage, data management, and analytics software to the edge of a network. There is no fixed definition of the physical location of the edge, but the basic concept is to move computational capabilities closer to the IoT device generating the data. The edge can range from on-device computing to a local enterprise, on-premises data centre, or server.


Cybersecurity is the practice of defending devices, networks, applications, and data from digital attacks. These attacks usually aim to access, change, or destroy sensitive information, extort money from users, or interrupt normal business processes.  

The cybersecurity approach has multiple layers and can be divided into a few common categories like endpoint security, cloud security, network security, application security, data security, and vulnerability management. 

Implementing effective cybersecurity measures is particularly challenging today because there are more connected devices than people, and attackers are becoming more innovative. In an IoT environment, facilitating data exchange between operational technology and information technology offers greater business benefits but introduces significant risks.  

Many IoT-related networks handle critical national infrastructure, such as power grids, and the impact of a breach resulting from immature IoT technology would be significant.


The need to extend connectivity capabilities to accommodate greater populations and remote geographical areas, alongside the lower power requirement of many IoT devices, has led to networking innovations. 

5G is a notable example, addressing the need for faster speeds, lower latency, and broader coverage. 5G refers to the fifth generation of global mobile wireless standards. It is based on the orthogonal frequency-division multiplexing (OFDM) method, modulating a digital signal across several channels to reduce interference.  

5G uses a 5G New Radio air interface alongside OFDM principles. It also uses a wider range of spectrum bands than previous generations of mobile wireless standards, including millimetre wave (mmWave) frequencies (generally defined as spectrum bands over 24 GHz), which allow much higher bandwidth, capacity, and lower latency services. 

On the other end of the spectrum, infrastructure IoT sensors require modest bandwidth, have very low power consumption, and often do not need low latency. Consequently, network protocols such as Bluetooth Low Energy, Wi-Fi, powerline, Digital Enhanced Cordless Telecommunications, low power wide area network (LoRaWAN), Matter, Sigfox, Weightless, and Zigbee have been developed. 

Each provides different capabilities, and it is still unclear which connectivity protocols will eventually dominate the market. For instance, Wi-Fi and Bluetooth offer high-quality wireless communication at lower costs, but their power consumption is still relatively high compared to their more limited reach. For example, BLE, Z-Wave, and ZigBee require less energy and costs but are also limited in their data range.  

Low-power wireless technologies include Narrowband Internet of Things, LTE-M, Sigfox, and LoRaWAN. The importance of low-power wide area network technologies relies on their contribution to energy saving and extended digital connectivity over long distances. However, the limited data transfer leads to the need to develop 6G technologies or other alternatives to increase IoT adoption. 

GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.  

GlobalData’s Thematic Intelligence uses proprietary data, research, and analysis to provide a forward-looking perspective on the key themes that will shape the future of the world’s largest industries and the organisations within them.