Technology Trends Identified by GlobalData

Combined with emerging technologies such as 5G and cloud computing, IoT can improve operational efficiency, minimize costs, improve decision-making and improve the customer experience.

Below are the key technology trends impacting the IoT theme, as identified by GlobalData.

Lack of global IoT security standards

The increase in the number of connected devices has increased significantly
potential points for cyber attacks and created a huge security gap. Current IoT ecosystems do not have adequate security regulations to close this gap. IoT security encompasses a range of threat vectors that can be based on devices, apps, networks, or data. The primary focus for IoT technology is endpoint security, which refers to protecting connected devices, from a refrigerator to a production tool. The world needs a unified, global IoT security standard to make pervasive IoT a reality.

Lack of global IoT communication standards

Currently, there are a plethora of IoT communication protocols (the technologies used to connect IoT devices to the Internet) that are used all over the world. The vast array of communication protocols can lead to interoperability issues between and within IoT ecosystems. There are currently no global IoT communication standards, making large-scale IoT implementation more complex than necessary. A unified IoT communication standard is required to realize the full potential of IoT.


IoT use cases requiring low latency, such as connected cars, predictive maintenance, and wearable healthcare technology, will benefit most from 5G. 5G’s ultra-reliable, low-latency communications (URLLC) capability and support for Time-Sensitive Networking (TSN) will be key to IoT adoption.

health technology

The healthcare sector has long resisted the digital revolution, lagging far behind other industries. The Covid-19 pandemic has led to the rapid adoption of medical IoT technologies such as remote patient monitoring and medical robots, opening huge digitization opportunities for IoT solution providers.

Artificial Intelligence of Things (AIoT)

Artificial intelligence (AI) technologies are often used to interpret and respond to some of the human-to-machine and machine-to-machine data streams in real time. The amalgamation of the two technologies, AI and IoT, has led to the concept of AIoT, where AI technology is embedded in IoT components. Combining data collected by connected sensors and actuators with AI delivers reduced latency, increased privacy and real-time intelligence at the edge. It also means less data to be sent and stored on cloud servers.

Intelligent edge computing

Sensors will appear everywhere as IoT technology grows, resulting in a massive increase in the amount of data collected. However, processing power on most IoT devices is limited, so data processing takes place in the cloud, in data centers that are typically far away from where the IoT devices that generate the sensor data.

Some data analytics capabilities are shifting to the edge of the network, closer to the source of data generation, as IoT ecosystems become more complex to reduce latency and enable near-autonomous decision-making when responding to sensor signals from IoT devices. This is especially important for time-critical applications such as health monitoring devices or autonomous vehicles, where split-second reactions can save lives.

IoT as a Service (IoTaaS)

IoTaaS vendors offer a variety of platforms to help organizations with IoT implementation without the need for in-house expertise. The technology aims to make it easy for businesses to deploy and manage their connected devices. It has become an accelerator for enterprise adoption of IoT, particularly in predictive maintenance, advanced automation, and condition monitoring. IoTaaS revenue is likely to grow dramatically as the world recovers from Covid-19.

Digital Twin

Digital twins can help optimize IoT deployments for maximum efficiency and help IoT users figure out where things should go or how they work before they are physically deployed. A digital twin is a software representation of physical assets and processes that allows an organization to run “what if” simulations. These simulations can be used to proactively identify and prevent problems, avoid downtime and accelerate new product development.


Covid-19-induced changes in consumer behaviour, including working from home, increased use of digital media and the popularity of virtual fitness workouts, are driving wearables adoption and increasing consumer adoption of IoT. Wearable technology vendors are integrating a range of health and fitness monitoring options into their devices, aided by advances in biometric sensor technologies.

Next Generation Chips

The emphasis in chip design has shifted from a race to put more transistors on a square millimeter of silicon to a focus on building microprocessors as multi-component systems, each performing a specialized task. The pressure on the semiconductor industry to develop smaller, cheaper and faster chips is increasing as more and more sensors and microcontrollers are packed into the connected devices. The underlying semiconductor technology embedded in IoT devices must be cheaper, more compact, and consume less power for IoT to be ubiquitous.

Software Defined Networks (SDN)

SDN is an emerging data network architecture that allows software rather than hardware to control the network path along which data packets flow. It is still under development, but eventually the Internet Protocol (IP) may replace networks, a hardware standard, as the main standard for the Internet’s transmission mechanisms.

SDN will have a major impact on IoT ecosystems as it fundamentally changes who runs the data center. SDN took off slowly, mainly due to cybersecurity concerns. SDN’s open hardware standards threaten to commercialize network and data center hardware, which is still largely based on proprietary systems, making it easier for Internet companies to program data networks.

This is an edited extract from the report Thematic Research: Internet of Things (2021), produced by GlobalData Thematic Research.

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