By Andy Gould
This article explores the integration of IoT into day-to-day industrial and consumer operations, highlighting its evolution, major trends and key challenges. It covers solutions such as IoT edge gateways and decision tracing, while addressing critical issues in security and data management to help businesses stay ahead in the IoT landscape.
The Internet of Things (IoT) means many things to many people and has multiple uses and applications. In short, it describes a network of physical objects that are embedded with sensors, software and other technologies which enable them to exchange information and data via the internet. This can be anything from a doorbell or a fitness tracker to industrial sensors used to monitor equipment and processes in an industrial setting.
Today, IoT is rapidly expanding. According to ABI Research, IoT connections will increase from 19.5 billion in 2025 to 40.1 billion in 2030 with a compound annual growth rate of 16%. This highlights the increasing integration of IoT into everyday operations, showing its importance to both consumer and industrial landscapes.
Major trends in IoT adoption
With the growth of IoT taking place over several years, the acceleration of technology across the board means its opportunities are rapidly expanding. We can see this with several key trends that are shaping the IoT landscape today.
With the increasing volume of data generated by IoT devices, edge computing is gaining prominence. This involves processing data closer to where it is generated, on the edge of the network, reducing latency and bandwidth costs.
Of course, it wouldn’t be 2024 without mentioning AI and machine learning. IoT devices are becoming smarter (and, therefore, useful) because they’re taking advantage of fast-improving AI and ML technologies. This, for example, enables real-time data analysis and decision making, vastly enhancing the efficiency and functionality of IoT systems.
The rollout of 5G connectivity is also accelerating the deployment and effectiveness of IoT devices by providing faster data transfer rates and more reliable connections. This is particularly beneficial for industrial applications.
One area where the sharp rise in the number of connected devices has caused concern is around vulnerabilities – within the devices themselves as well as within the network. That’s why enhanced security measures are a major focus. New regulations such as the UK’s Product Security and Telecommunications Act 2022 and their equivalents in the EU and US as well as advancements in cybersecurity are aimed at protecting data and ensuring the integrity and resilience of IoT networks.
Key challenges in IoT implementation
The IoT has clear benefits. But the scale of it, its vulnerable nature and widespread adoption mean it still brings several challenges.
Some IoT devices, especially consumer-grade products, have been criticised for being shipped with security flaws. With billions of devices being manufactured and shipped from different parts of the world, it is perhaps inevitable that not all will feature the highest, most robust security measures (not that this is an excuse). This makes some devices susceptible to cyber attacks, thanks to common vulnerabilities such as default passwords and lack of encryption. However, the new regulations are designed to prevent this and are likely to apply to any goods sold under their jurisdiction so we can expect the associated penalties to have an impact in the longer term.
With money talking, some devices fall foul of trade-offs between security, performance and user experience. In fairness, balancing these is a significant challenge because enhanced security measures can sometimes compromise devices performance or complicate the user experience – but security should always be prioritised.
An issue that is only going to continue to escalate – the sheer volume of data (and processing it). The amount of information generated by IoT devices can overwhelm traditional data processing systems, so managing, storing and analysing it all efficiently is a critical concern. Luckily, as fast as IoT tech is progressing so, too, is the technology able to handle these tasks.
And while we’re on the topic, the impact of AI and ML can be seen as a challenge (as well as a huge potential benefit). As mentioned, while these technologies enhance IoT functionality, they also introduce complexity and somewhat of the unknown in terms of data protection, decision tracing and security. Ensuring transparency and accountability in automated decision making is essential.
What solutions are available?
Unlike AI, IoT is better established, and solutions to many of these challenges are available thanks to years of research and banks of evidence.
IoT gateways, for example, can act as intermediaries, processing data locally before transmitting only essential information to central cloud servers. This approach has several advantages, including:
- cost reduction by reducing the amount of data sent to the cloud
- improved performance with reduced latency enabling faster decision making and real-time responses
- enhanced security with minimised exposure of data to external threats
- greater privacy and data confidentiality, given less data is shared outside of the local network, thus reducing the risk of exposure to data leaks
However, building effective IoT gateways involves selecting the right hardware and software components, ensuring compatibility with existing systems and implementing robust security measures from the outset.
As IoT systems become more integrated with AI, decision tracing and verification will become increasingly important. In industrial settings, being able to trace the decision making process is crucial for accountability and compliance, especially in cases of system failures or accidents. For example, in the automotive industry, the ability to trace decisions made by autonomous driving is essential for understanding incidents and improving safety.
Other solutions are, simply, down to businesses establishing clear policies on data governance – who owns it, how will it be used and managed, and how can we ensure compliance with regulations like GDPR and maintain transparency with consumers about how their data is used?
Then there’s maximising the use of the data we collect. Businesses need to invest in data analytics tools and platforms that can handle these large volumes and extract actionable insights.
Staying on top of IoT integration
As mentioned previously, IoT means many things to many people. The key to staying on top of IOT integration, is having a good understanding of what it means for your business, what value you hope to derive from your IoT implementation, and making sure that vision is clear to everyone involved.
Most importantly: don’t let the challenges overwhelm you. Staying on top of IoT integration is absolutely possible. In fact, all businesses should be making sure they stay informed about emerging trends, addressing inherent challenges and adopting innovative solutions.
By focusing on those mentioned above, we can harness the full potential of IoT while mitigating its risks (as well as responding to those which may crop up in the future).
As IoT continues to evolve, proactive adaptation and strategic planning will be essential for maintaining a competitive, and secure, edge.
About the Author
Andy Gould has worked at Mobica for 18 years, working on IoT, embedded systems, automotive solutions and various tech stacks. His main focus is working with customers to turn their needs into requirements and designs that software teams can deliver.
