10 things I know about the Internet of Things

Having been on the delivery end of the Internet of Things (IoT) space, and (as consumer and enterprise user) the receiving end of solutions that are technically "things" connected to the internet for pretty much all my life, I've come to know that the future of IoT is one that is imperative, it is still being formed, and one that - as with most major technology phenomena - has multiple diverging disciplines which we happen to term - IoT. Fast forward to us moving past the initial hype and experimentation ("the path of enlightenment") to a mature phase where industry practitioners are focused on applications and scaling ("a certain plateau of productivity").

This transition signifies a shift from simply exploring the potential of IoT to realising its tangible value. Here's my personal take on what I believe (notably with an enterprise mindset), on what is true.

1. IoT must generate outcomes. The power of IoT lies not in sensors, connections, and applications, but in the value created from the data these collectively unlock. It’s about solving real problems for customers and end-users - optimising processes, reducing costs, or enabling new revenue streams. For instance, in mining, IoT solutions that monitor equipment health can predict maintenance needs, reducing downtime and saving costs
2. Simplicity wins. IoT can seem complex, but successful solutions are those that are simple to implement, operate, and scale, despite their complexity. Given IoT spans a variety of original equipment manufacturer (OEM) protocols, device heterogeneity, and diverse communication standards, achieving simplicity at scale is arguably the toughest task. The businesses that remove friction across the journey for customers, giving confidence in delivery, will lead the way. This includes providing intuitive apps and insightful dashboards, seamless integration with existing systems, and robust support.
3. Insight is the product. The true currency of IoT is data - and data must generate insights that allow decisions and better business outcomes. Collecting data is step one; transforming it into actionable intelligence, consumable by humans and machines, is where the magic happens. This involves data cleaning, aggregation, analysis, and visualization. Data for data's sake is largely in the past - insights must drive actions and decisions. For example, in logistics, IoT data from tracking devices provides real-time visibility into shipment locations and conditions, enabling proactive decision-making to optimize routes and prevent delays.
4. Scalability makes or breaks solutions. A solution that works for 10 devices may not work for 10,000. Architecting for scale from the start separates pilots from successful rollouts, and the true exponential power and promise of IoT given its diversity is in its ability to transcend locations and ecosystems. This requires a robust infrastructure, flexible architecture, and the ability to handle increasing data volumes and device connections.
5. Edge Computing is a Key. The ability to process data closer to where it’s created - on the edge - reduces latency, cuts costs, and increases efficiency. In IoT, not everything needs to go to the cloud, and the interplay between the thick and thin edge will generate opex and capex gains for enterprises. Edge computing is particularly important for applications that require real-time responses, such as autonomous vehicles and industrial automation. In smart cities, edge devices can process traffic data locally to control traffic lights in real-time, improving traffic flow and reducing congestion.
6. Cybersecurity cannot be an afterthought. The more devices connect, the greater the attack surface. Security must be embedded at every layer - from the device to the platform and beyond. This is a people, process, and tech endeavour. It involves secure device provisioning, data encryption, access control, vulnerability management, and ongoing monitoring. The Mirai botnet attack, which exploited vulnerabilities in IoT devices to launch large-scale DDoS attacks, serves as a reminder of the importance of IoT security.
7. Interoperability drives adoption. IoT solutions and protocols don’t exist in silos. Integration with existing systems and technologies is essential for adoption and ROI. Open standards and APIs are key, and an ecosystem mindset is critical given IoT becomes the eyes and ears of a businesss operations, while northbound OEM and ERP system integration still remains critical. For example, integrating IoT data with an ERP system can provide a pro-active, holistic view of business transaction, systemic and process driven, interactions and improve employee productivity and ultimately customer service by having a virtual 'finger on the pulse' of operations.
8. Build a Strong BI Foundation before AI. Reliable, consistent, and accessible data is the backbone of transformative IoT - really, any - solution(s). Effective BI ensures data from multiple sources is harmonised, creating a solid foundation for advanced AI capabilities. Trying to implement AI on top of messy or inconsistent data will lead to inaccurate results and unreliable insights. While AI offers immense potential for predictive maintenance, anomaly detection, and optimisation in IoT, the data used to train and operate AI models must be trustworthy. It is also important to acknowledge the complexities of AI implementation, including data quality issues, model drift (where AI model accuracy degrades over time), and the need for explainable AI to understand how AI models arrive at their decisions.
9. IoT, like anything transformative, is a team sport. No one entity can do it all. Partnerships - across hardware, software, connectivity, and final mile services are essential for delivering end-to-end solutions that work. This collaborative approach allows companies to leverage specialised expertise and accelerate innovation. A successful utilities project will involve partnerships between sensor manufacturers, software developers, system integrators, connectivity providers, and facility managemers.
10. Technology is the enabler, not the story. IoT is guilty of allowing innovation, proof of concept, and short-term gains lead the headlines, creating false positives. The success comes from relentless focus on what the business needs as the outcome, with organizational committal to ensure success and adoption (nothing new in the world of ICT!). This requires a shift in mindset from what technology can we implement to what business problem are we trying to solve and how can technology help.The rest follows.

The rest follows. Connected devices and assets exist as part of our daily lives, and the more we see each as a gateway to a more insight-rich, connected, and productive world, where the mountains of data accumulate to generate value for humans, the sooner we will realise the gains that have been promised across myriads of analyst and commentator predictions about the future of a more connected world.