Acronyms can sometimes take on a bit of a life of their own and it’s good to define what we mean by IoT. One way of defining it is as a “network of interconnected physical objects or ‘things’”. These devices are embedded with sensors, software, and connectivity, allowing them to collect and exchange data with other devices or systems over the internet.
A quick history lesson
IoT is a concept that has been around for decades. The world’s first IoT device goes back all the way to 1982, when David Nichols, a student at Carnegie Mellon University connected their Coke machine to the ARPANET. His purpose: to enable students to check if their beverage of choice was in stock, and (importantly) ice cold. The genie was out of the bottle (pun intended).
That was the first, but it took until the early 2000s before the modern realisation of the concept began to take shape. 1999 had seen the first use of the term “Internet of Things”, having been coined by Kevin Ashton. Kevin, who was working at Procter and Gamble, discussed the concept of connecting everyday objects to the internet and enabling them to communicate with each other and with central systems, allowing for better tracking, monitoring, and control of physical objects and processes.
The current market
The global IoT market size reached $925.21 billion in 2023 and is expected to grow at a compound annual growth rate (CAGR) of more than 13% during 2022-2026 to reach $1,334.1bn in 2026 (GlobalData).
The applications of the technology are incredibly wide ranging, having an impact on both consumer and enterprise applications. Use cases include smart homes/cities, healthcare, supply chain & logistics, agriculture and weather.
At the consumer end, we are probably quite familiar with devices like internet connected heating thermostats that allow us to control our heating wherever we are. The really clever stuff happens when you start processing and manipulating the data obtained, and this is something we’re seeing take massive leaps forward right now.
For example, using the data from our internet connected thermostat, the system can calculate how long it takes to raise the temperature from whatever the current temperature is to the desired temperature of your living room (say 19 degrees).
In our scenario, as I leave work, my phone (using an app I have installed and is running in the background) triggers a geo-fence action (a geo-fence is a kind of virtual GPS-based boundary). This notifies our thermostat system that I am on the way home. Route tracking, incorporating real-time traffic data calculates the time I am likely to arrive, and using the historical heating data as a guide, pre-emptively turns on the heating to enable the living room to reach 19 degrees at the precise second I walk through the door.
It sounds like “tech for tech’s sake” until you realise that because you haven’t been heating an empty house, you’ll save yourself hundreds over the year.
The data issue
The above example is just one small use case, but it does highlight a challenge with a lot of IoT system integrations – data. Or to put it precisely, the absolute monolithic amount of it. IoT devices spew out data at such a rate that the amount of data globally is measured in zettabytes. Which is a lot. Let’s put it in context:
And with over 100 new IoT devices being connected to the internet every second you can see that the sheer volume of data is only going one way.
There’s an upside to all this data – once you know how to handle it. So much data gives us a window on the world (as software developers) that was previously unobtainable. We can analyse this data, and use it to deliver ever improving user and customer experiences.
Over the last few years, the explosion of machine learning (AI) and related technologies has unlocked the ability of rapidly processing vast amounts of data and enabled us to provide insights and actions incredibly quickly. These insights can be many different things depending on the application – it may be informing decisions, identifying areas where predictive maintenance on a system is required, enhancing a customer experience (as in the example earlier) or even identifying opportunities of new business models.
Storing and processing all this data in years gone by has been challenging, but in recent years solutions have become available to lower the barrier to entry for our partners. The use of cloud-based IoT solutions (e.g. Microsoft Azure IoT) takes away some of the heavy lifting around integration, processing, scalability and security, which is a great step forward.
We’ve been working with IoT technologies for almost a decade, and in that time have had the privilege to work on some fun and some truly groundbreaking products for partners internationally.
Our first exposure to IoT in Rant came in the early 2010s when we were tasked with developing an iBeacon (BLE) management and configuration app for iOS and Android. We learnt so much and you could say that it inspired us to try more sophisticated use cases. Over the course of a number of hack days we developed a coffee positioning system, experimented with an automatic flexible working sign-in/sign-out app, and an aptly named “hot in the office” IoT device that was built to tell us whether, well, it was, uh hot… in the office. We even developed a proof of concept game for kids called Parclings, which used BLE beacons to encourage kids to explore outdoor physical spaces and capture unique Parcling creatures via an in-app “Parcling sensor”.
On the automotive side we’ve built software to support an in-helmet head-up display for motorcyclists, and our design and build of a connected car app for Aston Martin. As you can imagine, the level of care and attention over data, security and customer experience doesn’t get much higher than that!
But let’s not stop there contact us today and start the ball rolling for your next IoT development.