Take a look around and you’ll see evidence of the widespread adoption of wearable sensors for health and fitness, such as the Fitbit, Garmin or other devices.
What many people many not know is that we are also using sensors to monitor the structural integrity of bridges and buildings, as well as tracking the movements of insects and other animals.
With the rapid growth of the Internet of Things (IoT), tens of billions of sensor devices are projected to connect in the next decade. These connected sensor devices will automate processes across a broad range of economic sectors, from industrial plants to healthcare management, delivering productivity gains and hopefully quality-of-life improvements.
The core of these sensor devices that will be deployed across this broad range of applications is largely the same, featuring a microprocessor, memory and a wired or wireless communication interface to the internet, along with a battery or other energy source.
Each application and IoT device will bring its own unique context, such as its location, the conditions of the surrounding environment and the behaviour of people in the area. Individual devices will observe and adapt to their unique contexts.
Enter Artificial Intelligence
So what happens when we introduce artificial intelligence (AI) into the mix? With AI, these devices can evolve their behaviour in response to changing contexts. Just like how living beings optimise their behaviour to their surroundings, even smaller IoT devices around us can run AI machines that evolve their software over time.
Consider a portable mobile device, such as a smartwatch or a smartphone, that typically ships in large volumes with one-size-fits-all features and apps for all users.
To personalise them, users have to manually configure each app individually, and keep updating these configurations as their preferences change over time.