More and more devices can communicate without the need for human input thanks to the rise of the Internet of Things (IoT). You might have a home assistant device, such as an Amazon Echo or a Google Home, that communicates with your doorbell to let you know when someone’s at the door. Alternatively, you might ask the same assistant to order certain items on a specific date each month. These home assistants harness the power of the IoT — and with artificial intelligence (AI) always evolving, it’s clear there’s a place for interconnected machines to learn some tricks on their own too.
In this guide, we’ll look at how AI and machine learning intersect with the IoT and what we can expect from this technology in the near future.
What is the IoT?
The Internet of Things refers to many devices that can interact with each other without the need for human triggers. For example, you could set up a light bulb to turn on at a specific time of day, or on a grander scale, a business might set up sensors to order more inventory. This, crucially, removes the need for human workers to manually reorder items when supplies are low.
IoT devices work on what are known as control loops, though different tasks and requests will vary in complexity and length. Studies of the IoT and its future are highly significant in some degree disciplines, including Online Master’s of Computer Science programs available at reputable institutions such as Baylor University. Through this program, students develop in-depth knowledge regarding algorithms, databases, data communications, operating systems and applied artificial intelligence, and the IoT plays an increasingly important part. With 100% online coursework, this program is ideal for those with existing commitments, such as work or caring for family.
How might the IoT interact with AI and machine learning?
Given there is a shared goal of autonomy between the IoT, AI and machine learning, it’s reasonable to expect there to be some form of crossover.
Let’s look at a few ways that the IoT and AI could hypothetically interact, and the benefits we could gain through these processes.
Predictive maintenance
In industrial and commercial settings, we can already use IoT devices and AI to keep on top of maintenance demands. For example, devices and sensors connected to machinery can detect system slowdowns, raise alarms and make recommendations. This saves people from having to constantly monitor machinery health.
Printing systems can also benefit from AI and IoT. For instance, when ink levels get low, AI can learn to order new supplies through connected devices, again, saving time and effort, and reducing the risk of a productivity slowdown.
State and event triggering
The simplest of IoT interactions revolve around basic triggers, such as “if X, do Y”. However, AI and machine learning help to create more advanced interactions based on additional conditions and concerns.
For instance, AI might specify that an IoT trigger is not only activated based on a set event, but also on an extra condition. The difference could be that a light bulb turns on at a specific time of day, but only if it’s dark outside.
General efficiency improvements
AI can effectively save people from having to make decisions based on actions taken by IoT hardware and applications.
It’s possible to program AI, or for machines to learn conditions themselves, so that some mundane or repetitive tasks are completely automated.
While there will always be some critical processes that require human insight and interaction, as both machine learning and IoT evolve, it’s likely more and more businesses will delegate some decision-making to machinery.
Safety controls
By learning about safe conditions and how to recognize threats, AI can work with IoT to both warn of potential security risks and take immediate action to terminate affected operations.
For example, AI sensors can ensure machinery shuts down if it reaches excessive temperatures, reducing the risk of injury and serious harm. IoT devices, such as internal thermostats and performance analytics, can help AI to learn when to shut down machinery and when to power it back up again.
This not only helps to improve on-site safety, but also ensures any loss of productivity should machinery falter is minimized.
Vehicle adaptations
Self-driving cars might not be everywhere just yet, but the technology behind these vehicles is growing increasingly impressive thanks to partnerships between AI and IoT devices. For instance, self-driving cars know when to stop at intersections and when to adhere to specific speed limits because their IoT sensors have learned how to adapt to the laws of the highway.
There are already IoT and AI adaptations available in standard vehicles, as some vehicles have lane warning systems, where physical sensors detect when a driver might stray out of a specific lane. This technology can alert drivers through alarms and sounds, and even activate hardware to nudge steering wheels back in the right direction.
Healthcare tracking
Wearable tech has been around for some time; however, developers continue to produce smartwatches that count steps taken, measure heart rates and evaluate nearby noise levels. IoT devices such as smartwatches can now analyze and deliver information to patient monitors in hospital settings. Clinics and hospitals can use smart tech to monitor blood oxygen levels, medication needs and heart rates to better inform care staff when they might need to intervene during a patient case.
This has become possible thanks to patches and sensors that can attach to patients or may even be swallowed or surgically implanted. These devices can monitor vital signs and report back to external devices so carers have a better understanding of medication interactions, and what action might be needed next.
It’s all in the name of delegation
While many of us are still learning the basics of artificial intelligence and machine learning, it’s safe to say that AI and IoT interactions are all around us. In the name of saving time and money, delegating tasks to machines is only likely to continue as the years go by.
While the idea of leaving so much in the hands of AI and machinery seems scary to some, it’s all in the name of making our lives easier and making work more efficient. Provided there are clear controls in place, there is little reason for people to fear the rise of the machines.
