The Potential and Early Impact of AIoT
Illustration: © IoT For All
The Internet of Things (IoT) has created a world based on connectivity that allows any device or object around us to become smarter and more responsive. The technology opens opportunities to create digital experiences based on physical objects – toys, appliances, vehicles, assembly lines, and more. But while this technology makes the devices we interact with smarter, technologists have started taking a step back to make IoT itself smarter as well.
Artificial Intelligence of Things (AIoT) enabled devices, in contrast, have the potential to be autonomous. Accomplishing this provides all the attributes of IoT devices, with device or local network reasoning. This allows for the ability to process input and generate data based on usage and provide a level of conclusion through rules, inference, and reasoning.
Through reasoning, devices will have greater efficiencies, new capabilities, and increased collaboration through decentralized AI on a local and global level. There is so much potential waiting to be unleashed.
Where Is AIoT Felt Most?
The most immediate impact on our society will, naturally, be in the consumer device space, as personal smart devices become AI-enabled. Both the smart home and the auto industries are rapidly adopting AIoT. The market for these devices is expanding with new home security systems, cooking appliances, and other devices that incorporate reasoning and understanding into their functionality. Technology that was once exclusive to an S-Class Mercedes or Tesla Model S can now be found in Kia or Hyundai cars.
AIoT adoption and comprehension outside of consumer devices become a little trickier. Inherently, we’re aware that the devices around us are getting smarter. But what has become less apparent and even less visible to people are smart cities. Outside of engineers or urban planners, most people aren’t aware of how AIoT has changed municipal services levels. energy grids, streetlights, public transportation are all aspects of smart cities that have become more efficient through automated connectivity.
One outlier where people are aware of AIoT’s impact behind the scenes is on the industrial level. One example of this is Amazon. Amazon has been at the forefront of automation for years, from their shipping methods to their product suggestion systems. People are very much aware that their lives are being made simpler through this technology.
Decentralization Is Paramount
The fundamental key that makes all of these devices and technology work more efficiently is Decentralized AI. Decentralized AI is a model that allows for the isolation of processing without the downside of aggregate knowledge sharing. By virtue, it enables you to process information independently, among varying computing devices. By utilizing this autonomy, decentralized AI will provide a structure in place to explain how things work. Simultaneously, the AIoT devices will be able to harness this power to grow smarter when providing a more efficient and personalized experience.
When powered by decentralized AI, there is incredible potential behind AIoT across business, sciences, and society. Devices will overcome adversity through real-world challenges, reasoning, and trial and error while having the results recorded.
AIoT will continue to change the way we interact with the world, but that will also rely on how widespread adoption is seen. To achieve the adoption necessary, there are hurdles to watch out for. First off, you’ll need to devise the best use of AI for a given device. Second, you’ll need to watch for technological challenges such as power and battery life, as well as processing power requirements. Without planning for these instances, the true adoption of AIoT will never be fully realized.
When its potential is realized, AIoT will ultimately act as a replacement for many IoT devices. For those where AI is not needed, it will be prudent for those devices to remain in a state of directed action or purpose. But even if those IoT devices are stuck in a state of stasis, they’ll likely need to adapt and evolve to incorporate levels of reasoning. There is too much potential behind AIoT to allow other devices to be stuck on a never-ending carousel.