In the tech world, 2 of the biggest trends are IoT and AI. Where these trends were previously buzzwords, they are quickly becoming much more. The tech industry is poised to move into the Industry 4.0 revolution where AI and IoT converging will be the future of industrial automation.
This convergence is known as AIoT—Artificial Intelligence of Things.
The difference between traditional IoT and AIoT is that AIoT allows intelligent, connected systems to self-heal and self-correct. Additionally, IoT can be described as a system’s digital nervous system whereas, AI is the decision-making brain.
AIoT is beneficial to both its parent technologies. AI benefits IoT by lending machine learning capabilities and IoT benefits AI by providing connectivity, data exchange and signaling. Additionally, as more industries utilize IoT networking, it will lead to an influx of unstructured data (both machine-derived and human-made). By also incorporating AI and evolving to AIoT, this jumble of data can be transformed into value.
Moreover, in cases where AIoT is used (instances where infrastructure components are embedded with AI and interconnected with IoT networks), APIs can then extend into the device, software and platform levels interoperability. At this level, the focus would be on network operations, extracting data value and optimizing systems.
Need some clarification? Let’s use a web-connected camera as an example. Taking pictures with the camera will save all the photos to its IoT-connected system. If you apply AI technology to this camera, it will filter and only send frames containing specific objects. This process can be duplicated with speech synthesis as well as other forms of telemetry data.
Smart home tech is a good example of AIoT because many of them have the capability to learn through both reactions and human responses.
