There is a clear intersection between the Internet of Things (IoT) and Artificial Intelligence (AI). IoT is about connecting machines and making use of the data generated from those machines. AI is about simulating intelligent behavior in machines of all kinds.
The Internet of Things (IoT) has the potential to fall into the general pit of buzzword-vagueness. Artificial intelligence (AI) often falls into the same trap, particularly with the advent of new terms such as “machine learning,” “deep learning,” “genetic algorithms,” and more. IoT and AI are two independent technologies that have a significant impact on multiple industry verticals. While IoT is the digital nervous system, AI becomes the brain that makes decisions which control the overall system. The lethal combination of AI and IoT brings us AIoT – Artificial Intelligence of Things – that delivers intelligent and connected systems that are capable of self-correcting and self-healing themselves.
Cloud computing provided three key aspects to connected systems – connectivity, storage, and compute. With an always-on architecture, cloud computing enabled multiple devices to seamlessly connect with each other. Apart from sending machine-to-machine (M2M) messages to each other, these devices sent telemetry data to the cloud that was ingested and stored centrally. The compute service in the cloud processed these large datasets representing the data from a diverse set of devices to derive insights.
Connectivity, storage, and compute became the foundation of the IoT. Initially, data was processed based on Big Data architectures such as Hadoop and Spark. IoT and Big Data helped stakeholders understand the patterns and the correlation between various devices and sensors. The outcome was presented in insightful visualizations and charts that were a part of IoT dashboards.
The 2019 Streaming Data and the Future Tech Stack report conducted by The New Stack –focuses on the use cases, technology choices and obstacles faced by early adopters of real-time data use cases for which streaming data is a major requirement.
The survey found that companies processing data in real-time for AI/ML use cases jumped from 6 percent from 2017 to 33 percent in 2019 — a more than five-fold increase. IoT experienced a three-fold increase in real-time data processing as another key use case driving streaming adoption.
As per Servion, by 2025, AI will drive 95% of customer interactions. Moving on, let us look at the top eight AI trends for 2018.