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Two trends that are dominating the technology industry are the Internet of Things (IoT) and Artificial Intelligence (AI). But for industrial automation, these two technologies are much more than the buzzwords or trending topics. The convergence of AI and IoT will redefine the future of industrial automation. It is set to lead the Industry 4.0 revolution.
The Artificial Intelligence of Things (AIoT) is the combination of artificial intelligence (AI) technologies with the Internet of Things (IoT) infrastructure to achieve more efficient IoT operations, improve human-machine interactions and enhance data management and analytics.
AIoT (Artificial Intelligence of Things) is a relatively new term and has recently become a hot topic which combines two of the hottest acronyms, AI (Artificial Intelligence) and IoT (Internet of Things). IoT consists of interconnected things with built-in sensors and has the potential to generate or collect a vast amount of data. The data can be then analyzed and utilized with AI for problem solving or decision making. Without AI, IoT would have limited value. AI can multiply the value of IoT; conversely, IoT can promote the learning and intelligence of AI.
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.
To appreciate the promise of AIoT, we need to look at the evolution of connected systems.
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.