Tiny Machine Learning Business Intelligence in the Semiconductor Industry: A Case Study

This paper sets its primary objective to  understand the transformative potential of Tiny Machine  Learning (Tiny ML) and Artificial Intelligence (AI) in  enhancing industrial efficiency. Using a research design that  juxtaposes the theoretical understanding of these technologies  with real-world applications, the methodology adopted  emphasizes three pivotal use cases, substantiated with tangible  examples. The main outcomes show the influential role of  STMicroelectronics, a leading semiconductor entity, in bridging  the gap between Tiny ML, AI, and industrial applications.  Results from in-depth examinations highlight the value of  Predictive Maintenance as evidenced by offshore wind farms,  the importance of Gesture Recognition in Human-Machine  Interaction with a focus on autonomous vehicles, and the  efficient integration of Tiny ML into IoT Sensor Networks,  notably seismic monitoring. In conclusion, this manuscript underscores the impending future where Tiny ML and AI  synergize, particularly hinting at breakthroughs in humanoid  robotics. Such advancements are anticipated to redefine the  contours of human-technology interaction impacting everyone  in everyday life.