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.