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