ABSTRACT
Machine learning (ML) has emerged as a powerful tool within the field of smart wearables, enabling intelligent and personalized reports for customers. This chapter offers an introductory assessment of machine learning techniques specifically tailored for smart wearables, exploring their applications, challenges, and capacity benefits. We delve into the fundamentals of the machine learning system getting to know supervised and unsupervised learning, gaining knowledge of algorithms, and discuss how those techniques may be leveraged to enhance numerous elements of smart wearables, which include beatified interface, health tracking, and context-consciousness. Additionally, we spotlight the significance of statistics collection and preprocessing in achieving correct and reliable results in wearable applications. Furthermore, we deal with the challenges faced in deploying machine learning models on aid-limited wearable gadgets and look at techniques to optimize overall performance and energy efficiency. Through this comprehensive introduction, readers will gain insights into the fascinating world of machine learning for smart wearables, and comprehend its capability to revolutionize personal experience, enhance fitness outcomes, and power innovation in the wearable technology industry.
