Exploring the Synergy of Automation, Machine Learning, and Embedded Systems: Components, Applications, and Future Trends (KEY IJP************643)

• Rathika Rathikabalamurugan

Abstract

Automation refers to the use of technology to perform tasks with minimal human intervention. It plays a crucial role in industries, homes, and various fields, enhancing productivity and efficiency. This process discusses the components, applications, types, and future trends in automation. By this overview understand that after analysing some data sets, machine learning can extract patterns and insights. After give instructions to the model it can make predictions or decisions on new, unseen data. Then the time may make way for improving the performance of the model. It empowers computers to learns from data, adapt to new inputs , and make predictions or decisions without being explicitly programmed . As a cornerstone of artificial (AI), machine learning has grown from a niche academic field to a critical tool driving innovation across industries. An embedded system is a combination of hardware and software designed to perform a specific task. These systems are used in various fields such as automotive, healthcare, and consumer electronics. This journal explores the basics, applications, and future trends of embedded systems.