In this chapter, we will explore several real-world use cases of Streamlit, including applications in data visualization, real-time dashboards, and time-series analysis. We will also demonstrate how to interface Streamlit applications with external subsystems such as Arduino microcontrollers, infrared temperature sensors, and sonar modules. By integrating with physical devices and peripherals, Streamlit can be extended beyond digital dashboards to support embedded systems and IoT applications. For example, we could develop an operations dashboard to remotely monitor a building’s temperature or control a valve motor on a factory line. The possibilities are virtually limitless. As the culmination of the concepts covered throughout this book, the final section of this chapter will guide readers through the development of an advanced machine learning application that ties together many of the techniques discussed previously.