Recent trends in machine learning can be leveraged to automate systems that handle complex tasks. One notable mobile computing technique, the smart grid (SG), is utilized to control interior security, temperature, and maintenance. The Internet of Things (IoT) can be integrated with various components to construct smart buildings. Through this operational process, smart devices are incorporated into IoT frameworks. In this context, IoT devices are essential for smart grids and can significantly enhance human efficiency. These advancements cater to contemporary life systems that are both secure and effective in sustaining life. The primary objective of this chapter is to highlight the motivation behind current IoT installations in smart buildings and smart grids. From this perspective, the infrastructure supporting IoT devices and their components is crucial. Remote configuration of smart grid monitoring systems can enhance the security and comfort of building occupants. Sensors are necessary to operate and monitor a range of devices, from consumer electronics to smart grids. Network-connected devices should be energy-efficient and capable of remote monitoring. The authors aim to contribute to the development of solutions based on machine learning (ML), artificial intelligence (AI), IoT, and smart grids. Additionally, this chapter explores networking, machine intelligence, and smart grid technologies. The final sections examine research on smart grids and IoT, discussing several IoT platform components. The first section reviews common machine learning methods for forecasting building energy demand. Subsequently, the authors explain the functionality of IoT, smart grids, and smart meters, which are crucial for receiving real-time energy data. Finally, the chapter investigates how various SG, IoT, and ML components integrate and operate within a simplified architecture, organized into layers of entities that communicate via interconnected networks.