In current digital age, the Internet of Things (IoT) plays a critical role in real-time data perception and computation in order to better manage the system in an automated manner. In this work, we will present the edge computing concept of IoT architecture, which increases the efficiency of complicated application processing and is known as fog computing. The rapid expansion of computing resources may be regarded to improve real-time data capabilities such as detection, capture, collecting, and processing across billions of linked devices and support a range of applications such as smart wearable devices, smart meters, and smart homes. The advancement of big data technologies makes it simpler to process and analyze massive volumes of IoT data. Smart devices continue to confront a number of problems in terms of computational power, memory storage, batteries, and frequency bandwidth, all of which degrade their Quality of Service (QoS) and user activities. Fog-embedded cloud computing is viewed as a computer paradigm that alleviates the fixed resource load for smart equipment by allowing end-users to develop programs with flexible resources at the lowest possible cost in terms of architecture, software, and platforms.