The amount of internet traffic produced by wired and wireless networks has increased at a never-before-seen pace due to the quick development of networking technology and smart devices. Similar to how fast-developing wireless networks have emerged, the Internet of Things (IoT) has undergone a new revolutionary breakthrough. Today, a broad spectrum of IoT device users across many platforms are uploading and searching through enormous amounts of data. These devices generate a tremendous quantity of traffic, which has a significant impact on a number of domains, including smart cities, automotive networks, e-health, smart industries, etc. Multimedia material makes up a significant amount of all internet traffic and is projected to continue growing rapidly in the future. The typical host-centric IP network design is dependent on host-to-host communication; thus, it is not appropriate to meet the needs of a high number of devices for content delivery. Users of these devices are more interested in the requested material than they are in learning where it is. The existing internet architecture is failing more and more often as content-centric apps develop since the internet was not initially intended to be a distribution network. A future internet architecture designed specifically for content-focused communication is called Information Centric Networking (ICN). By providing content name-based routing and forwarding, ICN has circumvented the host-centric communication problem of IP address sharing. With less latency and a higher hit ratio, efficient content delivery may be supported by ICN's pervasive in-network caching capability. ICN-IoT is made up of the ICN since it may function as an IoT enabler. The framework for caching methods in ICN to enable user Quality of Experience (QoS) is the main topic of this thesis. The caching solutions for managing multimedia traffic in two distinct ICN-IoT scenarios, such as smart cities and vehicle networks, have been discussed from both theoretical and practical perspectives. This is because the needs of caching may vary for various ICN-IoT applications. By taking into account either content factors (such as content popularity, content freshness, and etc.) or node attributes (such as node location, node cache space, and etc.), the existing research offered options for enhancing network performance. The goal of this research project is to develop a caching approach that will enhance network speed while also delivering greater quality of experience. Further, the cache performance may be greatly enhanced by using the ideas of edge computing (EC) and machine learning (MC).