RecIoT: A Deep Insight into IoT-Based Smart Recommender Systems

Abstract

Typically, Internet of Things (IoT) is perceived as the technology for connecting people, devices, vehicles, home appliances, etc., and 212 billion heterogenous devices are presumed to be connected by 2020 under its umbrella. This domain is gaining popularity worldwide because of the wave it has brought in both research and industrial sector. Smart applications of this scenario provide assistance and services to the users in smart homes, smart cities, smart retail, agriculture, healthcare, etc. However, researchers are now exploring the potential of IoT systems in other domains, one of them being recommender systems. In recent years, the focus of researchers has drifted towards utilizing recommender systems to improve offered selections to IoT users. Therefore, the aim of this paper is to study the present practices, approaches, and challenges in the aforementioned domain along with possible solutions. Briefly, the contributions of this paper are as follows: (1) providing an overview of the prevailing scenario in a range of application domains associated with IoT based recommender systems, (2) providing a framework of some real-world applications, (3) outlining key areas for the improvement towards context-aware personalized services in the future research, and (4) providing a bibliometric trend analysis prevalent in the concerned domain.