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A Novel IoT Application Recommendation System Using Metaheuristic Multi-Criteria Analysis

Mohammed Hayder Kadhim, Farhad Mardukhi*

Department of Computer Engineering and Information Technology, Razi University, Kermanshah, Iran

* Corresponding Author: Farhad Mardukhi. Email: email

(This article belongs to this Special Issue: Sensors and Nano-sensors Technologies for Health-Care Applications)

Computer Systems Science and Engineering 2021, 37(2), 149-158.


There are a variety of Internet of Things (IoT) applications that cover different aspects of daily life. Each of these applications has different criteria and sub-criteria, making it difficult for the user to choose. This requires an automated approach to select IoT applications by considering criteria. This paper presents a novel recommendation system for presenting applications on the IoT. First, using the analytic hierarchy process (AHP), a multi-layer architecture of the criteria and sub-criteria in IoT applications is presented. This architecture is used to evaluate and rank IoT applications. As a result, finding the weight of the criteria and sub-criteria requires a metaheuristic approach. In this paper, a sequential quadratic programming algorithm is used to find the optimal weight of the criteria and sub-criteria automatically. To the best of our knowledge, this is the first study to use an analysis of metaheuristic criteria and sub-criteria to design an IoT application recommendation system. The evaluations and comparisons in the experimental results section show that the proposed method is a comprehensive and reliable model for the construction of an IoT applications recommendation system.


Cite This Article

M. Hayder Kadhim and F. Mardukhi, "A novel iot application recommendation system using metaheuristic multi-criteria analysis," Computer Systems Science and Engineering, vol. 37, no.2, pp. 149–158, 2021.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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