Multi-criteria decision-making methods for the evaluation of the social internet of things for the potential of defining human behaviors

Abstract

Multi-criteria decision-making (MCDM) techniques increase evaluation performance and make the selection process easier while lowering illogical needs and expenses for the assessment of SIoT and its impact on the potential of human behaviors. To assess SIoT and its effects on the potential of human behavior, the MCDM-based solutions named the Entropy weighted method (EWM) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are often employed. The study focuses on developing intelligent and efficient SIoT technologies for human behaviors, enhancing activity precision and user performance. Nine key features are evaluated to determine their potential impact on human behaviors and their supporting facilities. Seven SIoT innovations and gadgets are used as alternatives for improving human behaviors. The EWM method is used to quantify the precision of SIoT studies and the TOPSIS methodology is considered a solid selection approach for selecting the best SIoT solution. The research findings indicate that MCDM-and-SIoT-based technologies are effective tools for evaluating and developing SIoT-based human behavior. The research area is expanded to include the adoption of SIoT in everyday living routines and the use of combined MCDM procedures. The study metrics and ranking outcomes of SIoT and their impact on human behaviors serve as benchmarks and a basis for decision-making. The experimental studies and monitoring techniques aim to support creators and researchers in integrating SIoT technologies into everyday user tasks.