The challenges of IoT-based applications in high-risk environments, health and safety industries in the Industry 4.0 era using decision-making approach

High-risk companies have to deal with problems related to the environment, health, and safety (EHS) since the products of such companies create serious challenges to environmental safety. The presence of various similar and dissimilar risk factors in these companies complicates the known and unknown causal relationships whose interpretation and understanding are difficult. Therefore, EHS improvement has remained a great challenge to be solved by these companies. The design and implementation of ubiquitous systems are supported by the development of the Internet of Things (IoT) as well as their enabling technologies. IoT has been found capable of solving different problems of high-risk companies in regard to EHS-related challenges. A wide window for preference elicitation has been opened to decision experts (DEs) through the development of the q-rung orthopair fuzzy set (q-ROFS). The extensive research conducted into q-ROFS implies a great urge for a decision approach that can use accessible information appropriately to make decisions of the highest rationality. Using the q-ROFS advantages, the present study develops a novel approach with the “entropy-rank sum-weighting integrated approach (ERSWIA)” and “weighted aggregated sum product assessment (WASPAS)” model termed as “q-ROF-ERSWIA-WASPAS”. In this line, the q-ROF-ERSWIA is applied to compute the integrated weights of criteria, and the q-ROF-WASPAS is implemented to find the prioritization of organizations. A case study to assess the challenges of IoT-based applications in EHS industries in the era of Industry 4.0 is taken. Comparison and sensitivity studies are discussed to illustrate the usefulness of the presented approach.