Quick fix for obstacles emerging in management recruitment measure using IOT-based candidate selection

In this paper, decision-making tool is developed for the identification of the optimal aspirant for the recruitment procedure. It is developed using the IoT-based smart sensor architecture and Visual Studio programming language. The ideal candidates are determined by using the objective function, which is extracted from the sequence of the pairwise comparison performed using the combination of MCDM algorithms. Later, after the pairwise comparison, the process is extended to the next step, that is to allocate ranking for the best suitable candidate. This makes the tool more feasible and accurate. To identify the ranking of the finest aspirant, the combination of two MCDM technologies is used that is TOPSIS and GRA. In TOPSIS, mainly two artificial alternatives are used that is positive ideal alternative and negative ideal alternative. The Grey relational grade reduced by Grey theory (Tsai et al. in Int J 11:45–53, 2003) will be used to make an integrated and authentic evaluation system for identifying who is the best aspirant among all the candidates applied for the job of a professor.