Healthcare waste management (HCWM) is a growing challenge in developing countries due to inadequate infrastructure, regulatory oversight, and proper utilization of technologies. In many divisions, IoT has been a significant part of their daily operations. The primary goals of IoT are to collect, exchange, and act on data, which also contributes to automation. This study aims to implement and assess key criteria of an IoT-based Smart Dustbin system with fill level detection in HCWM through a MCDM method called the Single-Valued Neutrosophic (SVN)-DEMATEL method. In this study, the experimental setup of the smart dustbin with the results of its fill level notification and location has been presented. Additionally, the real-time update is incorporated through the Blynk application. The SVN-DEMATEL method is applied to evaluate a total of nine criteria, where three of each are technical, environmental, and economic criteria, respectively. The results of this study showed that one of the criteria, “Carbon footprint (C5)”, is the strongest driver among the identified factors. The criterion named “Real-time monitoring, (C2)” is the strongest effect among others. These findings can guide future practitioners to decide which of these criteria are most impactful, as well as how to design a system similar to this with possible efficient outcomes. Lastly, a more dynamic application of the methods and findings can be achieved based on this study.