A Novel Fuzzy AHP-TOPSIS Model for IoT Protocol Selection in Smart Air Quality Monitoring Systems

The application of IoT in environmental monitoring systems revolutionized the process of real-time data acquisition, analysis, and subsequent decision-making. Finding the most feasible communication protocol for IoT-driven smart air quality monitoring systems has remained a significant challenge due to many factors attached to it, like latency, energy efficiency, scalability, reliability, and interoperability. Therefore, an integrated decision-making approach is required; Fuzzy AHP can be combined with TOPSIS. In this context, the Fuzzy AHP methodology is applied in this study by establishing the relative importance of criteria considering the integration of expert judgments made under uncertainty. In contrast, the ranking of IoT protocols will be made using the TOPSIS technique regarding their closeness to the optimum. This study compares four of the most used IoT protocols-MQTT, CoAP, LoRaWAN, and ZigBee-against the criteria identified. The results indicate that MQTT is the most suitable protocol for real-time applications due to its low latency and high energy efficiency. While LoRaWAN is ideal for large-scale deployments due to its scalability and energy efficiency. CoAP and ZigBee rank somewhat lower due to limitations in scalability and interoperability. The framework derived here defines a structured, flexible, robust methodology for selecting IoT protocol and bears wide-ranging implications, from smart city and environmental monitoring to industry-related applications. The study is bound to contribute toward developing efficient and reliable IoT-based ecological monitoring systems and provide a foothold for further studies related to advanced decision-making models for IoT applications.