Application of Fuzzy Logic in IoT to Optimize Hall-Effect Sensor Accuracy

The implementation of Fuzzy Logic in IoT-based volumetric measurement systems for LPG storage represents a significant improvement over traditional deterministic algorithms. This study addresses critical challenges, including measurement uncertainty and adaptability, demonstrating superior performance in both precision and reliability. The experimental results highlight that the Fuzzy Logic algorithm, employing the Takagi-Sugeno method, achieves a maximum uncertainty of ±2%, compared to a ±5% delta observed with DFA. This reduction is particularly relevant under industrial safety standards, such as ABNT NBR 14024, which enforces strict limits on volume thresholds. Additionally, Fuzzy Logic maintains consistent accuracy at higher volume levels (75% to 90%), showcasing its robustness when integrated with Hall effect sensors. The development process emphasizes accessibility and cost-effectiveness, leveraging C++ programming in an open-source environment and affordable hardware, such as the ESP or Arduino microcontroller. These features ensure scalability and economic viability, particularly in regions where cost barriers prevent the adoption of advanced technologies, such as in Brazil. This study not only underscores the transformative potential of Fuzzy Logic for volumetric monitoring but also paves the way for future innovations. These include exploring alternatives communication protocols and integrating additional sensors to expand functionality. By enhancing precision and compliance with industry standards, this IoT solution promotes safer, more efficient, and digitally connected LPG storage systems, offering a scalable and practical alternative for modernizing industrial applications.