## 5 Conclusions  
This study has developed and assessed a model for estimating dew point temperature (DPT), a crucial factor for thermal and energy applications. The new equation, obtained through non-linear regression fitting and parametric optimization, uses only ambient temperature and relative humidity, simplifying input requirements while maintaining high accuracy. Validated through extensive data comparison, it demonstrates consistent accuracy under real environmental conditions, ensuring reliable performance in critical applications. First-degree and a second-degree polynomial equations were modeled and compared together and against the commonly used rule of thumb equation for dew point. The findings demonstrate that the obtained second-degree equation provides significantly better predictions than the commonly used Thumb rule and the first-degree equation. Specifically, the second-degree equation achieved an R\({}^{2}\) value of 1, RMSE of 0.71, and a standard deviation of 0.62, highlighting its potential for reliable and precise estimations. The precision and reliability of the second-degree equation make it particularly useful for practical applications, including weather forecasting, water harvesting, thermal comfort in buildings, heat recovery systems, and humidity control in agricultural settings. The first-degree equation also showed good performance (R\({}^{2}\) equal to 0.98, RMSE of 1.82, STD of 1.82), surpassing the Thumb rule (R\({}^{2}\) equal to 0.95, RMSE of 2.67, STD of 2.39) in accuracy, which indicates that even simpler models can be effective. A notable advantage of the developed equations lies in their efficient memory usage, which remains stable and manageable even with large datasets, unlike the Magnus-Tetens equation, which exhibits high and exponentially increasing memory demands. The developed equations use 2.5 times less RAM than the Magnus-Tetens, enabling them to process large datasets more feasibly for real-time applications such as weather monitoring and industrial humidity control. The first-degree equation matches the Thumb rule in execution time, while the second-degree equation requires only half the processing time of the Magnus-Tetens, providing both memory and time efficiency. Furthermore, the simplicity of these equations makes them far easier to implement and integrate into various systems compared to complex ML models, which are often computationally intensive and act as \"black boxes.\" In contrast, the developed equations offer transparent and interpretable relationships between temperature, humidity, and dew point, eliminating the need for specialized recalibration. These characteristics make them robust, scalable, and well-suited for practical applications, addressing the complexity of traditional empirical models and the opacity of ML approaches. This equation is particularly useful for environmental studies that utilize GIS-based tools (e.g., PVGIS), which provide localized atmospheric data with a limited number of parameters. Having a model dependent on as few parameters as possible is crucial for its applicability and real-world implementation. For instance, in water harvesting from ambient air at various locations, this equation can accurately model and estimate potential water production, making it a helpful, reliable, and user-friendly tool for practical applications. Conceptualization, J.A.H.-T. and A.B. ([PERSON]); methodology, J.A.H.-T., J.P.T., A.B. ([PERSON]), and A.B. ([PERSON]); software, J.A.H.-T., R.S.-H. and A.B. ([PERSON]); validation, R.S.-H. and A.B. ([PERSON]); formal analysis, J.A.H.-T., A.B. ([PERSON]), and A.B. ([PERSON]); investigation, J.A.H.-T., A.B. ([PERSON]), and A.B. ([PERSON]); resources, R.S.-H. and J.P.T. ; data curation, J.A.H.-T., R.S.-H. and A.B. ([PERSON]); writing--original draft preparation, J.A.H.-T.; writing--review and editing, J.P.T., A.B. ([PERSON]), and A.B. ([PERSON]); visualization, J.A.H.-T., R.S.-H. and A.B. ([PERSON]); supervision, J.P.T., A.B. ([PERSON]), and A.B. ([PERSON]); project administration, J.P.T.