The primary focus of the conducted study lies in gathering the weather data from diverse sources, including hotels, surrounding areas, tourist attractions within the designated local, and the immediate vicinity of these tourist attractions. To accomplish this goal, we employed a range of sensors alongside an embedded system controller for the continuous acquisition of data. Subsequently, the gathered data was then transmitted and archived in a cloud-based database to facilitate subsequent analysis. The primary aim of this work is to harness the richness of this dataset to derive meaningful insights and take necessary actions based on these decision-making processes. To achieve effective visualization and comprehension of the amassed data, a dashboard has been created. This dashboard acts as an essential interface, presenting users with analyzed weather data. Leveraging machine learning algorithms, a predictive analysis model has been devised to generate accurate weather forecasts utilizing the acquired data. The aim of this research is to furnish users with valuable insights into weather patterns, thereby enhancing planning for tourist visits across various scenarios. Through the integration of these technologies, users are empowered to make more efficient and effective decisions grounded in data-driven analysis.