Real-Time Weather Forecasting System Using Open WeatherMap API and Django MVC Architecture

Abstract

Weather forecasting has long been a complex scientific challenge, requiring the analysis of vast meteorological datasets to predict atmospheric conditions accurately. In recent years, the increasing demand for timely and localized weather updates has driven the development of user-friendly, real-time forecasting tools. This research presents the design and development of a weather application that leverages modern web technologies and API integration to deliver accurate, real-time weather information to users across the globe. The application utilizes the OpenWeatherMap API, along with other reliable data sources, to provide key meteorological parameters such as temperature, humidity, wind speed, and precipitation.

Built using the Django framework and MVC architecture, the application features a robust backend for data processing and storage, and a dynamic, interactive frontend for enhanced user experience. The system supports both manual and GPS-based location detection, and offers multilingual support to improve accessibility for non-English speakers, including farmers and rural users. Additionally, users can customize their experience through unit conversion options and receive notifications for severe weather alerts. This paper outlines the technical architecture, development methodology, and implementation process of the application. It also highlights the challenges encountered in integrating real-time APIs and ensuring accurate data rendering. The proposed system demonstrates how integrating open-source tools, client-server architecture, and user-centered design principles can result in an efficient and accessible weather forecasting solution. The application not only bridges the gap between raw meteorological data and end users but also enhances public preparedness and decision-making in response to weather conditions.