International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 12 | Dec 2025
p-ISSN: 2395-0072
www.irjet.net
Weather Ease: A Python GUI Leveraging the Open Weather Map API with Native Accessibility Enhancements Anirban Mandal1, Gargi Chakraborty 2, Kunal Ghosh3 1,2 Associate Professor, Department of Electronics and Communication Engineering, Future Institute of Engineering
and Management, Kolkata, West Bengal, India
3 System Engineer, TCS, Kolkata, West Bengal, India
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Abstract - This work presents Weather Ease, a Python-
confined, Weather Ease reimagines engagement through dual accessibility channels: speech-to-text input for intuitive query handling and text-to-speech output for voice-based dissemination of results. This bidirectional interaction not only enhances inclusivity for differently-abled users but also exemplifies the growing relevance of human–computer symbiosis in user interface engineering. Technically, the application interfaces with the Open Weather Map database to retrieve real-time atmospheric parameters such as temperature, humidity, wind speed, and air pressure, while embedding temporal awareness through geolocation and time zone mapping. The resulting Graphical User Interface (GUI) dynamically adapts to diurnal transitions—morning, afternoon, dusk, and night—thereby transforming raw data into a contextual visual narrative of the Earth’s climatic pulse. Beyond its immediate functionality, Weather Ease underscores a pedagogical pursuit: it serves as a model framework for integrating API-based data analytics with accessible human-centred design.
based desktop application designed for real-time weather monitoring with a focus on usability and accessibility. The system employs Open Weather Map API for live meteorological data retrieval and a Tk inter-based GUI for interactive visualization. The interface supports both keyboard and voicebased interactions, integrating speech-to-text and text-tospeech modules to assist users with visual or motor impairments. The underlying architecture follows a modular design—comprising data acquisition, JSON parsing, visualization, and auditory feedback layers—to ensure scalability and maintainability. Experimental evaluation confirms that the system achieves sub-second data retrieval latency and over 90% speech recognition accuracy for city names, with high user satisfaction in responsiveness and audio clarity. The results validate the feasibility of creating accessible, intelligent, and user-friendly weather platforms through lightweight Python frameworks and open APIs Key Words: Python, Tk inter GUI, Open Weather Map API, JSON Parsing, Speech Recognition, Text-to-Speech, Realtime Weather Application, and Human–Computer Interaction.
Ultimately, this work proves itself at the intersection of software engineering, assistive technology, and environmental informatics. By embedding inclusivity into the algorithmic fabric of weather intelligence, the project contributes toward democratizing access to information— ensuring that technology not only forecasts change but also embodies it. Figure 1 shows a high-level application architecture of Weather Ease, and its components.
1. INTRODUCTION In an era where data-driven intelligence shapes everyday decision-making, weather information has transcended its traditional role from mere forecast to a critical enabler of adaptive human behaviour. From aviation to agriculture, and from personal mobility to healthcare, real-time meteorological insights inform both micro and macro decisions. The evolution of Internet-enabled platforms and Application Programming Interfaces (APIs) [1] has transformed how such data is captured, processed, and presented. Within this technological continuum, the project Weather Ease represents a convergence of accessibility, usability, and precision, an inclusive weather observation system designed through the synergy of Python programming and the Open Weather Map API. The system architecture emphasizes Python’s modular ecosystem and its inherent readability, deploying libraries such as Tk inter for graphical interface design [2], requests and JSON for network communication and structured data parsing, and gTTS and speech recognition for auditory and vocal interaction. Unlike conventional weather applications that remain visually
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Impact Factor value: 8.315
2. BACKGROUND AND LITERATURE REVIEW Previous research in the domain of weather applications has primarily focused on real-time data acquisition, visualization, and accessibility integration using Python-based frameworks. Studies leveraging Python’s Tk inter library have demonstrated its utility in developing responsive graphical interfaces that simplify data visualization and enhance usability across devices. Projects employing the Open Weather Map API have established its credibility for reliable meteorological data retrieval, given its structured JSON and XML outputs and widespread adoption among developers. Earlier implementations typically concentrated on temperature and humidity display systems; however, recent advancements have introduced accessibility components such as speech-to-text and text-to-speech for inclusivity, aligning with global trends in assistive technology. Works by
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