Utilizing IoT and Cloud Computing for Weather-Health Monitoring Application
This paper presents an innovative IoT-based weather monitoring system that integrates IoT technology and cloud computing. In order to provide comprehensive environmental data collection and analysis, the system utilizes a network of specialized sensors to measure temperature, humidity, pressure, rain levels, smoke concentration, and light intensity at regular intervals. Data is transmitted to Firebase cloud storage, enabling real-time access through a purpose-built Android application. The system effectively tracks atmospheric changes, including pressure fluctuations, nighttime variations in smoke levels, and light intensity influenced by both natural and artificial sources. All collected data is synchronized across digital platforms, providing users with timely and reliable environmental updates. The application’s graphical interface transforms raw data into intuitive visual representations, facilitating enhanced weather monitoring and analysis. The simultaneous updating of all parameters at an interval of 5 secs ensures high accuracy, while the efficient logging mechanism maintains optimal data consistency. This real-time environmental data stream has significant applications across multiple sectors, including agriculture, urban planning, and environmental research. By delivering seamless, accurate, and accessible weather information, this IoT-based system represents a potential revolution in environmental data collection, analysis, and utilization across industries.
Authors
- Syed Sajjad Haider Zaidi (ORCID: https://orcid.org/0000-0002-4033-4510)
- Asif Gulraiz (ORCID: https://orcid.org/0000-0003-2109-6956)
- Mohiuddin Zia
- Haseeb Gulraiz
- Shahnila Badar
Institutions
- DHA Suffa University (PK)
- Sir Syed University of Engineering and Technology (PK)
- National University of Sciences and Technology (PK)
Publication Details
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1109/icetecc65365.2025.11071126
- Citations
- 1
- Primary Topic
- Water Quality Monitoring Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.82