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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Sensor Data Management and Stream Data Management: A Conceptual Framework and Its Application in Weather Data Monitoring |
| Authors Name: | Mr. Mathew Daniel E. , Dr. Okoronkwo Mathew C. , Mrs.Ukeoma Pamela E. , Prof. Bakpo Francis S. , Dr. Udanor Collins N. |
| Unique Id: | IJSDR2312095 |
| Published In: | Volume 8 Issue 12, December-2023 |
| Abstract: | With the development of highly intelligent technology and computing, sensors have generated a stream of data that must be effectively collected, processed, and stored to provide an analytical foundation for crucial decisions that affect the global well-being of humans. This study introduces a comprehensive conceptual framework designed to address the challenges associated with these high-velocity data streams and provides an understanding of sensor data management operations like data ingestion, retrieval, queries, storage, and analytics. The focus was on applying atmospheric weather data using the Campbell Scientific weather station to monitor weather parameters. The Atmospheric Weather Station (AWS) used for this study has sensor data and is managed by the Centre for Atmospheric Research, National Space Research and Development Agency, Anyigba. The database designed for this atmospheric data has a twelve-column record where the sensor data has nine columns for the nine weather parameters (rainfall, air temperature, relative humidity, solar radiation, soil volumetric water, soil temperature, wind speed, wind direction, and barometric pressure) and the equipment data has three records. This work also demonstrated that machine learning models are used to train, test, and predict the sensor data collected thereafter, visualize the predicted weather parameters in real time and the results of this prediction would assist both government policymakers and individual decision-makers in planning and socio-economic growth in Nigeria. |
| Keywords: | Sensor data, stream data management, atmospheric weather station, weather prediction, machine learning, Internet of Things. |
| Cite Article: | "Sensor Data Management and Stream Data Management: A Conceptual Framework and Its Application in Weather Data Monitoring", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 12, page no.729 - 736, December-2023, Available :http://www.ijsdr.org/papers/IJSDR2312095.pdf |
| Downloads: | 000338719 |
| Publication Details: | Published Paper ID: IJSDR2312095 Registration ID:209549 Published In: Volume 8 Issue 12, December-2023 DOI (Digital Object Identifier): https://doi.org/10.5281/zenodo.10428115 Page No: 729 - 736 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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