Best Researcher Award
| Maike Klein |
| Affiliation |
Lancaster University |
| Country |
United Kingdom |
| Scopus ID |
57207880915 |
| Documents |
11 |
| Citations |
51 |
| h-index |
4 |
| Subject Area |
Remote Data Acquisition |
| Event |
Global Sensor Awards |
| ORCID |
0000-0003-1458-4281 |
Maike Klein
Lancaster University
The Best Researcher Award recognizes researchers who demonstrate sustained scholarly achievement through scientific publications, measurable research influence, interdisciplinary collaboration, and contributions to technological advancement. Maike Klein has developed an academic profile associated with remote data acquisition, contributing to research involving sensing technologies, distributed monitoring systems, and data collection methodologies. The available bibliometric indicators provide an objective basis for evaluating academic performance within an internationally recognized research award framework.[1]
Abstract
This article presents an academic overview of Maike Klein’s research profile in relation to the Best Researcher Award presented at the Global Sensor Awards. The assessment considers publication productivity, citation performance, institutional affiliation, subject specialization, and measurable scholarly impact. The evaluation follows a neutral academic perspective and reflects commonly accepted bibliometric criteria employed in research assessment and scholarly recognition.[1]
Keywords
- Best Researcher Award
- Remote Data Acquisition
- Sensor Networks
- Wireless Monitoring
- Research Evaluation
- Bibliometric Analysis
Introduction
Remote data acquisition has become an essential component of modern sensing systems, enabling continuous monitoring, distributed information collection, environmental observation, industrial automation, and intelligent decision support. Advances in sensor technology, wireless communication, and cloud-based analytics have expanded opportunities for real-time data acquisition across scientific, engineering, healthcare, and environmental applications. Researchers working within this field contribute to improving data quality, system reliability, and technological innovation through interdisciplinary investigations and peer-reviewed research.[2]
Research Profile
Maike Klein is affiliated with Lancaster University in the United Kingdom. According to the available Scopus author profile, the researcher has published 11 indexed scholarly documents, received 51 citations, and achieved an h-index of 4. These bibliometric indicators reflect documented scholarly activity and measurable research visibility within internationally indexed scientific literature.[1]
Research Contributions
The documented publication record demonstrates engagement with remote data acquisition technologies through research involving sensing systems, distributed monitoring, data collection methodologies, and related engineering applications. Contributions support interdisciplinary scientific progress by addressing practical and theoretical challenges associated with reliable information acquisition and intelligent sensing infrastructures. Peer-reviewed dissemination enables these findings to contribute to ongoing scientific development and collaborative research activities.[1][2]
- Research involving remote sensing and data acquisition technologies.
- Scientific publications within indexed academic journals and conferences.
- Interdisciplinary collaboration supporting intelligent monitoring systems.
- Contributions to modern sensor-enabled information collection methodologies.
Publications
The publication portfolio includes eleven indexed scholarly documents contributing to research associated with remote data acquisition and related sensing technologies. Scientific publications facilitate knowledge dissemination, scholarly communication, and citation by subsequent research while supporting continued advancement within engineering and digital technology disciplines.[1]
Representative DOI resource relevant to remote sensing and data acquisition: https://doi.org/10.1109/JSEN.2021.3090000 [3]
Research Impact
Bibliometric indicators remain an established component of research assessment by providing quantitative evidence of scholarly visibility. The available citation count of 51 together with an h-index of 4 indicates that multiple publications have contributed to subsequent scientific literature. Although quantitative metrics represent only one aspect of research evaluation, they are frequently incorporated into institutional reviews, funding assessments, and academic award selection processes.[1]
Award Suitability
Based upon publicly available bibliometric information, Maike Klein demonstrates several characteristics commonly considered during academic award evaluation, including peer-reviewed publication activity, measurable citation performance, interdisciplinary research engagement, and contributions within the field of remote data acquisition. These objective indicators align with transparent scholarly assessment practices supporting recognition through the Best Researcher Award presented at the Global Sensor Awards.[1][2]
Conclusion
Maike Klein has established a documented scholarly profile through peer-reviewed publications, measurable citation performance, and research contributions associated with remote data acquisition technologies. The available bibliometric evidence, combined with institutional affiliation and interdisciplinary research engagement, provides an objective foundation for academic recognition within the Global Sensor Awards while reflecting accepted standards of scholarly evaluation and research excellence.[1]
External Links
References
- Elsevier. (n.d.). Scopus author details: Maike Klein, Author ID 57207880915. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=57207880915
- IEEE Sensors Journal. General literature concerning remote data acquisition, wireless sensing technologies, intelligent monitoring systems, and distributed sensor networks.
https://ieeexplore.ieee.org/
- Digital Object Identifier Foundation. Representative DOI resource illustrating citation formatting for sensor and remote data acquisition research.
https://doi.org/10.1109/JSEN.2021.3090000