دورية أكاديمية
Lost in the woods: Forest vegetation, and not topography, most affects the connectivity of mesh radio networks for public safety.
| العنوان: | Lost in the woods: Forest vegetation, and not topography, most affects the connectivity of mesh radio networks for public safety. |
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| المؤلفون: | Zimbelman EG; Department of Forest, Rangeland and Fire Sciences, University of Idaho, Moscow, Idaho, United States of America., Keefe RF; Department of Forest, Rangeland and Fire Sciences, University of Idaho, Moscow, Idaho, United States of America. |
| المصدر: | PloS one [PLoS One] 2022 Dec 07; Vol. 17 (12), pp. e0278645. Date of Electronic Publication: 2022 Dec 07 (Print Publication: 2022). |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, P.H.S. |
| اللغة: | English |
| بيانات الدورية: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: San Francisco, CA : Public Library of Science |
| مواضيع طبية MeSH: | Idaho |
| مستخلص: | Real-time data- and location-sharing using mesh networking radios paired with smartphones may improve situational awareness and safety in remote environments lacking communications infrastructure. Despite being increasingly used for wildland fire and public safety applications, there has been little formal evaluation of the network connectivity of these devices. The objectives of this study were to 1) characterize the connectivity of mesh networks in variable forest and topographic conditions; 2) evaluate the abilities of lidar and satellite remote sensing data to predict connectivity; and 3) assess the relative importance of the predictive metrics. A large field experiment was conducted to test the connectivity of a network of one mobile and five stationary goTenna Pro mesh radios on 24 Public Land Survey System sections approximately 260 ha in area in northern Idaho. Dirichlet regression was used to predict connectivity using 1) both lidar- and satellite-derived metrics (LIDSAT); 2) lidar-derived metrics only (LID); and 3) satellite-derived metrics only (SAT). On average the full network was connected only 32.6% of the time (range: 0% to 90.5%) and the mobile goTenna was disconnected from all other devices 18.2% of the time (range: 0% to 44.5%). RMSE for the six connectivity levels ranged from 0.101 to 0.314 for the LIDSAT model, from 0.103 to 0.310 for the LID model, and from 0.121 to 0.313 for the SAT model. Vegetation-related metrics affected connectivity more than topography. Developed models may be used to predict the connectivity of real-time mesh networks over large spatial extents using remote sensing data in order to forecast how well similar networks are expected to perform for wildland firefighting, forestry, and public safety applications. However, safety professionals should be aware of the impacts of vegetation on connectivity. Competing Interests: The authors have declared that no competing interests exist. (Copyright: © 2022 Zimbelman, Keefe. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.) |
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| معلومات مُعتمدة: | U01 OH010841 United States OH NIOSH CDC HHS |
| تواريخ الأحداث: | Date Created: 20221208 Date Completed: 20221215 Latest Revision: 20230309 |
| رمز التحديث: | 20230309 |
| مُعرف محوري في PubMed: | PMC9728932 |
| DOI: | 10.1371/journal.pone.0278645 |
| PMID: | 36477301 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0278645 |