Drones applications for smart cities: Monitoring palm trees and street lights
This study explores drones’ applications and proposes a cost-effective drone monitoring system for both palm trees and street lighting networks. The planned drone technical system has two monitoring sections. First, a model is developed to examine the health of date palm trees, in which drone photos...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2022-12-01
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| Series: | Open Geosciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/geo-2022-0447 |
| _version_ | 1811171930832633856 |
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| author | Alkaabi Khaula El Fawair Abdel Rhman |
| author_facet | Alkaabi Khaula El Fawair Abdel Rhman |
| author_sort | Alkaabi Khaula |
| collection | DOAJ |
| description | This study explores drones’ applications and proposes a cost-effective drone monitoring system for both palm trees and street lighting networks. The planned drone technical system has two monitoring sections. First, a model is developed to examine the health of date palm trees, in which drone photos are used to determine whether palm trees are suffering from diseases such as black scorch and sudden decline syndrome. These images are transferred into a central computer to stimulate normalized difference vegetation index (NDVI) models using AgiSoft software. The simulated NDVI models indicated that there are no health issues with date palm trees, which has resulted in the positive feedback in terms of the economic growth. Second, drone technology is utilized to detect the technical faults in the lighting network to ensure proper maintenance and social security. Twelve images of street lights are captured to demonstrate the working condition and the operational status of the street lights. These images are processed in MATLAB software, and a stimulated image processing model is implemented to enhance the monitoring of the street lighting network. The simulation findings indicate that the light in one of the images is not functioning, and ArcGIS Pro is utilized to locate it. |
| first_indexed | 2024-04-10T17:22:33Z |
| format | Article |
| id | doaj.art-40962bea47ab42bbb5854ba435d1d338 |
| institution | Directory Open Access Journal |
| issn | 2391-5447 |
| language | English |
| last_indexed | 2024-04-10T17:22:33Z |
| publishDate | 2022-12-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Geosciences |
| spelling | doaj.art-40962bea47ab42bbb5854ba435d1d3382023-02-05T08:27:15ZengDe GruyterOpen Geosciences2391-54472022-12-011411650166610.1515/geo-2022-0447Drones applications for smart cities: Monitoring palm trees and street lightsAlkaabi Khaula0El Fawair Abdel Rhman1Department of Geography and Urban Sustainability, United Arab Emirates University, PO Box 15551, Al Ain City, United Arab EmiratesCivil and Environmental Engineering Department, Al Ain City, United Arab EmiratesThis study explores drones’ applications and proposes a cost-effective drone monitoring system for both palm trees and street lighting networks. The planned drone technical system has two monitoring sections. First, a model is developed to examine the health of date palm trees, in which drone photos are used to determine whether palm trees are suffering from diseases such as black scorch and sudden decline syndrome. These images are transferred into a central computer to stimulate normalized difference vegetation index (NDVI) models using AgiSoft software. The simulated NDVI models indicated that there are no health issues with date palm trees, which has resulted in the positive feedback in terms of the economic growth. Second, drone technology is utilized to detect the technical faults in the lighting network to ensure proper maintenance and social security. Twelve images of street lights are captured to demonstrate the working condition and the operational status of the street lights. These images are processed in MATLAB software, and a stimulated image processing model is implemented to enhance the monitoring of the street lighting network. The simulation findings indicate that the light in one of the images is not functioning, and ArcGIS Pro is utilized to locate it.https://doi.org/10.1515/geo-2022-0447smart sustainable cityunmanned aerial vehiclepalm treesstreet lightsnormalized difference vegetation index |
| spellingShingle | Alkaabi Khaula El Fawair Abdel Rhman Drones applications for smart cities: Monitoring palm trees and street lights Open Geosciences smart sustainable city unmanned aerial vehicle palm trees street lights normalized difference vegetation index |
| title | Drones applications for smart cities: Monitoring palm trees and street lights |
| title_full | Drones applications for smart cities: Monitoring palm trees and street lights |
| title_fullStr | Drones applications for smart cities: Monitoring palm trees and street lights |
| title_full_unstemmed | Drones applications for smart cities: Monitoring palm trees and street lights |
| title_short | Drones applications for smart cities: Monitoring palm trees and street lights |
| title_sort | drones applications for smart cities monitoring palm trees and street lights |
| topic | smart sustainable city unmanned aerial vehicle palm trees street lights normalized difference vegetation index |
| url | https://doi.org/10.1515/geo-2022-0447 |
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