TY - JOUR
T1 - Drones applications for smart cities
T2 - Monitoring palm trees and street lights
AU - Alkaabi, Khaula
AU - El Fawair, Abdel Rhman
N1 - Funding Information:
Funding information: The research was funded by UAE University Office of Sponsored Research (SURE Plus), UAE, under a grant number 2019/G00003071.
Publisher Copyright:
© 2022 the author(s), published by De Gruyter.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - 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.
AB - 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.
KW - normalized difference vegetation index
KW - palm trees
KW - smart sustainable city
KW - street lights
KW - unmanned aerial vehicle
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U2 - 10.1515/geo-2022-0447
DO - 10.1515/geo-2022-0447
M3 - Article
AN - SCOPUS:85146055521
SN - 2391-5447
VL - 14
SP - 1650
EP - 1666
JO - Open Geosciences
JF - Open Geosciences
IS - 1
ER -