scholarly journals A Secure Key Agreement Scheme for Unmanned Aerial Vehicles-Based Crowd Monitoring System

2022 ◽  
Vol 70 (3) ◽  
pp. 6141-6158
Author(s):  
Bander Alzahrani ◽  
Ahmed Barnawi ◽  
Azeem Irshad ◽  
Areej Alhothali ◽  
Reem Alotaibi ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Monitoring System ◽  
Key Agreement ◽  
Aerial Vehicles ◽  
Crowd Monitoring

Forest Firefighting Monitoring System Based on UAV Team and Remote Sensing

2019 ◽  
pp. 220-241
Author(s):  
Maryna Zharikova ◽  
Vladimir Sherstjuk
Keyword(s):  
Remote Sensing ◽  
Data Integration ◽  
Unmanned Aerial Vehicles ◽  
Monitoring System ◽  
Fire Response ◽  
Ground Support ◽  
Aerial Vehicles ◽  
Remote Sensing Techniques ◽  
Fire Spreading ◽  
Multi Uav

In this chapter, the authors propose an approach to using a heterogeneous team of unmanned aerial vehicles and remote sensing techniques to perform tactical forest firefighting operations. The authors present the three-level architecture of the multi-UAV-based forest firefighting monitoring system; features of patrolling, confirming, and monitoring missions; as well as functions of UAV in such missions. The authors consider an infrastructure for the UAV ground support and equipment used for the UAVs control. The method of the data integration into a fire-spreading model in a real-time DSS for the forest fire response is proposed. The proposed approach has been tested with the multi-UAV team that included three drones for the patrol missions, one helicopter for the confirmation mission, and one octocopter for the monitoring mission. The performance of such multi-UAV team has been studied in the laboratory conditions. The result of the experiment has shown that the proposed approach provides required credibility and efficiency of fire prediction and response.

Smart traffic monitoring system using Unmanned Aerial Vehicles (UAVs)

2020 ◽  
Vol 157 ◽  
pp. 434-443 ◽  
Author(s):  
Navid Ali Khan ◽  
N.Z. Jhanjhi ◽  
Sarfraz Nawaz Brohi ◽  
Raja Sher Afgun Usmani ◽  
Anand Nayyar
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Monitoring System ◽  
Traffic Monitoring ◽  
Aerial Vehicles ◽  
Smart Traffic

scholarly journals Geoinformation monitoring of green stands using remote sensing methods

2020 ◽  
Vol 11 (2) ◽  
pp. 4-14
Author(s):  
D. I. Bidolah
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicles ◽  
Monitoring System ◽  
Urban Landscape ◽  
Urban Landscapes ◽  
Automated Monitoring ◽  
Aerial Vehicles ◽  
Monitoring Process ◽  
Green Areas ◽  
Remote Sensing Methods

A green plantations monitoring is an important work, which includes regular monitoring of urban landscapes in order to identify negative timely changes and to prepare the informed decisions to prevent their degradation. In modern conditions, it is advisable to improve this process by using remote sensing methods, the materials of which are processed in geographic information systems, which allows to establish an automated monitoring system of green areas. The purpose of the study is to substantiate the feasibility of geo-information monitoring of urban landscapes using remote sensing methods, including unmanned aerial vehicles. To achieve this goal, structural schemes of the monitoring system organization to get the information about green plantation conditions are proposed, together with the possibilities of using orthophotoplans, which are obtained by remote sensing methods for the needs of regular study of urban landscapes. Repeated remote monitoring of the green plantations condition allows to detect the timely changes that have occurred with tree and shrub vegetation over a period in an automated mode. The use of remote sensing materials in this case can be used as a documentary basis to justify the implementation of measures for landscaping. Due to the expensive cost of high-resolution materials, we recommend to use in the process of urban landscape monitoring proposed approach with regular surveys of unmanned aerial vehicles for greenery facilities. On the basis of the conducted researches the multifunctional structure of the green plantings monitoring system is offered and carrying out of digital transformation of monitoring process of urban landscapes condition is recommended. These studies indicate the feasibility of introducing regular automated monitoring of green areas with the involvement of remote sensing methods, including using unmanned aerial vehicles.

scholarly journals Unmanned Aerial Vehicles for Crowd Monitoring and Analysis

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2974
Author(s):  
Muhammad Afif Husman ◽  
Waleed Albattah ◽  
Zulkifli Zainal Abidin ◽  
Yasir Mohd. Mustafah ◽  
Kushsairy Kadir ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
High Concentration ◽  
Coverage Area ◽  
Crowd Analysis ◽  
Aerial Vehicles ◽  
Crowd Density ◽  
Aerial Vehicle ◽  
Regulatory Bodies ◽  
Crowd Monitoring ◽  
Low Coverage

Crowd monitoring and analysis has become increasingly used for unmanned aerial vehicle applications. From preventing stampede in high concentration crowds to estimating crowd density and to surveilling crowd movements, crowd monitoring and analysis have long been employed in the past by authorities and regulatory bodies to tackle challenges posed by large crowds. Conventional methods of crowd analysis using static cameras are limited due to their low coverage area and non-flexible perspectives and features. Unmanned aerial vehicles have tremendously increased the quality of images obtained for crowd analysis reasons, relieving the relevant authorities of the venues’ inadequacies and of concerns of inaccessible locations and situation. This paper reviews existing literature sources regarding the use of aerial vehicles for crowd monitoring and analysis purposes. Vehicle specifications, onboard sensors, power management, and an analysis algorithm are critically reviewed and discussed. In addition, ethical and privacy issues surrounding the use of this technology are presented.

scholarly journals Estimation of Crowd Density from UAV Images based on Deep Learning

2021 ◽  
Vol 9 (VIII) ◽  
pp. 242-248
Author(s):  
Sarita Chauhan
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Unmanned Aerial Vehicles ◽  
Crowd Counting ◽  
Aerial Vehicles ◽  
Crowd Density ◽  
Ip Camera ◽  
Crowd Monitoring ◽  
Uav Images ◽  
Crowd Surveillance

Crowd monitoring is necessary to improve safety and controllable movements to minimize risk, especially in high crowded events, such as Kumbh Mela, political rallies, sports event etc. In this current digital age mostly crowd monitoring still relies on outdated methods such as keeping records, using people counters manually, and using sensors to count people at the entrance. These approaches are futile in situations where people's movements are completely unpredictable, highly variable, and complex. Crowd surveillance using unmanned aerial vehicles (UAVs), can help us solve these problems. The proposed paper uses a UAV on which an IP Camera will be attached to get media, we then use a convolutional neural network to learn a regression model for crowd counting, the model will be trained extensively by using three widely used crowd counting datasets, ShanghaiTech part A and part B, UCF-CC 50 and UCF-QNRF.

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