UAV Cluster-Based Video Surveillance System Optimization in Heterogeneous Communication of Smart Cities

Jin, Yanliang; Qian, Zhenjiang; Yang, Weiyong

doi:10.1109/access.2020.2981647

Cited by 44 publications

(16 citation statements)

References 40 publications

(40 reference statements)

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“…Their location-aware clustering scheme enhances the performance of UAV networks with limited resources. Jin et al [47] proposed an optimization algorithm for an efficient and reliable UAV cluster-based video surveillance system in the heterogeneous communication of smart cities. You et al [48] proposed a clustering scheme for UAV networks, which jointly optimizes UAV area coverage and mobile edge computing.…”

Section: Review Of Related Studiesmentioning

confidence: 99%

See 1 more Smart Citation

Bio-Inspired Approaches for Energy-Efficient Localization and Clustering in UAV Networks for Monitoring Wildfires in Remote Areas

Arafat

Moh

2021

IEEE Access

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In dynamic unmanned aerial vehicle (UAV) networks, localization and clustering are fundamental functions for cooperative control. In this article, we propose bio-inspired localization (BIL) and clustering (BIC) schemes in UAV networks for wildfire detection and monitoring. First, we develop a hybrid gray wolf optimization (HGWO) method and propose an energy-efficient three-dimensional BIL algorithm based on the HGWO, which reduces localization errors, avoids flip ambiguity in bounded distance measurement errors, and achieves high localization accuracy. In BIL, the bounding cube method is applied to reduce the initial search space. Second, we propose an energy-efficient BIC algorithm based on the HGWO. The BIC algorithm utilizes the gray wolf leadership hierarchy to improve clustering efficiency. We also develop an analytical model for determining the optimal number of clusters that provide the minimum number of transmissions. Finally, we propose a GWO-based compressive sensing (CS-GWO) algorithm to transmit data from cluster heads (CHs) to the base station (BS). The proposed CS-GWO constructs an efficient routing tree from CHs to the BS, thereby reducing the routing delay and the number of transmissions. Our performance evaluation shows that the proposed BIL and BIC significantly outperform conventional schemes in terms of various performance metrics under different scenarios.INDEX TERMS Bio-inspired algorithm, cluster head, clustering, energy efficiency, gray wolf optimization, localization, network lifetime, routing protocol, unmanned aerial vehicle network.

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Section: Review Of Related Studiesmentioning

confidence: 99%

“…CH mp (47) where d CH fs and d CH mp are the average distances from the CM to their corresponding CH in the free space and multipath models, respectively. For the case of d ≥ d th from (40), substituting ( 45), (46), and (47), we obtain…”

Section: Energy Consumption Of Cluster Headsmentioning

confidence: 99%

Bio-Inspired Approaches for Energy-Efficient Localization and Clustering in UAV Networks for Monitoring Wildfires in Remote Areas

Arafat

Moh

2021

IEEE Access

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“…Jin et al [16] present optimization algorithms and scheduling strategies based on an Unmanned Aerial Vehicle (UAV) cluster. In comparison, our paper proposed an all-in-one system of USVS, which includes video surveillance, scalable video streaming, Cloud computing, a middleware platform (SOUL) for a smart city, and a smart city paradigm (UTOPIA), and dealt with image processing for object detection with MapReduce using USVS.…”

Section: Related Workmentioning

confidence: 99%

A Cloud-Based UTOPIA Smart Video Surveillance System for Smart Cities

et al. 2020

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A smart city is a future city that enables citizens to enjoy Information and Communication Technology (ICT) based smart services with any device, anytime, anywhere. It heavily utilizes Internet of Things. It includes many video cameras to provide various kinds of services for smart cities. Video cameras continuously feed big video data to the smart city system, and smart cities need to process the big video data as fast as it can. This is a very challenging task because big computational power is required to shorten processing time. This paper introduces UTOPIA Smart Video Surveillance, which analyzes the big video images using MapReduce, for smart cities. We implemented the smart video surveillance in our middleware platform. This paper explains its mechanism, implementation, and operation and presents performance evaluation results to confirm that the system worked well and is scalable, efficient, reliable, and flexible.

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“…Over the last several decades, researchers and manufacturers have shown increasing interest in utilizing unmanned aerial vehicles (UAVs) for diverse purposes. UAVs are widely utilized in various domains, such as agricultural applications [ 1 ], environmental and wildlife monitoring [ 2 ], surveillance [ 3 ], public safety [ 4 – 6 ], photogrammetry for three-dimensional (3D) modeling [ 7 , 8 ], and logistics [ 9 ]. UAVs boast many advantages, including high maneuverability, low energy consumption, and the capacity for real-time monitoring.…”

Section: Introductionmentioning

confidence: 99%

A low-altitude public air route network for UAV management constructed by global subdivision grids

et al. 2021

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With an increasing number of unmanned aerial vehicles (UAVs), the difficulty of UAV management becomes more challenging, especially for low-altitude airspace due to complicated issues of security, privacy and flexibility. Existing management approaches to UAV flights include implementing registration of flight activity for supervision purposes, limiting the maximum flight height, setting different zones for different flight activities and prohibiting flights. In this research, we proposed a new air traffic management method for UAVs based on global subdivision theory. We designed four types of low-altitude air routes from grids, which correspond to grid sizes of 1.85 km, 128 m, 64 m and 32 m. Utilization of the subdivision grids transforms the complex spatial computation problem into a query process in the spatial database, which provides a new approach to UAV management in the fifth-generation (5G) era. We compared the number and data size of stored track records using longitude and latitude and different grid levels, computed time consumption for air route trafficability and simulated UAV flight to verify the feasibility of constructing this type of air traffic highway system. The amount of data storage and time consumption for air route trafficability can be substantially reduced by subdivision. For example, the data size using traditional expressions of latitude and longitude is approximately 1.5 times that of using a 21-level grid, and the time consumption by coordinates is approximately 1.5 times that of subdivision grids at level 21. The results of the simulated experiments indicate that in the 5G environment, gridded airspace can effectively improve the efficiency of UAV trajectory planning and reduce the size of information storage in the airspace environment. Therefore, given the increasing number of UAVs in the future, gridded highways have the potential to provide a foundation for various UAV applications.

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UAV Cluster-Based Video Surveillance System Optimization in Heterogeneous Communication of Smart Cities

Cited by 44 publications

References 40 publications

Bio-Inspired Approaches for Energy-Efficient Localization and Clustering in UAV Networks for Monitoring Wildfires in Remote Areas

Bio-Inspired Approaches for Energy-Efficient Localization and Clustering in UAV Networks for Monitoring Wildfires in Remote Areas

A Cloud-Based UTOPIA Smart Video Surveillance System for Smart Cities

A low-altitude public air route network for UAV management constructed by global subdivision grids

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