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

Video surveillance system is the integration of computers, networks, communications, and video CODEC, etc. Because of its distributed architecture, parallel image processing and ease of installation and expansion, it is widely used in many fields such as education, transportation and industry. However, there are some challenges of video surveillance applications in smart cities such as large scale of video events, low quality and big delay of video data transmission, and the loss of video surveillance data integrity. In order to solve the above problems, this paper designs a series of optimization algorithms and scheduling strategies based on Unmanned Aerial Vehicle (UAV) cluster. Firstly, we construct a full device coverage network with UAV cluster in heterogeneous communication environment of smart cities. Secondly, we formulate the scheduling problem of UAV cluster as bi-objective fragile bin packing problem, and design an optimal scheduling algorithm with constant approximation performance ratio. The simulation experimental results fully demonstrate the effectiveness, feasibility and robustness of the proposed solution in terms of system life cycle, video decodable frame rate, the ratio of UAV flight time to system life cycle, throughput and delay.

[1]  Suhaib A. Fahmy,et al.  Efficient Spectrum Sensing for Aeronautical LDACS Using Low-Power Correlators , 2018, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[2]  Mauro Barni,et al.  Anonymous subject identification and privacy information management in video surveillance , 2017, International Journal of Information Security.

[3]  Jan Bumberger,et al.  Long-term environmental monitoring infrastructures in Europe: observations, measurements, scales, and socio-ecological representativeness. , 2018, The Science of the total environment.

[4]  Hao Lu,et al.  Algorithms for Balanced Graph Colorings with Applications in Parallel Computing , 2017, IEEE Transactions on Parallel and Distributed Systems.

[5]  Rong Du,et al.  The Sensable City: A Survey on the Deployment and Management for Smart City Monitoring , 2019, IEEE Communications Surveys & Tutorials.

[6]  Steen Rasmussen,et al.  RAIN: A Bio-Inspired Communication and Data Storage Infrastructure , 2017, Artificial Life.

[7]  Mitra Djamal,et al.  The Reliability of Wireless Sensor Network on Pipeline Monitoring System , 2017 .

[8]  Guang Chen,et al.  A novel deep multi-channel residual networks-based metric learning method for moving human localization in video surveillance , 2018, Signal Process..

[9]  Andrew Chi-Chih Yao,et al.  Resource Constrained Scheduling as Generalized Bin Packing , 1976, J. Comb. Theory A.

[10]  Tobi Delbrück,et al.  The event-camera dataset and simulator: Event-based data for pose estimation, visual odometry, and SLAM , 2016, Int. J. Robotics Res..

[11]  Lianbing Deng,et al.  A FCM cluster: cloud networking model for intelligent transportation in the city of Macau , 2017, Cluster Computing.

[12]  Jinjun Tang,et al.  Real-Time Traffic Flow Parameter Estimation From UAV Video Based on Ensemble Classifier and Optical Flow , 2019, IEEE Transactions on Intelligent Transportation Systems.

[13]  Yuanzhang Li,et al.  DPPDL: A Dynamic Partial-Parallel Data Layout for Green Video Surveillance Storage , 2018, IEEE Transactions on Circuits and Systems for Video Technology.

[14]  Rafael Almar,et al.  Wavelet-Based Optical Flow Estimation of Instant Surface Currents From Shore-Based and UAV Videos , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[15]  Ismail Güvenç,et al.  UAV-Enabled Intelligent Transportation Systems for the Smart City: Applications and Challenges , 2017, IEEE Communications Magazine.

[16]  Swades De,et al.  Energy Sustainable IoT With Individual QoS Constraints Through MISO SWIPT Multicasting , 2018, IEEE Internet of Things Journal.

[17]  Xiao Xiang Zhu,et al.  Fusing Meter-Resolution 4-D InSAR Point Clouds and Optical Images for Semantic Urban Infrastructure Monitoring , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Jiajia Liu,et al.  Congestion-Aware Communication Paradigm for Sustainable Dense Mobile Crowdsensing , 2017, IEEE Communications Magazine.

[19]  Yohanes Khosiawan,et al.  Task scheduling system for UAV operations in indoor environment , 2016, Neural Computing and Applications.

[20]  Azzedine Boukerche,et al.  AVARAC: An Availability-Based Resource Allocation Scheme for Vehicular Cloud , 2019, IEEE Transactions on Intelligent Transportation Systems.

[21]  Geoffrey Ye Li,et al.  Dual-UAV-Enabled Secure Communications: Joint Trajectory Design and User Scheduling , 2018, IEEE Journal on Selected Areas in Communications.

[22]  Shaohua Liu,et al.  Vehicle tracking by detection in UAV aerial video , 2019, Science China Information Sciences.

[23]  Marco Ortolani,et al.  A Network Tomography Approach for Traffic Monitoring in Smart Cities , 2018, IEEE Transactions on Intelligent Transportation Systems.

[24]  Song Guo,et al.  A Differential Privacy-Based Query Model for Sustainable Fog Data Centers , 2019, IEEE Transactions on Sustainable Computing.

[25]  Virginia H. Dale,et al.  Interactive posters: A valuable means of enhancing communication and learning about productive paths toward sustainable bioenergy , 2017 .

[26]  Bahareh Kalantar,et al.  Multiple Moving Object Detection From UAV Videos Using Trajectories of Matched Regional Adjacency Graphs , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[27]  Xianbin Cao,et al.  Offline and Online Search: UAV Multiobjective Path Planning Under Dynamic Urban Environment , 2018, IEEE Internet of Things Journal.

[28]  Devesh Samaiya,et al.  Intelligent video surveillance for real time energy savings in smart buildings using HEVC compressed domain features , 2018, Multimedia Tools and Applications.

[29]  Zhongyuan Wang,et al.  Smart Monitoring Cameras Driven Intelligent Processing to Big Surveillance Video Data , 2018, IEEE Transactions on Big Data.

[30]  Farhad Shahnia,et al.  Provisional internal and external power exchange to support remote sustainable microgrids in the course of power deficiency , 2017 .

[31]  A. Bilzhause,et al.  Datalink security in the L-band digital aeronautical communications system (LDACS) for air traffic management , 2017, IEEE Aerospace and Electronic Systems Magazine.

[32]  J. Orteu,et al.  Evaluation of a charge-coupled-device-based video sensor for aircraft cargo surveillance , 2002 .

[33]  Soo Young Shin,et al.  Fog Computing-Based Smart Health Monitoring System Deploying LoRa Wireless Communication , 2019 .

[34]  Hans Antonson,et al.  Driving behaviour responses to a moose encounter, automatic speed camera, wildlife warning sign and radio message determined in a factorial simulator study. , 2016, Accident; analysis and prevention.

[35]  Jinlong Wang,et al.  Time-Frequency Scheduling and Power Optimization for Reliable Multiple UAV Communications , 2018, IEEE Access.

[36]  张志荣 Zhang Zhirong,et al.  Application of laser absorption spectroscopy for identification gases in industrial production processes and early safety warning , 2018 .

[37]  Xiaogang Wang,et al.  Intelligent multi-camera video surveillance: A review , 2013, Pattern Recognit. Lett..

[38]  Burak Kantarci,et al.  Anchor-Assisted and Vote-Based Trustworthiness Assurance in Smart City Crowdsensing , 2016, IEEE Access.

[39]  Pourang Irani,et al.  Interactive Exploration of Surveillance Video through Action Shot Summarization and Trajectory Visualization , 2013, IEEE Transactions on Visualization and Computer Graphics.