Barrier coverage in Wireless Visual Sensor Networks with importance of image consideration

Cheng, Chien-Fu; Tsai, Kuo-Tang

doi:10.1109/icufn.2015.7182651

Cited by 5 publications

(3 citation statements)

References 11 publications

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“…The coverage is one of the most significant criteria according to the state of art [14]. Three kinds of coverage are considered [15]: zone coverage which consist of maximizing the coverage of an entire zone [16], region or target coverage where the goal is to maximize the coverage of the different targets in the study zone [17], and barrier coverage which deals with barrier intrusion detection [18].…”

Section: Related Workmentioning

confidence: 99%

An Efficient Placement Approach of Visual Sensors Under Observation Redundancy and Communication Connectivity Constraints

FAGA,

TOSSA,

ABDOU

et al. 2024

Preprint

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Visual Sensor Networks (VSNs) have been the focus of numerous studies, emphasizing the quality of the information they generate. The primary goal of these networks is to capture data from an area, extract the pertinent information from the visual scene, and facilitate communication. However, the presence of objects in the study area can impacted the network's efficiency, linking the quality of acquired data directly to the positioning of the cameras. Strategically positioning multiple cameras in a potentially complex area, while ensuring effective communication between nodes, presents a challenging issue in VSNs applications. This paper introduces a specific method to enhance the deployment of visual sensors in indoor environments. The research addresses the theme of multi-objective optimization of VSN deployment, integrating various criteria: maximizing overall visual coverage, maximizing the observation of zones of interest, maximizing observation redundancy of zones of interest and ensuring communication connectivity for data transfers. To tackle this problem, we simulate the observed environment incorporating cameras, obstacles, and considering zones of interest. Camera positioning is performed while considering visual constraints and the scene's characteristics. The quality of positioning is evaluated based on the defined objective functions. Initially, a comparative study is conducted with a state-of-the-art approach, integrating the first three objective functions. Subsequently, we incorporate the fourth objective function to ensure data transfers. The proposed method demonstrates efficient camera network deployments in indoor areas, considering global coverage and observation redundancy. In contrast to the state-of-the-art, these results are achieved in areas with visual obstacles while ensuring communication connectivity between the different cameras.

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Section: Related Workmentioning

confidence: 99%

An Efficient Placement Approach of Visual Sensors Under Observation Redundancy and Communication Connectivity Constraints

FAGA,

TOSSA,

ABDOU

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…A few sensor deployment approaches consider both QoM and facing direction of objects [68,[80][81][82][83][84][85]. Tao et al in [80] proposed an algorithm to solve the problem that considers the priorities of sensing quality and sensing area.…”

Section: Continuous Directional Modelmentioning

confidence: 99%

“…Li et al in [82] first combined previous kcoverage QoM and full-view coverage, then proposed a k-full-view coverage algorithm to address the problem of covering fixed number of objects with a minimum number of camera sensors for a special case. Cheng et al in [83] first quantified the coverage QoM as breadth of barrier-coverage and proposed an algorithm to deploy sensors covering a belt-barrier achieving β breadth, then in [84] they introduced the facing direction of objects in coverage model.…”

Section: Continuous Directional Modelmentioning

confidence: 99%

MoniSys: Sensing, Communication, and Video Analysis in UAV Monitoring System

Wang

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Over the past 20 years, visual data has taken over every aspect of our lives, and camera deployment has experienced an unprecedented increase. For example, in the USA and UK, there is one camera for every 8 people used for diverse applications, like surveillance and public safety. However, in many extreme conditions, pre-deploying cameras are not feasible. Fortunately, the development of UAVs let these agile, flexible, and powerful devices make up the limitation of pre-deployed cameras. While high-resolution visual data offers rich information about the sensing environment, it causes significant challenges to the data analysis. Advances in computer vision present an excellent opportunity to process and analyze this massive amount of data; however, they have come at the expense of compute and network costs. For analysis, computing-resource-limited UAVs need to transmit sensing data to a computingresource-rich server (on the ground). This distributed architecture posits several network-level resource management challenges: to ensure optimal UAV trajectories for sensing visual data; and to address the mobility impact and fair data delivery in multi-UAV access networks; and to provide low-latency, high-accuracy, and lowbandwidth-cost analysis.We begin by presenting a general algorithm design schema for the waypoint planning problem to generate waypoints (i.e., UAVs hovering and sensing points) achieving quality bounded sensing data. This schema includes three steps: discretization divides the entire solution space into subspaces; then dominating set extraction find out all the optimal solutions in every subspace; at last, transform waypoint planning into submodular optimization problem and propose an approximate algorithm. We apply this schema to three scenarios and verify the performance of our method provides 1.6× gain in sensing data quality.Next, in order to address communication challenges, specifically the mobility impact and fairness among multiple UAV-server streamings, we develop VSiM -an easy-deployment and high-compatibility end-to-end solution to fairness in multiple mobile video streaming applications with a shared bottleneck bandwidth. It is pluggable to the server directly without caring and modifying any existing protocols or components. VSiM consists of three key techniques: dynamic and fair bandwidth allocation by incorporating mobile profile and QoE-related information; quick buffer filling for clients with lower playback time according to the requirement of the buffersensitive clients; adaptiveness to heterogeneous wireless network environments, like varied mobility patterns and topologies of base stations (BSes). It improves more iv than 40% on min QoE, which equals resolution improvement of viewing quality from 720p to 1080p) compared to state-of-the-art solutions.Finally, in order to achieve low-latency, high-accuracy, and low-bandwidth-cost analysis, we present AccDecoder -a new decoder that derives important video content from bits stream and enhances them by super-resolution (SR) model. SR m...

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