Energy-aware strategy for collaborative target-detection in wireless multimedia sensor network

Zam, Abdulaziz; Khayyambashi, Mohammad Reza; Bohlooli, Ali

doi:10.1007/s11042-019-7204-5

Cited by 15 publications

(5 citation statements)

References 37 publications

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“…e technological development characterized by multimedia applications can be said to be another innovation in electronic computers. In the field of computer science, media has two meanings, the quality of the media and the role of the media [20]. e former is a physical object that can store information, and the U disk we often use is a kind of coal.…”

Section: Multimedia and Visual Communicationmentioning

confidence: 99%

The Texture and Color Matching of Oil Painting Materials Based on Multimedia Visual Communication

Wang

Sun

2022

Advances in Materials Science and Engineering

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The obvious tendency of modern artists to change the concept of painting is to pay more and more attention to personal feelings and spiritual expression. In modern oil paintings, there are more and more oil paintings that convey emotions and the emotional expression methods of the colors of the works are becoming more and more abundant. This article aims to study the application of multimedia visual communication in the texture and color matching of oil painting creation materials and to put forward the viewpoint of applying more multimedia visual communication to oil painting creation. This article first gives a detailed introduction to oil painting creation materials and their texture, oil painting color matching, and so on. In addition, experiments were conducted on the application of multimedia visual communication in the texture and color matching of oil painting creation materials. The experimental results show that the texture and color matching of oil painting creation materials based on multimedia visual communication are more popular with the public, and oil painters are also satisfied with this method. And, the expressiveness of oil painting texture has been improved by 10%. This shows that the texture and color matching scheme of the oil painting material in this study is effective.

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Section: Multimedia and Visual Communicationmentioning

confidence: 99%

The Texture and Color Matching of Oil Painting Materials Based on Multimedia Visual Communication

Wang

Sun

2022

Advances in Materials Science and Engineering

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“…The work presented in [29] introduces an energy-aware collaborative tracking and moving detection scheme for WMSNs. The proposed method relies on collaboration among sensors to extract a lightweight image from a multiply captured scene to reduce computation and communication costs.…”

Section: Distributed Processing Approachmentioning

confidence: 99%

A Study on Energy Efficiency of a Distributed Processing Scheme for Image-Based Target Recognition for Internet of Multimedia Things

2023

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A growing number of services and applications are developed using multimedia sensing low-cost wireless devices, thus creating the Internet of Multimedia Things (IoMT). Nevertheless, energy efficiency and resource availability are two of the most challenging issues to overcome when developing image-based sensing applications. In depth, image-based sensing and transmission in IoMT significantly drain the sensor energy and overwhelm the network with redundant data. Event-based sensing schemes can be used to provide efficient data transmission and an extended network lifetime. This paper proposes a novel approach for distributed event-based sensing achieved by a cluster of processing nodes. The proposed scheme aims to balance the processing load across the nodes in the cluster. This study demonstrates the adequacy of distributed processing to extend the lifetime of the IoMT platform and compares the efficiency of Haar wavelet decomposition and general Fourier descriptors (GFDs) as a feature extraction module in a distributed features-based target recognition system. The results show that the distributed processing of the scheme based on the Haar wavelet transform of the image outperforms the scheme based on a general Fourier shape descriptor in recognition accuracy of the target as well as the energy consumption. In contrast to a GFD-based scheme, the recognition accuracy of a Haar-based scheme was increased by 26%, and the number of sensing cycles was increased from 40 to 70 cycles, which attests to the adequacy of the proposed distributed Haar-based processing scheme for deployment in IoMT devices.

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“…Other significant issues related to WVSN-based surveillance include scattered background viewpoint variation and changes in lighting. The task of camera prioritisation in large-scale WVSNs also becomes more challenging when large numbers of nodes and continuous streaming are used [37]. Researchers around the world are making efforts to tackle these challenges.…”

Section: Deep Learning-based Approachesmentioning

confidence: 99%

“…The authors of [20][21][22][23][24][25][26][27][28] proposed 3DCNN models for violent activity that performed rather well, but due to the large number of computations involved, these were not suitable for deployment in real-world surveillance systems. Similarly, the authors of [36,37] developed a surveillance system that prioritised video camera content. A surveillance system usually consists of resource-constrained devices such as CCTV cameras, and there is therefore an urgent need for a system that can accurately recognise violent activity in a complex environment with lower computational requirements.…”

Section: Deep Learning-based Approachesmentioning

confidence: 99%

Anomaly Based Camera Prioritization in Large Scale Surveillance Networks

Hussain¹,

Muhammad²,

Ullah³

et al. 2022

Computers, Materials &Amp; Continua

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Digital surveillance systems are ubiquitous and continuously generate massive amounts of data, and manual monitoring is required in order to recognise human activities in public areas. Intelligent surveillance systems that can automatically identify normal and abnormal activities are highly desirable, as these would allow for efficient monitoring by selecting only those camera feeds in which abnormal activities are occurring. This paper proposes an energy-efficient camera prioritisation framework that intelligently adjusts the priority of cameras in a vast surveillance network using feedback from the activity recognition system. The proposed system addresses the limitations of existing manual monitoring surveillance systems using a three-step framework. In the first step, the salient frames are selected from the online video stream using a frame differencing method. A lightweight 3D convolutional neural network (3DCNN) architecture is applied to extract spatio-temporal features from the salient frames in the second step. Finally, the probabilities predicted by the 3DCNN network and the metadata of the cameras are processed using a linear threshold gate sigmoid mechanism to control the priority of the camera. The proposed system performs well compared to state-of-theart violent activity recognition methods in terms of efficient camera prioritisation in large-scale surveillance networks. Comprehensive experiments and an evaluation of activity recognition and camera prioritisation showed that our approach achieved an accuracy of 98% with an F1-score of 0.97 on the Hockey Fight dataset, and an accuracy of 99% with an F1-score of 0.98 on the Violent Crowd dataset.

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Energy-aware strategy for collaborative target-detection in wireless multimedia sensor network

Cited by 15 publications

References 37 publications

The Texture and Color Matching of Oil Painting Materials Based on Multimedia Visual Communication

The Texture and Color Matching of Oil Painting Materials Based on Multimedia Visual Communication

A Study on Energy Efficiency of a Distributed Processing Scheme for Image-Based Target Recognition for Internet of Multimedia Things

Anomaly Based Camera Prioritization in Large Scale Surveillance Networks

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