Visual and Auditory Data Fusion for Energy-Efficient and Improved Object Recognition in Wireless Multimedia Sensor Networks

Koyuncu, Murat; Yazıcı, Adnan; Civelek, Muhsin; Çoşar, Ahmet; Sert, Mustafa

doi:10.1109/jsen.2018.2885281

Cited by 36 publications

(14 citation statements)

References 20 publications

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“…In 2019, Murat Koyuncu et al [5], worked on the energy effectuality and object classification and recognition in a precise way for the combination of visual-audio multimedia effects and scalar data gathered using the SN in a WMSN. A wireless multimedia sensor node was examined by means of audio and video processing and capturing abilities and conventional scalar sensors.…”

Section: Literature Surveymentioning

confidence: 99%

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Spiral Optimization Algorithm for Lifetime Enhancement of Wireless Multimedia Sensor Networks

Tambulunde¹

2021

JNACS

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The Wireless Sensor Network (WSN) is considered one of the most significant networks due to the participation of both the WMSNs and traditional WSNs in the last few decades. The WSNs are the network that consists of minimum power, low cost, and its size, is small. In addition, by exploiting the multi-hop, the information shared during the communication is handled and it also presents merely easy sensing data namely humidity, temperature, etc. The WMSNs are considered as distributed sensing networks that consist of the sector sensor area. The WMSNs have the ability to transmit, receive and process the video data information that is highly rigorous and by covering with the wireless transceiver. Regarding the characteristics such as directivity and turn ability, the WSNs and WMSNs are varied. Hence, the main contribution of this work is to extend the lifespan of the network with minimized energy utilization by exploiting highly developed optimization techniques. By optimizing the parameters of the system, the optimal transmission radius is attained in order to transfer the information of the sensor to consequential sensor nodes (SNs) that are presented within range. Hence, this work presents a spiral optimization algorithm (SOA) and then the optimal Cluster Head Selection (CHS) is also presented. At last, the developed technique performance is examined and evaluated with the conventional approaches regarding the convergence rate, network energy, and alive nodes.

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Section: Literature Surveymentioning

confidence: 99%

“…For bulk volume WMSNs there is a rising demand that creates it inconvenient to manually transport and process the data. Hence, the advantages of effectual and lightweight solutions to manage the data traffic on WMSNs turn out as important for the IoT and big data analytics areas [5].…”

Section: Introductionmentioning

confidence: 99%

Spiral Optimization Algorithm for Lifetime Enhancement of Wireless Multimedia Sensor Networks

Tambulunde¹

2021

JNACS

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“…On the other hand, audio data, which has a simpler structure and requires less processing power, can be used to compensate for such visual data loss, while providing better results when audio data is available. Interested readers may refer to [16] and [17] for more detailed information on the architecture of our WMS nodes and the other performance results obtained.…”

Section: Algorithm 2: Second Layer Fusionmentioning

confidence: 99%

“…The initial architecture of the WSN node with only video capability was already presented in [16] and its extension with audio functionality was introduced in [17]. Sert et al introduce the cluster-based routing algorithm of the proposed framework [18].…”

Section: Introductionmentioning

confidence: 99%

A Fusion-Based Framework for Wireless Multimedia Sensor Networks in Surveillance Applications

Yazıcı

Koyuncu

Sert³

et al. 2019

IEEE Access

Self Cite

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Multimedia sensors enable monitoring applications to obtain more accurate and detailed information. However, the development of efficient and lightweight solutions for managing data traffic over wireless multimedia sensor networks (WMSNs) has become vital because of the excessive volume of data produced by multimedia sensors. As part of this motivation, this paper proposes a fusion-based WMSN framework that reduces the amount of data to be transmitted over the network by intra-node processing. This framework explores three main issues: 1) the design of a wireless multimedia sensor (WMS) node to detect objects using machine learning techniques; 2) a method for increasing the accuracy while reducing the amount of information transmitted by the WMS nodes to the base station, and; 3) a new cluster-based routing algorithm for the WMSNs that consumes less power than the currently used algorithms. In this context, a WMS node is designed and implemented using commercially available components. In order to reduce the amount of information to be transmitted to the base station and thereby extend the lifetime of a WMSN, a method for detecting and classifying objects on three different layers has been developed. A new energy-efficient cluster-based routing algorithm is developed to transfer the collected information/data to the sink. The proposed framework and the cluster-based routing algorithm are applied to our WMS nodes and tested experimentally. The results of the experiments clearly demonstrate the feasibility of the proposed WMSN architecture in the real-world surveillance applications.

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“…The availability of multimedia sensor nodes coupled with the novel distributed signal processing [2] and multimedia source coding algorithms [3] have enabled the emergence of wireless multimedia sensor networks (WMSNs) that are capable of capturing, transmitting and receiving multimedia contents [4]. WMSNs support many civilian and military applications such as the detection of plant diseases [5], the detection of the presence of insects [6], wildlife tracking [7], situation awareness [8], security monitoring [9], and automatic threat classification [10]. This inherent ability to be deployed for a wide range of applications has made WMSNs an attractive platform for applications that need pervasive access to multimedia contents.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Multipath Routing Algorithm for Wireless Multimedia Sensor Network

Genta

Lobiyal

Abawajy

2019

Sensors

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Wireless multimedia sensor networks (WMSNs) are capable of collecting multimedia events, such as traffic accidents and wildlife tracking, as well as scalar data. As a result, WMSNs are receiving a great deal of attention both from industry and academic communities. However, multimedia applications tend to generate high volume network traffic, which results in very high energy consumption. As energy is a prime resource in WMSN, an efficient routing algorithm that effectively deals with the dynamic topology of WMSN but also prolongs the lifetime of WMSN is required. To this end, we propose a routing algorithm that combines dynamic cluster formation, cluster head selection, and multipath routing formation for data communication to reduce energy consumption as well as routing overheads. The proposed algorithm uses a genetic algorithm (GA)-based meta-heuristic optimization to dynamically select the best path based on the cost function with the minimum distance and the least energy dissipation. We carried out an extensive performance analysis of the proposed algorithm and compared it with three other routing protocols. The results of the performance analysis showed that the proposed algorithm outperformed the three other routing protocols.

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Visual and Auditory Data Fusion for Energy-Efficient and Improved Object Recognition in Wireless Multimedia Sensor Networks

Cited by 36 publications

References 20 publications

Spiral Optimization Algorithm for Lifetime Enhancement of Wireless Multimedia Sensor Networks

Spiral Optimization Algorithm for Lifetime Enhancement of Wireless Multimedia Sensor Networks

A Fusion-Based Framework for Wireless Multimedia Sensor Networks in Surveillance Applications

Energy Efficient Multipath Routing Algorithm for Wireless Multimedia Sensor Network

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