Efficient and Accurate Object Classification in Wireless Multimedia Sensor Networks

Oztarak, Hakan; Yılmaz, Tuğba; Akkaya, Kemal; Yazıcı, Adnan

doi:10.1109/icccn.2012.6289244

Cited by 6 publications

(3 citation statements)

References 19 publications

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“…Depending on technological developments, it has become possible to develop sensor nodes with higher processing capabilities in recent years. Dependently, there are studies performing object classification at the sensor node and sending only information about the detected objects in text format and, thus, reducing drastically the size of data to be transmitted [27], [28]. While there are studies on video data processing at sensor nodes to minimize the size of the data to be transmitted, as explained above, additional research is needed to find energy efficient solutions for WMSNs.…”

Section: Related Workmentioning

confidence: 99%

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

Yazıcı

Koyuncu

Sert³

et al. 2019

IEEE Access

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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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Section: Related Workmentioning

confidence: 99%

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

Yazıcı

Koyuncu

Sert³

et al. 2019

IEEE Access

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“…According to the obtained experimental results, authors achieved promising accuracy without introducing a major energy consumption. Efficient and accurate object classification from video frames in WMSNs has been studied in [39]. Here authors describe the efficiency of the method considering the extracted effective features and accuracy by using a genetic algorithm whose memory requirements is minimal.…”

Section: Selected Sample Studies Concerning Sensor Typesmentioning

confidence: 99%

“…Then, two features from video frames, namely Shape-Ratio and Speed, are extracted by using MBR (Minimum Bounding Rectangle) of the detected object. Because our problem definition and our goals here are the same, in this second level classification, we follow the approach depicted in [39]. This approach is also suitable for our purpose since we manually deploy the network and know the coordinates of camera sensors for speed calculation.…”

Section: Hierarchical Data Fusionmentioning

confidence: 99%

An efficient fuzzy fusion-based framework for surveillance applications in Wireless Multimedia Sensor Networks

Sert

Yazıcı

Çoşar

et al. 2014

2014 International Wireless Communications and Mobile Computing Conference (IWCMC)

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, 86 pages Previous advances in Information Technologies and especially in Micro Electro-Mechanical Systems, have made the production and deployment of tiny, battery-powered nodes communicating over wireless links possible. Networks comprised of such nodes with sensing capability are called Wireless Sensor Networks. The early deployment aim was to use these nodes only in a passive way for indoor applications. These kinds of early nodes had the ability to sense scalar data such as temperature, humidity, pressure and location of surrounding objects. However, recently available sensor nodes have higher computation capability, higher storage space and better power solutions with respect to their predecessors. With these developments in addition to scalar data delivery, multimedia content has become the core focus. A wireless sensor network with multimedia capabilities is called Wireless Multimedia Sensor Network. There has always been a trade-off between accuracy and energy-efficiency in these new generation networks because of their resource-constrained nature. In this thesis we introduce a new approach to address this trade-off in Wireless Multimedia Sensor Networks. Although a number of previous studies have focused on various special topics in Wireless Multimedia Sensor Networks in detail, to the best of our knowledge, none presents a fuzzy multi-modal data fusion system, which is lightweight and provides a high accuracy ratio. Especially, a multi-modal data fuv sion system targeting surveillance applications make it inevitable to work within a multi-level hierarchical framework. In this thesis, our primary focus is on accuracy and efficiency by utilizing our framework. Along with the fuzzy fusion framework, a new fuzzy clustering algorithm, namely Multi-Objective Fuzzy Clustering Algorithm (MOFCA), is introduced and evaluated in detail as well.

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Improving resource-constrained IoT device lifetimes by mitigating redundant transmissions across heterogeneous wireless multimedia of things

din¹,

Rehman²,

Ullah³

et al. 2022

Digital Communications and Networks

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Efficient and Accurate Object Classification in Wireless Multimedia Sensor Networks

Cited by 6 publications

References 19 publications

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

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

An efficient fuzzy fusion-based framework for surveillance applications in Wireless Multimedia Sensor Networks

Improving resource-constrained IoT device lifetimes by mitigating redundant transmissions across heterogeneous wireless multimedia of things

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