Low power scheme for image based object identification in wireless multimedia sensor networks

Alhilal, Mohsin S.; Soudani, Adel; Al-Dhelaan, Abdullah

doi:10.1109/icmcs.2014.6911274

Cited by 9 publications

(11 citation statements)

References 16 publications

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“…This technique can reduce image data redundancies and lower the network traffic data while preserving adequate image quality. 26–28 A way to accomplish this method is to use an ROI descriptor at the sensor node to detect whether the image captures an even interest and sends the minimum required data to the end-user. This approach reduces the data transmitted to the sink node; consequently, it preserves the energy of the source sensor and the energy of the other nodes of the network.…”

Section: Related Workmentioning

confidence: 99%

A distributed scheme for energy-efficient event-based target recognition using Internet of Multimedia Things

Al-Sabhan

Soudani

AlMusallam

2022

International Journal of Distributed Sensor Networks

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The availability of low-cost embedded devices for multimedia sensing has encouraged their integration with low-power wireless sensors to create systems that enable advanced services and applications referred to as the Internet of Multimedia Things. Image-based sensing applications are challenged by energy efficiency and resource availability. Mainly, image sensing and transmission in Internet of Multimedia Things severely deplete the sensor energy and overflow the network bandwidth with redundant data. Some solutions presented in the literature, such as image compression, do not efficiently solve this problem because of the algorithms’ computational complexities. Thus, detecting the event of interest locally before the communication using shape-based descriptors would avoid useless data transmission and would extend the network lifetime. In this article, we propose a new approach of distributed event-based sensing scheme over a set of nodes forming a processing cluster to balance the processing load. This approach is intended to reduce per-node energy consumption in one sensing cycle. The conducted experiments show that our novel method based on the general Fourier descriptor decreases the energy consumption in the camera node to only 2.4 mJ, which corresponds to 75.32% of energy-saving compared to the centralized approach, promising to prolong the network lifetime significantly. In addition, the scheme achieved more than 95% accuracy in target recognition.

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Section: Related Workmentioning

confidence: 99%

A distributed scheme for energy-efficient event-based target recognition using Internet of Multimedia Things

Al-Sabhan

Soudani

AlMusallam

2022

International Journal of Distributed Sensor Networks

Self Cite

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“…This way, the authors managed to reduce the average rate of false positives in the context of detection in traffic scenes. In the work presented by Alhilal et al [26], a low complexity vision system was designed for the identification of objects in WVSN. The proposed architecture is characterized by low power processing, thus achieving the energy efficiency of the node.…”

Section: Related Workmentioning

confidence: 99%

Impact of Input Data on Intelligence Partitioning Decisions for IoT Smart Camera Nodes

et al. 2021

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Image processing systems exploit image information for a purpose determined by the application at hand. The implementation of image processing systems in an Internet of Things (IoT) context is a challenge due to the amount of data in an image processing system, which affects the three main node constraints: memory, latency and energy. One method to address these challenges is the partitioning of tasks between the IoT node and a server. In this work, we present an in-depth analysis of how the input image size and its content within the conventional image processing systems affect the decision on where tasks should be implemented, with respect to node energy and latency. We focus on explaining how the characteristics of the image are transferred through the system until finally influencing partition decisions. Our results show that the image size affects significantly the efficiency of the node offloading configurations. This is mainly due to the dominant cost of communication over processing as the image size increases. Furthermore, we observed that image content has limited effects in the node offloading analysis.

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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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Low power scheme for image based object identification in wireless multimedia sensor networks

Cited by 9 publications

References 16 publications

A distributed scheme for energy-efficient event-based target recognition using Internet of Multimedia Things

A distributed scheme for energy-efficient event-based target recognition using Internet of Multimedia Things

Impact of Input Data on Intelligence Partitioning Decisions for IoT Smart Camera Nodes

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

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