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

Abstract

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.

Data Transmission and Processing Analysis of Power Economic Management Terminal Based on the Internet of Things

“…The initial value of the current weight NC of each subserver before the first request is sent is {0,0,0}, and the current weight NC of the selected subserver for the first request is {4,2,2} [20]. It can be known that the selected subserver is 1 for the first time.…”

MPIGA – Multipath Selection Using Improved Genetic Algorithm

“…Where, Empf and Efrs are requisite energies to transmit the data bits through a multipath fading channel in the free space, Eec is the energy that requires for running an electronic circuit of SN; Empf*d 4 or Efrs*d 4 represent the distance between a sender and receiver for identification of multi-path fading or free space model's amplifier energy; d refers to the distance between a sender and receiver; and dthresh refers to the threshold distance, which is given by:…”

“…The clustering method is an efficient strategy for energy consumption of WMNs in data aggregation, where the network categorizes into 'n' number of clusters. The nodes' collaboration and network energy consumption should be simplified based on clustering that restricts the spatial redundant data transmission [4]. Based on a structure of network, protocol operation, and how routing data collect and maintain, the routing protocols can be made into classification in wireless networks.…”