Energy-Efficient SRAM FPGA-Based Wireless Vision Sensor Node: SENTIOF-CAM

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dc.contributor.author Muhammad Imran
dc.contributor.author Khurram Shahzad
dc.contributor.author Naeem Ahmad
dc.contributor.author Mattias O’Nils
dc.contributor.author Najeem Lawal
dc.contributor.author Bengt Oelmann
dc.date.accessioned 2017-12-26T11:47:21Z
dc.date.available 2017-12-26T11:47:21Z
dc.date.issued 2014
dc.identifier.uri http://hdl.handle.net/123456789/5190
dc.description.abstract Many wireless vision sensor networks (WVSNs) applications are characterized to have a low duty cycling. An individual wireless vision senor node (VSN) in WVSN is required to complete the tasks as quickly as possible. The execution of the tasks can be speeded up by exploiting the inherited parallelism in the tasks by using a hardware platform such as field-programmable gate array (FPGA). Traditionally, SRAM FPGAs are considered to be inefficient for duty cycled applications. This paper presents a low-complexity, energyefficient, and reconfigurable VSN architecture based on SRAM FPGA using a design matrix, which includes tasks’ partitioning, a low-complexity background subtraction, bilevel coding, and duty cycling. The proposed VSN, referred to as SENTIOF-CAM, has been implemented on a prototype board and energy values of different states are measured for three real applications. The comparison results with existing solutions show that the proposed architecture with SRAM FPGA can achieve energy reduction of up to a factor of 69 as compared with software VSN solutions and approximately similar energy values to that for the FLASH FPGA-based VSN solutions. The lifetime based on measured energy values shows that, for a sample period of 5 min, a 3.2-years lifetime can be achieved with a battery of 37.44-kJ energy. In addition, the proposed solution offers a generic architecture with a smaller design complexity on a hardware reconfigurable platform and offers easy adaptation for a number of applications. en_US
dc.language.iso en en_US
dc.publisher Bahria University Islamabad Campus en_US
dc.subject Department of Computer Engineering CE en_US
dc.title Energy-Efficient SRAM FPGA-Based Wireless Vision Sensor Node: SENTIOF-CAM en_US
dc.type Article en_US


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