Energy Efficient SRAM FPGA based Wireless Vision Sensor Node: SENTIOF‐CAM
2014 (English)In: IEEE transactions on circuits and systems for video technology (Print), ISSN 1051-8215, Vol. 24, no 12, 2132-2143 p.Article in journal (Refereed) Published
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 operate with limited resources i.e., processing, memory and wireless bandwidth on available limited energy. For such resource constrained VSN, this paper presents a low complexity, energy efficient and programmable VSN architecture based on a design matrix which includes partitioning of processing load between the node and a server, a low complexity background subtraction, bi-level video coding and duty cycling. The tasks partitioning and proposed background subtraction reduces the processing energy and design complexity for hardware implemented VSN. The bi-level video coding reduces the communication energy whereas the duty cycling conserves energy for lifetime maximization. The proposed VSN, referred to as SENTIOF-CAM, has been implemented on a customized single board, which includes SRAM FPGA, microcontroller, radio transceiver and a FLASH memory. The energy values are measured for different states and results are compared with existing solutions. The comparison shows that the proposed solution can offer up to 69 times energy reduction. The lifetime based on measured energy values shows that for a sample period of 5 minutes, a 3.2 years lifetime can be achieved with a battery of 37.44 kJ energy. In addition to this, the proposed solution offers generic architecture with smaller design complexity on a hardware reconfigurable platform and offers easy adaptation for a number of applications.
Place, publisher, year, edition, pages
2014. Vol. 24, no 12, 2132-2143 p.
Architecture, image coding, SRAM field-programmable gate array (FPGA), wireless vision sensor networks (WVSNs), wireless vision sensor node (VSN
Engineering and Technology
IdentifiersURN: urn:nbn:se:miun:diva-21103DOI: 10.1109/TCSVT.2014.2330660ISI: 000346150200010ScopusID: 2-s2.0-84916934186OAI: oai:DiVA.org:miun-21103DiVA: diva2:689621