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Silicon retinas, Dynamic Vision Sensors (DVS), capture only changes in scene reflections, i.e., report only the on/off triggering of brightness in the observed scene. The principal operation of silicon retinas achieves 10-fold reduction in power consumption, i.e., 10-20 mW of power requirements for DVS camera, as compared to hundreds of milli-watts power consumption for conventional frame-based vision sensors. The fast expansion of Internet-of-Things (IoTs) networks and the increasing demand for pervasive video have highlighted the need to support visual communication over machine-to-machine (M2M) networks. Achieving this at appropriate quality and in an energy and delay-efficient manner is a major challenge for future IoT deployments. We are presenting a PhD proposal on the new paradigm of dynamic visual sensing and aims to design layered representations and transmission frameworks for DVS data in a manner that is amenable to advanced M2M communications systems.
I am an experience Senior Software Test Developer with full system development life-cycle experience, including designing, developing and implementing test plans, test cases and test processes. I have been creating test automation framework solutions using python within the Telecommunication and networking industry. I spearheaded the QA team for creating automation test framework for performance testing of CEPH clusters for CDN and was able to generate heatmaps automatically based on the objects list for CEPH storage.