Total Pageviews

Design and implementation of reconfigurable virtual instruments using Raspberry Pi core

Abstract:
Virtual Instrument is a combination of hardware and software that allows the emulation of an instrument through a custom virtual console and a graphical user interface. A virtual instrument consists of a PC equipped with powerful application software, cost-effective hardware such as plug-in boards, which together perform the functions of traditional instruments. In a virtual instrument, it is the software which performs the actual process of measurement. Using virtual instruments one can design a customized instrument and automation setup that is user-defined instead of being limited by traditional fixed-function vendor-defined instruments. Virtual instruments are not efficient systems to handle time critical instrument tasks since they are run by a PC operating system which introduced substantial timing errors into the measurement. The Reconfigurable Virtual Instrument (RVI) system can be considered as a general purpose measurement instrument designed with reconfigurable hardware like FPGA connected to PC through a standard port. By designing a high level software application, one can select any specific instrument functionality from a library of instruments. The high level software application configures the RVI system to convert it into the selected instrument(s) with its associated console. By this technique, one can emulate multiple instrument functionalities like function generator, oscilloscope, multimeter, logic analyzer in a single hardware platform. In this paper, hardware realization of RVI is done using FPGA and Raspberry Pi core.

Real-time emotion recognition from facial images using Raspberry Pi II

Abstract:
In present day technology human-machine interaction is growing in demand and machine needs to understand human gestures and emotions. If a machine can identify human emotions, it can understand human behavior better, thus improving the task efficiency. Emotions can understand by text, vocal, verbal and facial expressions. Facial expressions play big role in judging emotions of a person. It is found that limited work is done in field of real time emotion recognition using facial images. In this paper, we propose a method for real time emotion recognition from facial image. In the proposed method we use three steps face detection using Haar cascade, features extraction using Active shape Model(ASM), (26 facial points extracted) and Adaboost classifier for classification of five emotions anger, disgust, happiness, neutral and surprise. The novelty of our proposed method lies in the implementation of emotion recognition at real time on Raspberry Pi II and an average accuracy of 94% is achieved at real time. The Raspberry Pi II when mounted on a mobile robot can recognize emotions dynamically in real time under social/service environments where emotion recognition plays a major role.

Road sign recognition system on Raspberry Pi

Real-time nonintrusive monitoring and detection of eye blinking in view of accident prevention