63 research outputs found

    Body powered thermoelectric systems

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    Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 107-111).Great interest exists for and progress has be made in the effective utilization of the human body as a possible power supply in hopes of powering such applications as sensors and continuously monitoring medical devices [1]. This report furthers into the area of thermal energy harvesting, which focuses on using the temperature differential generated between the human body and the ambient environment to generate power. More specifically, a body-powered, thermoelectric-based power supply and system will be introduced and examined, with hopes that this technology will be utilized alongside low-power, medical monitoring applications in order to achieve self-sufficiency. This report also analyzes the performance of existing thermoelectric-based body-powered energy harvesting applications and compares that with the new design introduced in this work. The new designs were able to output upwards of 25[mu]W/cm2 or, equivalently, 280µW for the entire heat sink system. Additionally, this report details the physics associated with thermoelectric modules, addresses the issues with modern thermoelectric heat-sinks, introduces two new types of wearable, conformal heat sinks, quantifies the performance of the body-powered thermoelectric supply, tests a flexible EKG processing board, and analyzes future paths for this project.by Krishna Tej Settaluri.M.Eng

    Identification of Wheat Varieties with a Parallel-Plate Capacitance Sensor Using Fisher’s Linear Discriminant Analysis

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    Fisher’s linear discriminant (FLD) models for wheat variety classification were developed and validated. The inputs to the FLD models were the capacitance (C), impedance (Z), and phase angle (θ), measured at two frequencies. Classification of wheat varieties was obtained as output of the FLD models. Z and θ of a parallel-plate capacitance system, holding the wheat samples, were measured using an impedance meter, and the C value was computed. The best model developed classified the wheat varieties, with accuracy of 95.4%, over the six wheat varieties tested. This method is simple, rapid, and nondestructive and would be useful for the breeders and the peanut industry
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