Determination of Sugar Level and the Existence of Magic Sugar in Various Beverages using a Glucose Meter with Four-Point Probe and Electrochemical Impedance

Nowadays, people are being inconsiderate about the healthy lifestyle that might lead us to be unhealthy and be prone to developing tumors in the kidney due to some kind of sugar being used. In order to minimize these problems, the team will raise people awareness. Raising people awareness is not the same as telling them what to do. It is about giving them the knowledge to let them decide for themselves. This is why the team developed a device that can measure the sugar level and determine the existence of magic sugar in various beverages. The device is composed of two major parts: first is the circuit that will measure the impedance of a liquid sample and second, is a four-point probe, which includes a microcontroller that will display and interpret the results. The Four-point probe applies the concept of Wenner method and Electrochemical Impedance. After constructing the device, the team performed its calibration that requires different liquid samples. Based on its gathered data, different graphical representations were formulated and translated into mathematical equations in order to integrate it onto the microcontroller. Whenever the microcontroller encounters an unknown solution, it can determine the sugar level and classify the type of sugar being used

Full Custom Rail-to-Rail Self-Calibrating Comparator for Low Voltage Successive Approximation Register Analog-to-Digital Converter

The demand for low power consuming devices is increasing, particularly that of wireless sensor networks (WSN). This study aims to address this problem by designing a novel rail-to-rail comparator for SAR ADC integrated with selfcalibration to null offset. In this study, rail-to-rail comparator, self-calibrating comparator, and rail-to-rail self-calibrating comparator are the circuits that will be designed, compared and analyzed. The three circuit designs were realized using the 0.18um CMOS technologyand has undergonePVT variations. The designed comparators all operate with a 1.8 V supply. In comparing and determining which circuit is the best in terms of their response, all the circuits will be compared based on six parameters to be measured thru the use of Simulation Program with Integrated Circuit Emphasis, also known as SPICE. The rail-to-rail comparator design resulted in an ICMR of 700mV. The self-calibratingcomparator design has a prominent value of 78dB for its CMRR. On the other hand, the novel rail-to-rail self-calibrating comparator design has highlighted a 5.15 V/us slew rate, with a power dissipation of only 22.40uW. A layout of the novel rail-to-rail self-calibrating comparator was also implemented which has a power dissipation 25.60uW and a slew rate of 4.16 V/us. It was found that the proposed design’s key features are stable performance over wide temperature ranges from 0°C up to 49°C, high value of slew rate and low power consumption without compromising its function

WIRELESS FLOOD MONITORING USING INTEGRATED HYDROLOGICAL SENSORS AND FLOOD PREDICTION VIAARTIFICIAL NEURAL NETWORK

Flooding is a natural phenomenon that is very difficult to model into an equation because of its nonlinear characteristics. As a result, early warning flood prediction systems are seldom developed and often rely on meteorological satellites and hydrological maps. However, in the advent of technology, randomness and nonlinearity can now be modelled using artificial neural network. The goal of this study is to develop a wireless flood monitoring and prediction system using artificial neural network, specifically the Nonlinear Autoregressive Network with External Inputs (NARX) neural network that can be used in a small community as flood early warning system. The flood monitoring system was developed by integration of different hydrological sensors such as rain gauge, float sensor, flow meter, soil resistivity meter, air humidity and temperature sensors. The wireless communication was achieved by the use of Zigbee modules. Training of ANN was done via the backpropagation algorithm and an MSE of 0.0032 was achieved using seven epochs having the fourth epoch having the best validation. During the field testing, an average prediction rate accuracy of 98.65% was achieved. A two-sample t-test was done to see if the actual field test is different from the predicted values and the result was there is no significant difference between the two that validates the accuracy of the predictio

PARAMETER EXTRACTION OF OPTOELECTRONIC pH SENSOR BASED ON THE HUE ABSORBANCE OFA pH TEST STRIP

Optical pH measurement commonly uses a strip of paper with embedded indicator. A pH test strip which has four (4) test pads changes its color when it is dipped in a sample solution. A Bogen universal indicator solution is used in one of the study to cause a color change in a sample depending on the pH of the sample. It is combined with a white light source and CMOS optical sensor chip to measure pH with color change as an input. The output voltage of the CMOS photodetector will give the equivalent pH value. This sensor can determine the pH of the sample from pH 1 to 9 in real-time. Aside from using Bogen universal indicator, paper-based indicator like test strip has also been introduced that shows color change when it is dipped in the solution. To determine the pH value of the sample, the color change of the test strip is compared to a color chart. A schematic diagram of the absorption-measuring optical module is developed. This is composed of tri-chromatic LED, photodiodes and polymer light guide. This device is able to detect the color change by measuring the optical absorbance of the urine test strip. The color change is analyzed to determine the amount of glucose, protein and red blood cells. The purpose of this study is to extract the parameter of an optoelectronic pH sensor based on the hue absorbance of the pH test strip and be implemented on Simulation Program with Integrated Circuit Emphasis (SPICE). Through experiments using a devised sensor module, highest linearity is obtained when the ILED is 20 mA. The sensitivity of the device at pad I is 0.4217 mV/pH with a correlation coefficient of 0.8177, pad 2 is 0.3667 V/pH with a correlation coefficient of 0.9597, pad 3 is 0.2659 V/pH with a correlation coefficient of 0.0.9923, and pad 4 is 0.0347 V/pH with a correlation coefficient of 0.9948. It outputs the RGB Hue levels (in voltage) of the pH test strip. Optoelectric characteristics of the pH sensor are described by the result acquired in the experiments on parameter extraction. The transconductance of the device is derived based on the phototransistor current and pH-dependent voltage. The extracted parameters used on the equivalent circuit of the optoelectronic pH sensor are simulated on SPICE. The percent error between the responses on experimental and simulation of the test pads 1, 2, 3 and 4 are 10.28%, 0.01%, 0.34% and 0.86% respectively. Based on these results, an optoelectronic pH sensor model is developed