Determining the Outdoor Air Ventilation with Carbon Dioxide (CO2) as a Tracer Gas

Insufficient ventilation can lead to occupant complaints of discomfort and reduced productivity as human and building generated pollutants build up. Some combinations of these elevated pollutants may have short or long-term detrimental health effects. Carbon Dioxide (CO2) is very rarely a pollutant of direct health concern itself. Rather a tracer gas, because building occupants exhale CO2 and is used as a tracer gas that is an excellent indicator of adequate (or inadequate) ventilation. Keeping in view this fact we measured CO2 as a marker, or tracer gas, to determine the outdoor air ventilation (dilution air) rate in an occupied space. Low CO2 concentration, when measured during periods of average and higher occupancy, implies that human generated pollutants are being properly diluted. And in the absence of a specific pollutant source, it is a rough estimator that the thousands of potential building generated pollutants are being dispersed. This makes it a key indoor air quality indicator.qscienc

Calibration & Temperature Controlled Setup for Air Quality Sensors

Indoor air pollution is a major issue affecting public health. Due to hot climate, humidity and lack of natural green spaces, life is mostly confined indoors in many countries of the MENA region. Vulnerable population, including young children and senior citizens who spend most of their time indoors, are at risk because of the effects of indoor air quality (IAQ) on their health. An indoor air quality monitoring system is a need of the hour to detect and improve Indoor Air Quality (IAQ). The monitoring systems presently available are bulky, expensive and need periodic calibration to maintain high degree of accuracy. Frequent recalibration of a number of densely deployed individual sensors in the network is a time-consuming and laborious task therefore self-calibration is indispensable. Gas sensors, even if factory-calibrated, tend to drift with time/usage. Therefore these should be regularly calibrated under controlled environments. Calibration may be carried out using test gas mixtures with known composition. Pre-mixed gas cylinders with known composition may be used for the purpose; however this solution is not flexible as the number of calibration points and testing conditions (e.g. effect of temperature and humidity on CO2 sensor) are limited. In the current project, a computer-controlled test and calibration test bed system is being designed and assembled along with temperature controller. Calibration set-up would help in self calibration of the air quality sensors. Calibration curves obtained from proposed calibration test bed are updated automatically and fed into the sensor node through wireless communication without going in the field or replacing the sensor. A computer-controlled test and calibration test bed system is designed and assembled containing the sensor(s) under test and in which gas composition; temperature can be precisely and dynamically controlled. ATMEGA328 micro controller is used to receive the temperature set point from the computer running the test rig.qscienc

Continuous-Time ΣΔ ADC with Implicit Variable Gain Amplifier for CMOS Image Sensor

This paper presents a column-parallel continuous-time sigma delta (CTSD) ADC for mega-pixel resolution CMOS image sensor (CIS). The sigma delta modulator is implemented with a 2nd order resistor/capacitor-based loop filter. The first integrator uses a conventional operational transconductance amplifier (OTA), for the concern of a high power noise rejection. The second integrator is realized with a single-ended inverter-based amplifier, instead of a standard OTA. As a result, the power consumption is reduced, without sacrificing the noise performance. Moreover, the variable gain amplifier in the traditional column-parallel read-out circuit is merged into the front-end of the CTSD modulator. By programming the input resistance, the amplitude range of the input current can be tuned with 8 scales, which is equivalent to a traditional 2-bit preamplification function without consuming extra power and chip area. The test chip prototype is fabricated using 0.18 m CMOS process and the measurement result shows an ADC power consumption lower than 63.5 W under 1.4 V power supply and 50 MHz clock frequency

Continuous-Time Sigma Delta ADC with Implicit Variable Gain Amplifier for CMOS Image Sensor

This paper presents a column-parallel continuous-time sigma delta (CTSD) ADC for mega-pixel resolution CMOS image sensor (CIS). The sigma delta modulator is implemented with a 2nd order resistor/capacitor-based loop filter. The first integrator uses a conventional operational transconductance amplifier (OTA), for the concern of a high power noise rejection. The second integrator is realized with a single-ended inverter-based amplifier, instead of a standard OTA. As a result, the power consumption is reduced, without sacrificing the noise performance. Moreover, the variable gain amplifier in the traditional column-parallel read-out circuit is merged into the front-end of the CTSD modulator. By programming the input resistance, the amplitude range of the input current can be tuned with 8 scales, which is equivalent to a traditional 2-bit preamplification function without consuming extra power and chip area. The test chip prototype is fabricated using 0.18 mu m CMOS process and the measurement result shows an ADC power consumption lower than 63.5 mu W under 1.4 V power supply and 50 MHz clock frequency

Two-Step Single Slope/SAR ADC with Error Correction for CMOS Image Sensor

Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR) ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 mu m CMOS technology. The chip area of the proposed ADC is 7 mu m x 500 mu m. The measurement results show that the energy efficiency figure-of-merit (FOM) of the proposed ADC core is only 125 pJ/sample under 1.4V power supply and the chip area efficiency is 84 k mu m(2).cycles/sample

Impact of feature reduction and operating temperature on gas identification

Tin-oxide based gas sensor requires an operating temperature typically in the range of 200 °C to 400 °C and its performance dependents on this temperature. In this paper a deep examination has been made to analyze the best operating temperature suitable for gas identification application in which an array of sensors is used along with an appropriate feature reduction algorithm. The two most common feature reduction algorithms for gas classification are principal component analysis (PCA) and linear discriminant analysis (LDA); both of them have been used in this analytical work. The feature reduction is followed by a binary decision tree (BDT) or K-nearest neighbor (KNN) based classifier. Results obtained with data from an array of sensors used for detecting C6H6, CH2O, CO, NO2 and SO2 indicates that at 400 °C the BDT can classify 100% of gases after LDA based feature reduction, whereas KNN can classify 100% of gases at 200 °C and 300 °C using data before and after feature reduction. Furthermore, experimental results from the given sensor data suggest that with and without considering the operating temperature the BDT can classify 96% of gases using first four LDA components. While KNN can classify 98% to 99% of gases using first four LDA or first five PCA components of resulting data obtained after feature reduction. Thus, after LDA-based feature reduction both classifiers provide superior identification with minimum number of components. 2006-2015 Asian Research Publishing Network (ARPN).Scopu