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Search results for: SENSOR CORRECTION
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Application of Multiplicative Drift Correction and Component Correction methods on simulated gas sensor array responses
PublicationSensor response drift is one of the most challenging problems in gas-analyzing systems. Such systems, commonly called electronic noses, are expected to be reliable and reproducible in the long term. Due to the drift phenomena, electronic noses usability is limited to the relatively short period of time, and frequent recalibrations of device are required. Because it is very hard to fabricate sensors without drift, this phenomenon...
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<title>Correction of fiber optic ion sensor readings using a fiber optic temperature sensor</title>
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On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction
PublicationNitrogen dioxide (NO2) is a prevalent air pollutant, particularly abundant in densely populated urban regions. Given its harmful impact on health and the environment, precise real-time monitoring of NO2 concentration is crucial, particularly for devising and executing risk mitigation strategies. However, achieving precise measurements of NO2 is challenging due to the need for expensive and cumbersome equipment. This has spurred...
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A measurement method for lossy capacitive relative humidity sensors based on a direct sensor-to-microcontroller interface circuit
PublicationA new time-domain measurement method for determining the capacitance and resistance values of lossy relative humidity capacitive sensors is presented. The method is based on a direct sensor-to-microcontroller interface for microcontrollers with internal analog comparators and timers. The interface circuit consists only of four reference resistors (two reference resistors if a microcontroller includes a voltage reference source),...
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A Surrogate-Assisted Measurement Correction Method for Accurate and Low-Cost Monitoring of Particulate Matter Pollutants
PublicationAir pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublicationDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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A Development of a Capacitive Voltage Divider for High Voltage Measurement as Part of a Combined Current and Voltage Sensor
PublicationThis article deals with the development of capacitive voltage divider for high voltage measurements and presents a method of analysis and optimization of its parameters. This divider is a part of a combined voltage and current sensor for measurements in high voltage power networks. The sensor allows continuous monitoring of the network distribution status and performs a quick diagnosis and location of possible network failures....
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High-Performance Machine-Learning-Based Calibration of Low-Cost Nitrogen Dioxide Sensor Using Environmental Parameter Differentials and Global Data Scaling
PublicationAccurate tracking of harmful gas concentrations is essential to swiftly and effectively execute measures that mitigate the risks linked to air pollution, specifically in reducing its impact on living conditions, the environment, and the economy. One such prevalent pollutant in urban settings is nitrogen dioxide (NO2), generated from the combustion of fossil fuels in car engines, commercial manufacturing, and food processing. Its...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Methodology for the Correction of the Spatial Orientation Angles of the Unmanned Aerial Vehicle Using Real Time GNSS, a Shoreline Image and an Electronic Navigational Chart
PublicationUndoubtedly, Low-Altitude Unmanned Aerial Vehicles (UAVs) are becoming more common in marine applications. Equipped with a Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) receiver for highly accurate positioning, they perform camera and Light Detection and Ranging (LiDAR) measurements. Unfortunately, these measurements may still be subject to large errors-mainly due to the inaccuracy of measurement of the optical...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublicationAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Efficient Calibration of Cost-Efficient Particulate Matter Sensors Using Machine Learning and Time-Series Alignment
PublicationAtmospheric particulate matter (PM) poses a significant threat to human health, infiltrating the lungs and brain and leading to severe issues such as heart and lung diseases, cancer, and premature death. The main sources of PM pollution are vehicular and industrial emissions, construction and agricultural activities, and natural phenomena such as wildfires. Research underscores the absence of a safe threshold for particulate exposure,...
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Measurement method for capacitive sensors for microcontrollers based on a phase shifter
PublicationA complete measurement method dedicated to capacitive sensors has been developed. It includes the development of hardware (an analogue interface circuit for microcontrollers with built-in times/counters and analogue comparators) and software (a measurement procedure and a systematic error calibration (correction) algorithm which is based on a calibration dictionary). The interface circuit consists of a low-pass filter and a phase...
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Inverse Modeling and Optimization of CSRR-based Microwave Sensors for Industrial Applications
PublicationDesign optimization of multivariable resonators is a challenging topic in the area of microwave sensors for industrial applications. This paper proposes a novel methodology for rapid re-design and parameter tuning of complementary split-ring resonators (CSRRs). Our approach involves inverse surrogate models established using pre-optimized resonator data as well as analytical correction techniques to enable rapid adjustment of geometry...
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DETERMINING THE TIME CONSTANT USING TWO METHODS AND DEFINING THE THERMOCOUPLE RESPONSE TO SINE EXCITATION OF GAS TEMPERATURE
PublicationThis paper describes the two methods of determining the time constant of type K thermocouple, for two construction solutions: the exposed weld and the mantle fillet weld. This is an important parameter indicating the response time of the thermocouple on the recorded signal. The first method consists of determining the value of τ in the way of numerical simulation of heat exchange between the thermocouple and the current of gas...
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Hazard Control in Industrial Environments: A Knowledge-Vision-Based Approach
PublicationThis paper proposes the integration of image processing techniques (such as image segmentation, feature extraction and selection) and a knowledge representation approach in a framework for the development of an automatic system able to identify, in real time, unsafe activities in industrial environments. In this framework, the visual information (feature extraction) acquired from video-camera images and other context based gathered...
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Sea surface temperature in the Baltic Sea derived from Landsat 8 satellite data - path 194
Open Research DataThe data set contains high resolution sea surface temperature (SST) maps estimated from Landsat 8 Level 1 Thermal Infrared Sensor (TIRS) data using NLSST algorithm. SST was calculated only for granules (185 x 180 km) from satellite path number 194, that covered at least 2000 km2 of the cloud-free area of the Baltic Sea.
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Sea surface temperature in the Baltic Sea derived from Landsat 8 satellite data - path 192
Open Research DataThe data set contains high resolution sea surface temperature (SST) maps estimated from Landsat 8 Level 1 Thermal Infrared Sensor (TIRS) data using NLSST algorithm. SST was calculated only for granules (185 x 180 km) from satellite path number 192, that covered at least 2000 km2 of the cloud-free area of the Baltic Sea.
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Sea surface temperature in the Baltic Sea derived from Landsat 8 satellite data - path 191
Open Research DataThe data set contains high resolution sea surface temperature (SST) maps estimated from Landsat 8 Level 1 Thermal Infrared Sensor (TIRS) data using NLSST algorithm. SST was calculated only for granules (185 x 180 km) from satellite path number 191, that covered at least 2000 km2 of the cloud-free area of the Baltic Sea.
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Sea surface temperature in the Baltic Sea derived from Landsat 8 satellite data - path 193
Open Research DataThe data set contains high resolution sea surface temperature (SST) maps estimated from Landsat 8 Level 1 Thermal Infrared Sensor (TIRS) data using NLSST algorithm. SST was calculated only for granules (185 x 180 km) from satellite path number 193, that covered at least 2000 km2 of the cloud-free area of the Baltic Sea.
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Sea surface temperature in the Baltic Sea derived from Landsat 8 satellite data - path 190
Open Research DataThe data set contains high resolution sea surface temperature (SST) maps estimated from Landsat 8 Level 1 Thermal Infrared Sensor (TIRS) data using NLSST algorithm. SST was calculated only for granules (185 x 180 km) from satellite path number 190, that covered at least 2000 km2 of the cloud-free area of the Baltic Sea.
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Interferometric Sensor of Wavelength Detuning Using a Liquid Crystalline Polymer Waveplate
PublicationOperation of a polarization interferometer for measurement of the wavelength changes of a tunable semiconductor laser was investigated. A lambda/8 waveplate made from liquid crystalline polymer is placed in one of interferometers’ arms in order to generate two output signals in quadrature. Wavelength was measured with resolution of 2 pm in the wavelength range 628–635 nm. Drift of the interferometer, measured in the period of 500...