scholarly journals Assessing the Performance of a Low-Cost Thermal Camera in Proximal and Aerial Conditions

2020 ◽  
Vol 12 (21) ◽  
pp. 3591
Author(s):  
Matheus Gabriel Acorsi ◽  
Leandro Maria Gimenez ◽  
Maurício Martello
Keyword(s):  
Thermal Imaging ◽  
Low Cost ◽  
Temperature Measurements ◽  
Aerial Images ◽  
Thermal Camera ◽  
Calibration Models ◽  
Accurate Temperature ◽  
Thermal Cameras ◽  
Accuracy Indices ◽  
Better Than

The development of low-cost miniaturized thermal cameras has expanded the use of remotely sensed surface temperature and promoted advances in applications involving proximal and aerial data acquisition. However, deriving accurate temperature readings from these cameras is often challenging due to the sensitivity of the sensor, which changes according to the internal temperature. Moreover, the photogrammetry processing required to produce orthomosaics from aerial images can also be problematic and introduce errors to the temperature readings. In this study, we assessed the performance of the FLIR Lepton 3.5 camera in both proximal and aerial conditions based on precision and accuracy indices derived from reference temperature measurements. The aerial analysis was conducted using three flight altitudes replicated along the day, exploring the effect of the distance between the camera and the target, and the blending mode configuration used to create orthomosaics. During the tests, the camera was able to deliver results within the accuracy reported by the manufacturer when using factory calibration, with a root mean square error (RMSE) of 1.08 °C for proximal condition and ≤3.18 °C during aerial missions. Results among different flight altitudes revealed that the overall precision remained stable (R² = 0.94–0.96), contrasting with the accuracy results, decreasing towards higher flight altitudes due to atmospheric attenuation, which is not accounted by factory calibration (RMSE = 2.63–3.18 °C). The blending modes tested also influenced the final accuracy, with the best results obtained with the average (RMSE = 3.14 °C) and disabled mode (RMSE = 3.08 °C). Furthermore, empirical line calibration models using ground reference targets were tested, reducing the errors on temperature measurements by up to 1.83 °C, with a final accuracy better than 2 °C. Other important results include a simplified co-registering method developed to overcome alignment issues encountered during orthomosaic creation using non-geotagged thermal images, and a set of insights and recommendations to reduce errors when deriving temperature readings from aerial thermal imaging.

scholarly journals A.I. Driven Thermal People Counting for Smart Window Facade Using Portable Low‐Cost Miniature Thermal Imaging Sensors

2020 ◽  
Author(s):  
Moveh Samuel ◽  
Samuel-soma M Ajibade ◽  
Fred Fudah Moveh
Keyword(s):  
Thermal Imaging ◽  
Air Conditioning ◽  
Low Cost ◽  
Thermal Camera ◽  
Smart Window ◽  
People Counting ◽  
The People ◽  
Thermal Cameras ◽  
Pass Through ◽  
Imaging Sensors

People counting applications have been used in diverse applications. The ability and accuracy of thermal imaging over conventional image cameras has led to the implementation of thermal cameras in people counting applications. This paper present a thermal people counting smart glass windows. The people counting application would be remotely monitored from a single centralized PC station as it’s connected to a multiplex of mass monitoring of 20 thermal camera, all embedded into different glass windows. The thermal cameras would then be able to detect body temperatures of all individuals who pass through any of the camera range and also count the numbers of people who passed through the camera range. The data gotten can then be further utilized in various ways, example is in the control of air conditioning and lightening.

scholarly journals Imaging Luminescence Thermometry to 750 °C for the Heat Treatment of Common Engineering Alloys and Comparison with Thermal Imaging

2022 ◽  
Vol 43 (3) ◽  
Author(s):  
Gavin Sutton ◽  
Sofia Korniliou ◽  
Aurik Andreu ◽  
David Wilson
Keyword(s):  
Heat Treatment ◽  
Thermal Imaging ◽  
Elevated Temperatures ◽  
Imaging Technique ◽  
Thermal Imager ◽  
Bare Metal ◽  
Mean Values ◽  
Accurate Temperature ◽  
Engineering Alloys ◽  
Better Than

AbstractAccurate temperature measurements are critical in manufacturing, affecting both product quality and energy consumption. At elevated temperatures, non-contact thermometers are often the only option. However, such instruments require prior knowledge of the surface emissivity, which is often unknown or difficult to determine, leading to large errors. Here we present a novel imaging luminescence thermometer based on the intensity ratio technique using magnesium fluorogermanate phosphor, with the potential to overcome this limitation. We describe measurements performed on a number of engineering alloys undergoing heat treatment at temperatures of up to 750 °C and compare these measurements against a traditional contact thermocouple and thermal imager system. Agreement between the luminescence and embedded thermocouple temperatures was found to be better than 45 °C at all temperatures. However, the thermal imager measurement on the bare metal samples, with the instrument emissivity set to 1.0, showed differences of up to 500 °C at 750 °C, a factor of 10 larger. In an effort to improve the thermal imager accuracy, its instrument emissivity was adjusted until its temperature agreed with that of the thermocouple. When measuring on the bare metal, the effective emissivity was strongly sample dependent, with mean values ranging from 0.205 to 0.784. Since the phosphor derived temperatures exhibited substantially smaller errors compared to the thermal imager, it is suggested that this method can be used to compliment the thermal imaging technique, by providing a robust mechanism for adjustment of the instrument emissivity until agreement between the thermal imager and phosphor thermometer is obtained.

scholarly journals Instant Stress: Detection of Perceived Mental Stress Through Smartphone Photoplethysmography and Thermal Imaging (Preprint)

2018 ◽  
Author(s):  
Youngjun Cho ◽  
Simon J Julier ◽  
Nadia Bianchi-Berthouze
Keyword(s):  
Perceived Stress ◽  
Stress Responses ◽  
Thermal Imaging ◽  
Mental Stress ◽  
Low Cost ◽  
The Self ◽  
Stress Detection ◽  
Thermal Camera ◽  
High Quality

BACKGROUND A smartphone is a promising tool for daily cardiovascular measurement and mental stress monitoring. A smartphone camera–based photoplethysmography (PPG) and a low-cost thermal camera can be used to create cheap, convenient, and mobile monitoring systems. However, to ensure reliable monitoring results, a person must remain still for several minutes while a measurement is being taken. This is cumbersome and makes its use in real-life situations impractical. OBJECTIVE We proposed a system that combines PPG and thermography with the aim of improving cardiovascular signal quality and detecting stress responses quickly. METHODS Using a smartphone camera with a low-cost thermal camera added on, we built a novel system that continuously and reliably measures 2 different types of cardiovascular events: (1) blood volume pulse and (2) vasoconstriction/dilation-induced temperature changes of the nose tip. 17 participants, involved in stress-inducing mental workload tasks, measured their physiological responses to stressors over a short time period (20 seconds) immediately after each task. Participants reported their perceived stress levels on a 10-cm visual analog scale. For the instant stress inference task, we built novel low-level feature sets representing cardiovascular variability. We then used the automatic feature learning capability of artificial neural networks to improve the mapping between the extracted features and the self-reported ratings. We compared our proposed method with existing hand-engineered features-based machine learning methods. RESULTS First, we found that the measured PPG signals presented high quality cardiac cyclic information (mean pSQI: 0.755; SD 0.068). We also found that the measured thermal changes of the nose tip presented high-quality breathing cyclic information and filtering helped extract vasoconstriction/dilation-induced patterns with fewer respiratory effects (mean pSQI: from 0.714 to 0.157). Second, we found low correlations between the self-reported stress scores and the existing metrics of the cardiovascular signals (ie, heart rate variability and thermal directionality) from short measurements, suggesting they were not very dependent upon one another. Third, we tested the performance of the instant perceived stress inference method. The proposed method achieved significantly higher accuracies than existing precrafted features-based methods. In addition, the 17-fold leave-one-subject-out cross-validation results showed that combining both modalities produced higher accuracy than using PPG or thermal imaging only (PPG+Thermal: 78.33%; PPG: 68.53%; Thermal: 58.82%). The multimodal results are comparable to the state-of-the-art stress recognition methods that require long-term measurements. Finally, we explored effects of different data labeling strategies on the sensitivity of our inference methods. Our results showed the need for separation of and normalization between individual data. CONCLUSIONS The results demonstrate the feasibility of using smartphone-based imaging for instant stress detection. Given that this approach does not need long-term measurements requiring attention and reduced mobility, we believe it is more suitable for mobile mental health care solutions in the wild.

scholarly journals A Low Cost Thermal Imaging System for Medical Diagnostic Applications

2018 ◽  
Vol 7 (3.27) ◽  
pp. 314
Author(s):  
U Jayalatsumi ◽  
A Feza Naaz ◽  
Kodavaluru Sravani3 ◽  
A Anusha ◽  
Alla Vasavi
Keyword(s):  
Thermal Imaging ◽  
Imaging System ◽  
Low Cost ◽  
Body Part ◽  
The Body ◽  
Thermal Camera ◽  
Medical Diagnostic ◽  
Diagnostic Applications ◽  
The Individual ◽  
Thermal Imaging System

This paper presents a low cost thermal imaging system for medical diagnostic applications. Available systems are expensive and are mostly meant for industrial applications. In this paper the existing system which is a basic system consisting of thermopile based sensor which produces thermal array is replaced with a “Thermal Imaging Camera” for medical diagnosis applications. The thermal camera scans the entire body of the individual to diagnose the diseases ie, infrared radiations from the human body part and then converts them to electronic signal. If there is any lump or any other unusual change inside the body, then the body temperature at that particular part will alone be high or low which indicates the “Hypo” or “Hyper” condition of the disease. Scene captured by the thermal camera is represented as a matrix. Each element of matrix represents a temperature value. Temperature values are divided into different ranges and each range is represented by an RGB value by the Raspberry Pi.  Based on this thermal camera image we can detect the exact location in individual body part and further for that part alone we can take test and detect what kind of disease the individual is suffering. This system can be used in wide applications in the field of medicine such as detection of breast cancer, fever screening, thyroid disease detection, early detection of risk for diabetic peripheral neuropathy, Reynaud’s phenomenon, orthopedics etc.  

scholarly journals Instant Stress: Detection of Perceived Mental Stress Through Smartphone Photoplethysmography and Thermal Imaging

10.2196/10140 ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. e10140 ◽  
Author(s):  
Youngjun Cho ◽  
Simon J Julier ◽  
Nadia Bianchi-Berthouze
Keyword(s):  
Perceived Stress ◽  
Stress Responses ◽  
Thermal Imaging ◽  
Mental Stress ◽  
Low Cost ◽  
The Self ◽  
Stress Detection ◽  
Thermal Camera ◽  
High Quality

Background A smartphone is a promising tool for daily cardiovascular measurement and mental stress monitoring. A smartphone camera–based photoplethysmography (PPG) and a low-cost thermal camera can be used to create cheap, convenient, and mobile monitoring systems. However, to ensure reliable monitoring results, a person must remain still for several minutes while a measurement is being taken. This is cumbersome and makes its use in real-life situations impractical. Objective We proposed a system that combines PPG and thermography with the aim of improving cardiovascular signal quality and detecting stress responses quickly. Methods Using a smartphone camera with a low-cost thermal camera added on, we built a novel system that continuously and reliably measures 2 different types of cardiovascular events: (1) blood volume pulse and (2) vasoconstriction/dilation-induced temperature changes of the nose tip. 17 participants, involved in stress-inducing mental workload tasks, measured their physiological responses to stressors over a short time period (20 seconds) immediately after each task. Participants reported their perceived stress levels on a 10-cm visual analog scale. For the instant stress inference task, we built novel low-level feature sets representing cardiovascular variability. We then used the automatic feature learning capability of artificial neural networks to improve the mapping between the extracted features and the self-reported ratings. We compared our proposed method with existing hand-engineered features-based machine learning methods. Results First, we found that the measured PPG signals presented high quality cardiac cyclic information (mean pSQI: 0.755; SD 0.068). We also found that the measured thermal changes of the nose tip presented high-quality breathing cyclic information and filtering helped extract vasoconstriction/dilation-induced patterns with fewer respiratory effects (mean pSQI: from 0.714 to 0.157). Second, we found low correlations between the self-reported stress scores and the existing metrics of the cardiovascular signals (ie, heart rate variability and thermal directionality) from short measurements, suggesting they were not very dependent upon one another. Third, we tested the performance of the instant perceived stress inference method. The proposed method achieved significantly higher accuracies than existing precrafted features-based methods. In addition, the 17-fold leave-one-subject-out cross-validation results showed that combining both modalities produced higher accuracy than using PPG or thermal imaging only (PPG+Thermal: 78.33%; PPG: 68.53%; Thermal: 58.82%). The multimodal results are comparable to the state-of-the-art stress recognition methods that require long-term measurements. Finally, we explored effects of different data labeling strategies on the sensitivity of our inference methods. Our results showed the need for separation of and normalization between individual data. Conclusions The results demonstrate the feasibility of using smartphone-based imaging for instant stress detection. Given that this approach does not need long-term measurements requiring attention and reduced mobility, we believe it is more suitable for mobile mental health care solutions in the wild.

scholarly journals Towards an improved helium-based refractometer for pressure measurements

ACTA IMEKO ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 305
Author(s):  
Z. Silvestri ◽  
D. Bentouati ◽  
P. Otal ◽  
J.-P. Wallerand
Keyword(s):  
Temperature Stability ◽  
Temperature Measurements ◽  
Pressure Measurements ◽  
Short Term ◽  
Term Stability ◽  
Accurate Temperature ◽  
Pressure Standard ◽  
Optical Pressure ◽  
532 Nm ◽  
Better Than

This paper describes a quantum realization of the pascal based a helium absolute refractometer at 532 nm. The short-term stability in pressure is ± 2 mPa with a resolution in pressure of this new optical pressure standard is better than 1 mPa with temperature stability about 1 mK. A new design of the refractometer is presented to have better temperature stability and accurate temperature measurements to reach uncertainties in pressure better than current conventional methods.

Evaluating the use of thermal imaging cameras to monitor the endangered greater bilby at Astrebla Downs National Park

2020 ◽  
Vol 42 (3) ◽  
pp. 329
Author(s):  
John Augusteyn ◽  
Anthony Pople ◽  
Maree Rich
Keyword(s):  
Sample Size ◽  
Thermal Imaging ◽  
Detection Probability ◽  
National Park ◽  
Arid Zone ◽  
Thermal Camera ◽  
Density Estimates ◽  
Abundance Estimates ◽  
Thermal Cameras ◽  
Larger Sample

Spotlight surveys are widely used to monitor arid-zone-dwelling species such as the greater bilby (Macrotis lagotis). These surveys require a sufficient sample size to adequately model detection probability. Adequate sample sizes can be difficult to obtain for low-density populations and for species that avoid light and or have poor eyeshine like the bilby. Abundance estimates based on burrow counts can be problematic because of the variable relationship between the number of burrows used and bilby abundance. In 2013, feral predators devastated a Queensland bilby population and a method was required that could locate and monitor the remaining bilbies. We report on a study that compared density estimates derived from spotlighting and thermal cameras. Bilbies were surveyed annually over three years, using spotlights and thermal cameras on different nights but using the same transects to compare the methods. On average, thermal cameras detected twice the number of bilbies per kilometre surveyed than spotlighting. Despite this difference in the number of bilbies detected, density estimates (bilbies km−2) were similar (thermal camera versus spotlight: 0.6 versus 0.2 (2014), 3.4 versus 3.4 (2015) and 4.8 versus 3.3 (2016)). Nevertheless, the larger sample size obtained using thermal cameras gave greater confidence in modelling detection probability.

scholarly journals Pixel-Based Calibration and Atmospheric Correction of a UAS-Mounted Thermal Camera for Land Surface Temperature Measurements

2021 ◽  
Vol 64 (6) ◽  
pp. 2137-2150
Author(s):  
Yan Zhu ◽  
Keith Cherkauer
Keyword(s):  
Land Surface ◽  
Atmospheric Correction ◽  
Correction Method ◽  
Temperature Measurements ◽  
List Type ◽  
Thermal Camera ◽  
Thermal Imagery ◽  
Calibration Methods ◽  
Thermal Cameras ◽  
Calibration Algorithm

HighlightsA novel pixel-based calibration algorithm and an atmospheric correction method are developed.Application of the calibration methods reduces the RMSE of measurements to less than 1.32°C.The calibrations facilitate stitching of images together to form whole-field mosaics.Abstract. Thermal imagery can be used to provide insight into the water stress status and evapotranspiration demand of crops, but satellite-based sensors are generally too coarse spatially and too infrequent temporally to provide information of use for the management of specific fields. Thermal cameras mounted on small unmanned aerial systems (UAS) have potential to provide canopy temperature information at high spatial and temporal resolutions useful for crop management; however, without appropriate camera corrections, the measurement biases of these uncooled thermal cameras can be larger than ±5°C. Such uncertainty can render such camera measurements useless. In this research, a pixel-based (non-uniformity) calibration algorithm and an atmospheric correction method based on in-field approximate blackbody sources (water targets) were developed for a thermal camera. The objective was to improve the temperature measurement accuracy of the thermal camera on various land surfaces including soil and vegetation. With sufficient accuracy, temperature measurements can be used for the estimation of latent heat flux of field crops in the future. The thermal camera was first calibrated in a laboratory setting where the camera and environmental conditions were controlled. The results indicated that in the range between 10°C and 45°C, the calibrated temperatures were accurate, with an average bias of 1.76°C, and had a high linear correlation with reference temperatures (water target temperatures) (R2 > 0.99). Variability of measurements was also better constrained. In-field atmospheric correction is also important for obtaining high-accuracy thermal imagery. By applying both pixel-based calibration and atmospheric corrections, the RMSE (root mean square error) of validation targets from two dates in 2017 was reduced from 4.56°C and 6.36°C before calibration to 1.32°C and 1.24°C after calibration. The calibration process also increased the range of temperatures in the imagery, which enhanced contrast and may help with identification of tie-points and stitching of images together to form whole-field mosaics. Keywords: Atmospheric correction, Pixel-based calibration, Thermal remote sensing, UAS, Water targets.

scholarly journals Floral infrared emissivity estimates using simple tools

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Michael J. M. Harrap ◽  
Sean A. Rands
Keyword(s):  
Thermal Imaging ◽  
Plant Biology ◽  
Water Bath ◽  
Infrared Emissivity ◽  
Thermal Camera ◽  
Vegetative Tissue ◽  
Floral Tissue ◽  
A Value ◽  
Accurate Temperature ◽  
Thermal Infrared Radiation

Abstract Background Floral temperature has important consequences for plant biology, and accurate temperature measurements are therefore important to plant research. Thermography, also referred to as thermal imaging, is beginning to be used more frequently to measure and visualize floral temperature. Accurate thermographic measurements require information about the object’s emissivity (its capacity to emit thermal radiation with temperature), to obtain accurate temperature readings. However, there are currently no published estimates of floral emissivity available. This is most likely to be due to flowers being unsuitable for the most common protocols for emissivity estimation. Instead, researchers have used emissivity estimates collected on vegetative plant tissue when conducting floral thermography, assuming these tissues to have the same emissivity. As floral tissue differs from vegetative tissue, it is unclear how appropriate and accurate these vegetative tissue emissivity estimates are when they are applied to floral tissue. Results We collect floral emissivity estimates using two protocols, using a thermocouple and a water bath, providing a guide for making estimates of floral emissivity that can be carried out without needing specialist equipment (apart from the thermal camera). Both protocols involve measuring the thermal infrared radiation from flowers of a known temperature, providing the required information for emissivity estimation. Floral temperature is known within these protocols using either a thermocouple, or by heating the flowers within a water bath. Emissivity estimates indicate floral emissivity is high, near 1, at least across petals. While the two protocols generally indicated the same trends, the water bath protocol gave more realistic and less variable estimates. While some variation with flower species and location on the flower is observed in emissivity estimates, these are generally small or can be explained as resulting from artefacts of these protocols, relating to thermocouple or water surface contact quality. Conclusions Floral emissivity appears to be high, and seems quite consistent across most flowers and between species, at least across petals. A value near 1, for example 0.98, is recommended for accurate thermographic measurements of floral temperature. This suggests that the similarly high values based on vegetation emissivity estimates used by previous researchers were appropriate.

Kajian Model Fisik Pengaruh Freeboard dan Susunan Buis Beton Sebagai Pemecah Gelombang Tenggelam Ambang Rendah (Pegar) Dalam Mereduksi Gelombang

2017 ◽  
Vol 1 (2) ◽  
pp. 34
Author(s):  
Zulkarnain Zulkarnain ◽  
Nadjadji Anwar
Keyword(s):  
Low Cost ◽  
Relative Depth ◽  
Submerged Breakwater ◽  
Wave Flume ◽  
Concrete Cylinder ◽  
Engineering Department ◽  
Sea Area ◽  
The Waves ◽  
Transmission Test ◽  
Better Than

The Research Center and Development of Water (Puslitbang) is currently developing the Submerged Breakwater in shallow sea area (PEGAR). The author is interested to examine the material that easily obtained in the field of RCP concrete cylinder. The observation is how it to be ability in function as submerged breakwater an go green and low cost. The physical model of wave transmission test is how the response to the structure in ability to damping of wave as the breakwater function. In this research breakwater used is submerged breakwater type by using concrete cylinder (buis beton). The purpose from this research is to know how the response of breakwater structure to the waves through it, with some variation of the structure by creating a structure with three variations of the arrangement and freeboard that is the relative depth with the crest width is constant. The wave generated test in this study is using regular waves in wave flume at FTSP Civil Engineering Department of Institute Technology Ten November. From the analysis of the effect of the installation of submerged breakwater by using concrete cylinder to the wave damping value, it can be concluded that the factors that are very influential is the freeboard and the composition of concrete cylinder. Scenario A (rigid vertical massive) is capable of producing the smallest value of kt is 0.33. As for scenario B (rigid horyzontal massive) with a damping value of 0.5, while the scenario C (rigid permeable) is only able to produce kt value of 0.71. Scenario A is better than scenario B and C Because the position of arrangement of A is very good used to damp wave in small or big freeboard conditions.

Sign in / Sign up

Export Citation Format

Share Document