Ultraviolet Imaging with Low Cost Smartphone Sensors: Development and Application of a Raspberry Pi-Based UV Camera

Compact and low-cost deep-ultraviolet microscope system for label-free molecular imaging and point-of-care hematological analysis

Deep-ultraviolet (UV) microscopy enables label-free, high-resolution, quantitative molecular imaging and enables unique applications in biomedicine, including the potential for fast hematological analysis at the point-of-care. UV microscopy has been shown to quantify hemoglobin content and white blood cells (five-part differential), providing a simple alternative to the current gold standard, the hematological analyzer. Previously, however, the UV system comprised a bulky broadband laser-driven plasma light source along with a large and expensive camera and 3D translation stage. Here, we present a modified deep-UV microscope system with a compact footprint and low-cost components. We detail the novel design with simple, inexpensive optics and hardware to enable fast and accurate automated imaging. We characterize the system, including a modified low-cost web-camera and custom automated 3D translation stage, and demonstrate its ability to scan and capture large area images. We further demonstrate the capability of the system by imaging and analyzing blood smears, using previously trained networks for automatic segmentation, classification (including 5-part white blood cell differential), and colorization. The developed system is approximately 10 times less expensive than previous configurations and can serve as a point-of-care hematology analyzer, as well as be applied broadly in biomedicine as a simple compact, low-cost, quantitative molecular imaging system.

'I had a bigger cancer risk than I thought…': The experience of receiving personalized risk information as part of a skin cancer prevention intervention in the college setting

BACKGROUND

Diagnoses of both melanoma and nonmelanoma skin cancers are becoming increasingly common among young adults. Interventions in this population are a priority because they do not consistently follow skin cancer prevention recommendations.

OBJECTIVES

The goal of the current study was to examine college students' perspectives on and experience with receiving a skin cancer prevention intervention that provided personalized skin cancer risk feedback in the form of an ultraviolet (UV) photograph, the results of genetic testing for common skin cancer risk variants, and/or general skin cancer prevention education.

METHODS

Qualitative interviews were conducted with 38 college students who received a skin cancer prevention intervention. The interview covered students' feelings about their personal skin cancer risk information, the impact of the intervention on their skin cancer risk perceptions, actions or intentions to act with regard to their sun protection practices and feedback for improvement of the intervention content or delivery.

RESULTS

Participants reported that different intervention components contributed to increased awareness of their sun protection behaviours, shifts in cognitions about and motivation to implement sun protection strategies and reported changes to their skin cancer prevention strategies.

CONCLUSION

Our findings indicate that college students are interested in and responsive to these types of multicomponent skin cancer preventive interventions. Further, students demonstrate some motivation and intentionality toward changing their skin cancer risk behaviour in the short term.

PATIENT OR PUBLIC CONTRIBUTION

Participants involved in this study were members of the public (undergraduate students) who were involved in a skin cancer prevention intervention, then participated in semistructured interviews, which provided the data analysed for this study.

Application of Image Sensors to Detect and Locate Electrical Discharges: A Review

Today, there are many attempts to introduce the Internet of Things (IoT) in high-voltage systems, where partial discharges are a focus of concern since they degrade the insulation. The idea is to detect such discharges at a very early stage so that corrective actions can be taken before major damage is produced. Electronic image sensors are traditionally based on charge-coupled devices (CCDs) and, next, on complementary metal oxide semiconductor (CMOS) devices. This paper performs a review and analysis of state-of-the-art image sensors for detecting, locating, and quantifying partial discharges in insulation systems and, in particular, corona discharges since it is an area with an important potential for expansion due to the important consequences of discharges and the complexity of their detection. The paper also discusses the recent progress, as well as the research needs and the challenges to be faced, in applying image sensors in this area. Although many of the cited research works focused on high-voltage applications, partial discharges can also occur in medium- and low-voltage applications. Thus, the potential applications that could potentially benefit from the introduction of image sensors to detect electrical discharges include power substations, buried power cables, overhead power lines, and automotive applications, among others.

Real-Time Monitoring of SO2 Emissions Using a UV Camera with Built-in NO2 and Aerosol Corrections

Nitrogen dioxide (NO₂) absorption correction of the sulfur dioxide (SO₂) camera was demonstrated for the first time. The key to improving the measurement accuracy is to combine a differential optical absorption spectroscopy (DOAS) instrument with the SO₂ camera for the real-time NO₂ absorption correction and aerosol scattering correction. This method performs NO₂ absorption correction by the correlation between the NO₂ column density measurement of the DOAS and the NO₂ optical depth of the corresponding channel from the SO₂ camera at a narrow wavelength window around 310 and 310 nm. The error of correction method is estimated through comparison with only using the second channel of the traditional SO₂ camera to correct for aerosol scattering and it can be reduced by 11.3% after NO₂ absorption corrections. We validate the correction method through experiments and demonstrate it to be of greatly improved accuracy. The result shows that the ultraviolet (UV) SO₂ camera system with NO₂ absorption corrections appears to have great application prospects as a technology for visualized real-time monitoring of SO₂ emissions.

Image Correction and In Situ Spectral Calibration for Low-Cost, Smartphone Hyperspectral Imaging

Developments in the portability of low-cost hyperspectral imaging instruments translate to significant benefits to agricultural industries and environmental monitoring applications. These advances can be further explicated by removing the need for complex post-processing and calibration. We propose a method for substantially increasing the utility of portable hyperspectral imaging. Vertical and horizontal spatial distortions introduced into images by ‘operator shake’ are corrected by an in-scene reference card with two spatial references. In situ light-source-independent spectral calibration is performed. This is achieved by a comparison of the ground-truth spectral reflectance of an in-scene red–green–blue target to the uncalibrated output of the hyperspectral data. Finally, bias introduced into the hyperspectral images due to the non-flat spectral output of the illumination is removed. This allows for low-skilled operation of a truly handheld, low-cost hyperspectral imager for agriculture, environmental monitoring, or other visible hyperspectral imaging applications.

Spot tests: past and present

Microchemistry, i.e., the chemistry performed at the scale of a microgram or less, has its roots in the late eighteenth and early nineteenth centuries. In the first half of the twentieth century a wide range of spot tests have been developed. For didactic reasons, they are still part of the curriculum of chemistry students. However, they are even highly important for applied analyses in conservation of cultural heritage, food science, forensic science, clinical and pharmacological sciences, geochemistry, and environmental sciences. Modern pregnancy tests, virus tests, etc. are the most recent examples of sophisticated spot tests. The present ChemTexts contribution aims to provide an overview of the past and present of this analytical methodology.

Multiple Compact Camera Fluorescence Detector for Real-Time PCR Devices

The polymerase chain reaction is an important technique in biological research because it tests for diseases with a small amount of DNA. However, this process is time consuming and can lead to sample contamination. Recently, real-time PCR techniques have emerged which make it possible to monitor the amplification process for each cycle in real time. Existing camera-based systems that measure fluorescence after DNA amplification simultaneously process fluorescence excitation and emission for dozens of tubes. Therefore, there is a limit to the size, cost, and assembly of the optical element. In recent years, imaging devices for high-performance, open platforms have benefitted from significant innovations. In this paper, we propose a fluorescence detector for real-time PCR devices using an open platform camera. This system can reduce the cost, and can be miniaturized. To simplify the optical system, four low-cost, compact cameras were used. In addition, the field of view of the entire tube was minimized by dividing it into quadrants. An effective image processing method was used to compensate for the reduction in the signal-to-noise ratio. Using a reference fluorescence material, it was confirmed that the proposed system enables stable fluorescence detection according to the amount of DNA.

Corona Discharge Characteristics under Variable Frequency and Pressure Environments

More electric aircrafts (MEAs) are paving the path to all electric aircrafts (AEAs), which make a much more intensive use of electrical power than conventional aircrafts. Due to the strict weight requirements, both MEA and AEA systems require to increase the distribution voltage in order to limit the required electrical current. Under this paradigm new issues arise, in part due to the voltage rise and in part because of the harsh environments found in aircrafts systems, especially those related to low pressure and high-electric frequency operation. Increased voltage levels, high-operating frequencies, low-pressure environments and reduced distances between wires pose insulation systems at risk, so partial discharges (PDs) and electrical breakdown are more likely to occur. This paper performs an experimental analysis of the effect of low-pressure environments and high-operating frequencies on the visual corona voltage, since corona discharges occurrence is directly related to arc tracking and insulation degradation in wiring systems. To this end, a rod-to-plane electrode configuration is tested in the 20–100 kPa and 50–1000 Hz ranges, these ranges cover most aircraft applications, so that the corona extinction voltage is experimentally determined by using a low-cost high-resolution CMOS imaging sensor which is sensitive to the visible and near ultraviolet (UV) spectra. The imaging sensor locates the discharge points and the intensity of the discharge, offering simplicity and low-cost measurements with high sensitivity. Moreover, to assess the performance of such sensor, the discharges are also acquired by analyzing the leakage current using an inexpensive resistor and a fast oscilloscope. The experimental data presented in this paper can be useful in designing insulation systems for MEA and AEA applications.

Natural environment statistics in the upper and lower visual field are reflected in mouse retinal specializations

Pressures for survival make sensory circuits adapted to a species' natural habitat and its behavioral challenges. Thus, to advance our understanding of the visual system, it is essential to consider an animal's specific visual environment by capturing natural scenes, characterizing their statistical regularities, and using them to probe visual computations. Mice, a prominent visual system model, have salient visual specializations, being dichromatic with enhanced sensitivity to green and UV in the dorsal and ventral retina, respectively. However, the characteristics of their visual environment that likely have driven these adaptations are rarely considered. Here, we built a UV-green-sensitive camera to record footage from mouse habitats. This footage is publicly available as a resource for mouse vision research. We found chromatic contrast to greatly diverge in the upper, but not the lower, visual field. Moreover, training a convolutional autoencoder on upper, but not lower, visual field scenes was sufficient for the emergence of color-opponent filters, suggesting that this environmental difference might have driven superior chromatic opponency in the ventral mouse retina, supporting color discrimination in the upper visual field. Furthermore, the upper visual field was biased toward dark UV contrasts, paralleled by more light-offset-sensitive ganglion cells in the ventral retina. Finally, footage recorded at twilight suggests that UV promotes aerial predator detection. Our findings support that natural scene statistics shaped early visual processing in evolution.

Sensing Optimum in the Raw: Leveraging the Raw-Data Imaging Capabilities of Raspberry Pi for Diagnostics Applications

Single-board computers (SBCs) and microcontroller boards (MCBs) are extensively used nowadays as prototyping platforms to accomplish innovative tasks. Very recently, implementations of these devices for diagnostics applications are rapidly gaining ground for research and educational purposes. Among the available solutions, Raspberry Pi represents one of the most used SBCs. In the present work, two setups based on Raspberry Pi and its CMOS-based camera (a 3D-printed device and an adaptation of a commercial product named We-Lab) were investigated as diagnostic instruments. Different camera elaboration processes were investigated, showing how direct access to the 10-bit raw data acquired from the sensor before downstream imaging processes could be beneficial for photometric applications. The developed solution was successfully applied to the evaluation of the oxidative stress using two commercial kits (d-ROM Fast; PAT). We suggest the analysis of raw data applied to SBC and MCB platforms in order to improve results.

Smartphone-based optical analysis systems

During the past few decades, there has been a growing trend towards the use of smartphone-based analysis systems. This is mainly due to its ubiquity, its increasing computing capacity, its relatively low cost and the ability to acquire and process data at the same time. Furthermore, there are many sensors integrated into a smartphone, for example a complementary metal-oxide semiconductor (CMOS) sensor. A CMOS sensor enables optical analysis for example by using it as a colorimeter, photometer or spectrometer. This review explores the current state-of-the-art smartphone-based optical analysis systems in various areas of application. It is organized into three sections, each of which investigates one class of smartphone-based devices: (i) smartphone-based colorimeters (ii) smartphone-based photo- and spectrometers and (iii) smartphone-based fluorimeters.

Real-time continuous calibration method for an ultraviolet camera

The accuracy of SO₂ cameras is significantly determined by the ability to obtain an accurate calibration. This work presents a real-time continuous calibration method for SO₂ cameras with a moderate resolution spectrometer by taking realistic radiative transfer into account. The effectiveness and accuracy of the proposed method have been verified through simulations and experiments. The calibration error can be reduced by about 20-80% compared with the commonly used cell calibration, especially for situations of long distance, poor visibility, or optically thick plumes.

Ultraviolet Camera Measurements of Passive and Explosive (Strombolian) Sulphur Dioxide Emissions at Yasur Volcano, Vanuatu

Here, we present the first ultraviolet (UV) camera measurements of sulphur dioxide (SO2) flux from Yasur volcano, Vanuatu, for the period 6–9 July 2018. These data yield the first direct gas-measurement-derived calculations of explosion gas masses at Yasur. Yasur typically exhibits persistent passive gas release interspersed with frequent Strombolian explosions. We used compact forms of the “PiCam” Raspberry Pi UV camera system powered through solar panels to collect images. Our daily median SO2 fluxes ranged from 4 to 5.1 kg s−1, with a measurement uncertainty of −12.2% to +14.7%, including errors from the gas cell calibration drift, uncertainties in plume direction and distance, and errors from the plume velocity. This work highlights the use of particle image velocimetry (PIV) for plume velocity determination, which was preferred over the typically used cross-correlation and optical flow methods because of the ability to function over a variety of plume conditions. We calculated SO2 masses for Strombolian explosions ranging 8–81 kg (mean of 32 kg), which to our knowledge is the first budget of explosive gas masses from this target. Through the use of a simple statistical measure using the moving minimum, we estimated that passive degassing is the dominant mode of gas emission at Yasur, supplying an average of ~69% of the total gas released. Our work further highlights the utility of UV camera measurements in volcanology, and particularly the benefit of the multiple camera approach in error characterisation. This work also adds to our inventory of gas-based data, which can be used to characterise the spectrum of Strombolian activity across the globe.

Combined ground and aerial measurements resolve vent-specific gas fluxes from a multi-vent volcano

Volcanoes with multiple summit vents present a methodological challenge for determining vent-specific gas emissions. Here, using a novel approach combining multiple ultraviolet cameras with synchronous aerial measurements, we calculate vent-specific gas compositions and fluxes for Stromboli volcano. Emissions from vent areas are spatially heterogeneous in composition and emission rate, with the central vent area dominating passive emissions, despite exhibiting the least explosive behaviour. Vents exhibiting Strombolian explosions emit low to negligible passive fluxes and are CO₂-dominated, even during passive degassing. We propose a model for the conduit system based on contrasting rheological properties between vent areas. Our methodology has advantages for resolving contrasting outgassing dynamics given that measured bulk plume compositions are often intermediate between those of the distinct vent areas. We therefore emphasise the need for a vent-specific approach at multi-vent volcanoes and suggest that our approach could provide a transformative advance in volcano monitoring applications.

Combining multiple ultraviolet cameras with synchronous aerial measurements, the authors here present vent-specific gas compositions and fluxes for Stromboli volcano. The results show that gas compositions vary between different vents, mirroring differences in eruptive behavior.

A review on the ability of smartphones to detect ultraviolet (UV) radiation and their potential to be used in UV research and for public education purposes

The effects of ultraviolet (UV) radiation on life on Earth have continuously been the subject of research. Over-exposure to UV radiation is harmful, but small amounts of exposure are required for good health. It is, therefore, crucial for humans to optimise their own UV exposure and not exceed UV levels that are sufficient for essential biological functions. Exceeding those levels may increase risk of developing health problems including skin cancer and cataracts. Smartphones have been previously investigated for their ability to detect UV radiation with or without additional devices that monitor personal UV exposure, in order to maintain safe exposure times by individuals. This review presents a comprehensive overview of the current state of smartphones' use in UV radiation monitoring and prediction. There are four main methods for UV radiation detection or prediction involving the use smartphones, depending on the requirements of the user: devoted software applications developed for smartphones to predict UV Index (UVI), wearable and non-wearable devices that can be used with smartphones to provide real-time UVI, and the use of smartphone image sensors to detect UV radiation. The latter method has been a growing area of research over the last decade. Built-in smartphone image sensors have been investigated for UV radiation detection and the quantification of related atmospheric factors (including aerosols, ozone, clouds and volcanic plumes). The overall practicalities, limitations and challenges are reviewed, specifically in regard to public education. The ubiquitous nature of smartphones can provide an interactive tool when considering public education on the effects and individual monitoring of UV radiation exposure, although social and geographic areas with low socio-economic factors could challenge the usefulness of smartphones. Overall, the review shows that smartphones provide multiple opportunities in different forms to educate users on personal health with respect to UV radiation.

Experimental Study of Visual Corona under Aeronautic Pressure Conditions Using Low-Cost Imaging Sensors

Visual corona tests have been broadly applied for identifying the critical corona points of diverse high-voltage devices, although other approaches based on partial discharge or radio interference voltage measurements are also widely applied to detect corona activity. Nevertheless, these two techniques must be applied in screened laboratories, which are scarce and expensive, require sophisticated instrumentation, and typically do not allow location of the discharge points. This paper describes the detection of the visual corona and location of the critical corona points of a sphere-plane gap configurations under different pressure conditions ranging from 100 to 20 kPa, covering the pressures typically found in aeronautic environments. The corona detection is made with a low-cost CMOS imaging sensor from both the visible and ultraviolet (UV) spectrum, which allows detection of the discharge points and their locations, thus significantly reducing the complexity and costs of the instrumentation required while preserving the sensitivity and accuracy of the measurements. The approach proposed in this paper can be applied in aerospace applications to prevent the arc tracking phenomenon, which can lead to catastrophic consequences since there is not a clear protection solution, due to the low levels of leakage current involved in the pre-arc phenomenon.

Measuring and Visualizing Solar UV for a Wide Range of Atmospheric Conditions on Hawai'i Island

Hawai’i Island often receives extreme (UV Index ≥ 11) solar ultraviolet radiation (UVR). While the UV Index (UVI) has been measured since 1997 at Hawai’i’s high-altitude Mauna Loa Observatory (MLO), measurements where people live and recreate are rare. We measured UVI on the face of a rotating mannequin head with UVR sensors at its eyes, ears and cheeks while simultaneously measuring the UVI with a zenith-facing sensor at MLO and seven sites at or near sea level from 19 July to 14 August 2018. The mannequin sensors received higher UVR at midmorning and midafternoon than at noon. For example, at sea level the peak UVI at the left cheek was 5.2 at midmorning and 2.9 at noon, while the horizontal UVI at noon was 12.7. Our measurements were supplemented with wide-angle (190° and 360°) sky photographs and UV images of the mannequin head. Because the UVI applies to horizontal surfaces, people in tropical and temperate latitudes should be informed that their face may be more vulnerable to UVR at midmorning and midafternoon than at noon. Finally, our instruments provided opportunities to measure unexpected UVR-altering events, including rare biomass smoke over MLO and spectroscopic measurements of substantial UVR-absorbing sulfur dioxide in the eruption plume of the Kilauea volcano.

Thermal Imaging Metrology with a Smartphone Sensor

Thermal imaging cameras are expensive, particularly those designed for measuring high temperature objects with low measurement uncertainty. A wide range of research and industrial applications would benefit from lower cost temperature imaging sensors with improved metrology. To address this problem, we present the first ever quantification methodology for the temperature measurement performance of an ultra-low cost thermal imaging system based on a smartphone sensor. The camera was formed from a back illuminated silicon Complementary Metal Oxide Semiconductor (CMOS) sensor, developed for the smartphone camera market. It was packaged for use with a Raspberry Pi computer. We designed and fitted a custom-made triplet lens assembly. The system performance was characterised with a range of state-of-the-art techniques and metrics: establishing a temperature resolution of below 10 °C in the range 600⁻1000 °C. Furthermore, the scene dependent aspects of combined uncertainty were considered. The minimum angular subtense for which an accurate thermal measurement could be made was determined to be 1.35°, which corresponds to a 23 mm bar at a distance of 1 m, or 45:1 field-of-view in radiation thermometer nomenclature.

Smartphone Spectrometers

Smartphones are playing an increasing role in the sciences, owing to the ubiquitous proliferation of these devices, their relatively low cost, increasing processing power and their suitability for integrated data acquisition and processing in a 'lab in a phone' capacity. There is furthermore the potential to deploy these units as nodes within Internet of Things architectures, enabling massive networked data capture. Hitherto, considerable attention has been focused on imaging applications of these devices. However, within just the last few years, another possibility has emerged: to use smartphones as a means of capturing spectra, mostly by coupling various classes of fore-optics to these units with data capture achieved using the smartphone camera. These highly novel approaches have the potential to become widely adopted across a broad range of scientific e.g., biomedical, chemical and agricultural application areas. In this review, we detail the exciting recent development of smartphone spectrometer hardware, in addition to covering applications to which these units have been deployed, hitherto. The paper also points forward to the potentially highly influential impacts that such units could have on the sciences in the coming decades.

Low-cost 3D printed 1 nm resolution smartphone sensor-based spectrometer: instrument design and application in ultraviolet spectroscopy

We report on the development of a low-cost spectrometer, based on off-the-shelf optical components, a 3D printed housing, and a modified Raspberry Pi camera module. With a bandwidth and spectral resolution of ≈60  nm and 1 nm, respectively, this device was designed for ultraviolet (UV) remote sensing of atmospheric sulphur dioxide (SO₂), ≈310  nm. To the best of our knowledge, this is the first report of both a UV spectrometer and a nanometer resolution spectrometer based on smartphone sensor technology. The device performance was assessed and validated by measuring column amounts of SO₂ within quartz cells with a differential optical absorption spectroscopy processing routine. This system could easily be reconfigured to cover other UV-visible-near-infrared spectral regions, as well as alternate spectral ranges and/or linewidths. Hence, our intention is also to highlight how this framework could be applied to build bespoke, low-cost, spectrometers for a range of scientific applications.

Characterisation of a smartphone image sensor response to direct solar 305nm irradiation at high air masses

This research reports the first time the sensitivity, properties and response of a smartphone image sensor that has been used to characterise the photobiologically important direct UVB solar irradiances at 305nm in clear sky conditions at high air masses. Solar images taken from Autumn to Spring were analysed using a custom Python script, written to develop and apply an adaptive threshold to mitigate the effects of both noise and hot-pixel aberrations in the images. The images were taken in an unobstructed area, observing from a solar zenith angle as high as 84° (air mass=9.6) to local solar maximum (up to a solar zenith angle of 23°) to fully develop the calibration model in temperatures that varied from 2°C to 24°C. The mean ozone thickness throughout all observations was 281±18 DU (to 2 standard deviations). A Langley Plot was used to confirm that there were constant atmospheric conditions throughout the observations. The quadratic calibration model developed has a strong correlation between the red colour channel from the smartphone with the Microtops measurements of the direct sun 305nm UV, with a coefficient of determination of 0.998 and very low standard errors. Validation of the model verified the robustness of the method and the model, with an average discrepancy of only 5% between smartphone derived and Microtops observed direct solar irradiances at 305nm. The results demonstrate the effectiveness of using the smartphone image sensor as a means to measure photobiologically important solar UVB radiation. The use of ubiquitous portable technologies, such as smartphones and laptop computers to perform data collection and analysis of solar UVB observations is an example of how scientific investigations can be performed by citizen science based individuals and groups, communities and schools.