scholarly journals Optical sensing of chlorophyll(in) with dual-spectrum Si LEDs in SOI CMOS technology

2021 ◽  
Author(s):  
Satadal Dutta ◽  
Peter Steeneken ◽  
Gerard J. Verbiest
Keyword(s):  
Absorption Coefficient ◽  
Optical Sensors ◽  
Near Infrared ◽  
Agricultural Sector ◽  
Low Cost ◽  
Cmos Technology ◽  
Light Sources ◽  
Effective Absorption Coefficient ◽  
Color Ratio ◽  
Soi Cmos

Small and low-cost chlorophyll sensors are popular in agricultural sector and food-quality control. Combining such sensors with silicon CMOS electronics is challenged by the absence of silicon-integrated light-sources. We experimentally achieve optical absorption sensing of chlorophyll based pigments with silicon (Si) micro light-emitting diodes (LED) as light-source, fabricated in a standard SOI-CMOS technology. By driving a Si LED in both forward and avalanche modes of operation, we steer its electroluminescent spectrum between visible (400–900 nm) and near-infrared (~1120 nm). For detection of chlorophyll in solution phase, the dual-spectrum light from the LED propagates vertically through glycerol micro-droplets containing sodium copper chlorophyllin at varying relative concentrations. The transmitted light is detected via an off-chip Si photodiode. The visible to near-infrared color ratio (COR) of the photocurrent yields the effective absorption coefficient. We introduce the LED-specific molar absorption coefficient as a metric to compute the absolute pigment concentration (?~0.019 ?M) and validate the results by measurements with a hybrid spectrophotometer. With the same sensor, we also show non-invasive monitoring of chlorophyll in plant leaves. COR sensitivities of ? 3.9? x 10<sup>4</sup> M<sup>-1</sup> and ? 5.3? x 10<sup>4</sup> M<sup>-1</sup> are obtained for two leaf species, where light from the LED propagates diffusely through the thickness of the leaf prior to detection by the photodiode. Our work demonstrates the feasibility of realizing fully CMOS-integrated optical sensors for biochemical analyses in food sector and plant/human health.

scholarly journals Optical sensing of chlorophyll(in) with dual-spectrum Si LEDs in SOI CMOS technology

2021 ◽  
Author(s):  
Satadal Dutta ◽  
Peter Steeneken ◽  
Gerard J. Verbiest
Keyword(s):  
Absorption Coefficient ◽  
Optical Sensors ◽  
Near Infrared ◽  
Agricultural Sector ◽  
Low Cost ◽  
Cmos Technology ◽  
Light Sources ◽  
Effective Absorption Coefficient ◽  
Color Ratio ◽  
Soi Cmos

Small and low-cost chlorophyll sensors are popular in agricultural sector and food-quality control. Combining such sensors with silicon CMOS electronics is challenged by the absence of silicon-integrated light-sources. We experimentally achieve optical absorption sensing of chlorophyll based pigments with silicon (Si) micro light-emitting diodes (LED) as light-source, fabricated in a standard SOI-CMOS technology. By driving a Si LED in both forward and avalanche modes of operation, we steer its electroluminescent spectrum between visible (400–900 nm) and near-infrared (~1120 nm). For detection of chlorophyll in solution phase, the dual-spectrum light from the LED propagates vertically through glycerol micro-droplets containing sodium copper chlorophyllin at varying relative concentrations. The transmitted light is detected via an off-chip Si photodiode. The visible to near-infrared color ratio (COR) of the photocurrent yields the effective absorption coefficient. We introduce the LED-specific molar absorption coefficient as a metric to compute the absolute pigment concentration (?~0.019 ?M) and validate the results by measurements with a hybrid spectrophotometer. With the same sensor, we also show non-invasive monitoring of chlorophyll in plant leaves. COR sensitivities of ? 3.9? x 10<sup>4</sup> M<sup>-1</sup> and ? 5.3? x 10<sup>4</sup> M<sup>-1</sup> are obtained for two leaf species, where light from the LED propagates diffusely through the thickness of the leaf prior to detection by the photodiode. Our work demonstrates the feasibility of realizing fully CMOS-integrated optical sensors for biochemical analyses in food sector and plant/human health.

scholarly journals Commercial polycarbonate track-etched membranes as substrates for low-cost optical sensors

2019 ◽  
Vol 10 ◽  
pp. 677-683 ◽  
Author(s):  
Paula Martínez-Pérez ◽  
Jaime García-Rupérez
Keyword(s):  
Optical Sensors ◽  
Mesoporous Material ◽  
Near Infrared ◽  
Low Cost ◽  
Ethanol Solution ◽  
Infrared Range ◽  
Refractive Index Sensing ◽  
Fabry Perot ◽  
Pattern Characteristic ◽  
Near Infrared Range

Porous materials have become one of the best options for the development of optical sensors, since they maximize the interaction between the optical field and the target substances, which boosts the sensitivity. In this work, we propose the use of a readily available mesoporous material for the development of such sensors: commercial polycarbonate track-etched membranes. In order to demonstrate their utility for this purpose, we firstly characterized their optical response in the near-infrared range. This response is an interference fringe pattern, characteristic of a Fabry–Pérot interferometer, which is an optical device typically used for sensing purposes. Afterwards, several refractive index sensing experiments were performed by placing different concentrations of ethanol solution on the polycarbonate track-etched membranes. As a result, a sensitivity value of around 56 nm/RIU was obtained and the reusability of the substrate was demonstrated. These results pave the way for the development of optical porous sensors with such easily available mesoporous material.

Demonstration of environmental chemistry with microscale chemistry and a low-cost four-led based photom

2018 ◽  
Vol 16 (4) ◽  
pp. 510
Author(s):  
Wai Kin Kee ◽  
Wing Hong Chan
Keyword(s):  
Phenolic Compounds ◽  
Environmental Chemistry ◽  
Low Cost ◽  
Light Sources ◽  
Electrochemical Degradation

<span>In this article, a four-LED based photometer, in which four LEDs are used as light sources, are demonstrated to be a useful instrument for the study of pollution problems caused by phenols and of their remediation by electrochemical degradation method and the iron (II) catalyzed homogeneous Fenton’s reaction. The fate of phenols can be monitored by the photometer via the 4-aminoantipyrine method. The results revealed that the latter method was a superior method to treat the phenolic compounds.</span>

scholarly journals A 40 Mb/s VLC System Reusing an Existing Large LED Panel in an Indoor Office Environment

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1697
Author(s):  
Xicong Li ◽  
Zabih Ghassemlooy ◽  
Stanislav Zvánovec ◽  
Paul Anthony Haigh
Keyword(s):  
Modulation Depth ◽  
Light Emitting Diode ◽  
Low Cost ◽  
Data Communication ◽  
Experimental System ◽  
Digital Signal ◽  
Visible Light Communication ◽  
Cost Driver ◽  
Limiting Factors ◽  
Light Sources

With advances in solid-state lighting, visible light communication (VLC) has emerged as a promising technology to enhance existing light-emitting diode (LED)-based lighting infrastructure by adding data communication capabilities to the illumination functionality. The last decade has witnessed the evolution of the VLC concept through global standardisation and product launches. Deploying VLC systems typically requires replacing existing light sources with new luminaires that are equipped with data communication functionality. To save the investment, it is clearly desirable to make the most of the existing illumination systems. This paper investigates the feasibility of adding data communication functionality to the existing lighting infrastructure. We do this by designing an experimental system in an indoor environment based on an off-the-shelf LED panel typically used in office environments, with the dimensions of 60 × 60 cm2. With minor modifications, the VLC function is implemented, and all of the modules of the LED panel are fully reused. A data rate of 40 Mb/s is supported at a distance of up to 2 m while using the multi-band carrierless amplitude and phase (CAP) modulation. Two main limiting factors for achieving higher data rates are observed. The first factor is the limited bandwidth of the LED string inside the panel. The second is the flicker due to the residual ripple of the bias current that is generated by the panel’s driver. Flicker is introduced by the low-cost driver, which provides bias currents that fluctuate in the low frequency range (less than several kilohertz). This significantly reduces the transmitter’s modulation depth. Concurrently, the driver can also introduce an effect that is similar to baseline wander at the receiver if the flicker is not completely filtered out. We also proposed a solution based on digital signal processing (DSP) to mitigate the flicker issue at the receiver side and its effectiveness has been confirmed.

scholarly journals An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 343
Author(s):  
Kim Bjerge ◽  
Jakob Bonde Nielsen ◽  
Martin Videbæk Sepstrup ◽  
Flemming Helsing-Nielsen ◽  
Toke Thomas Høye
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Vision System ◽  
Low Cost ◽  
Light Trap ◽  
Automatic Monitoring ◽  
Light Sources ◽  
Monitoring Methods ◽  
Computer Vision System ◽  
Substantial Investment

Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.

scholarly journals Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Moving Average ◽  
Nir Spectroscopy ◽  
Control Treatment ◽  
Residue Detection ◽  
Non Destructive ◽  
Reflective Spectroscopy

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

Sign in / Sign up

Export Citation Format

Share Document