Optimum microclimate parameters, including air temperature (T), relative humidity (RH) and vapor pressure deficit (VPD) that are uniformly distributed inside greenhouse crop production systems are essential to prevent yield loss and fruit quality. The objective of this research was to determine the spatial and temporal variations in the microclimate data of a commercial greenhouse with tomato plants located in the mid-west of Iran. For this purpose, wireless sensor data fusion was incorporated with a membership function model called Optimality Degree (OptDeg) for real-time monitoring and dynamic assessment of T, RH and VPD in different light conditions and growth stages of tomato. This approach allows growers to have a simultaneous projection of raw data into a normalized index between 0 and 1. Custom-built hardware and software based on the concept of the Internet-of-Things, including Low-Power Wide-Area Network (LoRaWAN) transmitter nodes, a multi-channel LoRaWAN gateway and a web-based data monitoring dashboard were used for data collection, data processing and monitoring. The experimental approach consisted of the collection of meteorological data from the external environment by means of a weather station and via a grid of 20 wireless sensor nodes distributed in two horizontal planes at two different heights inside the greenhouse. Offline data processing for sensors calibration and model validation was carried in multiple MATLAB Simulink blocks. Preliminary results revealed a significant deviation of the microclimate parameters from optimal growth conditions for tomato cultivation due to the inaccurate timer-based heating and cooling control systems used in the greenhouse. The mean OptDeg of T, RH and VPD were 0.67, 0.94, 0.94 in January, 0.45, 0.36, 0.42 in June and 0.44, 0.0, 0.12 in July, respectively. An in-depth analysis of data revealed that averaged OptDeg values, as well as their spatial variations in the horizontal profile were closer to the plants' comfort zone in the cold season as compared with those in the warm season. This was attributed to the use of heating systems in the cold season and the lack of automated cooling devices in the warm season. This study confirmed the applicability of using IoT sensors for real-time model-based assessment of greenhouse microclimate on a commercial scale. The presented IoT sensor node and the Simulink model provide growers with a better insight into interpreting crop growth environment. The outcome of this research contributes to the improvement of closed-field cultivation of tomato by providing an integrated decision-making framework that explores microclimate variation at different growth stages in the production season.
Nitrogen dioxide (NO2) is a major cause of respiratory disorders in outdoor and indoor environments. Real-time NO2 monitoring using nonintrusive wearable devices can save lives and provide valuable health data. This study reports a room-temperature, wearable, and flexible smart NO2 gas sensor fabricated via cost-effective printing technology on a polyimide substrate. The sensor uses alkali lignin with edge-oxidised graphene oxide (EGO-AL) ink, demonstrating a sensitivity of 1.70% ppm⁻1 and a detection limit of 12.70 ppb, with excellent selectivity towards NO2. The high sensing properties are attributed to labile oxygen functional groups from GO and alkali lignin, offering abundant interacting sites for NO2 adsorption and electron transfer. The sensor fully recovers to the baseline after heat treatment at 150 °C, indicating its reusability. Integration into lab coats showcased its wearable application, utilising a flexible printed circuit board to wirelessly alert the wearer via cell phone to harmful NO2 levels (>3 ppm) in the environment. This smart sensing application underscores the potential for practical, real-time air quality monitoring, personal safety enhancement, and health management.
Illuminance level in the softcopy image viewing room is a very important factor to optimize productivity in radiological diagnosis. In today's radiological environment, the illuminance measurements are normally done during the quality control procedure and performed annually. Although the room is equipped with dimmer switches, radiologists are not able to decide the level of illuminance according to the standards. The aim of this study is to develop a simple real-time illuminance detector system to assist the radiologists in deciding an adequate illuminance level during radiological image viewing. The system indicates illuminance in a very simple visual form by using light emitting diodes. By employing the device in the viewing room, illuminance level can be monitored and adjusted effectively.
In this paper, we present the effect of varying humidity levels on the electrical parameters and the multi frequency response of the electrical parameters of an organic-inorganic composite (PEPC+NiPc+Cu2O)-based humidity sensor. Silver thin films (thickness ~200 nm) were primarily deposited on plasma cleaned glass substrates by the physical vapor deposition (PVD) technique. A pair of rectangular silver electrodes was formed by patterning silver film through standard optical lithography technique. An active layer of organic-inorganic composite for humidity sensing was later spun coated to cover the separation between the silver electrodes. The electrical characterization of the sensor was performed as a function of relative humidity levels and frequency of the AC input signal. The sensor showed reversible changes in its capacitance with variations in humidity level. The maximum sensitivity ~31.6 pF/%RH at 100 Hz in capacitive mode of operation has been attained. The aim of this study was to increase the sensitivity of the previously reported humidity sensors using PEPC and NiPc, which has been successfully achieved.
Emerging pollutants known as endocrine-disrupting compounds (EDCs) are a contemporary global issue, especially in aquatic ecosystems. As aquaculture production through mariculture activities in Malaysia supports food production, the concentration and distribution of EDCs in estuarine water ecosystems may have changed. Therefore, this current study aims to prepare a suitable and reliable method for application on environmental samples. Besides, this study also presented the occurrence of EDCs pollutant in Pulau Kukup, Johor, where the biggest and most active mariculture site in Malaysia takes place. Analytical methods based on a combination of solid-phase extraction with liquid chromatography tandem mass spectrometry (Solid-phase extraction (SPE)-LC-MS/MS) have been modified and optimised to examine the level of targeted EDCs contaminant. In the current study, this method displays high extraction recovery for targeted EDCs, ranging from 92.02% to 132.32%. The highest concentration detected is diclofenac (<0.47-79.89 ng/L) followed by 17β-estradiol (E2) (<5.28-31.43 ng/L) and 17α-ethynylestradiol (EE2) (<0.30-7.67 ng/L). The highest percentage distribution for the targeted EDCs in the current study is diclofenac, followed by EE2 and dexamethasone with the percentages of 99.44%, 89.53% and 73.23%, respectively. This current study can be a baseline assessment to understand the pollution profile of EDCs and their distribution in the estuarine water of the mariculture site throughout the world, especially in Malaysia. Owing to the significant concentration of targeted EDCs detected in water samples, the need for further monitoring in the future is required.
An advanced image processing approach integrated with communication technologies and a camera for waste bin level detection has been presented. The proposed system is developed to address environmental concerns associated with waste bins and the variety of waste being disposed in them. A gray level aura matrix (GLAM) approach is proposed to extract the bin image texture. GLAM parameters, such as neighboring systems, are investigated to determine their optimal values. To evaluate the performance of the system, the extracted image is trained and tested using multi-layer perceptions (MLPs) and K-nearest neighbor (KNN) classifiers. The results have shown that the accuracy of bin level classification reach acceptable performance levels for class and grade classification with rates of 98.98% and 90.19% using the MLP classifier and 96.91% and 89.14% using the KNN classifier, respectively. The results demonstrated that the system performance is robust and can be applied to a variety of waste and waste bin level detection under various conditions.
A new home-made diffusive bag-type passive sampler called Lanwatsu was developed for benzene, toluene, ethylbenzene and xylene monitoring in roadside air. The passive samplers were outdoor validated and deployed together with two commercial passive samplers, Ultra I SKC Inc. and Radiello, for daily roadside air monitoring in East Asian cities including HoChiMinh, Hanoi, Cantho, Danang, Vungtau, Hue (Vietnam), Kuala Lumpur (Malaysia), Kyoto, Osaka (Japan), Nanjing (China) and Singapore in 2011. High daily benzene concentrations of 87, 52, 32, 23, 13, 12 and 48 µg/m³ were observed in HoChiMinh, Hanoi, Cantho, Danang, Hue, Vung Tau (Vietnam), and Kuala Lumpur (Malaysia), respectively. Kyoto and Osaka (Japan) were clean with daily benzene concentrations below 2.3 μg/m³. The daily benzene concentrations in Nanjing (China) and Singapore were 5.6 and 6.9 μg/m³, respectively. The three passive samplers were equivalent. Passive sampling by the Lanwatsu passive sampler is acceptable for daily outdoor benzene monitoring.
Adult mosquito collections were conducted for 12 weeks in two residential areas in Kuala Lumpur. The CDC light traps were compared using dry ice and yeast as sources of carbon dioxide attractants for mosquitoes. The efficacy of the dry ice baited trap was significant over yeast generated CO2 trap. The predominant species obtained were Culex quinquefasciatus, Stegomyia albopicta and Armigeres subalbatus.
The sensitivity of a novel silica-based fibre-form thermoluminescence dosimeter was tested off-site of a rare-earths processing plant, investigating the potential for obtaining baseline measurements of naturally occurring radioactive materials. The dosimeter, a Ge-doped collapsed photonic crystal fibre (PCFc) co-doped with B, was calibrated against commercially available thermoluminescent dosimetry (TLD) (TLD-200 and TLD-100) using a bremsstrahlung (tube-based) x-ray source. Eight sampling sites within 1 to 20 km of the perimeter of the rare-earth facility were identified, the TLDs (silica- as well as TLD-200 and TLD-100) in each case being buried within the soil at fixed depth, allowing measurements to be obtained, in this case for protracted periods of exposure of between two to eight months. The values of the dose were then compared against values projected on the basis of radioactivity measurements of the associated soils, obtained via high-purity germanium gamma-ray spectrometry. Accord was found in relative terms between the TL evaluations at each site and the associated spectroscopic results. Thus said, in absolute terms, the TL evaluated doses were typically less than those derived from gamma-ray spectroscopy, by ∼50% in the case of PCFc-Ge. Gamma spectrometry analysis typically provided an upper limit to the projected dose, and the Marinelli beaker contents were formed from sieving to provide a homogenous well-packed medium. However, with the radioactivity per unit mass typically greater for smaller particles, with preferential adsorption on the surface and the surface area per unit volume increasing with decrease in radius, this made for an elevated dose estimate. Prevailing concentrations of key naturally occurring radionuclides in soil,226Ra,232Th and40K, were also determined, together with radiological dose evaluation. To date, the area under investigation, although including a rare-earth processing facility, gives no cause for concern from radiological impact. The current study reveals the suitability of the optical fibre based micro-dosimeter for all-weather monitoring of low-level environmental radioactivity.
The progress of novel sorbents and their function in preconcentration techniques for determination of trace elements is a topic of great importance. This review discusses numerous analytical approaches including the preparation and practice of unique modification of solid-phase materials. The performance and main features of ion-imprinting polymers, carbon nanotubes, biosorbents, and nanoparticles are described, covering the period 2007-2012. The perspective and future developments in the use of these materials are illustrated.
In this study, the construction and test of tapered plastic optical fiber (POF) sensors, based on an intensity modulation approach are described. Tapered fiber sensors with different diameters of 0.65 mm, 0.45 mm, and 0.35 mm, were used to measure various concentrations of Remazol black B (RBB) dye aqueous solutions at room temperature. The concentrations of the RBB solutions were varied from 0 ppm to 70 ppm. In addition, the effect of varying the temperature of the RBB solution was also investigated. In this case, the output of the sensor was measured at four different temperatures of 27 °C, 30 °C, 35 °C, and 40 °C, while its concentration was fixed at 50 ppm and 100 ppm. The experimental results show that the tapered POF with d = 0.45 mm achieves the best performance with a reasonably good sensitivity of 61 × 10(-4) and a linearity of more than 99%. It also maintains a sufficient and stable signal when heat was applied to the solution with a linearity of more than 97%. Since the transmitted intensity is dependent on both the concentration and temperature of the analyte, multiple linear regression analysis was performed to combine the two independent variables into a single equation. The resulting equation was then validated experimentally and the best agreement between the calculated and experimental results was achieved by the sensor with d = 0.45 mm, where the minimum discrepancy is less than 5%. The authors conclude that POF-based sensors are suitable for RBB dye concentration sensing and, with refinement in fabrication, better results could be achieved. Their low fabrication cost, simple configuration, accuracy, and high sensitivity would attract many potential applications in chemical and biological sensing.
Luminescence-based assays for toxicants such as Microtox, ToxAlert, and Biotox have been used extensively worldwide. However, the use of these assays in near real time conditions is limited due to nonoptimal assay temperature for the tropical climate. An isolate that exhibits a high luminescence activity in a broad range of temperatures was successfully isolated from the mackerel, Rastrelliger kanagurta. This isolate was tentatively identified as Photobacterium sp. strain MIE, based on partial 16S rDNA molecular phylogeny. Optimum conditions that support high bioluminescence activity occurred between 24 and 30°C, with pH 5.5 to 7.5, 10 to 20 g/L of sodium chloride, 30 to 50 g/L of tryptone, and 4 g/L of glycerol as the carbon source. Assessment of near real time capability of this bacterial system, Xenoassay light to monitor heavy metals from a contaminated river running through the Juru River Basin shows near real time capability with assaying time of less than 30 minutes per samples. Samples returned to the lab were tested with a standard Microtox assay using Vibrio fishceri. Similar results were obtained to Xenoassay light that show temporal variation of copper concentration. Thus, this strain is suitable for near real time river monitoring of toxicants especially in the tropics.
Anionic surfactants are one of the pollutants derived from particulate matter (PM) and adversely affect the health of living organisms. In this study, the compositions of surfactants extracted from PM and vehicle soot collected in an urban area were investigated. A high-volume air sampler was used to collect PM sample at urban area based on coarse (> 1.5 µm) and fine (
In this article a luminescence fiber optic biosensor for the microdetection of heavy metal toxicity in waters based on the marine bacterium Aliivibrio fischeri (A. fischeri) encapsulated in alginate microspheres is described. Cu(II), Cd(II), Pb(II), Zn(II), Cr(VI), Co(II), Ni(II), Ag(I) and Fe(II) were selected as sample toxic heavy metal ions for evaluation of the performance of this toxicity microbiosensor. The loss of bioluminescence response from immobilized A. fischeri bacterial cells corresponds to changes in the toxicity levels. The inhibition of the luminescent biosensor response collected at excitation and emission wavelengths of 287 ± 2 nm and 487 ± 2 nm, respectively, was found to be reproducible and repeatable within the relative standard deviation (RSD) range of 2.4-5.7% (n = 8). The toxicity biosensor based on alginate micropsheres exhibited a lower limit of detection (LOD) for Cu(II) (6.40 μg/L), Cd(II) (1.56 μg/L), Pb(II) (47 μg/L), Ag(I) (18 μg/L) than Zn(II) (320 μg/L), Cr(VI) (1,000 μg/L), Co(II) (1700 μg/L), Ni(II) (2800 μg/L), and Fe(III) (3100 μg/L). Such LOD values are lower when compared with other previous reported whole cell toxicity biosensors using agar gel, agarose gel and cellulose membrane biomatrices used for the immobilization of bacterial cells. The A. fischeri bacteria microencapsulated in alginate biopolymer could maintain their metabolic activity for a prolonged period of up to six weeks without any noticeable changes in the bioluminescence response. The bioluminescent biosensor could also be used for the determination of antagonistic toxicity levels for toxicant mixtures. A comparison of the results obtained by atomic absorption spectroscopy (AAS) and using the proposed luminescent A. fischeri-based biosensor suggests that the optical toxicity biosensor can be used for quantitative microdetermination of heavy metal toxicity in environmental water samples.