Search Results (133)

It is a well-known fact that proper nutrition is essential for human beings to live healthy lives. For thousands of years, it has been considered that dates are one of the best nutrient providers. To have better-quality dates and to enhance the shelf life of dates, it is vital to preserve dates in optimal conditions that contribute to food security. Hence, it is crucial to know the shelf life of different types of dates. In current practice, shelf life assessment is typically based on manual visual inspection, which is subjective, error-prone, and requires considerable expertise, making it difficult to scale across large storage facilities. Traditional cold storage systems, whilst being capable of monitoring temperature and humidity, lack the intelligence to detect spoilage or predict shelf life in real-time. In this study, we present a novel IoT-based shelf life estimation system that integrates multichannel gas sensors and a lightweight machine learning model deployed on an edge device. Unlike prior approaches, our system captures the real-time emissions of spoilage-related gases (methane, nitrogen dioxide, and carbon monoxide) along with environmental data to classify the freshness of date fruits. The model achieved a classification accuracy of 91.9% and an AUC of 0.98 and was successfully deployed on an Arduino Nano 33 BLE Sense board. This solution offers a low-cost, scalable, and objective method for real-time shelf life prediction. This significantly improves reliability and reduces postharvest losses in the date supply chain. Full article

Combustible gas leakage remains a critical safety concern in industrial and indoor environments, necessitating the development of detection systems that are both accurate and practically deployable. This study presents a wireless gas detection system that integrates a gas sensor array, a low-power microcontroller with Zigbee-based communication, and a Back Propagation (BP) neural network optimized via a sequential hybrid strategy. Specifically, Particle Swarm Optimization (PSO) is employed for global parameter initialization, followed by Dung Beetle Optimization (DBO) for local refinement, jointly enhancing the network’s convergence speed and predictive precision. Experimental results confirm that the proposed PSO-DBO-BP model achieves high correlation coefficients (above 0.997) and low mean relative errors (below 0.25%) for all monitored gases, including hydrogen, carbon monoxide, alkanes, and smog. The model exhibits strong robustness in handling nonlinear responses and cross-sensitivity effects across multiple sensors, demonstrating its effectiveness in complex detection scenarios under laboratory conditions within embedded wireless sensor networks. Full article

This study examines the impact of Au nanoparticles (Au-NPs) on the chemoresistive gas sensing properties as a function of particle size. The sensing material is composed of ultrathin CuO/Cu₂O films, which are fabricated by either thermal deposition technology or spray pyrolysis. These are used on a silicon nitride (Si₃N₄) micro hotplate (µh) chip with Pt electrodes and heaters. The gas sensing material is then functionalised with Au-NP of varying sizes (12, 20, and 40 nm, checked by transmission electron microscopy) using drop coating technology. The finalised sensors are tested by measuring the electrical resistance against various target gases, including carbon monoxide (CO), carbon dioxide (CO₂), and a mixture of hydrocarbons (HC_Mix), in order to evaluate any cross-sensitivity issues. While the sensor response is markedly contingent on the structural surface, our findings indicate that the dimensions of the Au-NPs exert a discernible influence on the sensor’s behaviour in response to varying target gases. The 50 nm thermally evaporated CuO/Cu₂O layers exhibited the highest sensor response of 78% against 2000 ppm CO₂. In order to gain further insight into the surface of the sensors, a scanning electron microscope (SEM) was employed, and to gain information about the composition, Raman spectroscopy was also utilised. Full article

In order to effectively monitor harmful gas leakage, this paper presents the design of an ultra-low-power IoT-based harmful gas monitoring system. The system is equipped with a custom-designed, low-power microcontroller motherboard, carefully selected low-power sensors, and high-efficiency, low-power communication modules. In addition, the system optimizes data acquisition and processing algorithms to segment gases of different concentrations. While ensuring real-time data acquisition and transmission, it achieves extremely low power consumption. By controlling the concentration of harmful gases and current for sensor performance testing, the experiment has shown that when the concentration of carbon monoxide reaches 500 ppm and methane reaches 2000 ppm, the system will trigger an alarm and upload relevant information; the sensor can detect and respond to the harmful gases within 60 s; and the system’s operating current fluctuation range remains within 0.5 mA, with an average power consumption much lower than that of other devices. Full article

This study presents the performance of a multi-gas sensor for greenhouse detection based on quartz-enhanced photoacoustic spectroscopy (QEPAS). The QEPAS sensor exploits an innovative, compact three-wavelength laser module as excitation source. The module integrates three interband cascade laser chips with a beam combining system, all enclosed in a compact metallic package with sizes of 40 × 52 × 17 mm to generate a single output beam. The multi-gas QEPAS sensor was tested in a laboratory environment for the sequential detection of two greenhouse gases, methane (CH₄) and carbon dioxide (CO₂), and a precursor greenhouse gas, carbon monoxide (CO). At an integration time of 100 ms, minimum detection limits of 21 ppb, 363 ppb, and 156 ppb, were estimated for CH₄, CO_2, and CO detection, respectively, all well below their natural abundance in air. Full article

With greenhouse gas emissions and climate change continuing to be major global concerns, researchers are increasingly focusing on reducing energy consumption as a key strategy to address these challenges. In recent years, various devices and technologies have been developed for residential buildings to implement energy-saving strategies and enhance energy efficiency. This paper presents a real-time IoT-based smart monitoring system designed to optimize energy consumption and enhance residents’ safety through efficient monitoring of home conditions and appliance usage. The system is built on a Raspberry Pi Model 4B as its core platform, integrating various IoT sensors, including the DS18B20 for temperature monitoring, the BH1750 for measuring light intensity, a passive infrared (PIR) sensor for motion detection, and the MQ7 sensor for carbon monoxide detection. The Adafruit IO platform is used for both data storage and the design of a graphical user interface (GUI), enabling residents to remotely control their home environment. Our solution significantly enhances energy efficiency by monitoring the status of lighting and heating systems and notifying users when these systems are active in unoccupied areas. Additionally, safety is improved through IFTTT notifications, which alert users if the temperature exceeds a set limit or if carbon monoxide is detected. The smart home monitoring device is tested in a university residential building, demonstrating its reliability, accuracy, and efficiency in detecting and monitoring various home conditions. Full article

This parameter study examines the impact of two distinct adhesion layers, chromium (Cr) and titanium (Ti), on the performance of CuO/Cu₂O-based chemoresistive gas sensors by varying the layer thickness. The sensing material utilised on a Si-SiO₂ sensor chip with Pt electrodes is an ultrathin CuO/Cu₂O film fabricated through thermal deposition of Cu and subsequent oxidation. The sensors were evaluated by measuring the change in electrical resistance against a range of target gases, including carbon monoxide (CO), carbon dioxide (CO₂) and a mixture of hydrocarbons (HC_Mix), in order to assess any potential cross-sensitivity issues. As the reactions occur at the surface, the surface was characterised by scanning electron microscopy (SEM) and the composition by grazing incidence X-Ray diffraction (GIXRD) measurement to gain further insight into the influence of the adhesion layer on the sensing performance. Full article

The development of high-performance carbon monoxide (CO) sensors is essential for protecting human health, ensuring industrial safety, and maintaining environmental well-being. Among various types of sensors, chemiresistive sensors exhibit considerable promise for real-time applications due to their operational capabilities. To achieve high performances of chemiresistive sensors, this review emphasizes various enhancement strategies, encompassing the refinement of sensing materials, the augmentation of sensor structures, and the optimization of gas recognition algorithms. Specifically, the modification techniques of sensing materials, which include the construction of heterostructures, the decoration with noble metals, surface functionalization, hetero-element-doping, and morphology engineering, are delved into comprehensively. This review provides insights into the rational design of cost-effective CO sensors. Full article

Chemical sensors, relying on electrical conductance changes in a gas-sensitive material due to the surrounding gas, have the (dis-)advantage of reacting with multiple target gases and humidity. In this work, we report CMOS-integrated SnO₂ thin film-based gas sensors, which are functionalized with mono-, bi-, and trimetallic nanoparticles (NPs) to optimize the sensor performance. The spray pyrolysis technology was used to deposit the metal oxide sensing layer on top of a CMOS-fabricated micro-hotplate (µhp), and magnetron sputtering inert-gas condensation was employed to functionalize the sensing layer with metallic NPs, Ag-, Pd-, and Ru-NPs, and all combinations thereof were used as catalysts to improve the sensor response to carbon monoxide and to suppress the cross-sensitivity toward humidity. The focus of this work is the detection of toxic carbon monoxide and a specific hydrocarbon mixture (HC_mix) in a concentration range of 5–50 ppm at different temperatures and humidity levels. The use of CMOS chips ensures low-power, integrated sensors, ready to apply in cell phones, watches, etc., for air quality-monitoring purposes. Full article

The need for safe and healthy air quality has become critical as urbanization and industrialization increase, leading to health risks and environmental concerns. Gas leaks, particularly of gases like carbon monoxide, methane, and liquefied petroleum gas (LPG), pose significant dangers due to their flammability and toxicity. LPG, widely used in residential and industrial settings, is especially hazardous because it is colorless, odorless, and highly flammable, making undetected leaks an explosion risk. To mitigate these dangers, modern gas detection systems employ sensors, microcontrollers, and real-time monitoring to quickly identify dangerous gas levels. This study introduces an IoT-based system designed for comprehensive environmental monitoring, with a focus on detecting LPG and butane leaks. Using sensors like the MQ6 for gas detection, MQ135 for air quality, and DHT11 for temperature and humidity, the system, managed by an Arduino Mega, collects data and sends these to the ThingSpeak platform for analysis and visualization. In cases of elevated gas levels, it triggers an alarm and notifies the user through IFTTT. Additionally, the system includes a microphone and a CNN model for analyzing audio data, enabling a thorough environmental assessment by identifying specific sounds related to ongoing activities, reaching an accuracy of 96%. Full article

This paper presents the results of a study on the characteristics of semiconductor sensors based on thin SnO₂ films modified with antimony, dysprosium, and silver impurities and dispersed double Pt/Pd catalysts deposited on the surface to detect carbon monoxide (CO). An original technology was developed, and ceramic targets were made from powders of Sn-Sb-O, Sn–Sb-Dy–O, and Sn–Sb-Dy-Ag–O systems synthesized by the sol–gel method. Films of complex composition were obtained by RF magnetron sputtering of the corresponding targets, followed by technological annealing at various temperatures. The morphology of the films, the elemental and chemical composition, and the electrical and gas-sensitive properties were studied. Special attention was paid to the effect of the film composition on the stability of sensor parameters during long-term tests under the influence of CO. It was found that different combinations of concentrations of antimony, dysprosium, and silver had a significant effect on the size and distribution of nanocrystallites, the porosity, and the defects of films. The mechanisms of degradation under prolonged exposure to CO were examined. It was established that Pt/Pd/SnO₂:0.5 at.% Sb film with optimal crystallite sizes and reduced porosity provided increased stability of carbon monoxide sensor parameters, and the response to the action of 100 ppm carbon monoxide was G₁/G₀ = 2–2.5. Full article

Chemical sensors, relying on changes in the electrical conductance of a gas-sensitive material due to the surrounding gas, typically react with multiple target gases and the resulting response is not specific for a certain analyte species. The purpose of this study was the development of a multi-sensor platform for systematic screening of gas-sensitive nanomaterials. We have developed a specific Si-based platform chip, which integrates a total of 16 sensor structures. Along with a newly developed measurement setup, this multi-sensor platform enables simultaneous performance characterization of up to 16 different sensor materials in parallel in an automated gas measurement setup. In this study, we chose the well-established ultrathin SnO₂ films as base material. In order to screen the sensor performance towards type and areal density of nanoparticles on the SnO₂ films, the films are functionalized by ESJET printing Au-, NiPt-, and Pd-nanoparticle solutions with five different concentrations. The functionalized sensors have been tested toward the target gases: carbon monoxide and a specific hydrogen carbon gas mixture of acetylene, ethane, ethne, and propene. The measurements have been performed in three different humidity conditions (25%, 50% and 75% r.h.). We have found that all investigated types of NPs (except Pd) increase the responses of the sensors towards CO and HC_mix and reach a maximum for an NP type specific concentration. Full article

Carbon monoxide (CO) gas sensors are widely used, especially for environmental monitoring in confined spaces such as the landscape of mining cave ruins in mining parks, which is essential for ensuring the health and safety of tourists and staff. In this paper, a flexible CO gas sensor based on polyimide, interdigital electrodes, and reduced graphene oxide (RGO)/cuprous chloride (CuCl) composite film is designed and manufactured for reliable room temperature detection of high-concentration CO gas. The structure size of RGO/CuCl gas-sensitive film is 5 × 5 mm. The RGO with a 62.65% C-C bond is prepared by the thermal reduction method. The test results show that the sensor has a high response in the range of 400–2000 ppm CO gas concentration, and the maximum response is 1.56. The linear correlation coefficient of the sensor is 0.981, which indicates that the sensor has good output response characteristics. The response time of the sensor for 400 ppm CO gas is 332 s, which indicates that the sensor has a fast response rate. Furthermore, compared with other gases, the sensor shows higher gas selectivity for CO gas. This sensor has the characteristics of small size and easy attachment; therefore, it can be installed on the shoulder or helmet of tourists’ safety suits, providing personalized real-time warning prompts for tourists’ physical health status. Full article

This research aims to delve into the intricacies of combustion processes, specifically focusing on heating oil and a blend of heating oil with Tire Pyrolysis Oil (TPO) in a self-developed evaporative combustion chamber featuring steam injection. The primary objective is to scrutinize the impact of steam injection on the combustion dynamics. Conducting a series of tests, the investigation involved the meticulous manipulation of stoichiometric ratios while introducing ambient air through gravity fuel flow. Subsequent iterations of these tests incorporated the introduction of steam into the ambient air stream. The examination encompassed the combustion of both heating oil and the TPO blend within the combustion chamber. The evaluation criteria comprised an in-depth analysis of flame characteristics, temperature distribution within the combustion chamber, and the quantification of emissions such as particulate matter (PM), nitrogen oxides (NO_x), carbon dioxide (CO₂), carbon monoxide (CO), and water vapor (H₂O). Throughout the experimentation phase, commercially available diesel fuel served as the primary fuel source. To facilitate the tests, the combustion chamber under scrutiny was seamlessly integrated into an AVL engine test bench system. Essential parameters, including fuel consumption, were meticulously gauged using an AVL 735 fuel flow meter, while fuel temperature was monitored using the AVL 745 fuel temperature conditioning system. The intake air, a crucial element in the combustion process, was quantified with precision using an AVL Flowsonix sensor. Emission measurements were conducted meticulously using state-of-the-art equipment, with gaseous emissions analyzed using an AVL FTIR AMA i60 exhaust gas analyzer. Simultaneously, soot emissions were quantified through employment of an AVL Micro Soot sensor. This comprehensive approach not only delves into the fundamental aspects of combustion but also extends its reach to the exploration of innovative techniques, such as steam injection, to enhance combustion efficiency and reduce emissions. The integration of advanced measurement tools ensures a robust and thorough analysis of the combustion process and its environmental implications. Full article

We herein demonstrate the pulsed-mode temperature operation of chemical sensor devices based on thin SnO₂ films, which were synthesized by magnetron sputtering. The gas-sensitive films were integrated on SiN-based micro-hotplate (µhp) chips, which enable operation temperatures up to 500 °C. We compared the gas sensor performance in constant temperature mode with pulsed temperature mode operation towards the test gases carbon monoxide and toluene. In contrast to constant temperature, the pulsed temperature mode operation reveals additional information about the type of test gas. Full article