Gas Sensor Module Research Articles

Advanced Fire & Gas Detection System

Abstract: This paper presents a cost-effective, user-friendly, and dependable fire and gas detection system leveraging the capabilities of an Arduino microcontroller. The system employs an MQ2 gas sensor module for gas detection and a flame sensor module for fire detection. Upon the detection of either gas or fire, the system initiates an alarm, activates LED indicators, and communicates the situation through a 16x2 LCD display. Furthermore, the system can be configured to issue SMS alerts to specific recipients. Designed for versatile applications, it finds utility in diverse settings, including residential, commercial, and educational environments. It exhibits proficiency in detecting an extensive array of gasses, encompassing methane, propane, and carbon monoxide, while also displaying sensitivity to various flame types, including those generated by wood, paper, and plastic. Installation and upkeep are straightforward, with the Arduino microcontroller and sensor modules easily adaptable to a small breadboard or circuit board. The strategically positioned LCD display and alarm ensure swift notifications to occupants in case of potential hazards. Notably, this system is budget-friendly, with the Arduino microcontroller and sensor modules available at reasonable prices from numerous online and retail suppliers. Rigorous testing has validated its effectiveness in gas and fire detection, establishing it as an invaluable asset for safeguarding lives and property against fire and gas-related risks

Fast switching hydrogen gas leakage identification using FPGA

Hydrogen will play a key part in the decarbonization of the global energy supply as the wealth of hydrogen continues to rise. However, applying hydrogen knowledge necessitates the installation of strong safety protocols, including the use of reliable hydrogen gas-detecting devices. Gas detection and monitoring at a large scale in industries need programmable electronic systems that can provide fast response and switching. The objective of the research work is to analyze the hydrogen gas detection system using a field programmable gate array (FPGA). The system is integrated with the gas sensor module, temperature control module, buzzer for alarm, liquid crystal display (LCD) and light-emitting diode (LED) for information display, and global system for mobile communication (GSM) for wireless message communication to the mobile. The temperatures module works on the sampling of the heater resistance using a voltage divider and inbuilt analog-to-digital converter (ADC), which depend on the output voltage of the digital-to-analog converter (DAC). The comparator module compares the gas concentration with the pre-decided threshold limit and acknowledges the buzzer accordingly. The system behavior for monitoring and gas concentration detection is simulated in Xilinx Vivado design suite 2020.1. The functionality of the chip is also verified in the Modelsim 10.0 waveform simulator. for the testbench tata sand samples used. LCD (16x2) displays the messages whether hydrogen gas is detected or not and the same message is delivered on mobile. The novelty of the work is that the system is applicable for faster switching in industrial applications and the designed system supported 550 MHz frequency in our simulation and synthesis.

Novel pyroelectric single crystals PIN-PMN-PT and their applications for NDIR gas detectors

Ternary manganese-doped (1−x−y)Pb(In1/2Nb1/2)O3-xPb(Mg1/3Nb2/3)O3-yPbTiO3 (Mn-doped PIN-PMN-PT) single crystals have demonstrated remarkable pyroelectric properties alongside enhanced temperature stability. These attributes hold substantial promise for the advancement of high precision nondispersive IR (NDIR) applications. In this study, Mn-doped 0.21Pb(In1/2Nb1/2)O3-0.49Pb(Mg1/3Nb2/3)O3-0.30PbTiO3 single crystals were introduced and carefully investigated. A compensated structure of pyroelectric IR detector based on Mn-doped PIN-PMN-PT single crystal was designed and fabricated, and a CO2 gas concentration monitoring module was built. Results showed that Mn-doped PIN-PMN-PT single crystals exhibit high pyroelectric coefficient, and better thermal stability than binary (1−x)Pb(Mg1/3Nb2/3)O3-xPbTiO3 system. The compensated pyroelectric IR detectors using Mn-doped PIN-PMN-PT single crystals as element chips showcase a performance that is approximately fourfold higher than that of commercial LiTaO3 pyroelectric detectors. The NDIR CO2 gas sensor module was assembled and exhibited remarkable accuracy along with an impressively low minimum detection concentration. These outcomes underscores its substantial potential for practical utilization in gas monitoring applications.

Design and Implementation of an Intelligent Safety and Security System for Vehicles Based on GSM Communication and IoT Network for Real-Time Tracking

In recent years, the surge in car theft cases, often linked to illicit activities, has become a growing concern. Simultaneously, countries grappling with oil shortages have shifted towards converting vehicles to run on liquid propane gas, presenting new safety challenges for car owners. This paper introduces a novel integrated intelligent system designed to address the challenges of car theft and safety concerns associated with gas-based vehicles. By seamlessly integrating these concerns into a single system, it aims to achieve significantly improved performance compared to traditional alarm systems. The proposed system consists of three primary parts: the car security subsystem, an Internet of Things (IoT)-based real-time car tracking subsystem, and the car safety subsystem. Utilizing key technologies such as the Arduino Microcontroller, Bluetooth module, vibration sensor, keypad, solenoid lock, GSM module, NodeMCU microcontroller, GPS module, MQ-4 gas sensor, flame sensor, temperature sensor, and Bluetooth module, the system aims to provide a comprehensive solution for the mentioned issues. Furthermore, the vibration sensor plays a crucial role in identifying unauthorized vehicle operations. Its significance lies in detecting the vibrations emanating from the running engine. Concurrently, other modules and sensors are utilized for real-time tracking and enhancing vehicle safety. These measures include safeguarding against incidents like fire outbreaks or gas leaks within the gas container. Finally, after assembling the system, a practical test was conducted, yielding favourable performance results. This paper describes a meaningful step towards improving the protection and safety for the cars, simultaneously addressing the stealing prevention and gas-related accident alleviation.

Portable In-Car Formaldehyde Detector Based on Fully Integrated Gas Sensor

A portable formaldehyde detector is designed for the detection of formaldehyde gas in the automobile. By using the gas sensor module to detect the change of the formaldehyde concentration in the air environment of the car, the current data change caused by the formaldehyde gas is processed by the single chip microcomputer to determine the formaldehyde concentration, combined with the communication protocols such as integrated circuit bus, display the results on the screen. The results of the laboratory test and in-car test show that the function of formaldehyde detection is accurate, reliable and easy to use.

Design of Seafood Freshness Detector based on Trimethylamine Gas Measurement

Food safety has become an important concern to people’s healthy life, the project is based on the TGS2603 gas sensor module, a minimum STM32 microcontroller system, and release of food trimethylamine gas sensitive quick measurement, as a basis for judging the freshness of food. The device is minimized by integration to realize real-time detection of data, and the freshness of food is presented as a simple and clear data prompt. The design scheme has been tested and verified by the prototype, and the performance indexes meet the design functions and requirements, providing maximum convenience for difficult people who cannot judge whether the seafood is fresh or not.

Evaluation of Red Wine Acidification Using an E-Nose System with Venturi Tool Sampling.

The quality of wine is checked both during the production process and upon consumption. Therefore, manual wine-tasting work is still valuable. Due to the nature of wine, many volatile components are released, and it is therefore difficult to determine which elements need to be controlled. Acetic acid is one of the substances found in wine and is a crucial substance for wine quality. Gas sensor systems may be a potential alternative for manual wine tasting. In this work, we have developed a TGS2620 gas sensor module to analyze acetic acid levels in red wine. The gas sensor module was refined according to the Venturi effect along with signal slope analysis, providing promising results. The example included in this paper demonstrates that there is a direct relationship between the slope of the MOS gas sensor response and the acetic acid concentration. This relationship is useful to evaluate the ethanol oxidation in acetic acid in red wine during its production process.

Machine Learning-Based IOT Air Quality and Pollution Detection

In India, gas leakage from the different factories harmful to human surveying in the last fifty years is very low. However, there is a lack of prior detection of the chemical gases detection system in the situation raised. So, In this regard, there is a gap identification of chemical gases intensity detection needed. In this work, the main objective is to identify chemical gases intensity and maintain the stream data in the database from different locations. To fill this gap, that is identifying the high-intensity chemical gases from the chemical gas disaster areas. The first step needs to identify the different chemical gases and natural gas compositions. In this regard in this work for design internet-based gases in the air system. So, the sensors MQ2(Ethanol i-Butane Methane Alcohol Gas Sensor Sensor), MQ3(Sensitivity Alcohol Detector), MQ4 (Methane and Natural Gas (CNG)), MQ-5 ( LPG GAS SENSOR), MQ-7 (CO Gas Sensor Module Test Carbon Monoxide Detector), MQ-8 (hydrogen Gas Sensor), MQ-9 (carbon monoxide), MQ-135 Sensor(Air Quality Sensor Hazardous Gas Detector) and DHT11 Digital Temperature Humidity Sensors. These sensors are interfacing with the micro-control STM 32 board. It is also called one Pollution identification terminal by using it to pull the sensor stream data from location to centralized data. This stream data transportation is a service to pull the data. For this Data pulling, design an algorithm store into a cloud database. In this research work, design the electronic terminal with a wifi circuit using IoT technologies.Moreover, getting these attributes as data. Data need to apply the preprocessing techniques and extracted feature techniques also. This paper discusses mainly designing the terminal for pollution attributes , cleaning the data, and applying the Machine Learning based Feature extraction techniques.

Monitoring indoor air quality using smart integrated gas sensor module (IGSM) for improving health in COPD patients.

Technology advancement, industrialisation, and globalisation have been significant reasons for air pollution outdoors and indoors. It may surprise us that we spend about 80% of our time indoors breathing toxic, stale, polluted air, making us sluggish and fretful. In contrast to outdoor air, indoor air does not recycle consistently. It traps and builds pollutants from wood and coal stoves, furniture and building materials, paints and solvents, cigarette smoke, and cleaning supplies. The prolonged exposure to these hidden pollutants can prompt respiratory disorders such as lung disease, pneumonitis, asthma, pulmonary hypertension, and chronic obstructive pulmonary disease (COPD). It is enduring and is not curable, which has been a threat to humanity for ages. COPD's major cause is airborne particulate matter and other toxic compounds emitted from indoor and outdoor sources. Outdoor air pollution can be controlled only by acquiring changes in the vast population, wherein for indoor, every individual may create a major impact on improving air purity, thereby promoting health. The proposed design model for monitoring indoor air quality was tested in a normal and stimulating environment where we live. Parameters tested included temperature, humidity, amount of PM2.5, and the concentration of CO, CO2, and NH3. These parameters were monitored for five to 6 h per day for 8 days. Results indicate that the total air quality lies in the moderate range. Further study will be helpful to utilise this module as an effective Indoor air quality (IAQ) monitoring system. HIGHLIGHTS: • A simple, effective, inexpensive integrated gas sensor module (IGSM) has been proposed in this study to monitor the indoor air quality index (IAQI). • Indoor air quality was tested in a normal and stimulating environment for 8 days. • The integrated gas sensor module (IGSM) was composed of sensors in series, and the outputs for the respective parameter were measured easily. • Among the parameters tested, CO and PM2.5 lie in the moderate range, while other pollutants within the normal range reveal that the tested air quality is moderate.

Design and Fabrication of a Gas Sensor Based on a Polypyrrole/Silver Nanoparticle Film for the Detection of Ammonia in Exhaled Breath of COVID-19 Patients Suffering from Acute Kidney Injury.

One of the serious complications of COVID-19 is acute kidney injury (AKI), leading to a decrease in kidney function and even death. The concentration of ammonia (NH3) in the exhaled breath (EB) of COVID-19 patients suffering from AKI symptoms will be significantly increased. In this work, the detection of breath NH3 was performed at gold interdigital electrodes modified with a soluble polypyrrole microparticle and silver nanoparticle film (Au-IDEs/S-PPyMPs/AgNPs) as a noninvasive chemiresistor gas sensor. The response behavior of unmodified and modified gas sensors toward NH3 and other interfering compounds was studied. The Au-IDEs/S-PPyMPs/AgNPs exhibited NH3 detection in the linear dynamic range of 1.00-19.23 ppm, with a limit of detection of 0.12 ppm. Finally, the fabricated gas sensor was used to monitor the NH3 concentration in the EB of COVID-19 patients suffering from AKI symptoms. For this purpose, the gas sensor was validated in 19 EB samples (seven COVID-19-positive patients, four COVID-19-negative patients, and eight post-COVID-19 patients). The gas sensor was directly exposed to the EB samples, followed by recording the changes in electrical resistance via a low-cost digital multimeter. The sensing mechanism was explained as the interaction between breath NH3 and sensing materials. The breath NH3 concentrations have a desirable correlation (R2 = 0.8463) with the estimated glomerular filtration rate (eGFR) values in COVID-19-positive patients. The fabricated gas sensor can distinguish COVID-19-positive patients suffering from AKI symptoms from COVID-19-negative patients and post-COVID-19 patients. The present work can pave the way for the development of a simple and efficient analytical approach for COVID-19 patients with AKI without the need for sample pretreatment.

Dynamic Coassembly of Amphiphilic Block Copolymer and Polyoxometalates in Dual Solvent Systems: An Efficient Approach to Heteroatom-Doped Semiconductor Metal Oxides with Controllable Nanostructures.

Dynamic coassembly of block copolymers (BCPs) with Keggin-type polyoxometalates (POMs) is developed to synthesize heteroatom-doped tungsten oxide with controllable nanostructures, including hollow hemispheres, nanoparticles, and nanowires. The versatile coassembly in dual n-hexane/THF solvent solution enables the fomation of poly(ethylene oxide)-b-polystyrene (PEO-b-PS)/POMs (e.g., silicotungstic acid, H4SiW12O40) nanocomposites with different morphologies such as spherical vesicles, inverse spherical micelles, and inverse cylindrical micelles, which can be readily converted into diverse nanostructured metal oxides with high surface area and unique properties via in situ thermal-induced structural evolution. For example, uniform silicon-doped WO3 (Si-WO3) hollow hemispheres derived from coassembly of PEO-b-PS with H4SiW12O40 were utilized to fabricate gas sensing devices which exhibit superior gas sensing performance toward acetone, thanks to the selective gas–solid interface catalytic reaction that induces resistance changes of the devices due to the high specific surface areas, abundant oxygen vacancies, and the Si-doping induced metastable ε-phase of WO3. Furthermore, density functional theory (DFT) calculation reveals the mechanism about the high sensitivity and selectivity of the gas sensors. On the basis of the as-fabricated devices, an integrated gas sensor module was constructed, which is capable of real-time monitoring the environmental acetone concentration and displaying relevant sensing results on a smart phone via Bluetooth communication.

Fish Spoilage Detector

This project work involves using Arduino Uno software integrated with MQ 137- Ammonia Gas Sensor, MQ 135- Gas Sensor Module and Humidity Sensor Module DHT11 to set up a Fish Spoilage Detector model for the determination of spoilage in fish. The study takes into consideration spoilage seen in fishes and how to detect it. To study the threshold values of Ammonia, and other gases like Carbon Monoxide, model trial runs are carried out to arrive at appropriate hard measures of the threshold values, to improve the stability of a conceptual fish spoilage detector. The ammonia sensor is initially tested with a pure ammonia sample before being used to quantify total volatile basic nitrogen in various fish samples of various freshness levels. When compared to standard procedures like microbe count and chromatography, which take hours to get a result, the sensor can determine the freshness of a sample in a matter of seconds. The sensor response was shown to be highly linked with fish deterioration, demonstrating that using sensors is an effective technique to swiftly test for spoiling in a sample. After calibrating the sensor(which involved watching the fish degrade for almost two days), it was put to the test using random samples, demonstrating that it can accurately distinguish the degree of freshness of the preserved fish at varied temperatures(for measuring which a temperature sensor is also fixed). The model is run until visible indications of fish spoilage are seen. The sensors detect critical levels of ammonia, carbon monoxide and also measure humidity and temperature thereby, emitting warning signals in the form of flashes of light and a sound warning. The model setup also consists of a 1602 (16x2) LCD Display with a 12C/11C Interface that will display the temperature, humidity levels as well as that of ammonia and other gases like carbon monoxide and thus, helps in spoilage detection when the levels of these reach a particular threshold value. Calibration could be improved with detailed studies containing data regarding the rate of spoilage in fishes, temperature and humidity parameters.

Design and Integration of a Gas Sensor Module that Indicates the End of Service Life of a Gas Mask Canister

AbstractIn a filtration system, a chemical cartridge packed with porous adsorbents needs to be replaced when its maximum adsorption capacity is exceeded. An end of service life indicator (ESLI) informs when to replace the cartridge. However, ESLI technology for filtration of toxic gases is overlooked despite high toxicity of the gases even at low concentrations. In this study, a real‐time ESLI is demonstrated for filtration of chemical warfare agents by inserting four chemiresistors made of carbon nanotubes into the adsorbent layer of a canister for gas masks. The sensors are installed on a flexible printed circuit board with a 3D structure to minimize the channeling effect in the canister. As the breakthrough of dimethyl methylphosphonate, a nerve agent simulant, progresses in the canister, the resistance of the sensors increases sequentially with time. The inflection points in the responses from sensors designated #1–#4 indicate that the percentage of remaining service life is 75%, 50%, 25%, and 0%, respectively. The ESLI potentially applies to a wide range of toxic gases and cartridge designs, regardless of the sensitivity and selectivity of the sensors, as supported by the breakthrough of ammonia as well as the results from a smaller canister.

HIDUNG ELEKTRONIK BERBASIS SENSOR GAS MOS UNTUK KARAKTERISASI KEMATANGAN BUAH KELAPA SAWIT

The ripeness of oil palm fruits is one of the key factors for crude palm oil qualities. Recently, electronic nose systems have been developed intensively for fruit quality assessment which relates odors to ripeness levels. This study developed an electronic nose system to characterize the ripeness levels of oil palm fruits using output voltage of each sensor and fruit hardness. The system consisted of a sensor chamber and a sample chamber. The sensor chamber consisted of eight MOS gas sensor modules of MQ series. Samples were oil palm fruits taken from oil palm fresh fruit bunches (FFB) which were previously categorized traditionally into unripe, ripe, over ripe, peeled and put into the sample chamber. Some of the fruits were also used for hardness measurement. To quantify the output voltages for each sensor, integrated trapezoid areas were calculated and related to the fruit hardness values. The results showed a significant voltage difference of each sensor for the three ripeness levels. Only four out of eight sensors showed significantly higher voltages. Three sensors which can significantly differentiate the ripeness levels are MQ3, MQ5, and MQ135 which MQ135 is the best. This shows that the electronic nose is potential for oil palm fruits. Keywords: electronic nose, fruit hardness, MOS gas sensor, oil palm fruit, ripeness

Design of IoT-Based Home Fire Detection System Equipped with a Data Logger

In Industrial Era 4.0, one of the solutions to secure a house from potential fires is to design a smart home. The smart home design described in this paper is the design of a home monitoring system for potential fires. Home fire early detection monitoring system is designed based on the IoT concept and is equipped with a data logger. Data loggers function as data logging and data recorders from time to time. The hardware system design consists of Arduino Mega2560, ESP8266, fire sensor, gas sensor and datalogger module as data storage. The software design that also functions as a system monitoring display is the Blynk application on Android smartphones. Fire sensor and gas sensor activities were recorded on the data logger module. The system test was carried out around the gas stove in the kitchen room. The system design results were displayed via the Blynk application on a smartphone. Fire detection system is a change in the Virtual Button from the initial color to red. While the monitoring display of the gas detection system is in the form of moving the Virtual Level when a gas leak is detected. Fire sensor activity recording data from the datalogger is displayed in the form of a graph of the relationship of the working voltage of the fire sensor versus time. While the data recording of gas sensor activity from the datalogger is displayed in the form of a graph of the relationship of gas concentration versus time. All system response results and graphic data are displayed in realtime through the Blynk application on a smartphone. In addition, system performance data records are stored on a micro SD card for further analysis. From the results of the design of this system is expected to be a reference of home monitoring technology from potential fire equipped with a data storage system.

Coal Mine Safety Monitoring and Alert System

The accidents in coal mines are increased day by day. There are numerous life losses of many skilled workers and laborers. There is no advent precaution measure to detect the alarming cause of the coal mine accidents and provide an alert system. Occupational accidents and occupational diseases are common in the mining. The most common causes of accidents in coal mining are firedamp and dust explosions, landslips, mine fires, and technical failures related to transport and mechanization. An analysis of occupational accidents in the consideration of social and economic factors reports that the real causes behind these accidents, which are said to happen inevitably due to technical deficiencies or failures. Thus an automated alarming coal mine accident detect ion system is employed to rescue and protect the workers from the hazards. This system incorporates the combined action of the temperature, pressure and gas sensor and IOT module to detect the temperature, pressure and atmosphere in the coal mine and log every data onto the cloud using data logging. Then these data are accepted by a admin controlled sever page through data acquisition. The data processing takes place at a server page and the alert is send to the device to glow the alarm and to the concerned officials and rescue stations for taking the prevention measures.

Using Recurrent Neural Network to Optimize Electronic Nose System with Dimensionality Reduction

Electronic nose is an electronic olfactory system that simulates the biological olfactory mechanism, which mainly includes gas sensor, data pre-processing, and pattern recognition. In recent years, the proposals of electronic nose have been widely developed, which proves that electronic nose is a considerably important tool. However, the most recent studies concentrate on the applications of electronic nose, which gradually neglects the inherent technique improvement of electronic nose. Although there are some proposals on the technique improvement, they usually pay attention to the modification of gas sensor module and barely consider the improvement of the last two modules. Therefore, this paper optimizes the electronic nose system from the perspective of data pre-processing and pattern recognition. Recurrent neural network (RNN) is used to do pattern recognition and guarantee accuracy rate and stability. Regarding the high-dimensional data pre-processing, the method of locally linear embedding (LLE) is used to do dimensionality reduction. The experiments are made based on the real sensor drift dataset, and the results show that the proposed optimization mechanism not only has higher accuracy rate and stability, but also has lower response time than the three baselines. In addition, regarding the usage of RNN model, the experimental results also show its efficiency in terms of recall ratio, precision ratio, and F1 value.

Design, Development and Validation of a Portable Gas Sensor Module: A Facile Approach for Monitoring Greenhouse Gases

We report the unique design and prototype of a portable gas sensor module for monitoring greenhouse gases. The commercially available gas sensors (MQ-02, MQ-135, and TGS2602) were adopted in designing the module using Arduino Uno. Different locations in the city of Solapur, India (17.6599° N, 75.9064° E), were scanned for the usability of the developed prototype of the mobile gas sensor module. The choice of gas sensors in combination with Arduino Uno led to an excellent prototype for measuring the concentration of greenhouse gases, and therefore the wrong alarm for toxic gases. The prototype model and corresponding greenhouse gas concentrations (ppm) are described using an interplay of sensor design, software program, and greenhouse gases sites.

Study of Effectiveness of CO and Smoke Alarm in Smoldering Fire

Introduction One of the main causes of home fires in Japan is smoking in bed, and carbon monoxide poisoning and suffocation account for a high proportion of cause of death in bedding fires [1]. In this study, using a full-scale building model, a smoldering fire initiated with a lighted cigarette placed still on cotton bedding was reproduced. The COHb concentration (blood COHb concentration) inhaled into a human body and the density and concentration behavior of smoke and CO alarms were compared by monitoring the change in the CO concentrations while smoldering fire. Early detection of fires and effects on a human body were discussed based on the data and the effectiveness of a smoke and CO alarm placed on an indoor wall was examined. Experimental In this study, single function CO gas sensor modules and smoke and CO alarms equipped with photoelectric smoke detectors and electrochemical CO sensors were arranged in a full-scale building model, as shown in Figure 1. Smoldering fire was caused in cotton bedding using a cigarette as a source of fire, and the COHb concentration of an expiratory position and the smoke densities and the CO concentrations of smoke and CO alarms placed on walls were examined. The laboratory was W2.12 ×D2.58 × H2.42 m and a set of cotton bedding was arranged. The source of the fire was set almost at the center of the laboratory and the CO sensor modules were arranged at the pillow, in the bedding, and on the upper part of the bedding (L1-300～L5-400), and on the lower part of the ceiling (L1-2120～L5-2120). Also, smoke and CO alarms (A1～A4) were placed 300 mm off the ceiling on the four walls of the laboratory. The CO concentration outputs and smoke density outputs at each measuring point were collected per 5 seconds using data loggers. After the lighted cigarette (MEVIUS SUPER LIGHTS) was placed still, each measured data was being continuously monitored. Also, based on the CO concentration data from the CO sensor modules surrounding the bedding, the COHb concentration accumulated in a human body was calculated. Result and Conclusions Each CO concentration data from the CO sensor modules placed 400 mm above the lower part of the mattress, in the bedding, and at the expiratory position were extracted as representative data (Fig.2). The CO concentration right above the fire point started rising 50 seconds after the cigarette was placed still, sharply surged to a high concentration level over 1000 ppm at 440 seconds. The CO concentration under the coverlet also suddenly surged a bid later than the one right above the source of the fire, exceeding 1000 ppm at 350 seconds. For the CO concentration at position near the pillow as expiratory position, the rise of CO concentration was confirmed 380 seconds after the cigarette was placed still and the concentration exceeded 1000 ppm at 1240 seconds. Figure 3 shows it is sufficiently possible to detect CO on the wall’s position since it was found in the comparison of the data of the CO sensor module near the ceiling and the smoke and CO alarms on the laboratory walls that the trends of CO concentration were similar in terms of the ways of rising and the concentration values. In this experiment, assuming a respiratory position of a sleeping person, the COHb concentration accumulated through breathing based on the CO concentrations of the upper part of the bedding (L2-300～L5-400) and the CO concentrations and smoke densities of the alarms placed on the walls were compared. Here, the smoke and CO alarms were set to at 10%/m for smoke and 100ppm for CO. Figure 4 shows the relationship between the CO concentration and smoke density values of A2 which responded last among the alarms placed on the walls and the COHb concentrations of the pillow position was related to these data. It was found that the CO alarm detected 280 seconds faster than the smoke alarm. The COHb concentration at the pillow position in the case of this extremely dangerous situation was calculated and it was found that the concentration was 15.1% when the smoke alarm went off. From the results above, it has been confirmed that the CO detection function of a CO and smoke alarm placed on a wall enables people to evacuate well in advance and the alarm is effective in early detection of fire.

Study of Effectiveness of CO and Smoke Alarm in Smoldering Fire

Study of Effectiveness of CO and Smoke Alarm in Smoldering Fire