MQ2 Sensor Research Articles

IoT Based Poultry Cage Quality Monitoring System

This research aims to create a better cage quality monitoring system in poultry farms, the parameters observed in particular are ammonia gas, where this gas greatly affects the health and productivity of laying hens, the data taken is processed in percentage terms and a comparison of several conditions in the location where the equipment is placed. The system is made using ESP32 microcontroller as the main board, DHT22 as a temperature and humidity sensor, MQ135 as a sensor to detect ammonia gas levels, GY302/BH1750 as a light sensor, light sensor or light meter sensor is used to optimize the circadian cycle of laying hens, the monitor system uses data sent by the main board to the database and taken as output by the mobile application. At the implementation stage, the system is able to function properly where the monitor system can send and receive data with the database as an intermediary between hardware and software. The DHT22 sensor can detect temperature and humidity changes with minimal error, the error rate obtained for DHT22 sensor reaches 2.26%, the MQ135 sensor can detect ammonia gas levels according to set program, the GY302/BH1750 sensor can detect changes in light with quite optimal accuracy, all sensor activities can be monitored through the software that has been created, when the system is used for a long period of time periodically the main board will stop sending data to the database, This can last 30 to 40 minutes, with a reboot solution.

Implementation of An Application-Based Motor Vehicle Exhaust Emission Level Detection System

Currently, air conditions on earth are getting worse over time due to the impact of air pollution. One example of air pollution is motor vehicle exhaust emissions. Exhaust gas emissions are the result of combustion residue in motor vehicle engines that use fuel. Motor vehicle exhaust emissions contain carbon monoxide (CO), hydrocarbons (HC), carbon dioxide gas (CO2) which have a negative impact on the environment and living creatures. This research will create a motor vehicle exhaust emission detection device. In this design, an Arduino microcontroller was used and the manufacture of this tool used an MQ-7 gas sensor to detect carbon monoxide (CO) gas, an MQ-2 sensor to detect hydrocarbon gas (HC), and an MQ-135 to detect carbon dioxide (CO2) gas. The emission test results will be sent to the application, this data includes plate number, vehicle type, vehicle brand, vehicle year and emission test results. The results of the carbon monoxide (CO) gas sensor calibration test taken from 5 data showed an error of 5.51%. The results of the hydrocarbon (HC) gas sensor calibration test taken from 5 data showed an error of 4.23%. The results of the carbon dioxide (CO2) gas sensor calibration test taken from 5 data showed an error of 1.06%. In the implementation of the tool and application, the test results were obtained for 15 vehicles. Where the highest hydrocarbon (HC) gas content value was 412 ppm, the highest carbon monoxide (CO) gas content value was 1.48%, and the highest carbon dioxide (CO2) gas content value was 21.4%.

Development and prototyping of a concentrated ethanol gas monitoring system based on the MQ-3 sensor using the KAVi machine calibrator for environmental safety

This research outlines the development of a device for measuring concentrated ethanol gas concentrations using the MQ-3 sensor. The device is engineered utilizing an Arduino Uno microcontroller and an LCD as the output interface. The MQ-3 sensor has demonstrated optimal sensitivity and a linear response to ethanol gas. The range of ethanol gas concentrations tested, from 10% to 70%, was selected to match the capabilities of the KAVi machine in generating ethanol gas. The testing process of the sensor was conducted to generate data that were subsequently calibrated to ensure measurement accuracy. Validation results indicate that the MQ-3 sensor can measure ethanol gas concentrations with high accuracy and good linearity within this range. However, discrepancies between the sensor measurements and the calibrator values were observed and need attention. The development of this device provides improvements in the accuracy and linearity of the MQ-3 sensor compared to previous studies. It is important to note that the KAVi machine has limitations in producing ethanol gas concentrations above 70%, which should be considered in the practical applications of this device. Overall, this device shows great potential in applications for monitoring ethanol gas concentrations, with a note to consider the limitations of the ethanol gas production process from the KAVi machine for more optimal results.

Non-contact identification of essential oils with IR sensors and analysis of components with an electronic nose

AbstractIn this study, the odour values of rosemary, mint, black cumin, lavender, and thyme oils were determined by an electronic nose working with an Arduino microprocessor. The components of the plants were compared with the sensor data, and the most sensitive sensors were determined by sorting according to the highest components. The study data indicated that the MQ3 sensor exhibited the highest sensitivity for thyme, black cumin, and lavender oils, which contain 63% carvacrol, 38% thymoquinone, and 36% linalool, respectively. Also, MQ7 was the most sensitive sensor for menthone (68%) in mint oil and eucalyptol (45%) in rosemary oil. In addition, a low-cost and non-contact device that works with an infrared sensor has been developed to detect the identity of the oil added into the vial. The study data showed that low-cost Arduino-based IR and odour sensors can determine the identity and component percentage of oils. The fact that the developed device can detect with 100 percent accuracy even in case of peppermint and rosemary oils, which are very similar in appearance, shows that the study data will be an inspiration for contactless determination of oil quality and type.

Design and Development of an IoT-Based Leakage Detection System for Kitchens

In Nigeria, the frequent loss of lives and properties due to LPG usage for cooking necessitates urgent intervention. This paper presents an Internet of Things (IoT) based detection system to monitor LPG leakage in kitchens. Key components include a solenoid valve for gas flow control, an MQ6 sensor for LPG monitoring, and an STM32F411CEU6 microcontroller, programmed in embedded C, as the central processing unit of the system. The system introduces an emergency shutdown mechanism using an MMBT3904 NPN transistor. Upon detecting a leak, the MQ6 sensor informs the microcontroller, which prompts the user with a Short Message Service (SMS) and calls, and then triggers the transistor to close the solenoid valve if the leakage poses an explosion risk, thus preventing potential disasters. Additionally, a custom mobile app allows for remote monitoring and control of LPG leakage. To address Nigeria's unreliable electricity supply, the system includes a 5V power pack, a solar panel, and a battery for continuous power supply to the system. Deploying this system will significantly reduce the risks associated with LPG leaks in kitchens across Nigeria.

Ambient Air Quality Detection System Powered by Internet of Things-Based Sansevieria Plant (Case Study of Manduro Health Center)

Puskesmas Manduro is one of the public health service centers located at Jl. Raya Ngoro KM 14, Manduro MG Village, Ngoro District, Mojokerto Regency, East Java. As a basic health service center, it is important to monitor air quality and maintain air quality in accordance with the Environmental Quality Standard (SBMKL). This study aims to design an Internet of Things-based air quality detection system that utilizes Sansevieria plants as one of the natural solutions in absorbing air pollution levels. The method used is the research and development method which includes system design, tool making, website design, tool integration, and system testing. The sensors used are MQ-7 sensors for carbon monoxide gas, MQ-135 sensors for nitrogen dioxide gas, MQ-131 sensors for ozone gas, Dust GP2Y1010AU0F sensors for PM2.5, and DHT22 sensors for temperature and humidity. The results of testing the system for three days obtained the average temperature 30.64C, humidity 73.62%, CO 735.63 µg/m³. NO2 27.30 µg/m³, O3 32.13 30 µg/m³, and PM2.5 2.14 µg/m³. Based on the test results that have been carried out, it shows that the air quality monitoring system can provide data, graphs, and indicator levels for the Air Pollution Standard Index (ISPU). Air quality data obtained from sensors can be displayed on the LCD and also displayed in real-time through the website.

The Implementation of a Cooling and Storage System for Bakpia Pathok Based on IoT Technology (Case Study : Bakpia Pathok 79)

Bakpia Pathok 79, a food product made from flour, has a short shelf life and faces challenges in maintaining quality due to inadequate storage and conventional cooling methods. This study aims to design a temperature control and spoilage detection system for Bakpia Pathok 79 using gas sensors and the DHT-22 temperature sensor. Over a 6-day test period, results indicated that bakpia is best consumed immediately after cooling and remains optimal until the fourth day. In showcase 1, the MQ4 sensor detected methane levels below 195 ppm, and the MQ3 sensor detected ethanol levels below 300 ppm. In showcase 2, the MQ4 readings were below 200 ppm, and the MQ3 readings were below 260 ppm. The highest temperature of bakpia before cooling was 32°C, stabilizing at 29°C within 7 minutes. The system connects to an Android application for real-time temperature monitoring and spoilage detection, providing notifications when the bakpia is ready for packaging. Test results show the system is effective in detecting spoilage and accurately monitoring temperature.

Prototype smart integrated fire detection based on deep learning YOLO v8 and IoT (internet of things) to improve early fire detection

The high incidence of fires in Indonesia in 2018-2023 is 5,336 fire incidents have caused many deaths and enormous material losses. This system is designed to identify early signs of fire through object detection and sensor technology, which is integrated with the Blynk IoT platform for real-time sensor monitoring and Telegram for instant notifications to users. The waterfall prototype method was designed through observation, system design, program code creation, tool testing, and tool implementation. This research uses Deep Learning YOLOv8 technology and IoT using ESP 32 as a microcontroller. Based on the training datasets, it produces precision=0.95872; recall=0.91; mAP50=0.97; mAP50-95 =0.66. The system uses the integration of a multisensor KY-026 flame sensor, DHT 22 temperature and humidity sensor, and MQ-2 sensors can detect CO, LPG, and smoke gas. All these multisensors can be monitored on Blynk IoT and Telegrambot in real time.

STUDENT MANUAL : TESTING A HYDROCARBON REFRIGERANT LEAK DETECTOR WITH ARDUINO NANO AND MQ-2 SENSOR

This research aims to address public concerns regarding the use of hydrocarbon refrigerants, which are prone to leakage and have the potential to cause explosions and fires. Therefore, a hydrocarbon refrigerant gas leak detector was developed using the MQ-2 sensor for accurate detection. This device utilizes an Arduino Nano microcontroller to detect the gas. The manufacturing method includes both hardware and software development. The results show that this device is effective in detecting leaks by measuring the PPM (parts per million) values from five sensors, producing 70 buzzer sounds in 20 minutes when 105 grams of hydrocarbon refrigerant is released, and the device tsemperature reaches 30°C. The visual indicator provides "safe" and "leak" statuses at a pressure of 130 Psi, and the light indicator remains on during testing. In conclusion, this device improves the maintenance procedures of hydrocarbon refrigerants in refrigeration systems, giving users peace of mind because leaks can be detected with sound and visual indicators every 17 seconds.

IoT Architecture for Vehicle Pollutant Gas Emission Monitoring and Validation through Machine Learning

This study proposes an IoT architecture for monitoring emissions of polluting gases in vehicles, in response to the growing concern about air pollution and global warming. The architecture is based on a node equipped with DHT22, MQ9, and MQ135 sensors to capture temperature, humidity, and gas emissions, respectively. This node effectively communicates through the LTE network to send the data to the ThingSpeak platform. An analysis of CO2, CO, and CH4 pollution levels is conducted using the collected data. These data are validated through the technical review of a test vehicle. Subsequently, an Artificial Neural Network (ANN) is trained using a specific database of CO2 emissions from vehicles in Canada. As a result, a high R2 of 99.2% is achieved, along with low values of RMSE and MSE, indicating that the model is making accurate predictions and fits well to the training data. The ANN aims to predict CO2 emissions and verify CO2 data from the IoT network. The architecture demonstrates its capability for real-time monitoring and its potential to contribute to pollution reduction.

Design and implementation of an alcohol detection driver system

A technology called an alcohol detection driver system is used to stop drunk driving by identifying alcohol in a motorist's breath or blood. This technology correctly measures the amount of alcohol a driver has in their system using sensors and algorithms, and it stops the car from starting if the amount is more than the legal limit. The number of fatal accidents and traffic fatalities caused by drinking could be greatly decreased thanks to this technology. The main focus of this project is to carry out the experiment in lowering the number of alcohol-related incidents on the road. Alcohol detection devices come in a variety of forms right now, including ignition interlocks, passive alcohol sensors, and in-car breathalyzers. Although these systems have reduced the number of drunk driving accidents, there remain questions about their efficiency, dependability, and cost. According to the sensor's specs, the output voltage of the MQ-3 sensor reduces by 69% during the sensor's recovery period of 30 seconds at 69% of baseline resistance. To assess the long-term viability and efficiency of these systems in lowering alcohol-related accidents and enhancing traffic safety, more research is required.

DESIGN OF CARBON MONOXIDE (CO) MEASUREMENT TOOL USING SIM900A AND SOLAR PANEL BASED ON WEMOS D1 MINI

With abundant natural resources, East Kalimantan has a major environmental issue: forest fires. Several cases in East Kalimantan currently garner pros and cons regarding relocating Indonesia's new capital to the region. Fires in peatlands are usually dominated by smoldering processes, resulting in the highest emissions of carbon monoxide (CO) particles. Carbon monoxide gas is odorless, colorless, and tasteless, making it difficult to detect, yet highly toxic, and can cause illness in humans. Considering the dangers caused by CO gas, this research aims to create a CO gas detector to determine air pollution conditions in the environment. This research uses an MQ-7 sensor to detect CO gas, where the data is processed into parts per million (ppm), Wemos D1 Mini as the microcontroller, and SIM900A module as the data transmitter to the website. The system uses solar panels to fulfill its power needs independently. The device's characteristics can measure CO levels ranging from 51.55 to 907.61 ppm with an average accuracy rate of 95.10% and precision of 97.18%. The model performed well overall.

Pengembangan Alat Pendeteksi Kebocoran Gas LPG Menggunakan Sensor Mq-2 Sebagai Upaya Pencegahan Dini Terhadap Risiko Kebakaran

This research aims to find out how to design a security system that has a role as an LPG gas leak detection tool which is able to detect the presence of polluted gas in the surrounding air which can cause fires using a device, namely the mq-2 sensor and to find out how the gas leak detection tool works. the LPG. In preparing this research, the methodology used was ADDIE which is a development model that focuses on the suitability of the product being designed with the approach used. This research was carried out by carrying out several stages, including the analysis stage, namely analyzing the background and benefits of product development, design is the activity of making a product design, development is the stage of making a product according to the design that has been made, implementation is the application of a product that has been made, evaluation is the stage carried out to evaluate products that have been developed. The way this tool works is by detecting indications of polluted gas in the surrounding air, then the sensor sends a signal to the buzzer to provide a warning in the form of a sound produced by the buzzer.

SMART SAFETY HELMET: PENDETEKSI KARBON MONOKSIDA (CO) DI LOKASI PENGGALIAN SUMUR DAN PERTAMBANGAN

The well excavation or drainage process often results in casualties due to the presence of poison gas at the bottom of the well. Workplace accidents caused by toxic gases in mining locations also frequently loss of life. This research aims to create a smart safety helmet, a project helmet for personal protection equipped with an MQ-2 sensor to detect toxic gases, connected to a smartphone application using IoT (Internet of Things) technology. Data collection involves calibration tests and simulation tests. Data analysis employs descriptive statistical analysis in the form of numbers and tables. The creation of the smart safety helmet involves integrating Arduino devices with an MQ-2 sensor, LCD, buzzer, power bank, and IoT technology connected to the mobile phones of operators or project supervisors. This integration enables the helmet to detect and relay information about CO gas and its safety status. Based on the performance test results and calibration tests using Automotive Diagnostic Solutions owned by the Cilacap District Transportation Agency, the smart safety helmet has been proven effective in detecting the presence of carbon monoxide by being worn by mining workers and well diggers, thus detecting CO levels and its safety status. If the CO level reaches 1500 ppm or more, the operator or project manager can immediately prepare rescue measures.

Design and Build Noise and CO2 Control Devices in IOT (Internet of Things) Based Libraries

The library is a source of knowledge, information, and support for learning. It is equipped with facilities to support comfort and maintain concentration while carrying out activities in the library. For human resources to progress further, libraries must be made as comfortable as possible to support learning. This study aims to design a noise and CO2 control device in an IOT (Internet of Things) based library by using 4 sound sensors KY-037 to detect noise and 1 MQ-135 sensor to detect CO2 gas. This research method uses a literature review study. The noise and CO2 control device in the IOT (Internet Of Things) based library has been completed and can work as planned, the accuracy obtained from the KY-037 sound sensor is quite high, which is 97.6%. However, the good thing is that if the sensor accuracy is improved again, the accuracy obtained from the MQ-135 sound sensor is also quite high, which is 99.16%. Conclusion If the accuracy of the sensor is improved again, the web server runs smoothly using AJAX (Asynchronous et al.) so that the resulting website does not need to load the entire page and the ESP32 as a microcontroller can control the entire system well.

Gas Concentration Measuring-System (CH4, NH3, CO2) Upon Cow Feces in an Encased-Space Based on Arduino Uno

The goal of this exploration is to fabricate an estimating instrument for perceiving Methane, Smelling salts, and Carbon Dioxide gas concentrations in cow feces within a confined space. The feasibility of gas concentration detection devices using MQ-2 sensors, MQ-4 sensors, and Arduino Uno-based MQ-135 sensors will also be tested. This research relates to physics, particularly instrument physics. The research will employ hardware design, software design, and testing methodologies. The gas used for testing was produced from 500 grams of cow feces through three treatments: no treatment, addition of 50 grams of activated charcoal, and addition of 50 milliliters of EM4. The tool validation test was conducted by three experts, and the typical worth acquired was 95.8%, classified as entirely achievable. The experiment yielded the highest concentrations of CH4, NH3, and CO2 gases at 11:30 AM (plus EM4), 03:00 AM (plus EM4), and 24:00 AM (without treatment), respectively, with readings of 9.49 ppm, 26.89 ppm, and 4.57 ppm.

Measuring The Amount Of Ammonia Gas In Cattle Using The MQ137 Sensor In Rawan Village, Mayang District, And Member District With The Goal Of Raising Public Health Standards

The majority of the farmers in Pringtali Hamlet, Mayang Village, Jember Regency, are also cattle breeders. Cattle breeders make up the majority of farmers. They construct basic cow enclosures; the majority are joined to the home, while others are independent. For the two of them, the cage's quality does not match the standards for cleanliness. Even in cages attached to the home, the smell of cow poo can be detected up to three meters outside the cage and within the main house. Ammonia is often the gas that is released from either liquid or solid cow manure. This gas can have some negative effects on health; in fact, it can irritate respiratory blood vessels in those 60 years of age and older. Because ammonia gas from cages has not been handled adequately, the living environment is contaminated. The goal of our service is to measure the threshold level of ammonia gas surrounding the cage (using the MQ-135 sensor) in order to ascertain whether the cage is ecologically friendly and healthy. Two cow pens one adjacent to a domestic main house in Pringtali Hamlet and the other from a separate traditional pen have had measurements taken. By monitoring liquid excrement drainage channels and promoting air circulation around the cage, the measurements seek to maintain the cleanliness of the cage environment and the management of ammonia gas content. Cage management so that the livestock community can improve the cleanliness of the living environment.

Gas Leakage Detection and Prevention Using Sensors and IoT

In today's world, safety is critical, and good safety systems must be put in place. The principal objective of this study is to design a gas sensing and warning system based on Internet Of Things. LPG is used for cooking and in industries. Since LPG is stored and handled by civilian’s, it is easily damaged. In any case, when the gas cylinder, controller, and tube are not in great state, breaks occur, resulting in an issue. Accidents can cause problems such as suffocation and can start fires. Installing gas leakage detectors in vulnerable areas is the most important measure to avoid accidents caused by gas spill. The primary purpose of this study is to propose a framework for detecting and eliminating gas leakage in vulnerable areas. The gas sensor is one such way of detecting and alerting people to gas spills in their initial stages. The gas leak detection system includes a GSM module that sends SMS messages when a gas leak is noticed. It also turns on the exhaust fan and alerts the firefighter department and helps us prevent unexpected disasters. This device can be used in households and industrial facilities, they can be controlled and observe conditions remotely. Key Words: Node MCU, MQ6 Sensor, ESP2866 WIFI, Servo Motor, GSM module.

Alcohol Detection Robotic Car

"Prevention is better than cure." This quote perfectly summarizes the purpose of the alcohol engine lock system with MQ3 sensor. This system is a proactive approach to prevent accidents caused by drunk driving, rather than waiting for an accident to happen and then trying to remedy the situation. The use of technology in preventing drunk driving has proven to be an effective tool in saving lives and preventing injuries on the road. The implementation of the alcohol engine lock system with MQ3 sensor has been met with some resistance from those who feel that it in fringe son their personal freedoms. However, it is important to remember that the safety of all road users should be a top priority. The use of the system can help reduce the number of accidents caused by drunk driving and ultimately save lives. It is a small price to pay for the safety of all road users. In conclusion, the alcohol engine lock systemwithMQ3 sensor is a critical technology in preventing alcohol-related accidents on the road. This system has been successfully implemented in various countries around the world and has proven to be an effective tool in reducing the number of accidents 4 caused by drunk driving. As the famous saying goes, "Safety doesn't happen by accident." It is up to all of us to take proactive measures to ensure the safety of ourselves and others on the road.

Perancangan Sistem Pendeteksi Polusi Udara Di Dalam Kamar Mesin Secara Wireless Menggunakan Sensor MQ135 Dan TGS2106 Berbasis Lora Ra-02

Air pollution is a problem that needs attention because it can threaten human life. Many human activities cause air pollution. Especially in closed rooms such as ship engine rooms. Therefore, an air pollution detection tool is needed to determine the air pollution index in that place in order to maintain pollution levels below the threshold value. Therefore, it is necessary to have a tool to detect air pollution using the MQ-135 gas sensor to detect carbon dioxide (CO2) gas and TGS2106 to detect nitrogen dioxide (NO2) gas. The type of research method used is the experimental research method. After designing the tool, testing the tool, the air pollution detection system in the engine room wirelessly using the MQ135 and TGS2106 sensors based on LoRa Ra-02 had an average error rate of 1.3% for the MQ135 sensor reading while the TGS2106 sensor reading had an average level. -average error of 6%. Therefore, the Air Pollution Detection System in the Engine Room Wirelessly Using the MQ135 and TGS2106 Sensors Based on LoRa Ra-02 can work well.