MQ2 Sensor Research Articles

Design and Implementation of an Intelligent IoT System based on Fuzzy Logic for Carbon Monoxide Detection

Carbon monoxide (CO) as been frequently identified as the origin of deadly domestic accidents. The heavy toll it makes every winter is often caused by using gas heaters. CO is difficult to detect without a detector because it has not particular odor or color. In this paper, we create and implement a prototype based on the Internet of Things (IoT) to combat this dangerous gas and save human lives. This prototype first allows the detection of carbon monoxide leaks and then the execution of the necessary reactions based on fuzzy logic. These responses entail turning on a ventilation system to ventilate the area where the leak occurs. The system also alerts users by making calls, emails, or notifications. In order to alert the relevant services when the gas level exceeds a predetermined threshold, this task is specifically carried out using an MQ2 sensor, calibrated to detect the level of gas present in the air, and a GMS sensor. Both of these sensors are connected to an Arduino development board.

Design and Prototype of Vertical PVC Pipe Climbing Device for Gas Leakage Detection

This paper describes the Design and Prototype of vertical PVC pipe climbing device for gas leakage Detection. However, manually it is very difficult to reach up and inspect the vertical pipes for leakage or damage, because the pipe height is too long and sometime it installed in very high places and also the environmental condition is not safe. To overcome this type of problem and carry out the inspection more easily, we developed a PVC Vertical Pipe Climbing device to climb up and down vertically to detect the gas leakage, and when the leakage is detecting, the device is automatically stop on detected place. In this project we used the butane gas from cigarette lighter and check the leakage up to the level of 4 feet on vertical PVC pipe with the help of toggle switch. Here MQ-2 sensor is used with the device to help us for inspection of pipe.

RANCANG BANGUN SISTEM PEMBERSIH KOTORAN OTOMATIS PADA KANDANG KELINCI BERBASIS IOT (INTERNET OF THINGS)

Rabbits have their charm for breeding because of the benefits they get from rabbits. However, rabbit farming has a fairly high challenge, namely rabbits die easily because of the cleanliness of the cage. The accumulation of rabbit droppings results in increased levels of ammonia gas which are harmful to rabbits, breeders, and even the environment. In cleaning the cage, rabbit breeders still use manual methods that are ineffective and inefficient. For this reason, a systemwas created to create an automatic feces cleaning system in the rabbit cage based on IoT (Internet of Things) by utilizing loadcell sensors to detect the weight of rabbit droppings that are accommodated on the conveyor belt. Belt conveyor as a medium that transports rabbit droppings. The MQ-135 sensor is used to detect the concentration of ammonia gas and the MCUESP8266 Node as a controller and IoT as a notification and as a system control via a smartphone. Based on testing of the system, the loadcell sensor as a measure of the weight of rabbit droppings has an accuracy rate of 97.43%. The MQ-135 sensor as a measure of theconcentration of ammonia gas in rabbit cages has an accuracy rate of 99.19%. The conveyor belt can move to dispose of rabbit droppings when the weight is > 1000 grams or the ammonia gas content is > 25 ppm. Then the Telegram application bot can 100% control the system by inputting commands and can receive notifications from the system. From testing the system as a whole, the system can work according to the desired function with a 100% success rate.

Design and Implementation of In-Vehicle Alcohol Detection and Speed Control System

This study presented an effective method for reducing the rise in the number of road accidents instigated by drivers' excessive alcohol consumption on Nigerian roadways. Although speed restrictions and other preventative measures have been introduced, traffic accidents continue to occur daily. Over speeding, rash driving and drunk driving are all major contributors to motor vehicle accidents. To introduce this concept, this study has built an IOT-based in-vehicle alcohol detection and speed control system using the Arduino Nano microcontroller connected to the alcohol sensor, LCD display, and DC motor with the Bluetooth Low Energy (BLE) Application and Blynk Cloud Server for remote control and monitoring. This system uses the MQ-3 sensor to continuously monitor the blood alcohol concentration (BAC) and detect the presence of alcohol during breathing. This system can continuously monitor the alcohol content of the driver's breathing by installing a sensor in the steering wheel. This device was capable of detecting excessive speed and was programmed to alert with an SMS. After testing, it was determined that the suggested system met the standards for starting a car's engine. If the driver's breath alcohol level is discovered to be greater than the prescribed level (BAC) of 0.5 mg/mL, relevant individuals and authorities will be notified through GSM. The experimental results indicate that the alcohol sensor can respond rapidly when alcohol is detected and also operate for an extended period.

IOT BASED SMART HOME AUTOMATION AND MONITORING SYSTEM

The concept of a smart home is becoming increasingly popular these days. It reduces the amount of physical labor required. In a traditional home, we cannot monitor the electrical appliances, environmental conditions, home security, and cannot control them remotely. Typical residential systems cannot automatically change a systems state in response to a specific scenario. However, this study proposes an IoT-based smart home automation system that works in different modules to automate the entire home. In one module, the system determines the human movement inside the room by using a IR sensor and detects the light level using an LDR sensor. The light level will be adjusted based on the output of the IR sensor. Also, the system operates the fans and heater based on the home temperature and humidity by using an AM2301 sensor. In another module, a flame sensor aids the detection of fire, MQ-135 sensor measures the air quality. In case of fire is detected in the home, the system will also alert the users instantly. To control everything remotely, a mobile application (Blynk App) is used. Converting to a smart home, it can provide security, energy efficiency, and the ability to manage every existing home appliance from a centralized location or remotely. As a result, the system focuses on generating the most excellent possible environmental conditions while requiring the least amount of human effort possible. Beyond everything, it helps in saving time in every manner conceivable.

Air Pollution Monitoring System Using Micro Controller Atmega 32A and MQ135 Gas Sensor at Chandragiri Municipality of Kathmandu City

Air is one of the essential elements of human’s surroundings. The earth’s atmosphere is full of air which contains gases such as Nitrogen, Oxygen, Carbon Monoxide and traces of some rare elements. But quality of the air has been degrading for some decades due to various activities conducted by the human beings that directly or indirectly affect the atmosphere leading to the air pollution. There are different techniques to measure air quality.However, with the evolution of time the expensive and less efficient analog devices have been replaced by more efficient and less expensive electronics device. In this research, MQ135 sensor is used to measure air quality of a particular location. I2C display is used to monitor the data. Indeed, with the increasing in number of vehicles, unplanned urbanization and rapid population growth, air pollution has considerably increased in the last decades in various areas of Kathmandu. Thus, this project ‘Air Pollution Monitoring System’ was focused on collection of the data specific location of Chandragiri municipality of Kathmandu city. In conclusion,analysis of the data is done with the help of origin software which shows that the Arduino device in this device works perfectly for measuring the air pollution. Air quality of the selected area is found to be less than 500 PPM which concludes that the air quality of this area is normal.

IoT Based Air Quality Monitoring System

IoT Based Air Pollution Monitoring System '' supports showing the quality of air in PPM over the LCD along with that on the web sheet therefore, as this can simply be scrutinized. In order to show the impact of “IoT based Air Quality Monitoring System '', flowcharts, graphs, digraphs and tables have been shown in an effective manner. According to the Statista, it has been estimated that “air quality monitoring IoT '' services along with products would be a significant economic value of 50 up to 60 billion US dollars by the year of 2025. In the present times the condition of air is not that good due to the increasing pollution rate in the past several years. In order to conduct this research work in an effective manner, a secondary data collection method has been taken and all the secondary data resources have been taken to conduct the research in a suitable manner. “IoT based Air Quality Monitoring system” has been suitably designed to quantity the mutual “air quality index” and it also helps in standardizing the results with “India’s Air Pollutant Index'' to suitably indicate the strictness of air superiority. The most harmful air pollutant gasses are NOx, LPG, CO2, NH3, Benzene, alcohol and benzene. In addition, with the help of this system, temperature along with humidity both can effectively be monitored. LPG gas has been suitably detected to use MQ135 and MQ6 sensors and this has been used for monitoring the air’s quality as it helps in detecting all these harmful elements. In this research work, it has been shown that focusing on “Triple Bottom Line '' theory can be effective as this theory helps in showing the ways through which environmental sustainability can be maintained easily. Keyword : IoT based Air Quality Monitoring system, India’s Air Pollutant Index, air quality monitoring IoT .

Design of Formaldehyde Detector Based on Gas Sensors

Food products that are extensively distributed in the community, notably in traditional markets, and often consumed by the public, such as tofu, are frequently discovered to contain formaldehyde, according to BPOM laboratory tests in 2020. In reality, the usage of these materials is quite hazardous. As a result, a more accurate and cost-effective detector for detecting formaldehyde is required. Therefore, the authors of this study intended to create a formaldehyde detector based on a gas sensor. The purpose of this research was to design a formaldehyde detector utilizing a gas sensor and to identify a gas sensor that can detect formaldehyde. The gas sensors that were utilized in this research were MQ-2, MQ-4, MQ-5, MQ-6, and MQ-9 gas sensors. The test was carried out on a specific sort of pure formaldehyde solution with a determined concentration. There were five replications of each treatment: 0 ppm, 100 ppm, and 200 ppm formaldehyde solutions. Based on the results of the study, the gas sensor with an adequate response to detect formaldehyde is MQ-2 at concentrations of 0 ppm, 100 ppm, and 200 ppm. Conversely, MQ-4, MQ-5, MQ-6, and MQ-9 gas sensors were less accurate to formaldehyde compounds.

Rancang Bangun Alat Pendeteksi Kebocoran Gas LPG Berbasis Internet of Things Dengan Katup Regulator Otomatis

Liquefied Petroleum Gas (LPG) is a flammable gas. Leaks in LPG gas cylinders that are not known to the user can have a fatal impact if there is no system that detects and stop the leak. Therefore, this study designed a system to detect and solve LPG gas leaks based on the Internet of Things automatically. The way this system works is that the MQ-6 sensor detects the concentration of LPG gas around the cylinder with an analog value limit when the safe condition is <400 and the danger condition is 400. The sensor will continue to detect as long as the tool is on and send data to the microcontroller in the form of NodeMCU ESP8266 which then transmits the data to Firebase. From Firebase, users will get information about LPG gas levels in safe/dangerous conditions, gas position control, as well as fan and buzzer conditions through a smartphone application in real time. If the conditions are safe, the green LED will light up and the condition is dangerous, the microcontroller will physically respond to the servo motor to turn the regulator valve open, the fan, the red LED and the buzzer while virtually the user will get information through the application and notifications via the WhatsApp application in the form of a short message as a warning that gas was detected. The test results show that the LPG gas detection system can work well.

Design of a Weather Station with IoT in the Wetlands of the District of Ventanilla – Callao.

Currently, pollution and global warming is a very controversial problem, due to the various consequences and effects it generates on health and the environment. There are studies that highlight that the main pollutants are due to human action that generates the extermination of certain ecosystems, as well as the increase in various acute and chronic diseases. The ecosystems most neglected by the authorities and the citizens are the wetlands, which can be seen reflected in the wetlands of Ventanilla, whose surface has been reduced from 1,500 to 275.45 hectares due to overpopulation and contamination by the citizens themselves in recent years. These accessions endanger the extermination of the habitat of 126 birds and 27 species of native plants that inhabit a certain place, which is of great concern because these ecosystems are rapidly degrading. That is why, in the face of this problem, the design of a weather station applying the internet of things is proposed, which aims to inform the caretakers of the current state of the wetlands through a web server, where it will serve to carry out preventive actions. regarding the care of a certain ecosystem that are essential for the stabilization of CO2 emissions. This system is made up of the ESP32 platform, which will activate the emergency lights and a siren when the DHT 22, BMP180, ML8511 and MQ135 sensors detect abnormal values in temperature, humidity, atmospheric pressure, altitude, UV radiation and toxic gases.

Chloro Fluro Carbon Gas Leak Monitoring System in Internet of Things-Based Air Conditioner

Refrigerant leaks have a major impact on system operating performance, increasing power consumption, damage to components, and worse, global warming. This study aims to use a monitoring system based on the Internet of Things (IoT) to track Chloro Fluro Carbon gas in the air conditioning system. Using NodeMCU as a microcontroller-based control tool that has been assisted by a Wi-Fi module. The sensitivity level of refrigerant leakage is very high based on the sensitivity of the sensor used, namely MQ135. In experimenting, the refrigerant leak starts with the closest distance to the inaccessibility of the sensor readings to determine the acceleration of the sensor in detecting leaks. The voltage required for the MQ135 sensor is 5 Volt DC. This system uses an android application, namely blynk which has features for monitoring and warning users that the AC unit has detected a leak. The results of measuring the sensitivity level of the sensor are very high for alcohol, benzene, and NH3 gases. It can detect small leaks at a distance of 20 cm, at a moderate level of leakage it can detect further at 80 cm, and at a maximum detection level at a distance of 160 cm in closed rooms or low winds. Because the leakage distance is quite far, it will be affected by the wind, the sensor reading will be hampered because the refrigerant cannot hit the sensor.

IoT-Based Harmful Toxic Gases Monitoring and Fault Detection on the Sensor Dataset Using Deep Learning Techniques

One of the main reasons for accidents among workers is harmful gas leakage. Many people die in chemical industries and their surrounding areas. The present invention is responsible for monitoring and controlling hazardous toxic gases like nitrogen dioxide (NO2), carbon monoxide, ozone (O3), sulfur dioxide (SO2), LPG, hydrocarbon gases, silicones, hydrocarbons, alcohol, CH4, hexane, benzine, as well as environmental conditions, such as temperature and relative humidity to prevent industrial accidents. The Arduino UNO R3 board is used as the central microcontroller. It is connected to the Cloud via AQ3 sensor, Minipid 2 HS PID sensor, IR5500 open path infrared gas detector, DHT11 Temperature and Humidity Sensor, MQ3 sensor, and ESP8266 and WIFI Module, which can store real-time sensor data and send alert messages to the industry’s safety control board. Machine learning and artificial intelligence will be used to make an intelligent prediction (AI). The information gathered will be examined in real-time. The real-time data provided through the sensor can be accessed worldwide. Sensor data quality is critical in the Internet of Things (IoT) applications because poor data quality renders them useless. Error detection in sensor data improves the IoT-based toxic gas monitoring, controlling, and prediction system. Live data from sensors or datasets should be analyzed properly using appropriate techniques. Hence, hybrid hidden Markov and artificial intelligence models are applied as an error detection technique in the sensor dataset. This technique outperformed the dataset gas sensor array under dynamic gas mixtures and lived data. Our method outperformed harmful gas monitoring and error detection in sensor datasets compared to other existing technologies. The hybrid HMM and ANN fault detection methods performed well on the datasets and produced 0.01% false positive rate.

Analysis of Air Quality Measuring Device Using Internet of Things-Based MQ-135 Sensor

Air is a gas that is indispensable for the survival of living beings. As the times progress, the air we breathe is increasingly not good for the health of living beings. In most situations, humans cannot tell the difference between good and bad air conditions. The purpose of this research is to design a tool that can monitor air quality in many places using an Internet of Things-based concept, the MQ-135 gas sensor and display it on a 16x2 LCD and Blynk application. This study uses a direct test method to identify gases around the MQ-135 sensor with the NodeMCU ESP 8266 as a controller. Air quality is divided into 5 categories, which consists of good, average, unhealthy, very unhealthy, and dangerous. After the air quality value is displayed on the 16x2 LCD screen, the user can monitor the air quality remotely using the blynk application on the smartphone. It can be concluded that the design of this tool can detect air quality in classrooms, vehicle exhaust fumes, gas lighters, house rooms, and burned paper. If the air quality is bad, the buzzer will release the sound to notify that the air quality is poor according to the index of air quality.

Mobile Gas Leakage Detection System

Abstract: The most prominent industrial disasters are caused due to gas leakage. One of the preventive methods to stop accident associated with the gas leakage is to install mobile gas leakage detection system at vulnerable places. The aim of this paper is to present such a design that can automatically detect the gas leakage and send alerts to the nearby workers in vulnerable premises. Gas sensor has been used which has high sensitivity for propane (C3H8) and butane (C4H10). Gas leakage system consists of Arduino microcontroller with inbuilt Wi-fi module (ESP8266), ultrasonic sensor for crack detection, MQ2 sensor for gas leakage detection and Blynk app to receive the alerts. This paper provides the design approach on both software and hardware

Rancang Bangun Alarm Kebocoran Gas Lpg Dengan Sensor MQ-2

In today's human life, both at home and in industry, it is very necessary to have LPG gas to meet daily needs. We know that gas can also have a bad impact, especially if there is no known leak from the LPG gas cylinder or storage area. The cause of this gas cylinder leak could be a leak in the hose, tube or also the regulator that is not installed properly and the gas cylinders that are distributed are of poor quality or physically damaged. This study aims to produce a tool that is an LPG gas cylinder leak alarm using the MQ-2 sensor. The way this tool works is, the Arduino UNO reads the MQ-2 sensor with analog data output, if it reads that there is gas leaking, the alarm will sound.

A Simple and Real-Time Support System for Firefighters Using Low-Cost 3-DOF Accelerometer and CO Sensor

During the operations, firefighters can be injured or killed because of the smoke and heat emission from the fire area, broken structure elements such as floors, walls, or boiling liquid ejection and gas explosion. Therefore, this paper aims to develop an efficient and portable system to monitor falls and high CO level through integrating a three degrees of freedom accelerometer and an MQ7 sensor to recorded acceleration and measured CO concentration with the embedded fall and high CO detection algorithms. The embedded fall detection algorithm can detect fall events with ultra-high accuracy without mistakenly identifying normal activities such as walking, standing, jogging, and jumping as fall events. The posture recognition and cascade posture recognition after three seconds are proposed in this paper to gain the accuracy of our proposed fall detection system. If a firefighter falls and is unable to stand up, the alert signal message will be sent to their commander outside through the GSM/GPRS module. The embedded high CO detection algorithm used to alert the dangerous CO level to recommend using self-contained breathing apparatuses (SCBA) and saving fresh air with acceptable CO level. We carefully investigated the proposed thresholds and window size before embedding them into the microcontroller. The sensitivity and accuracy achieved were around 96.5% and 93% respectively in our recorded data. Furthermore, the proposed fall detection algorithm also achieved higher geometric mean in comparison with Support Vector Machine classifier (SVM) and a nearest neighbor rule (NN) in the public datasets with the achieved around 99.44%, 98.41% and 95.76% respectively.

Android Based Spark and Gas Leak Detection and Monitoring

LPG cylinder leakage is one of the causes of fires in the community. To prevent fires, a fire and gas leak detection and monitoring device were made using a fire detector sensor and an Android-based MQ-6 to trigger it. Data collection techniques in the manufacture of gas and fire leak detection using a flame detector and the MQ-6 sensor can be obtained from datasheets, journals, books and articles, and several internet sites that support the manufacture of this device. In the manufacture of gas leak detection devices or tools, there are also two parts, namely the first to make hardware (hardware), then software (software). The result of this tool detection is that users can find out the level of LPG due to leaking of LPG cylinders and detect fire using Android notifications in real-time and the data is displayed in detail on the browser page. The conclusion of this study is that users are safer because there is a gas leak, the tool will detect LPG gas, then a message will be displayed on the LCD screen and a notification on Android and the buzzer will automatically turn on. If there is a fire from detecting the gas leak, the fire detector will detect the fire, which will result in a notification sent to Android that there is a fire and the buzzer will turn on

Pendeteksi Kebocoran Gas dan Kebakaran Dini Menggunakan NodeMCU Berbasis Telegram

The utilization of natural resources and energy is increasing day by day, one of which is the use of natural gas as fuel for both household and industrial needs. Safety aspects in the use of this gas must be considered because gas leaks can trigger fires. Therefore we need a tool that can detect and notify gas leaks as early as possible. This study proposes a gas leak detector based on the Internet of Things (IoT) using NodeMCU ESP8266 as a microcontroller. This detection system uses the MQ-2 sensor as a detector of gas levels and a flame sensor as a detector of ultraviolet light as an indication of a fire. The resulting output is a notification message from the Telegram Bot sent via NodeMCU. In this case, the buzzer and LED will give a signal if the MQ-2 sensor detects gas levels above 500 ADC, then the NodeMCU will send a command to the Telegram Bot to send a notification message in real-time. In addition, the detected gas levels are also displayed on the 16x2 LCD screen. The experimental results show that the ideal distance to detect gas is under 6 cm and fire below 20 cm with a sensor response time of 2 seconds. The existence of this tool is expected to minimize the risk of fire due to gas leakage.
 Keywords—fire, gas leak, NodeMCU, Telegram

Internet of Things-based Gas Leak Detection with Alerts Via SMS and Blynk App

Gas cylinders are one of the needs that humans use every day. The use of gas cylinders is often used for cooking, both for household needs and industrial needs. Gas leaks are a big problem that can give rise to explosions and fires due to combustible gas. Explosions and fires that occur as a result of this gas leak can cause a lot of losses. This study aims to build an Internet of Things-based gas leak detection tool using NodeMCU ESP8266 as a microcontroller that functions as a brain to execute commands that have been made. Blynk App and SMS to provide information to users in case of gas leaks detected by MQ-6 sensors. This tool will detect gas leaks that occur by receiving data from the MQ-6 sensor which is then processed by NodeMCU ESP8266. If a gas leak is detected, the buzzer will sound and the tool will give an alert by popping up a notification on the Blynk application with an internet connection and sending an alert via SMS so that the alert can be sent even in the absence of an internet connection. With this tool, users can find out earlier if there is a gas leak by getting a notification on the Blynk application and receiving a gas leak SMS, to avoid explosions and minimize damage and losses caused by gas leaks.

IoT Based Coal Mine Tracking and Worker Safety Emergency Alert

Abstract: Due to global warming and climate change, there are now difficult conditions in the coal mining industry. Automation in the field of coal mine-shaft is in fact necessary to reduce costs and boost profitability while also improving product quality, and it will also reduce diggers' efforts. Mining is both necessary for the manufacture of goods, infrastructure, and services that improve people's lives and one of the world's most dangerous trades. The need for coal as a source of energy is always high and significant. However, hundreds of people have died in mining accidents around the world, and working in the earth poses a variety of security and health risks. Underground miners in some nations lack safety and social protection, and in the event of injury, they may be left to fend for themselves. There are also negative societal consequences, such as displacement and lost income. Among all industries, the mining industry has the greatest rate of occupational mortality. Rock falls, a sagging roof, and a sagging pillar are all common causes of workplace deaths. Underground mines provide a lot of case studies. To deal with all of these tragedies, we need to improve communication technology, which will be used to create an intelligent sensing and warning system. For communication within the mines, RF technology has been adopted. So, utilizing a microcontroller-based circuit on worker safety, we suggest a mining tracking and safety system for the mining business. To detect workers moving throughout the mining site, we deploy RF-based circuitry. The main microcontroller was an ARDUINO UNO. The system employs ATMEGA microcontroller-based RF tracker circuitry to transmit and receive data through the usage of an EM-18 RFID reader module and RFID cards. This aids in the tracking of workers' present locations across the entire mining site. The DHT11 sensor is used to determine the current temperature and humidity. The accelerometer sensor is used to determine whether or not a worker has fallen. MQ2 and MQ135 sensors are used in mines to detect dangerous chemicals and smoke and inform workers. A flame sensor detects a fire in a mine and alerts the workers. Furthermore, safety is the most important aspect of every industry. Safety and security are extremely important in the mining business. Each RFID card circuit includes an emergency button to prevent any form of mishap. When this button is touched, an emergency alert appears. This technology can be used to safeguard the safety of mine workers through the usage of IoT