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Relevant bibliographies by topics / MQ Sensor

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Academic literature on the topic 'MQ Sensor'

Author: Grafiati

Published: 5 June 2025

Last updated: 15 July 2025

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Journal articles on the topic "MQ Sensor"

1

Dr. S.Usha, Sadhari Viswa Teja, Vemula Siva Dilip, and R Subhash Reddy. "Machine Learning-Driven System for Real-Time Air Quality Monitoring and Prediction." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 2781–90. https://doi.org/10.32628/cseit251112283.

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This project introduces a machine learning-driven system for real-time air quality monitoring and prediction, utilizing MQ-135, MQ-9, and MQ-6 sensors alongside a DHT sensor. The MQ-13 sensor measures the concentration of carbon dioxide (CO2) and ammonia (NH3), the MQ-9 sensor detects methane (CH4) and liquefied petroleum gas (LPG), while the MQ-6 sensor monitors alcohol and carbon monoxide (CO) levels. The DHT sensor provides concurrent temperature and humidity data. This multi-sensor data is collected and transmitted to a machine learning model to compute the Air Quality Index (AQI), which represents the overall air quality. The system aims to deliver accurate, real-time air quality assessments and predictive insights, enabling timely interventions and better environmental management. By combining diverse sensor data with advanced machine learning techniques, this approach enhances the precision and effectiveness of air quality monitoring and prediction.

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Rusdianto, Andrew Setiawan, Winda Amilia, and Laila Adhani Putri Malik. "Design of an E-Nose Detector for Contaminated Gas in Cow Farming Waste." International Journal on Food, Agriculture and Natural Resources 4, no. 4 (2023): 62–69. http://dx.doi.org/10.46676/ij-fanres.v4i4.213.

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Cattle farm waste is organic waste produced by the livestock industry in the form of feces and can emit gases that cause air pollution. Cow dung contamination can cause environmental problems, disturbing humans and livestock. Hazardous gases produced from the decomposition of livestock manure, namely methane (CH4), sulfur dioxide (SO2), ammonia (NH3), and hydrogen sulfide (H2S), can cause respiratory diseases, deplete ozone and contribute to the greenhouse effect. Based on these problems, measuring gas levels using an Electronic Nose (E-Nose) tool capable of detecting harmful gases in livestock pens is necessary. The E-nose is a device that mimics the human nose and consists of several gas sensors that can detect environmental odors. The design of the detection and measurement of toxic gases using an electronic nose in this study adopts the Internet of Things (IoT) concept using the Arduino Uno and ESP8266 microcontrollers and MQ-4, MQ-136, and MQ-137 gas sensors to read levels of pollutant gas in units of ppm with an average of 46.25 ppm for the MQ-4 sensor, 1.86 ppm for the MQ-136 sensor, and 4.97 ppm for the MQ-137. The sensors were subjected to functional tests consisting of validity testing, resulting in a calculated r value of 1, meaning that each gas sensor performs its measurement function correctly or validly. The reliability test of the MQ-4 sensor is 0.00, the MQ-136 sensor is 2.442× 10-15, and the MQ-137 sensor is 1.554× 10-15, which means that the data reading from each gas sensor is unstable, less accurate, or unreliable compared to secondary data. However, the designed E-Nose tool can work well and improve farmers' performance in their daily work.

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Sihombing, Yuan alfinsyah, and Muhammad Dennis Herlambang. "Detection and Extraction of Aroma Characteristics of Fuel Oil Using Gas Sensors Through Electronic-Nose System." Journal of Technomaterial Physics 4, no. 2 (2022): 150–56. http://dx.doi.org/10.32734/jotp.v4i2.9440.

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Fuel oil is an indispensable strategic source of energy for the fuel of vehicles and other engines. This study aims to detect and differentiate fuel oil using an electronic-nose system. The fuel oil used is Pertalite, Pertamax, and Pertamax Turbo. Four gas sensors are used, namely MQ 4, MQ 7, MQ 9, and MQ 136. The average output voltage values of Pertalite, Pertamax, and Pertamax Turbo fuel oil for MQ 4 sensors are 1.07 V, 1.22 V, and 0.96 V. For MQ 7 sensors, the output voltage values of the samples are 1.44 V, 1.43 V, and 1.37 V, respectively. For the MQ 9 gas sensor, the sample output voltage values are 1.23 V, 1.43 V, and 1.09 V. As for the MQ 136 gas sensor, the output voltage value of each oil is 1.26 V, 1.25 V, and 0.91 V. Sensors that provide the highest response in each sample are MQ 136 sensors. The electronic-nose system can extract characteristics from all three samples using the principal component analysis (PCA) method.

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Ajiboye, A. T., J. F. Opadiji, A. O. Yusuf, and J. O. Popoola. "Analytical determination of load resistance value for MQ-series gas sensors: MQ-6 as case study." TELKOMNIKA Telecommunication, Computing, Electronics and Control 19, no. 2 (2021): pp. 575~582. https://doi.org/10.12928/TELKOMNIKA.v19i2.17427.

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The MQ-series gas sensors are attractive candidates in the area of gas concentration sensing due to their high sensitivity and low cost. Even though the sensor circuit sensitivity and sensor power dissipation level both depend on load resistance, the process of the load resistance selection has not been well researched, hence the need for this study. The derivation of model equations for determining the sensor circuit sensitivity and sensor power dissipation is presented. The derived equations were used to investigate a typical scenario of MQ-6 gas sensor under the influence of liquified petroleum gas (LPG). The variation of sensitivity with load resistance and that of power dissipation with sensor resistance were parametrically investigated. The load resistance that yields maximum sensor circuit sensitivity with the maximum sensor power dissipation less than the set threshold is the candidate resistance for the sensor circuit. The 20 kΩ load resistance recommended for MQ-6 in the datasheet was authenticated in this study, yielding the maximum possible sensor circuit sensitivity and tolerable sensor power dissipation of 0.195 mV/ppm and 3.125 × 10-4 W, respectively.  

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Ainur Rahma, Mellynia, Melania Suweni Muntini, and Iwan Sugriwan. "Methane (CH₄) Detection System Using The TGS2611 Sensor and MQ-4 Sensor." Journal of Physics: Conference Series 2780, no. 1 (2024): 012034. http://dx.doi.org/10.1088/1742-6596/2780/1/012034.

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Abstract This research focused on cow dung digesters as measurement samples, utilizing the TGS2611 and MQ-4 sensors, both known for their affordability. The objective was to develop a low-cost gas sensor system for monitoring methane gas concentrations through a straightforward web-based data acquisition platform. The DHT11 sensor was employed to measure air temperature and humidity. The electronic sensor circuit in this research utilized a voltage divider circuit. Testing the performance of the low-cost gas sensor involved integrating it with an anaerobic digestion system. For both the TGS2611 and MQ-4 sensors, the graph illustrating the relationship between sensor voltage (volts) and methane gas concentration (ppm) formed a logarithmic or non-linear pattern. The measurement range for the system was around 4700 ppm to 6300 ppm for TGS2611 and 4000 ppm to 5100 ppm for MQ-4. The sensor sensitivity was determined as 0.5433 Volts/ppm for TGS2611 and 0.5639 Volt/ppm for MQ-4. The TGS2611 sensor exhibited a higher response to changes in methane gas concentration, while the MQ-4 sensor successfully detected methane gas within its designated range. Interestingly, the TGS2611 sensor accurately detected methane gas concentrations above its specified range. The gas sampling procedure involved automatic gas sampling in a vacuum chamber for measurement, a strategy potentially enhancing sensor robustness. This research successfully amalgamated sensor advantages, circuit control, and data analysis to realize an economical yet reliable monitoring system.

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Kuncoro, Purwoko Hari, Arief Sudarmaji, Susanto Budi Sulistyo, Krissandi Wijaya, and Agus Margiwiyatno. "Respon dan Akurasi Sensor Gas MOS (MQ-Series Module) Dalam Mengidentifikasi Minyak Nilam (Patchouli Oil)." Jurnal Keteknikan Pertanian Tropis dan Biosistem 11, no. 1 (2023): 28–40. http://dx.doi.org/10.21776/ub.jkptb.2023.011.01.03.

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Dalam penelitian ini dilakukan pengujian terhadap sensor gas MOS tipe MQ (MQ-2.1, MQ-2.2, MQ-3, MQ-4, MQ-5, MQ-6 MQ-7, MQ-8, MQ-9, dan MQ-135) untuk mendeteksi kemurnian minyak nilam. Penelitian ini dilakukan dengan tujuan: 1) mempelajari respons sensor gas MOS tipe MQ dalam mengidentifikasi kemurnian minyak nilam, dan 2) mempelajari akurasi sensor gas MOS tipe MQ dalam mengidentifikasi kemurnian minyak nilam. Minyak nilam yang digunakan adalah minyak nilam pada berbagai tingkat pencampuran dengan minyak zaitun. Terdapat 2 jenis perlakuan yang diamati, yaitu: dengan pemanasan dan tanpa pemanasan. Pengukuran dilakukan terhadap nilai Baseline measurement (Ro) dan Atsiri measurement (Rg) guna menentukan nilai sensitivitas sensor (S). Selanjutnya nilai Rg dan S digunakan untuk membuat grafik loading plot berdasarakan metode PCA (Principal Component Analysis) untuk menentukan respon individu setiap sensor. Tingkat akurasi sensor dalam mendeteksi minyak nilam ditentukan berdasarkan: identifikasi minyak nilam menggunakan grafik score plot, klasifikasi data menggunakan metode COG (Center of Gravity) dan ED (Euclidean Distance), serta penghitungan akurasi. Dari kesepuluh sensor gas yang diujikan, terdapat 2 sensor yang memberikan respon rendah yaitu MQ-3 dan MQ-7. Sedangkan 8 sensor yang lain memberikan respon yang baik dan relatif stabil, dengan respon tertinggi diperoleh dari sensor MQ-4. Rerata tingkat akurasi sensor yang dihasilkan pada nilai resistensi (Rg) lebih tinggi dibandingkan nilai sensitivitas (S), dan lebih tinggi pada perlakuan tanpa pemanasan dibandingkan perlakuan dengan pemanasan. Pada perlakuan tanpa pemanasan nilai rerata akurasi Rg dan S masing-masing adalah 88.79% dan 79.51%, sedangkan pada perlakuan dengan pemanasan masing-masing adalah 80.84% dan 74.52%.

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Carrillo-Amado, Yersson Ramiro, Miguel Angel Califa-Urquiza, and Jacipt Alexander Ramón-Valencia. "Calibration and standardization of air quality measurements using MQ sensors." Respuestas 25, no. 1 (2020): 70–77. http://dx.doi.org/10.22463/0122820x.2408.

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To perform the calibration and standardization of the air quality measurements through the MQ sensors, a mathematical relation was used based on the information provided by the manufacturers of the sensors through their data sheets, using the linear mathematical regression model that allowed to create the libraries for the sensors MQ-2, MQ-3, MQ-4, MQ-5, MQ-6, MQ-7, MQ-8, MQ-9, MQ-135, MQ-131, MQ-303A, MQ-309A, These libraries are characterized by being open source, and are available to the public, whose software tool allows to take values in parts per million (ppm) from the value of the resistance read in the sensor, allows to obtain data which are similar to other scientific studies given that they give in the same units, which serve to perform studies in the environment, pollution, analysis in industrial processes.

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AJIBOYE, Aye Taiwo, Jaye Femi OPADIJI, and Adebimpe Ruth AJAYI. "GRAPHICAL METHOD FOR DETERMINATION OF MQ-SERIES GAS SENSOR CIRCUIT PARAMETERS FOR A STAND-ALONE GAS ALARM SYSTEM." SOUTHERN BRAZILIAN JOURNAL OF CHEMISTRY 29, no. 31 (2021): 01–09. http://dx.doi.org/10.48141/sbjchem.v29.n31.2021.01_ajiboye_pgs_01_09.pdf.

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Background: MQ-series gas sensors belong to the metal oxide semiconductor (MOS) family of sensors that can sense the presence of many gases. These sensors find their application in gas alarm systems as key components. While necessary sensor circuit output voltage value for alarm point in a stand-alone gas alarm system is desirable, but what exact combination of the sensor circuit parameters is required? Hitherto, the determination of these circuit parameters has not been given much attention in the research community. Aim: the purpose of this work is to explore a structured graphical approach of determination of MQ series gas sensor circuit parameters for a stand-alone gas alarm system that yields desired sensor circuit output voltage value for the alarm point; the main objective of the study was to develop mathematical model equations that relate the: (i) sensor resistance (RS) with the gas concentration (x) and the sensor resistance at standard calibration concentration of the sensor base gas in the clean air (Ro) and (ii) sensor circuit output voltage (VRL), load resistance (RL) and sensor resistance (RS). It is expected from the model equations developed that graphical correlations of the sensor circuits parameters will be generated. Using these graphs for a particular case of an MQ-4 gas sensor under the influence of LPG, the parameters that yield desired sensor circuit output voltage of 2V for 1000 ppm of LPG alarm point will be determined. Methods: Model equations were developed for the sensor dynamics, and based on these model equations, graphs for the determination of required sensor parameters were plotted for a case of MQ-4 gas sensor response to LPG. Results and Discussion: The results yielded optimal values for R_O,R_S and R_L of 20 kΩ, 30 kΩ and 20 kΩ respectively, for alarm settings of 1000 ppm and a desired sensor circuit output voltage of 2 V. Based on determined parameters, the calibration equation for determination of best concentration value for a given value of emulated LPG concentration was developed. Using the method proposed in this study makes the process of determining the MQ-series gas sensor circuit parameters less cumbersome as their value can easily be obtained from the resulting graphs. Conclusions: a structured graphical approach for determination of MQ-series gas sensor circuit parameters for alarm points in a stand-alone gas alarm system showed that using MQ-4 gas sensor and LPG as the target gas, and for a sensor circuit output voltage of 2 V for alarm point at 1000 ppm of LPG, the corresponding value of R_O, R_S and R_L obtained were 20 kΩ, 30 kΩ, and 20 kΩ respectively. Hence, a structured graphical approach is suitable for determining MQ series gas sensor circuit parameters for a stand-alone gas alarm system under the influence of its associated gases.

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Prasad, Ram. "Microcontroller based AVR Hazardous Gas Detection System using IoT." International Journal on AdHoc Networking Systems 13, no. 2 (2023): 01–07. http://dx.doi.org/10.5121/ijans.2023.13201.

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MQ-6 Semiconductor Sensor for Combustible Gas detection is a Sensitive Gas sensor. The sensitive material of this MQ-6 gas sensor is SnO2, which works with lower conductivity in clean air. When the target combustible gas exist, the sensors conductivity is higher along with the gas concentration rising. As the conductivity increases the current in the circuit of the sensor increases which results in lower sensor resistance. This change is used to correspond, the output signal of gas concentration. MQ-6 gas sensor has high sensitivity to Methane, Propane and Butane and could be used to detect both Methane and Propane. The sensor could be used to detect different combustible gas especially Methane, it is with low cost and suitable for different application.

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Laksmana, Bisma. "Rancang Bangun Alat Penanganan Dan Pengendalian Kebakaran Berbasis Arduino Nano Dengan Si stem IoT." Teknologi Rekayasa Jaringan Telekomunikasi (TRekRiTel) 1, no. 1 (2021): 1–12. http://dx.doi.org/10.51510/trekritel.v1i1.395.

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This will be very useful for residents of the house to prevent what can cause a fire incident. In the main research, system design will make a fire detector and smoke and gas detector, using 3 Flame Sensors and 3 MQ-2 Sensors. This design concept will be installed in each room which consists of 3 rooms. The microcontroller used in this design system is an Arduino Nano microcontroller which functions as part of the Flame Sensor controller, MQ-2 Sensor, WeMos D1 Mini, Relay, and Buzzer. Furthermore, the system output uses a Flame Sensor which is already in a HIGH state so that it can activate automatic shutdown, and the tool can submit a notification to the occupants of the house via an android application called Blynk and an alarm sounds. If the implementation of the MQ-2 Sensor is in a HIGH state, the system will provide warning instructions in the form of a notification from the android and an alarm will sound for the occupants of the house. So that the residents of the house will be prepared to take action to extinguish the fire in the house. Keywords : Fire, Flame Sensor, MQ-2 Sensor

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Book chapters on the topic "MQ Sensor"

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Sharma, Prerna, and Suman Madan. "Comparative Analysis and Experimental Study on MQ Sensor Series." In Healthcare and Knowledge Management for Society 5.0. CRC Press, 2021. http://dx.doi.org/10.1201/9781003168638-12.

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Kavya, C., R. Janis, P. Ezilarasi, and S. Rajesh Kannan. "Development of a Non-Invasive Glucose Monitoring System using Acetone Gas Detection via Exhaled Breath Analysis and MQ Sensor Integration." In Atlantis Highlights in Engineering. Atlantis Press International BV, 2025. https://doi.org/10.2991/978-94-6463-754-0_16.

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Borah, Abinash, Sandeep Jangid, Amisha Kumari, Anita Gehlot, and Rajesh Singh. "Pollution Control by Installation of MQ-Smoke Sensors in Car Exhausts with IOT-Based Monitoring." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5903-2_124.

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Andriyadi, Anggi, Chandra Wijaya, Shih-Yen Chen, Ding-Hsiang Huang, and Chao-Tung Yang. "Edge AI Robot Technology Application with YOLOv8, MQTT and MQ-5 Sensors for Realtime Fire and Smoke Detection." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2395-2_11.

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Syedakbar, S., S. SankaraNarayanan, B. Seralathan, and F. Allwin Raj. "ENSURING FOOD QUALITY BASED ON IOT." In Futuristic Trends in IOT Volume 3 Book 8. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3baio8p7ch3.

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The objective of this project is to create a food quality sensor system utilizing the Arduino platform and a DHT-11 temperature and humidity sensor and the MQ-3 alcohol vapour detection sensor .The system provides a cost-effective solution for monitoring the freshness and safety of perishable food items. The DHT-11 sensor is employed to measure the temperature and humidity levels inside a food storage container. By monitoring these parameters, the system can determine whether the storage conditions are suitable for maintaining the quality of the food. If the temperature or humidity deviates from the desired range, the system can trigger an alert to notify the user. The MQ-3 sensor is utilized to detect alcohol vapour, which can be an indicator of food spoilage or contamination. When certain foods undergo decomposition, they release volatile compounds such as ethanol. The system can now detect the presence of alcohol vapours and generate an alert if detected beyond a predetermined threshold thanks to the integration of the MQ-3 sensor. The central processing unit for gathering data from the sensors and carrying out the required algorithms is the Arduino microcontroller. It interfaces with the DHT-11 and MQ-3 sensors to retrieve sensor readings. These readings are then processed to determine the food quality status. The Arduino can be programmed to send notifications via SMS, email, or other communication methods to inform the user about any potential issues. Overall, this food quality sensor system provides a cost-effective and easily implementable solution for monitoring the freshness and safety of food items. It can be utilized in various settings, including homes, restaurants, or food storage facilities, to ensure that the stored food remains within optimal conditions and to prevent the consumption of spoiled or contaminated items

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J, Sathya Priya, Bharathi S L, and Sathyabama A R. "Anomaly Based Sensor Nodes with IoT for Environment Sustainability." In Intelligent Systems and Computer Technology. IOS Press, 2020. http://dx.doi.org/10.3233/apc200206.

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The proposed works implements a prototype of detecting harmful gases in a given environment, along with air and water quality monitoring. This device is capable of detecting temperature and LPG leakage in home environment, monitoring water quality in a given area along with warm body detection and methane concentration inside drains. The temperature and LPG leakage is detected with the help of temperature and MQ-6 sensors, the water quality is monitored with the help of pH and turbidity sensors. The human presence inside the drain is detected with the help of PIR sensor and methane concentration with the help of MQ-4 sensor. The sensor nodes are based on wifi enabled Arduino microcontroller, that receives data from the sensors and converts it into digital data that are transmitted to the webpage. The main concern of this paper is the real time monitoring of various parameters by implementing low-cost sensors that are useful for both home and the society.

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Vijay Patil, Durgesh, Parikshit Sharadkumar Mali, Om Kamlakar Chaudhari, Aniket Sharad Chaudhari, Lokesh Dayaneshwar Patil, and Gunpesh Chandan Tayade. "GAS SENSOR BY USING ARDUINO UNO." In Futuristic Trends in Electrical Engineering Volume 3 Book 2. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bdee2p4ch1.

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Gas leak detection is of paramount importance for ensuring safety in various industrial, commercial, and residential settings. This paper presents a detailed investigation into the development of an LPG gas sensor system using Arduino, an open-source electronics platform. The gas sensor system utilizes an MQ-series gas sensor to detect LPG gas concentrations and triggers safety measures when the gas concentration exceeds a predefined threshold. The project's design, implementation, and performance evaluation showcase its potential for cost-effective gas leak detection applications.

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Bato, Pancress Eddie, Norfaradilla Wahid, and Nur Liesa Mohammad Azemi. "Prototype of the Multi-Points IoT-Based Heat and Smoke Monitoring for Open Sites." In Emerging Technologies in Digital Manufacturing and Smart Factories. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-0920-9.ch007.

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Public awareness is one of the most neglected causes of fire. To ensure the security of the premises and its clients, the crucial highlights rely upon the fire precautionary measure framework and hardware which ought to accord the standard necessities. This also means that the fire safety precautions also need to be taken in an open site working space. This application with all means is to operate a portable fire alarm and monitoring system built using IoT in order to provide fire safety to open site working space. The prototype is developed using the Arduino IDE, Android Studio, PyCharm, and Command Prompt. Meanwhile, the hardware used during the development of this system are MQ-2 smoke sensor, MPL3115A2 12C temperature sensor, MH Flying Fish infrared sensor, NodeMCU ESP8266, and a buzzer. At the end of this application prototype development, the testing phase has shown that the development of the application is a success and the application was able to conduct its functional requirements.

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Pragadeswaran, S., R. Mounitha, K. Nijandhan, S. Varunika, and S. Rohith Sai Kumar. "SMART HELMET FOR COAL MINERS." In Futuristic Trends in Network & Communication Technologies Volume 3 Book 4. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bfnc4p1ch4.

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The smart helmet concept designed for enhancing coal miners' safety demonstrates a well-considered approach. It integrates a variety of sensors and cutting-edge communication technologies to ensur components: The environmental conditions within the mine are monitored by sensors such as the DHT11, which tracks temperature and humidity, and the MQ-02, which detects harmful gas concentrations like methane and carbon monoxide. A vibration sensor is also utilized to identify any unusual movements or shifts that might indicate potential structural instability. The device's communication system is notably robust. LoRa technology, known for its extensive range and low power consumption, is used to transmit data over significant distances, especiall e the well-being of miners working in coal mines. The device functions through a combination of several key y in areas where conventional communication methods like Zigbee might fall short. Additionally, GSM technology serves as a backup communication channel in case LoRa connectivity is compromised. The core data processing unit is an Arduino microcontroller. It collects data from the various sensors, processes it into a suitable format, and then facilitates its transmission through the chosen communication methods (LoRa and GSM). The microcontroller can also execute predefined algorithms to locally analyze the sensor data against established safety thresholds. Received data is then sent to a control room, where safety personnel analyze the information. Based on the sensor readings, the control room staff can make informed decisions regarding miner safety. This could involve actions such as initiating evacuations or implementing measures to rectify working conditions. By thoughtfully integrating both LoRa and GSM, the design ensures effective communication across extended distances while maintaining a contingency option. The sensors chosen cover a comprehensive range of potential risks, spanning from environmental factors to gas concentrations and structural integrity. To enhance the system's functionality, potential additions might encompass real-time data visualization, predictive analytics for hazard anticipation, and wearables to track miner locations for efficient evacuation procedures. It's imperative to uphold regular maintenance and sensor calibration to guarantee the accuracy of collected data

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Anitha R, Veerasundaram M, Rajarajan S, Jaya Prakash E, NandhaKishore J, and Ajay Krishnan S R. "Cascading of Air Quality Detector and Digital Data Transmission with Zero Error in Minimum Duration." In Recent Trends in Intensive Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210269.

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The paper proposes a system to monitor the environment air quality using an Arduino microcontroller, to enhance the quality IOT Technology is used. The utilization of IoT technology improves the method of monitoring various factors of the environment issues. The MQ-02 gas sensor is used to detect the various gases which are harmful to humans. A Wi-Fi module connects the whole system to the internet and an LCD is employed for the visual Output. This Automated Air management system may be a breakthrough to contribute an answer to the most important threat. The air quality detector overcomes the problems of the highly polluted areas which may be a major issue. This technique has features for the user to monitor the quantity of pollution on their smart devices using the appliance.

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Conference papers on the topic "MQ Sensor"

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Singewar, Hrutik, Shiv Nath Chaudhri, and Subodhkumar Daronde. "Reducing False Alarm Situation in LPG Leak Detection Using Arduino-Based Multi-Sensor (MQ-2, MQ-5, and MQ-6 Gas Sensor) Module." In 2024 2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIEI). IEEE, 2024. https://doi.org/10.1109/idicaiei61867.2024.10842833.

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Gomathi, S., and M. Renuka Devi. "Onion Smart Storage System using IoT Humidity Sensor (DHT11), Gas Sensor(MQ-6)." In 2024 5th International Conference on Smart Electronics and Communication (ICOSEC). IEEE, 2024. http://dx.doi.org/10.1109/icosec61587.2024.10722444.

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Aceveda, Earl John B., Eugine S. Lopez, Charles Darren H. Mendoza, Jen Aldwayne B. Delmo, Jeffrey S. Sarmiento, and Mark John Fel T. Rayos. "Evaluating the Correlation between MQ Gas Sensors with Temperature and Humidity Sensor on an Outdoor Setting." In 2024 14th International Conference on System Engineering and Technology (ICSET). IEEE, 2024. https://doi.org/10.1109/icset63729.2024.10774817.

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AJIBOYE, Aye Taiwo, Jaye Femi OPADIJI, and Adebimpe Ruth AJAYI. "GRAPHICAL METHOD FOR DETERMINATION OF MQ-SERIES GAS SENSOR CIRCUIT PARAMETERS FOR A STANDALONE GAS ALARM SYSTEM." In SOUTHERN BRAZILIAN JOURNAL OF CHEMISTRY 2021 INTERNATIONAL VIRTUAL CONFERENCE. DR. D. SCIENTIFIC CONSULTING, 2022. http://dx.doi.org/10.48141/sbjchem.21scon.20_abstract_ajiboye.pdf.

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MQ-series gas sensors belong to the metal oxide semiconductor (MOS) family of sensors that can sense the presence of many gases. These sensors find their application in gas alarm systems as key components. While necessary sensor circuit output voltage value for alarm point in a standalone gas alarm system is desirable, but what exact combination of the sensor circuit parameters is required? Hitherto, the determination of these circuit parameters has not been much attention in the research community. This study explores a structured graphical approach of determining MQ series gas sensor circuit parameters for a standalone gas alarm system that yields the desired sensor circuit output voltage value for the alarm point. Model equations were developed for the sensor dynamics, and based on these model equations, graphs for the determination of required sensor parameters were plotted for a case of MQ-4 gas sensor response to liquefied petroleum gas (LPG). A structured graphical approach for determining MQ-series gas sensor circuit parameters for alarm points in a standalone gas alarm system showed that using MQ-4 gas sensor and LPG as the target gas. For a sensor circuit output voltage of 2 V for alarm point at 1000 ppm of LPG, the corresponding value of RO, RS, and RL obtained were 20 kΩ, 30 kΩ, and 20 kΩ, respectively. Hence, the developed structured graphical approach is suitable for determining MQ series gas sensor circuit parameters for a standalone gas alarm system under the influence of its associated gases.

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Sampson, Jenyfal, M. Sridharan, Vankadara Jaswanth, and Sudhakar Reddy Venna. "Smart Vehicle Locking System Using Pollution Sensor (Mq-07)." In 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI). IEEE, 2022. http://dx.doi.org/10.1109/icoei53556.2022.9776911.

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Zhao, Jian, Yun Zhang, and De Ge. "Research and application of MQ-7 sensor compensation method." In International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), edited by Fengli Liu and Yonghe Wei. SPIE, 2024. http://dx.doi.org/10.1117/12.3025514.

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Aditya, Upma Jain, Akansha Yadav, Shubhangi Joshi, Vipashi Kansal, and Shruti Bhatla. "Mosquito Coil Smoke Monitoring System Using Arduino and MQ-2 sensor." In 2023 International Conference on Computer Science and Emerging Technologies (CSET). IEEE, 2023. http://dx.doi.org/10.1109/cset58993.2023.10346680.

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Gunawan, Gani, Fetri Lestari, Arief Yulianti, Haris Dhaifullah, and Erwin Harahap. "Smoke detector system with MQ-2 sensor based on ESP32 microcontroller." In SCIENCE AND TECHNOLOGY RESEARCH SYMPOSIUM 2022. AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0224595.

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Muqita, Saffanah Ghina. "KARAKTERISASI DAN PENGUJIAN SENSOR MQ-7 DAN MQ-136 UNTUK PENGEMBANGAN SISTEM MONITORING KONSENTRASI GAS KARBON MONOKSIDA (CO) DAN SULFUR DIOKSIDA (SO2)." In SEMINAR NASIONAL FISIKA 2016 UNJ. PRODI Pendidikan Fisika dan Fisika UNJ, 2024. http://dx.doi.org/10.21009/03.1201.fa13.

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Trisnawan, I. Kadek Nuary, Agung Nugroho Jati, Novera Istiqomah, and Isro Wasisto. "Detection of Gas Leaks Using The MQ-2 Gas Sensor on the Autonomous Mobile Sensor." In 2019 International Conference on Computer, Control, Informatics and its Applications (IC3INA). IEEE, 2019. http://dx.doi.org/10.1109/ic3ina48034.2019.8949597.

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Reports on the topic "MQ Sensor"

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Chappelle, Wayne L., Kent McDonald, and Raymond E. King. Psychological Attributes Critical to the Performance of MQ-1 Predator and MQ-9 Reaper U.S. Air Force Sensor Operators. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada525910.

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Craig-Gray, Robert, Wayne L. Chappelle, John Heaton, and Amber Salinas. NEO PI-R Normative Personality Data that Distinguish U.S. Air Force MQ-1 Predator and MQ-9 Reaper Sensor Operators from AC-130 Gunship Sensor Operators and Peers in the General Population. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada548330.

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