Submitted: 09-01-2021
Accepted: 09-04-2021
1,2Politeknik Aceh Selatan, Indonesia,3University of Babylon, Iraq, 4Universita digliStudi di Napoli, Italy, 5STIT-HAFAS Subulussalam,Indonesia
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Submitted: 09-01-2021 Accepted: 09-04-2021 |
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Air is one of the sources of human life that can be obtained freely. Good and bad air quality can affect human health and activities. Clean air can cause a person to feel comfortable in a certain place so that they can do activities well and have fun. On the other hand, poor air quality due to pollution can actually interfere with life activities because it is polluted with various kinds of toxic substances originating from natural pollution, vehicle pollution, and cigarette smoke pollution that are harmful to human health.
Cigarette smoke is one of the air pollutions. Inhaling other people's cigarette smoke is more dangerous than smoking your own cigarette. Even the dangers that must be borne by passive smokers are three times that of active smokers. Cigarette smoke is also very detrimental to the health of patients in hospitals, especially patients suffering from asthma. For people with asthma who experience problems in their airways, their asthma can relapse from time to time because of inhaling cigarette smoke. And from previous studies that discuss the detection of cigarette smoke, there are quite a number of them, including a cigarette detection system in a closed room based on the Internet of Things (IoT) (Sulistiyowati, Findawati, Ayubi, Jamaaluddin, & Sulistyanto, 2019). Design of a cigarette smoke detection system using an Arduino-Based Short Message Service (SMS) Alert (Mandarani et al., 2016) and (Utomo & Saputra, 2016). Design of the Multiple Warning system for detecting cigarette smoke using an Arduino-based MQ-135 sensor (Gustavia & Nurraharjo, 2018). Design and build an alarm for detection of cigarette smoke and noise in the classroom automatically based on a microcontroller (Ratnasari, 2018). Design of a smoke detector in a smoking room using an MQ-2 sensor with an Atmega328 microcontroller (Rahmadani, 2018). Sensor, microcontroller, and IoT based smoke and fire detection system design (Waworundeng, 2020). Design and build a detector and neutralizer of indoor cigarette smoke using the Arduino-based PI (Propositional Integral) method (Rahmat, Somawirata, & Nasional, 2018). Design and build a smoke and flame detector for health and fire prevention based on Arduino Uno and GSM Sim900A (Hamdani, Handayani, & Risdianto, 2019). The application of the internet of things has also been carried out for heart rate monitoring(Ilham, Hardisal, Balkhaya, Candra, & Sipahutar, 2019). also applied to light control using social media applications(Rudi Arif Candra, Ilham, Hardisal, & Sriwahyuni, 2019).Control the infusion run out with Arduino Uno with social media apps(Rudi Arif Candra, Saputra, Ilham, Setiawan, & Hardisal, 2020). Designing an Arduino-based Automatic Cocoa Fermentation Tool(Ilham, Balkhaya, Candra, Hardisal, & Hasbaini, 2020). control the water pump on traditional boats automatically(Ihsan, Ilham, Candra, Yunan, & Hardisal, 2020).Rain monitoring system for nutmeg drying based on internet of things(Ilham, Satria, Anugreni, Candra, & Kusumo, 2021). Amplitude range data validation in the Internet of Things (IoT) sensor (R. A. Candra, Suherman, & Ilham, 2021).
From the above background, this research will design a healthy smart room from Arduino Uno-based cigarette smoke by using the application of the MQ 2 sensor and displaying the percentage of smoke and also based on warning and neutralizing smoke in the room.
There were many previous studies that discussed smoke detection, there are quite a number of them, including a cigarette detection system in a closed room based on the Internet of Things (IoT)(Sulistiyowati et al., 2019). Design of a cigarette smoke detection system using an Arduino-Based Short Message Service (SMS) Alert (Mandarani et al., 2016) and (Utomo & Saputra, 2016). Design of the Multiple Warning system for detecting cigarette smoke using an Arduino-based MQ-135 sensor (Gustavia & Nurraharjo, 2018). Design and build an alarm for detection of cigarette smoke and noise in the classroom automatically based on a microcontroller (Ratnasari, 2018). Design of a smoke detector in a smoking room using an MQ-2 sensor with an Atmega328 microcontroller (Rahmadani, 2018). Sensor, microcontroller, and IoT based smoke and fire detection system design (Waworundeng, 2020). Design and build a detector and neutralizer of indoor cigarette smoke using the Arduino-based PI (Propositional Integral) method (Rahmat et al., 2018). Design and build a smoke and flame detector for health and fire prevention based on Arduino Uno and GSM Sim900A (Hamdani et al., 2019).
The tools and materials we use in designing a CO2 level detector in a smoke-free room consist of hardware and software, including:
The hardware used includes:
A computer with a minimum specification of Dual Core Ram
2Gb works as a place to run Arduino Applications
Minimum Arduino Uno Microcontroller System is the main
minimum board in running the Arduino Uno microcontroller
16x2 LCD as a tool to display the result of reading the
percentage value of CO . gas content
Buzzer as a tool to make sound
Relay as regulator On/Off Cooling Fan
MQ2 sensor as a CO . gas detection sensor
Power Supply 9 V as a microcontroller and relay power
supply
The software used in this research are:
Windows 7 Ultimate 32 Bit: The operating system used to run
all the software on the computer
Arduino IDE 1.8.2: a software used in developing
microcontroller applications starting from writing source
programs, compiling, uploading, and testing terminals.
Fritzing 0.9.3b.pc: open-source software that can be used
to design electronic circuits
Microsoft Visio 2007: a computer application program used
to create diagrams, flowcharts, and network schematics.
Proteus 8 Professional: software for PCB design with PSpice
simulation at the schematic level.
This design is made to simplify the process of designing a CO2 level detector in a smoke-free room. The series of tools is shown in Figure 1.
Figure 1. System Design
The following is a flowchart of how the CO2 level detection tool works. In Figure 2 there is a series of Flowchart programs for detecting CO2 levels in a smoke-free room where the program starts from the beginning then the source will be installed with an MQ2 sensor, a program that will detect CO2 levels if it is more than 20% then the fan and alarm will turn on.
Figure 2. The working principle of the tool
By using the Fritzing application, the following tool design is obtained, this co2 level detector works based on input from the MQ2 sensor which will read the co2 level, then the HX711 module will process the data, then be notified to NodeMCUESP8266 and controlled by Arduino, which then Node MCU instructs the fan and buzzer to live.
Figure 3. Schematic of the Tool
Tool Construction and Circuit explanation According to the tool design in Figure 3 are as follows:
Table 1. Tool specifications
| Component name | Specification | Number of units |
|---|---|---|
| Power Supply | 9V | 1 |
| Sensor | Mq2 | 1 |
| Buzzer | 5v | 1 |
| Arduino | Uno R3 | 1 |
| Relay Modul | 12V | 1 |
| LCD | LCM 1602 IIc | 1 |
| Cooling Fan | Fan | 1 |
| Kabel Jumper | Male to female | 12 |
When the voltage source is given, the power supply is on, the power supply provides a voltage of 9V to the relay, where the relay has 2 voltages, to activate the buzzer it takes 5 volts of power and to activate the Cooling Fan uses 5 volts of power too. The Mq2 sensor has been connected to the Arduino Uno Microcontroller and will activate when it detects smoke and the LCD will display the value to be detected, in the form of a percentage.
Hardware implementation for making prototypes is using one MQ-2 sensor, Arduino Uno, and Cooling Fan, assembled using a beard, for voltage divider using 5V Relay, 5v buzzer, while LCD to Arduino output to read the content value as soon as possible in the test process try.
Figure 4. Hardware Implementation
The MQ-2 smoke sensor circuit can be directly adjusted for sensitivity by turning the trim pot. This sensor is commonly used to detect gas leaks both at home and in the gas industry. The following table shows the measurement results of the MQ-2 sensor using an Analog Multimeter:
Table 2. Calculation of Voltage with Analog Multimeter
| No. Sensor Room MQ-2 | Sensor Voltage When There is Smoke | MQ-2 Sensor Voltage When There is Smoke |
|---|---|---|
| MQ-2 Sensor In Room 1 | 4.1 Volts | 4.2 - 4.4 Volt |
| MQ-2 Sensor In Room 2 | 4.1 Volts | 4.2 - 4.4 Volt |
In this experiment, the author conducted testing in several Cafés or Coffee Shops whose building constructions were closed, including Premier Cafe, Polytechnic Canteen, and Radja Kopi Café.
Table 3. Testing Criteria
| Nama Café | Room Area(meters) | Number of Smokers | Fast rate (%) | Room Criteria | Information |
|---|---|---|---|---|---|
| King Coffee | 8 x 8 m | 15 | 22, 24, 25, 27 | Semi Closed | 4 Fans |
| Premier Coffee | 8 x 7 m | 18 | 21,22,22,26,27, 30,32,33,35,36, 39, 42, 46 | Semi Closed | 2 Fans |
| Poltas Canteen | 4x5 m | 17 | 55,50,43,39,28, 27,26,25,24,23, 22,21,21,20,22, 21,19,19,20 | Open | No Fans |
Testing of the detection and cleaning system of cigarette smoke was carried out at three different locations, namely at Raja coffee, Primer Caffe, and Poltas Kantin, and the results showed that open spaces had higher CO2 levels than closed spaces because they were easy to detect and clean using a colling fan.
The ability of this smoke detector to detect the presence of cigarette smoke in the air depends on the concentration of smoke, the distance from the source and sensor, and the direction of movement of the smoke. and from the results of tests carried out at three locations, it was explained that a closed room equipped with a colling fan to clean cigarette smoke levels made the room cleaner and reduced co2 levels.
Candra, R. A., Suherman, & Ilham, D. N. (2021). Amplitude range data validation in Internet of Things (IoT) sensor.
Candra, Rudi Arif, Ilham, D. N., Hardisal, H., & Sriwahyuni, S. (2019). Light Control Design by Using Social Media Telegram Applications Based on Internet Of Things (IOT).
Candra, Rudi Arif, Saputra, D. S., Ilham, D. N., Setiawan, H., & Hardisal, H. (2020). The Infusion of Notification Design With an Application of Social Media Based on a Internet of Things (IOT).
Gustavia, R. A., & Nurraharjo, E. (2018). Rancang Bangun Sistem Multiple Warning Deteksi Asap Rokok.
Hamdani, D., Handayani, E., & Risdianto, E. (2019). Rancang Bangun Alat Pendeteksi Asap Rokok Dan Nyala Api Untuk Penanggulangan Kesehatan Dan Kebakaran Berbasis Arduino Uno Dan GSM SIM900A.
Ihsan, I., Ilham, D. N., Candra, R. A., Yunan, A., & Hardisal, H. (2020). Design of an Automatic Water Pump on a Traditional Boat.
Ilham, D. N., Balkhaya, B., Candra, R. A., Hardisal, H., & Hasbaini, H. (2020). Designing an Arduino-based Automatic Cocoa Fermentation Tool.
Ilham, D. N., Hardisal, H., Balkhaya, B., Candra, R. A., & Sipahutar, E. (2019). Heart Rate Monitoring and Stimulation with the Internet of Thing-Based (IoT) Alquran Recitation.
Ilham, D. N., Satria, E., Anugreni, F., Candra, R. A., & Kusumo, H. N. R. A. (2021). Rain Monitoring System for Nutmeg Drying Based on Internet of Things.
Mandarani, P., Ariani, R., Jurusan, D., Informatika, T., Industri, F. T., Jurusan, M., … Nanggalo, K. (2016). Perancangan Sistem Deteksi Asap Rokok Menggunakan Layanan Short Message Service ( Sms ) Alert Berbasis Arduino.
Rahmat, A., Somawirata, I. K., & Nasional, I. T. (2018).
Ratnasari, I. D. (2018). Rancang Bangun Alarm Deteksi Asap Rokok dan Kebisingan Pada Ruang Kelas Secara Otomatis Berbasis Mikrokontroler.
Sulistiyowati, I., Findawati, Y., Ayubi, S. K. A., Jamaaluddin, J., & Sulistyanto, M. P. T. (2019). Cigarette detection system in closed rooms based on Internet of Thing (IoT).
Utomo, B. T. W., & Saputra, D. S. (2016). Simulasi Sistem Pendeteksi Polusi Ruangan Menggunakan Sensor Asap Dengan Pemberitahuan Melalui SMS (Short Message Service) Dan Alarm Berbasis Arduino.
Waworundeng, J. M. S. (2020). Desain Sistem Deteksi Asap dan Api Berbasis Sensor, Mikrokontroler dan IoT.