CAMILLA, ALISSA (2026) ALAT PENDETEKSI KONDISI LINGKUNGAN DALAM KABIN SERTA KADAR GAS BUANG PADA KENDARAAN MOBIL BERBASIS IOT. S1 thesis, Fakultas Teknik Universitas Sultan Ageng Tirtayasa.
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Abstract
Cars have a higher level of comfort than two-wheeled motorized vehicles, because they have a cabin that is not too affected by the outside air. Driver comfort in the cabin is influenced by air quality factors such as CO, O2, noise, temperature, humidity, and air pressure. Many cases of death are caused by exhaust gases, especially in the use of four-wheeled vehicles or cars. Older vehicles often have problems, especially leaks from the AC (Air Conditioner), if the car engine has incomplete combustion, it produces CO. The purpose of this study is to design and develop a monitoring system for environmental conditions in the cabin and exhaust emissions of car vehicles based on the Internet of Things (IoT). This study uses MQ 7 sensors, DFRobot I2C oxygen, DHT22, BMP280, and KY-037. The sensor detects changes in physical values in the environment (car cabin) such as gas, oxygen, temperature, pressure, humidity, and noise, then via a microcontroller sent in real time to Blynk. From the research data, the average value is obtained based on all the measurement results that have been taken so that the data from each sensor is in the average range for the CO sensor, namely in the morning 3.19ppm, during the day 2.85ppm, and in the afternoon 2.81ppm. Oxygen sensor with an average morning of 21.26%, during the day 20.53%, and in the afternoon 20.90%. Temperature sensor with an average morning of 31.35°C, during the day an average of 34.81°C, and in the afternoon 32.83°C. Pressure sensor with an average in the morning of 1008.108hPa, during the day 1006.736hPa, and in the afternoon 1005.91hPa. Humidity sensor with an average morning of 54.73%RH, during the day an average of 46.45%RH, and in the afternoon 46.64%RH. The average noise sensor in the morning is 92.13dB, during the day 92.18dB, and in the evening 92.14dB. Based on the comparison results with the reference tool, the percentage error value obtained for the BMP280 temperature sensor was 3.919%, the DHT22 humidity sensor was 4.030%, and the KY-037 noise sensor was 57.660%.
| Item Type: | Thesis (S1) | |||||||||
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| Additional Information: | Kendaraan mobil memiliki tingkat kenyamanan yang tinggi dari pada kendaraan bermotor roda dua, karena memiliki kabin yang tidak terlalu berpengaruh terhadap udara di luar. Kenyamanan pengendara di dalam kabin dipengaruhi oleh faktor faktor kualitas udara seperti gas CO, O2, kebisingan, suhu, kelembapan, dan tekanan udara. Banyak kasus kematian yang disebabkan oleh gas buang, terutama dalam penggunaan kendaraan roda empat atau mobil. Kendaraan yang berusia tua sering terjadi masalah terutama pada kebocoran dari Air Conditioner (AC), apabila mesin mobil terjadi pembakaran yang tidak sempurna maka menghasilkan CO. Tujuan penelitian ini untuk merancang dan mengembangkan sebuah sistem pemantauan kondisi lingkungan dalam kabin serta emisi gas buang kendaraan mobil berbasis Internet of Things (IoT). Penelitian ini menggunakan sensor MQ-7, oksigen DFRobot I2C, DHT22, BMP280, dan KY-037. Sensor mendeteksi perubahan nilai fisik pada lingkungan (kabin mobil) seperti gas, oksigen, suhu, tekanan, kelembapan, dan kebisingan, kemudian melalui mikrokontroler dikirim secara real-time ke Blynk. Dari data hasil penelitian di dapatkan nilai rerata berdasarkan seluruh hasil pengukuran yang telah diambil sehingga menghasilkan data dari setiap sensor berada kisaran rerata untuk sensor CO yaitu di pagi hari 3,19ppm, saat siang hari 2,85ppm, dan sore hari 2,81ppm. Sensor oksigen dengan rerata pagi hari 21,26%, siang hari 20,53%, dan saat sore hari 20,90%. Sensor suhu dengan rerata pagi hari 31,35°C, siang hari rerata 34,81°C, dan sore hari 32,83°C. Sensor tekanan dengan rerata di pagi hari 1008,108hPa, saat siang hari 1006,736hPa, dan sore hari 1005,91hPa. Sensor kelembapan dengan rerata pagi hari 54,73 %RH, siang hari rerata 46,45%RH, dan sore hari 46,64%RH. Sensor kebisingan rerata pagi hari 92,13dB, siang hari 92,18dB, dan sore hari 92,14dB. Berdasarkan hasil perbandingan dengan alat acuan, diperoleh nilai persentase error pada sensor suhu BMP280 sebesar 3,919%, sensor kelembapan DHT22 sebesar 4,030%, serta sensor kebisingan KY-037 sebesar 57,660%. | |||||||||
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | |||||||||
| Divisions: | 03-Fakultas Teknik > 20201-Jurusan Teknik Elektro | |||||||||
| Depositing User: | Mrs ALISSA SYAFA CAMILLA | |||||||||
| Date Deposited: | 27 Jan 2026 09:13 | |||||||||
| Last Modified: | 27 Jan 2026 09:13 | |||||||||
| URI: | http://eprints.untirta.ac.id/id/eprint/57600 |
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