Zanuar, Muhammad (2024) Sistem Kontrol Kualitas Udara Partikulat PM1, PM2.5, dan PM10 dengan Penerapan Filter HEPA Berbasis Expert System Linguistik. Diploma thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Polusi udara dalam ruangan menjadi faktor utama yang memengaruhi kesehatan manusia. Jenis pencemaran udara dalam ruangan, seperti CO2, Particulate Matter (PM), dan TVOC, dapat menyebabkan sejumlah masalah kesehatan, termasuk kelelahan, iritasi, infeksi saluran pernapasan akut (ISPA), dan bahkan kanker paru-paru. Pada penelitian ini terfokus pada polusi udara yang mengandung konsentrasi partikulat (PM1, PM2.5, dan PM10) di dalam ruangan. Oleh karena itu, diperlukan penyempurnaan pada sistem pengendalian kualitas udara dalam ruangan. Penelitian ini memfokuskan pada pembuatan kontrol motor BLDC otomatis yang mampu mengatur kecepatan sesuai dengan konsentrasi partikel debu, serta dilengkapi dengan pemantauan temperatur dan kelembaban ruangan. Pemantauan parameter (PM1, PM2.5, PM10, Temperatur dan Kelembaban) yang dilakukan telah terintegrasi nextion display dan aplikasi yang dapat diakses melalui smartphone. Hasil pengujian validasi sensor partkulat PMS5003 menunjukkan bahwa sensor ini memiliki tingkat akurasi 95,2% dan Sensor DHT22 memiliki akurasi 99%. Sistem kontrol motor menggunakan expert system linguistik mampu menyesuaikan kecepatan exhaust fan secara otomatis berdasarkan konsentrasi partikulat yang terdeteksi. Pengujian sistem dilakukan empat kali dengan tanpa inject debu, asap rokok, asap vapor, dan asap pembakaran kertas A4. Data menunjukkan alat mampu memfilter udara dalam keadaan kembali baik dalam waktu 32 detik. Sistem kontrol memastikan kualitas udara dalam ruangan selalu pada tingkat yang baik.
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Indoor air pollution is a major factor affecting human health. Types of indoor air pollution, such as CO2, Particulate Matter (PM), and TVOC, can cause several health problems, including fatigue, irritation, acute respiratory infections (ARI), and even lung cancer. This study focuses on air pollution containing particulate concentrations (PM1, PM2.5, and PM10) indoors. This research making an automatic BLDC motor control that can adjust the speed according to the concentration of dust particles and is equipped with room temperature and humidity monitoring. Parameter monitoring (PM1, PM2.5, PM10, Temperature and Humidity) has been integrated with nextion display and application that can accessed via smartphone. Results of the PMS5003 particulate sensor validation test show that this sensor has an accuracy 95.2% and the DHT22 Sensor has an accuracy 98%. The motor control system using linguistic expert system can adjust the fan speed automatically based on particulate concentration detected. System testing was conducted four times with no dust injection, cigarette smoke, vapour smoke, and A4 paper burning smoke. The data showed that the device was able to filter the air back to a good state within 32 seconds. The control system ensures the indoor air quality is always at a good level.
| Item Type: | Thesis (Diploma) |
|---|---|
| Uncontrolled Keywords: | Partikulat, PM2.5, Motor, HEPA Filter, Expert System, Particulate matter |
| Subjects: | T Technology > TD Environmental technology. Sanitary engineering > TD883 Air quality management. T Technology > TD Environmental technology. Sanitary engineering > TD883.2 Automobiles--Motors--Exhaust gas T Technology > TD Environmental technology. Sanitary engineering > TD883.5 Air--Pollution |
| Divisions: | Faculty of Vocational > Instrumentation Engineering |
| Depositing User: | Muhammad Zanuar |
| Date Deposited: | 23 Aug 2024 07:29 |
| Last Modified: | 23 Aug 2024 07:29 |
| URI: | http://repository.its.ac.id/id/eprint/113754 |
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