Early Detection of Ammonia Gas Levels in the Air Using IoT-Based SVM

Authors

  • Lukman Lukman Department of Electrical Engineering, Muhammadiyah University Makassar, Indonesia, Indonesia

DOI:

https://doi.org/10.31004/jptam.v7i1.5819

Keywords:

SVM, Amoniak, Esp8266-01, Arduino Nano, Thingspeak

Abstract

Saat ini diyakini bahwa pengenalan teknologi Internet of Things (IoT) akan membantu Generasi 4.0. Teknologi ini dapat digunakan, misalnya, untuk menyaring kualitas air di fasilitas pengolahan air limbah (IPAL) rumah sakit. Pengujian ini diperlukan untuk melindungi dan menghindari risiko yang terkait dengan paparan alkali yang tidak terkendali. Sampai saat ini, sebagian besar klinik medis memperkirakan file batas air menggunakan metode konvensional. Dalam pekerjaan ini, modul ESP8266-01 dan Arduino Nano digunakan untuk memperkirakan pengelompokan gas amonia di iklim IPAL. Suhu, pH, dan TDS diperkirakan batas untuk kualitas air. Data dikirim sebagai kumpulan data eksplorasi dari pekerja thingspeak. Data yang diperoleh dievaluasi menggunakan Support Vector Machine untuk menentukan peringkat tingkat kontaminasi amoniak (SVM). Analisis 20% dari data line approval menunjukkan bahwa presisi 98% adalah tingkat yang optimal. Investigasi ini karenanya dapat berfungsi sebagai template untuk klinik darurat yang menangani tingkat kontaminasi amonia. 

References

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Published

01-04-2023

How to Cite

Lukman, L. (2023). Early Detection of Ammonia Gas Levels in the Air Using IoT-Based SVM . Jurnal Pendidikan Tambusai, 7(1), 3750–3757. https://doi.org/10.31004/jptam.v7i1.5819

Issue

Vol. 7 No. 1 (2023): April 2023

Section

Articles of Research

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