DISAIN SISTEM OTOMASI SUHU RUANGAN PERTEMUAN DENGAN PENERAPAN TEKNIK MACHINE LEARNING

  • Stephanie Imelda Pella Universitas Nusa Cendana
  • Hendro FJ L
Keywords: raspbery pi, machine learning, automated control

Abstract

This research presents an automation process of controlling room temperature based on the number of people detected in a room. The system consists of a single board raspberry pi computer, esp8266 micro controller, pi camera, and an infrared module. This research is divided into two parts, namely object detection using Raspbery Pi and Tensorflow and Open CV libraries and controlling air cooling system (ACS) using esp8266 and infrared modules by transmitting hexadecimal AC control codes. The ACS temperature is divided into four levels with a minimum value at 18o C and a maximum at 24o C. System testings were carried out in an empty room and a room with a capacity of 50 people that is fully occupied. The results show that the system is able to detect the number of people in the room and control the ACS, but under certain conditions some objects are not detected because the position and camera tilt is not optimal.

Downloads

Download data is not yet available.

References

[1] Measey, Mariah. "Indonesia: a vulnerable country in the face of climate change." Global Majority E-Journal 1.1 (2010): 31-45.
[2] Epstein, Paul R. "Climate change and human health." New England Journal of Medicine 353.14 (2005): 1433-1436.
[3] Santamouris, Matheos, et al. "On the impact of urban heat island and global warming on the power demand and electricity consumption of buildingsā€”A review." Energy and Buildings 98 (2015): 119-124.
[4] Prabasworo, Bagas Rasendriya, and Josi Ayu Wulandari Pratama Putri. "SMARTAC SEBAGAI SOLUSI OPTIMASI PENGGUNAAN AC UNTUK MENCAPAI KENYAMANAN TERMAL RUANGAN DI RUMAH TANGGA SMARTAC AS A SOLUTION FOR AC OPTIMIZATION USAGE TO ACHIEVE ROOM THERMAL COMFORT IN HOUSEHOLD." Prosiding Seminar Hari Tata Ruang 2016" Kota Inklusif dan Lestari. 2016.
[5] Rusliwando, Ferry Shandria. ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PERILAKU KONSUMSI ENERGI LISTRIK MENGGUNAKAN PARTIAL LEAST SQUARE-STRUCTURAL EQUATION MODELING (PLS-SEM)(Studi Kasus Sektor Rumah Tangga). Diss. Universitas Widyatama, 2016.
[6] Lami, Hendro FJ, and Stephanie Imelda Pella. "Implementasi Deteksi dan Pengenalan Wajah pada Sistem Ujian Online Menggunakan Metode Deep Learning Berbasis Raspberry Pi." Media Elektro (2019): 89-92.
[7] Holton, Jon, and Tim Fratangelo. "Raspberry Pi Architecture." Raspberry Pi Foundation, London, UK (2012).
[8] Zhang, Xingzhou, Yifan Wang, and Weisong Shi. "pcamp: Performance comparison of machine learning packages on the edges." {USENIX} Workshop on Hot Topics in Edge Computing (HotEdge 18). 2018.
Published
2019-10-30
How to Cite
Pella, S., & L, H. (2019). DISAIN SISTEM OTOMASI SUHU RUANGAN PERTEMUAN DENGAN PENERAPAN TEKNIK MACHINE LEARNING. Media Elektro, 117 - 120. Retrieved from http://ejurnal.undana.ac.id/jme/article/view/1781
Section
Articles

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.