Temperature and Humidity Prediction at Various Heights at Telkom University Landmark Tower (TULT) Using Neural Networks and the Internet of Things (IoT)
MUHAMMAD LUCKY REZA

Informasi Umum

Kode

23.04.6715

Klasifikasi

006.32 - Neural networks, perceptrons, connectionism, neural computers

Jenis

Karya Ilmiah - Skripsi (S1) - Reference

Subjek

Iot, Neural Networks,

Dilihat

21 kali

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Abstraksi

<p><i>Abstract </i>— TULT is used daily by at least 1000 students for teaching and learning activities. The air condition on each floor affects the comfort of learning. Therefore, a method is needed to monitor temperature and humidity, one of which is the Telkom University Landmark Tower (TULT) building, and each different floor or height affects the temperature and humidity inside the building. Therefore, it is difficult to predict because there are differences in temperature and humidity at each altitude. To solve the problem, it is hoped that neural networks and IoT methods can predict temperature and humidity at different heights in TULT buildings. Artificial Neural Network (JST) is one of the information processing systems that mimics the workings of the human brain. JST has the ability to make decisions on previously studied data.</p>

<p>Internet of things (IoT) is a term intended to encompass the increased use of the internet, the adoption and integration of mobile computing, and connectivity into everyday life. The Internet of Things is related to DoT (Disruption of Things) and serves as an introduction to changes or shifts in Internet usage from the previous Internet of People to the Internet of M2M (Machine-to-Machine).</p>

<p>Keywords— tult, jst, iot</p>

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