This is an outdated version published on 2023-04-01. Read the most recent version.

Rancang Bangun Perangkat Monitoring Temperatur dan Kelembapan di Laboratorium dan Ruang Panel Berbasis IoT

Authors

  • Ahmad Mahfud Politeknik Kelapa Sawit Citra Widya Edukasi
  • M. Farhan Anshori Politeknik Kelapa Sawit Citra Widya Edukasi

Keywords:

Temperature and humidity monitoring, DHT11 Sensor, Blynk Application and NodeMCU ESP8266.

Abstract

The palm oil mill laboratory and panel room have an important role in the processing process at the palm oil mill. The laboratory has an important role in ensuring the quality of the products from the palm oil mill processing, while the panel room has an important role in controlling and smoothing the production process. In order to ensure the smooth running and prevention of damage to the laboratory and panel room, there are several important aspects that must be maintained and monitored, one of which is temperature and humidity. Temperature and humidity measurements are the most common measurements carried out in laboratories and panel rooms with the aim of anticipating damage. The laboratory has a standard temperature limit of 25oC, while the panel room has a standard temperature limit of 30oC. In this study, researchers will implement a temperature and humidity monitoring system in the laboratory and panel room of a palm oil mill using the DHT11 sensor and NodeMCU Esp8266. The results of this study can be concluded that temperature and humidity measurements in the laboratory and panel room can be carried out automatically and in real time. The reading results from the sensor can be further processed by NodeMCU. NodeMCU has succeeded in sending the reading data to the Blynk application and the sensor reading data has also been sent automatically to Google Sheets and a notification (WhatsApp & Email) will appear and an alarm sound from the buzzer, if the temperature and humidity exceed the permissible standard limits. The DHT11 sensor that I use for this monitoring has a high sensor accuracy percentage value of 98.4%.

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Published

2023-04-01

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