Level and Temperature Monitoring System in Blending Process Using Zigbee Wireless Sensor Network
- DOI
- 10.2991/assehr.k.200529.077How to use a DOI?
- Keywords
- monitoring system, blending process, zigbee wireless sensor network
- Abstract
The use of cable transmission media has several drawbacks related to distance problems, geographical factors, the initial cost of procurement is quite expensive, and the arrangement of the cables is not practical. Wireless based systems appear to answer these challenges, one of which is the Wireless Sensor Network (WSN). In the industrial field the use of WSN is quite extensive in the field of monitoring and measurement. This study implements WSN technology for monitoring levels and temperatures in the Zigbee Wireless Network Sensor blending process. The implementation uses the Atmega 328 Arduino Uno, Xbee Pro and LabView 2017 microcontroller as its Human Machine Interface. Using statistical analysis methods paired t test and linear regression to analyse how the error rate and correlation of the observed variables. Based on the results of the study obtained correlations of level and temperature measurements respectively 99.97% for level measurements and 99.98% for temperature measurements. The average relative error is 2.76% for level measurements and 0.65% for temperature measurements. Tests are carried out to measure the level in the range 0–40 cm and temperatures 26°C − 70°C with ultrasonic sensors and LM35.
- Copyright
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Astrie Kusuma Dewi AU - Andrian Aziz Burhan Abid Sahaya AU - Wahid Sugiman PY - 2020 DA - 2020/05/04 TI - Level and Temperature Monitoring System in Blending Process Using Zigbee Wireless Sensor Network BT - Proceedings of the 1st Borobudur International Symposium on Humanities, Economics and Social Sciences (BIS-HESS 2019) PB - Atlantis Press SP - 372 EP - 375 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.200529.077 DO - 10.2991/assehr.k.200529.077 ID - Dewi2020 ER -