TY - GEN
T1 - Energy Consumption Collection Design for Smart Building
AU - Tantidham, T.
AU - Ngamsuriyaros, S.
AU - Tungamnuayrith, N.
AU - Nildam, T.
AU - Banthao, K.
AU - Intakot, P.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/20
Y1 - 2018/8/20
N2 - With increasing cost and energy consumption, many organizations would find a way for monitoring and to save energy. Our work would design and implement a monitoring system to collect energy usage data and use such data to analyze energy consumption patterns. We measure the amount of electricity of AC outlets, lights and air conditions in a building. Our work consists of 3 parts: Power Data Collection, Data Processing and Data Report. Power Data Collection is composed of power meters built on an ESP8266 Wi-Fi platform and PZEM-004T which will be attached to 3 types of devices: AC outlet, air condition and light. The Data Processing part is performed at the Elasticsearch server by gathering the measured power data from multiple power meters via MQTT protocol. The Data Report part uses Grafana to show usage statistics via a web interface. Usually, one room will have number of lights and outlets, and one or two air conditions. We also collect the measured data every 15 minutes. Thus, collected data will become very huge in a short period of time. In the future, we need to do pattern analysis of energy consumption of a building.
AB - With increasing cost and energy consumption, many organizations would find a way for monitoring and to save energy. Our work would design and implement a monitoring system to collect energy usage data and use such data to analyze energy consumption patterns. We measure the amount of electricity of AC outlets, lights and air conditions in a building. Our work consists of 3 parts: Power Data Collection, Data Processing and Data Report. Power Data Collection is composed of power meters built on an ESP8266 Wi-Fi platform and PZEM-004T which will be attached to 3 types of devices: AC outlet, air condition and light. The Data Processing part is performed at the Elasticsearch server by gathering the measured power data from multiple power meters via MQTT protocol. The Data Report part uses Grafana to show usage statistics via a web interface. Usually, one room will have number of lights and outlets, and one or two air conditions. We also collect the measured data every 15 minutes. Thus, collected data will become very huge in a short period of time. In the future, we need to do pattern analysis of energy consumption of a building.
KW - ESP8266
KW - Elasticsearch
KW - Energy Consumption
KW - MQTT
KW - PZEM-004T
KW - Power Meter
UR - https://www.scopus.com/pages/publications/85053430091
U2 - 10.1109/ICESIT-ICICTES.2018.8442052
DO - 10.1109/ICESIT-ICICTES.2018.8442052
M3 - Conference contribution
AN - SCOPUS:85053430091
SN - 9781538670637
T3 - 2018 International Conference on Embedded Systems and Intelligent Technology and International Conference on Information and Communication Technology for Embedded Systems, ICESIT-ICICTES 2018
BT - 2018 International Conference on Embedded Systems and Intelligent Technology and International Conference on Information and Communication Technology for Embedded Systems, ICESIT-ICICTES 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 International Conference on Embedded Systems and Intelligent Technology and International Conference on Information and Communication Technology for Embedded Systems, ICESIT-ICICTES 2018
Y2 - 7 May 2018 through 9 May 2018
ER -