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A High-Accuracy and Power-Efficient Self-Optimizing Wireless Water Level Monitoring IoT Device for Smart City.
Chi, Tsun-Kuang; Chen, Hsiao-Chi; Chen, Shih-Lun; Abu, Patricia Angela R.
Afiliação
  • Chi TK; Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan.
  • Chen HC; Department of Business Administration, Chung Yuan Christian University, Taoyuan City 320314, Taiwan.
  • Chen SL; Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan.
  • Abu PAR; Department of Information Systems and Computer Science, Ateneo de Manila University, Quezon City 1108, Philippines.
Sensors (Basel) ; 21(6)2021 Mar 10.
Article em En | MEDLINE | ID: mdl-33801852
ABSTRACT
In this paper, a novel self-optimizing water level monitoring methodology is proposed for smart city applications. Considering system maintenance, the efficiency of power consumption and accuracy will be important for Internet of Things (IoT) devices and systems. A multi-step measurement mechanism and power self-charging process are proposed in this study for improving the efficiency of a device for water level monitoring applications. The proposed methodology improved accuracy by 0.16-0.39% by moving the sensor to estimate the distance relative to different locations. Additional power is generated by executing a multi-step measurement while the power self-optimizing process used dynamically adjusts the settings to balance the current of charging and discharging. The battery level can efficiently go over 50% in a stable charging simulation. These methodologies were successfully implemented using an embedded control device, an ultrasonic sensor module, a LORA transmission module, and a stepper motor. According to the experimental results, the proposed multi-step methodology has the benefits of high accuracy and efficient power consumption for water level monitoring applications.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article