التفاصيل البيبلوغرافية
| العنوان: |
A High-Accuracy and Power-Efficient Self-Optimizing Wireless Water Level Monitoring IoT Device for Smart City |
| المؤلفون: |
Tsun-Kuang Chi, Hsiao-Chi Chen, Shih-Lun Chen, Patricia Angela R. Abu |
| المصدر: |
Sensors, Vol 21, Iss 6, p 1936 (2021) |
| بيانات النشر: |
MDPI AG, 2021. |
| سنة النشر: |
2021 |
| المجموعة: |
LCC:Chemical technology |
| مصطلحات موضوعية: |
Internet of Things, smart city, power saving, self-optimizing, water level monitoring, self-adapting software engineering, Chemical technology, TP1-1185 |
| الوصف: |
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. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
1424-8220 |
| Relation: |
https://www.mdpi.com/1424-8220/21/6/1936; https://doaj.org/toc/1424-8220 |
| DOI: |
10.3390/s21061936 |
| URL الوصول: |
https://doaj.org/article/602fdf55c4a6473da92e03a30ea221b8 |
| رقم الانضمام: |
edsdoj.602fdf55c4a6473da92e03a30ea221b8 |
| قاعدة البيانات: |
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