Low-Cost Internet of Things Based Real- Time Pavement Monitoring System

A low-cost IoT-based data collection apparatus for pavement monitoring systems was developed and tested in this study. The proposed system consists of various components, and each part requires a specific design. Therefore, the complete system is partitioned into five modules (Sensor, power, IoT, LT...

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Bibliographic Details
Published in2021 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics) pp. 17 - 22
Main Authors Bekiroglu, Korkut, Tekeoglu, Ali, Shen, Jiayue, Boz, Ilker
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2021
Subjects
Cloud computing
data collection
IoT
Life estimation
Microprocessors
pavement monitoring system
Real-time systems
Social computing
Temperature distribution
Temperature sensors
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Summary:A low-cost IoT-based data collection apparatus for pavement monitoring systems was developed and tested in this study. The proposed system consists of various components, and each part requires a specific design. Therefore, the complete system is partitioned into five modules (Sensor, power, IoT, LTE/4G, and UI/WebApp modules), and each module is developed according to the project specification. While designing the modules, rough environmental conditions alongside pavements in rural areas are considered. Therefore, the final product can be used in rural areas to collect real-time data as long as there are LTE connections in the area. The final product allows users to collect real-time, dense data such as strain, pressure, temperature, and humidity without traveling to the site. In addition, the data is accessible anywhere in the world as long as an internet connection is available. The developed apparatus is tested through the sensors embedded under the heavy vehicle simulator (HVS) at the Accelerated Pavement Testing (APT) facility located at Blacksburg, Virginia. The continuous data streaming to the Cloud, as well as even more dense data, is collected and recorded in the local microprocessor Raspberry-pi memory and Cloud at the same time. The sample data both from local R-pi and Cloud is presented in this paper.
DOI:10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics53846.2021.00018