This paper is published in Volume-5, Issue-2, 2019
Area
Computer Engineering
Author
Divya Muddala, Dhanashree Kamble, Pooja Nimbalkar, Ravina Patil, Sathish K. Penchala
Org/Univ
Dr. D. Y. Patil School of Engineering and Technology, Pune, Maharashtra, India
Pub. Date
03 May, 2019
Paper ID
V5I2-2111
Publisher
Keywords
Sensors [A.I.], Input/output and data communications, Microcontroller – Node MCU, M-7053D, tGW-715. [Barrier Lifting]

Citationsacebook

IEEE
Divya Muddala, Dhanashree Kamble, Pooja Nimbalkar, Ravina Patil, Sathish K. Penchala. IoT based bridge monitoring system, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Divya Muddala, Dhanashree Kamble, Pooja Nimbalkar, Ravina Patil, Sathish K. Penchala (2019). IoT based bridge monitoring system. International Journal of Advance Research, Ideas and Innovations in Technology, 5(2) www.IJARIIT.com.

MLA
Divya Muddala, Dhanashree Kamble, Pooja Nimbalkar, Ravina Patil, Sathish K. Penchala. "IoT based bridge monitoring system." International Journal of Advance Research, Ideas and Innovations in Technology 5.2 (2019). www.IJARIIT.com.

Abstract

A bridge monitoring system is significant to the structural health monitoring of both old/new bridges and flyovers an infrastructure daily used by citizens of their respective countries. The following report is proposed and developed as architecture for bridge monitoring on a more secure level taking into consideration the various parameters that are involved in the structural health of bridges. A 3-level distributed structure is adopted in the monitoring system, which includes a central server, intelligent acquisition node, and local controller. Acquisition nodes are located across the bridge. One local controller manages all the acquisition nodes. Every acquisition node has 8 channels, which can easily and approximately sample the deviation of the line of sight, the vibration of the bridge due to a load of various transports and as well the water level which when cross a threshold lead to a flood. To get high precision data, a 10 bits A/D converter is being used. Compared to the traditional method, the proposed architecture has two features. The acquisition node is a smart device based on a powerful controller. Signals of field sensors are analyzed and real-time compressed in the acquisition node. Only the processing results are sent to the local controller through the IEEE 802.11 wireless network. This operation can relieve the load of a central server. The intelligent monitoring system has run on a large span bridge. Running results show that the proposed system is stable and effective.