Bridge Monitoring is a critical application to ensure safety for people who cross. A bridge is in fact subject not only to excavations or soil handling provided by human activity, but also to water action(s) around pillars.
First of all, we had to decide which devices best fitted with the application and we found some sensor types:
Strain gauge is also a useful tool, but we decided not to use it, because it needs to be embedded in concrete to work properly and to monitor the curing process, so it needs to be placed during construction.
Then, we had to face the problem of many nodes of measure with different measure point each; in case of wired systems, this involves the presence of many cables running aside the bridge with the increases risk of fault possibility and of noise introduction - thus degrading the sensor signal. A single datalogger solution as concentration point is deprecated.
In order to propose a good and accured monitoring solutions, we had to keep clear in mind the critical parameters for the whole monitoring system (sensors and interface);
A miniOMNIAlog device was placed in every measure node, in order to monitor every joint, pillar and truss; all these recorded data have been stored and shown through Next Industries' IoT Cloud Web Portal, which also enables mail alarms and data analisys together with real time control of field devices. One of the most appreciated features of this Portal is the possibility to create different dashboards and to customize them through widgets like: Gauge, Gauges combination, Inclinometers, Line Charts, Histograms, Tables, Maps (to geolocalize sensor/daq system), Images (for example, a picture of the bridge with sensor's reading overlay where each sensor position is showed).
Thanks to the use of miniOMNIAlog SigFox, the following results have been achieved;
Key top feature of this solution is the open possibility to use the same monitoring and control system in a wide variety of environments including smart water, environment, exploration and a great number of other science applications.
Ability to provide samples: Yes
Production capabilities: 1,000-10,000 items