A method to operate a system for monitoring the health of civil and mechanical engineering structures on real-time basis to identify and predict future structural integrity of said structures through wireless transmission of data, the system comprising:
- at least one sensor (S) connected to at least one node processor (1, 1a, 1b, 1c, . . . 1n);
- two or more types of gateways;
- a communication module comprising a closed network communication module and an open network communication module;
- a trigger function software client;
- and
- a graphic user interface or dashboard,
- wherein said system communicates between the sensor (S), the node processor (1, 1a, 1b, 1c, . . . 1n) and the two or more gateways through said communication module (C) to identify structural anomaly on real-time basis and to predict structural integrity of civil structures by evaluating feasibility of wireless structural health monitoring (SHM) of civil structures encompassing internet-of-things (TOT) and machine learning models,
- wherein said two or more types of gateways comprising:
- a first type of gateway, wherein the first type of gateway is a physical device gateway that communicates data wirelessly with the node processor via closed network communication module;
- and
- a second type of gateway, wherein the second type of gateway is a cloud gateway that wirelessly authenticates and communicates data with the physical device gateway via open network communication module,
- wherein
- said node processor converts raw sensor data into engineering data and transfers said engineering data to said physical device gateway via said closed network communication module,
- said physical device gateway aggregates and validates said engineered data to the cloud gateway through a secure communication protocol,
- said trigger function software client evaluates the incoming real-time data on the cloud gateway and allows trigger function to route said engineering data to cloud storage and cloud analytics and alert depending upon predefined keywords or threshold on the cloud gateway,
- said system being capable of connecting one or more machine learning models to help user identify structural behavior anomalies and forecast trends,
- said method comprises the steps of:
- deploying said at least one sensor or actuator to collect raw sensor data;
- connecting each of said sensor to said at least one node processor to convert said raw sensor data into engineering data;
- transferring said engineered data to said physical device gateway via said closed network communication module where said physical device gateway aggregates and validates said engineering data;
- transmission of said validated data from said physical device gateway to said cloud gateway through a secure communication protocol;
- transmission of said validated data from said cloud gateway to said trigger function software client that evaluates the incoming real-time data on the cloud gateway and to trigger function to route said real-time data to said cloud storage or cloud analytics or alert system;
- and
- display of said data as the dataset on dashboard wherein conclusive conditional statement about real-time structural anomalies and forecast trends based on correlated analytics of multiple parameters is displayed;
- wherein said method employs machine learning models and Internet of things to predict the future maintenance and identity structural anomalies of civil and mechanical engineering structures through wireless data transfer enabling users to take early decisions on maintenance and rehabilitation.