An event-adaptive control mechanism of the tunnel monitoring system based on the information granularity

In applications of structural health monitoring of tunnels, wireless sensor network (WSN) is a useful technology for information extraction by using lots of different types of small-sized sensors. Existing tunnel monitoring systems have defects in understanding and using information, and there are few excellent data interpretation methods and adaptive feedback control mechanisms in WSNs. To improve the situation, an event-adaptive control mechanism of tunnel monitoring system based on the information granularity is presented in this work. The main idea in devising such a mechanism is to describe events quickly and then to adjust the monitoring system based on event description through the following two parts. Firstly, an information granularity model based on multi-sensor data is proposed. Its main process is implementing uncertain transforming between quantitative expressions and qualitative concepts through the fuzzy theory. Secondly, an event-adaptive control mechanism based on the information granularity model is presented. It is timely and effective to perceive the general condition of the tunnel by analyzing the information granularity evolved from large amounts of hybrid raw information. The information granularity is therefore used as the input of the event-adaptive control system which draws conclusions. Basing on these conclusions, this work realizes real-time feedback control of the tunnel monitoring system. The mechanism presented is validated on simulation experiments. The result shows that the information granularity can describe events with good accuracy and timeliness. And the event-adaptive control mechanism based on the information granularity can intelligently adjust the tunnel monitoring system with great efficiency and timeliness.