Remote Sensing Using Augmented Reality and Low-Cost Sensors

Abstract

The application of sensors in structural health monitoring (SHM) is of utmost importance, as they record the behavior of structures and help structural engineers to make and prioritize informed decisions about necessary repairs, replacement of infrastructure or maintenance procedures. However, although many of the sensors that are currently used in SHM provide the necessary quantitative information, it is difficult to collect it in the field, and they require further processing of data obtained in the field later in the office or at the decision-making headquarters. Such an approach to SHM delays decision making. Wireless sensors networks (WSN) are designed to analyze the data so that the decisions could be performed remotely. However, there is still a gap between remotely operated WSN and the way decisions are performed in the industry. In general, the industry relies on inspectors’ decisions. If WSN could provide direct information to inspectors, the industry decisions would be improved by the obtained data. This paper shows that the availability of WSN data to inspectors can be improved through the application of Augmented Reality (AR) tools. AR is a tool which overlays the known attributes of an object in the corresponding position on the computer screen. In this way it allows integration of reality with a virtual representation provided by a computer in real time. These additional synthetic overlays supply data that may be unavailable otherwise, but it may also display additional contextual information. For the SHM purposes, AR permits engineers to directly interact with the real world and it enables visualization and integration of SHM with inspectors at the field. For example, HoloLens make it possible to visualize information coming from the sensors in a graphic form in real time. Specifically, the results of the research carried out by the authors of this abstract indicate that the application of HoloLens enables effective communication from low-cost sensors (Accelerometer, Strain gauge, and Laser TFMini - Micro Lidar module) to a database in real time in a reliable way.