Combination of Image-Based Documentation and Augmented Reality for Structural Health Monitoring and Building Pathology

With the current deterioration rate of existing infrastructure, the importance of intervention and preservation efforts such as on-site visual inspections, non-destructive evaluation, structural health monitoring (SHM), and building pathology are on the rise. A critical aspect of these intervention and preservation methods is the visualization and accessibility of large, heterogeneous data sets. To enable diverse stakeholders to make informed choices, data and metadata for the built environment needs to be directly integrated into a user's viewing environment. To address this challenge, a human-machine interface which organizes these types of data and provides actionable information is necessary. The main aim of this work is to develop a preliminary framework for documenting and visualizing data about the built environment both on and off site using a combination of image-based documentation and augmented reality (AR). While this work illustrates preliminary annotation mechanisms such as drawing, the concept of projecting data between the image-based environment and the AR environment is the main contribution of this work. This method was applied to test objects as well as case studies in SHM and building pathology

A network-aware framework for energy-efficient data acquisition in wireless sensor networks

Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot+, a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot+ in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot+ using real datasets and show that KSpot+ provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN

Virtual Tour (VT), Informational Modeling (IM), and Augmented Reality (AR) for Visual Inspections (VI) and Structural Health Monitoring (SHM)

69A3551847102Existing infrastructure in the U.S. is deteriorating; the symptoms of overdue maintenance and underinvestment are ever-present in our society (rated with D+ by American Society of Civil Engineers, ASCE). To ensure the safety of existing infrastructure, on-site life-time inspections and monitoring are required. While these methods yield a great deal of raw and analyzed data, current methods for their simple and intuitive management, (i.e., simple and intuitive integration, documentation, access, and visualization), are severely lacking and can lead to mismanagement of infrastructure resources. To enable both on- and off-site documenting and viewing of infrastructure a novel method was developed in this project, which combines image-based documentation, Virtual Tours (VT) and informational modeling (IM), and augmented reality (AR). A cross-platform, client-server system for creating, saving, and viewing annotations was designed and implemented. The strengths and weaknesses of this implementation were addressed, and the accuracy of the approach was evaluated. The findings of this work show the promise of VT/IM/AR as a useful framework for documenting the built environment and assisting access and visualization of data and metadata related to SHM and visual inspections. This work presents a prototype and includes the proof of concept and real-life application

Low-cost sensors technologies for monitoring sustainability and safety issues in mining activities: advances, gaps, and future directions in the digitalization for smart mining

Nowadays, monitoring aspects related to sustainability and safety in mining activities worldwide are a priority, to mitigate socio-environmental impacts, promote efficient use of water, reduce carbon footprint, use renewable energies, reduce mine waste, and minimize the risks of accidents and fatalities. In this context, the implementation of sensor technologies is an attractive alternative for the mining industry in the current digitalization context. To have a digital mine, sensors are essential and form the basis of Industry 4.0, and to allow a more accelerated, reliable, and massive digital transformation, low-cost sensor technology solutions may help to achieve these goals. This article focuses on studying the state of the art of implementing low-cost sensor technologies to monitor sustainability and safety aspects in mining activities, through the review of scientific literature. The methodology applied in this article was carried out by means of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and generating science mapping. For this, a methodological procedure of three steps was implemented: (i) Bibliometric analysis as a quantitative method, (ii) Systematic review of literature as a qualitative method, and (iii) Mixed review as a method to integrate the findings found in (i) and (ii). Finally, according to the results obtained, the main advances, gaps, and future directions in the implementation of low-cost sensor technologies for use in smart mining are exposed. Digital transformation aspects for data measurement with low-cost sensors by real-time monitoring, use of wireless network systems, artificial intelligence, machine learning, digital twins, and the Internet of Things, among other technologies of the Industry 4.0 era are discussed.The authors are indebted to the projects PID2021-126405OB-C31 and PID2021-126405OB-C32 funded by FEDER funds—A Way to Make Europe and Spanish Ministry of Economy and Competitiveness MICIN/AEI/10.13039/501100011033/. The financial support of the Research Department of the Catholic University of Temuco and the Civil Engineering Department of the University of Castilla-La Mancha is also appreciated.Peer ReviewedPostprint (published version

Earth Observation Open Science and Innovation

geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc

Geospatial Information Research: State of the Art, Case Studies and Future Perspectives

Geospatial information science (GI science) is concerned with the development and application of geodetic and information science methods for modeling, acquiring, sharing, managing, exploring, analyzing, synthesizing, visualizing, and evaluating data on spatio-temporal phenomena related to the Earth. As an interdisciplinary scientific discipline, it focuses on developing and adapting information technologies to understand processes on the Earth and human-place interactions, to detect and predict trends and patterns in the observed data, and to support decision making. The authors – members of DGK, the Geoinformatics division, as part of the Committee on Geodesy of the Bavarian Academy of Sciences and Humanities, representing geodetic research and university teaching in Germany – have prepared this paper as a means to point out future research questions and directions in geospatial information science. For the different facets of geospatial information science, the state of art is presented and underlined with mostly own case studies. The paper thus illustrates which contributions the German GI community makes and which research perspectives arise in geospatial information science. The paper further demonstrates that GI science, with its expertise in data acquisition and interpretation, information modeling and management, integration, decision support, visualization, and dissemination, can help solve many of the grand challenges facing society today and in the future

Real-time environmental monitoring, visualization, and notification system for construction H&S management

Construction workers who are exposed to hot and humid environments are at high risk of heat stress. Excessive exposure to such environments can result in occupational illnesses and injuries. Acquisition of sensor data from such environments is essential to ensure improved Health and Safety (H&S) of workers. Building Information Modeling (BIM) offers a new epitome to provide comprehensive solutions for H&S and evacuation planning in buildings. Researchers around the globe have presented hybrid solutions for integrating different sensing technologies with BIM such as Radio Frequency Identification (RFID) tags, Ultra High Frequency (UHF) readers and sensors. A review and critical evaluation of literature on integrated solutions of BIM with various sensing technologies is performed in order to present a hybrid solution based on BIM and Wireless Sensors Network (WSN) along with a notification system for real-time environmental monitoring of buildings. The application, entitled “Real-Time Environmental Monitoring, Visualization and Notification System”, is expected to provide a new horizon for effective visualization, reliable data capturing and catering to time sensitive emergency situations for construction H&S management. The paper will also outline scope of future research in this domain