{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T18:41:12Z","timestamp":1768588872120,"version":"3.49.0"},"reference-count":23,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007179","name":"University of New Mexico","doi-asserted-by":"publisher","award":["Innovative Teaching 2018"],"award-info":[{"award-number":["Innovative Teaching 2018"]}],"id":[{"id":"10.13039\/100007179","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006602","name":"Air Force Research Laboratory","doi-asserted-by":"publisher","award":["FA9453-18-2-0022 P0002"],"award-info":[{"award-number":["FA9453-18-2-0022 P0002"]}],"id":[{"id":"10.13039\/100006602","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Transportation Consortium of South-Central States (TRANSET); US Department of Transportation (USDOT)","award":["17STUNM02"],"award-info":[{"award-number":["17STUNM02"]}]},{"name":"Transportation Consortium of South-Central States (TRANSET); US Department of Transportation (USDOT)","award":["18STUNM03"],"award-info":[{"award-number":["18STUNM03"]}]},{"DOI":"10.13039\/100008902","name":"Los Alamos National Laboratory","doi-asserted-by":"publisher","award":["493274"],"award-info":[{"award-number":["493274"]}],"id":[{"id":"10.13039\/100008902","id-type":"DOI","asserted-by":"publisher"}]},{"name":"New Mexico Consortium","award":["A19-0260-002"],"award-info":[{"award-number":["A19-0260-002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>Wireless sensor networks (WSN) are used by engineers to record the behavior of structures. The sensors provide data to be used by engineers to make informed choices and prioritize decisions concerning maintenance procedures, required repairs, and potential infrastructure replacements. However, reliable data collection in the field remains a challenge. The information obtained by the sensors in the field frequently needs further processing, either at the decision-making headquarters or in the office. Although WSN allows data collection and analysis, there is often a gap between WSN data analysis results and the way decisions are made in industry. The industry depends on inspectors\u2019 decisions, so it is of vital necessity to improve the inspectors\u2019 access in the field to data collected from sensors. This paper presents the results of an experiment that shows the way Augmented Reality (AR) may improve the availability of WSN data to inspectors. AR is a tool which overlays the known attributes of an object with the corresponding position on the headset screen. In this way, it allows the 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. The experiment reported in this paper involves the application of a smart Strain Gauge Platform, which automatically measures strain for different applications, using a wireless sensor. In this experiment, an AR headset was used to improve actionable data visualization. The results of the reported experiment indicate that since the AR headset makes it possible to visualize information collected from the sensors in a graphic form in real time, it enables automatic, effective, reliable, and instant communication from a smart low-cost sensor strain gauge to a database. Moreover, it allows inspectors to observe augmented data and compare it across time and space, which then leads to appropriate prioritization of infrastructure management decisions based on accurate observations.<\/jats:p>","DOI":"10.3390\/robotics9010003","type":"journal-article","created":{"date-parts":[[2020,1,3]],"date-time":"2020-01-03T04:43:03Z","timestamp":1578026583000},"page":"3","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Design and Implementation of a Connection between Augmented Reality and Sensors"],"prefix":"10.3390","volume":"9","author":[{"given":"Marlon","family":"Aguero","sequence":"first","affiliation":[{"name":"Department of Civil, Construction and Environmental Engineering, University of New Mexico, Albuquerque, NM 87131, USA"}]},{"given":"Dilendra","family":"Maharjan","sequence":"additional","affiliation":[{"name":"Department of Civil, Construction and Environmental Engineering, University of New Mexico, Albuquerque, NM 87131, USA"}]},{"given":"Maria del Pilar","family":"Rodriguez","sequence":"additional","affiliation":[{"name":"Department of Civil, Construction and Environmental Engineering, University of New Mexico, Albuquerque, NM 87131, USA"}]},{"given":"David Dennis Lee","family":"Mascarenas","sequence":"additional","affiliation":[{"name":"Los Alamos National Laboratory, Los Alamos, NM 87545, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7105-7843","authenticated-orcid":false,"given":"Fernando","family":"Moreu","sequence":"additional","affiliation":[{"name":"Department of Civil, Construction and Environmental Engineering, University of New Mexico, Albuquerque, NM 87131, USA"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chang, P.C., Flatau, A., and Liu, S.C. (2003). Health Monitoring of Civil Infrastructure. Struct. Health Monit., 257\u2013267.","DOI":"10.1177\/1475921703036169"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Cross, E., Worden, K., and Farrar, C. (2013). Structural health monitoring for civil infrastructure. Health Assessment of Engineering Structures: Bridges and Other Infrastructure, World Scientific Publishing.","DOI":"10.1142\/9789814439022_0001"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Chen, H.-P., and Ni, Y.-Q. (2018). Structural Health Monitoring of Large Civil Engineering Structures, Wiley-Blackwell.","DOI":"10.1002\/9781119166641"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Schmalstieg, D., and H\u00f6llerer, T. (2016). Augmented Reality: Principles and Practice, Addison-Wesley.","DOI":"10.1109\/ISMAR-Adjunct.2016.0015"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"50","DOI":"10.3389\/fbuil.2019.00050","article-title":"Combination of Image-Based Documentation and Augmented Reality for Structural Health Monitoring and Building Pathology","volume":"5","author":"Napolitano","year":"2019","journal-title":"Front. Built Environ."},{"key":"ref_6","unstructured":"Bleck, B.M., Katko, B.J., Trujillo, J.B., Harden, T.A., Farrar, C.R., Wysong, A.R., and Mascarenas, D.D.L. (2019, October 01). Augmented Reality Tools for the Development of Smart Nuclear Facilities, Available online: https:\/\/www.osti.gov\/servlets\/purl\/1374269."},{"key":"ref_7","unstructured":"Moreu, F., Lippitt, C., Maharjan, D., Aguero, M., and Yuan, X. (2019). Augmented Reality Enhancing the Inspections of Transportation Infrastructure: Research, Education, and Industry Implementation. Publications, 55. Available online: https:\/\/digitalcommons.lsu.edu\/transet_pubs\/55."},{"key":"ref_8","unstructured":"Morales Garcia, J.E., Gertsen, H.J., Liao, A.S.N., and Mascarenas, D.D.L. (2017). Augmented Reality for Smart Infrastructure Inspection, Los Alamos National Lab. (LANL). Technical report."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1007\/978-3-319-74793-4_23","article-title":"Augmented reality for next generation infrastructure inspections","volume":"Volume 3","author":"Ballor","year":"2019","journal-title":"Model Validation and Uncertainty Quantification"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Boller, C., Chang, F.-K., and Fujino, Y. (2009). Maintenance Principles for Civil Structures. Encyclopedia of Structural Health Monitoring, John Wiley & Sons.","DOI":"10.1002\/9780470061626"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1715","DOI":"10.1016\/j.engstruct.2005.02.021","article-title":"Technology developments in structural health monitoring of large-scale bridges","volume":"27","author":"Ko","year":"2005","journal-title":"Eng. Struct."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Doebling, S., Farrar, C., Prime, M., and Shevitz, D. (1996). Damage Identification and Health Monitoring of Structural and Mechanical Systems from Changes in their Vibration Characteristics: A Literature Review, Los Alamos National Laboratory. Los Alamos National Laboratory Report LA-13070-MS.","DOI":"10.2172\/249299"},{"key":"ref_13","unstructured":"Sohn, H., Farrar, C., Hemez, F., Shunk, D., Stinemates, D., and Nadler, B. (2004). A Review of Structural Health Monitoring Literature: 1996\u20132001, Los Alamos National Laboratory. Report LA-13976-MS."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/MIC.2006.38","article-title":"Monitoring civil structures with a wireless sensor network","volume":"10","author":"Chintalapudi","year":"2006","journal-title":"IEEE Internet Comput."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/S1389-1286(01)00302-4","article-title":"Wireless sensor networks: A survey","volume":"38","author":"Akyildiz","year":"2002","journal-title":"Comput. Netw."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Aguero, M., Ozdagli, A., and Moreu, F. (2019). Measuring Reference-Free Total Displacements of Piles and Columns Using Low-Cost, Battery-Powered, Efficient Wireless Intelligent Sensors (LEWIS2). Sensors, 19.","DOI":"10.3390\/s19071549"},{"key":"ref_17","unstructured":"Banzi, M. (2011). Getting Started with Arduino, O\u2019Reilly Media, Inc."},{"key":"ref_18","unstructured":"Arduino (2019, October 01). Arduino Uno Rev3. Available online: https:\/\/store.arduino.cc\/usa\/arduino-uno-rev3."},{"key":"ref_19","unstructured":"XBee Explorer (2019, October 01). SparkFun XBee Explorer USB. Product Information. Available online: https:\/\/www.sparkfun.com\/products\/11812."},{"key":"ref_20","unstructured":"Nanotech (2019, October 01). Turnigy Nano-Tech 1000mah 2S 25~50C Lipo Pack. Product information. Available online: https:\/\/hobbyking.com\/en_us\/turnigy-nano-tech-1000mah-2s-25-50c-lipo-pack.html?___store=en_us."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1016\/j.promfg.2015.07.333","article-title":"Human factors considerations for the application of augmented reality in an operational railway environment","volume":"3","author":"Hall","year":"2015","journal-title":"Procedia Manuf."},{"key":"ref_22","unstructured":"Holmdahl, T. (Microsoft Devices Blog, 2015). BUILD 2015: A closer look at the Microsoft HoloLens hardware, Microsoft Devices Blog."},{"key":"ref_23","unstructured":"Lass, W. (2015). The Future of Augmented Reality: Limitations, Possibilities and Hopes, Available online: https:\/\/www.emergingedtech.com\/2015\/07\/future-of-augmented-reality-limitations-possibilities-hopes\/."}],"container-title":["Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-6581\/9\/1\/3\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:28:30Z","timestamp":1760362110000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-6581\/9\/1\/3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,1]]},"references-count":23,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2020,3]]}},"alternative-id":["robotics9010003"],"URL":"https:\/\/doi.org\/10.3390\/robotics9010003","relation":{},"ISSN":["2218-6581"],"issn-type":[{"value":"2218-6581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,1]]}}}