بررسی قابلیت سنسور مدت پرواز گوشی‌های‌ هوشمند در داده‌بَرداری فضای داخلی ساختمان

نوع مقاله : مقاله پژوهشی

نویسندگان

• محمد عموشاهی
• اصغر میلان
• سعید صادقیان
• علیرضا قراگوزلو

دانشکده مهندسی عمران، آب و محیط‌زیست، دانشگاه شهید بهشتی، تهران، ایران

10.22067/jfcei.2024.88986.1315

چکیده

باتوجه‌به افزایش چشمگیر در استفاده از مدل‌سازی اطلاعات ساختمان (BIM ) و نقش برجسته آن در صنایع معماری، مهندسی و ساخت‌وساز (AEC )، دستیابی به یک مدل وضعیت موجود دقیق از اهمیت ویژه‌ای برخوردار است. درعین‌حال، ابزارهای کنونی برای تهیه داده‌های سه‌بعدی و بازسازی وضعیت موجود ساختمان‌ها با چالش‌هایی نظیر محدودیت در دقت و هزینه‌های بالا مواجه هستند. از زمان معرفی سنسور لیدار در گوشی‌های آیفون در سال 2020، تحقیقات گسترده‌ای برای ارزیابی قابلیت این سنسور در حوزه‌های مختلف به‌ویژه نقشه‌برداری صورت‌گرفته است. این پژوهش به مقایسه داده‌های اسکن سه‌بعدی آیفون در دو حالت با و بدون استفاده از گیمبال با داده‌های حاصل از فتوگرامتری و توتال استیشن می‌پردازد. نتایج نشان می‌دهد که استفاده از گیمبال باعث رفع خطای اسکن چندگانه و افزایش دقت هندسی می‌شود. در تحلیل ابر به ابر (C2C ) بدون گیمبال، خطاهای بیش از 35 سانتی‌متر مشاهده شد، درحالی‌که با استفاده از گیمبال، این خطاها به حداقل رسیده و اکثر اختلافات زیر 0.10 سانتی‌متر بودند. با وجود در برخی از قسمت ها خطا 10 تا 20 سانتی‌متر باقی ماند. مقدار خطای ریشه میانگین مربعات (RMSE) برای داده‌های بُرداری تلفن هوشمند بین 15 تا 20 سانتی‌متر بوده است. در مقایسه، RMSE توتال استیشن و فتوگرامتری به ترتیب 2 میلی‌متر و 1.5 سانتی‌متر اندازه‌گیری شده است. بنابراین داده‌های تلفن‌های هوشمند برای نقشه‌برداری داخلی با دقت متوسط مناسب هستند، اما برای پروژه‌های مهندسی دقیق قابل اعتماد نیستند.

کلیدواژه‌ها

• گوشی هوشمند
• اسکنر سه‌بعدی
• فتوگرامتری
• مدل‌ اطلاعات ساختمان
• کاداستر سه‌بعدی

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عنوان مقاله [English]

Investigating The Capability Of The Smartphones Time-Of-Flight Sensor To data-capturing Interior Spaces Of Building

نویسندگان [English]

• Mohammad Amooshahi
• Asghar Milan
• Saeid Sadeghian
• Alireza Gharagozlou

Faculty of Civil, Water and Environment Engineering Faculty, Shahid Beheshti University, Tehran, Iran.

چکیده [English]

Considering the significant increase in the use of Building Information Modeling (BIM) and its prominent role in the Architecture, Engineering, and Construction (AEC) industries, achieving an accurate as-built model is of critical importance. However, current tools for acquiring 3D data and reconstructing as-built building conditions face challenges such as limitations in accuracy and high costs. Since the introduction of the LiDAR sensor in iPhones in 2020, extensive research has been conducted to evaluate the capabilities of this sensor across various fields, especially in surveying. This study compares 3D scan data from the iPhone in two modes— with and without the use of a gimbal— with data obtained from photogrammetry and a total station. The results show that using a gimbal eliminates the errors from multiple scans and enhances geometric accuracy. In the cloud-to-cloud (C2C) analysis without a gimbal, errors exceeding 35 cm were observed, while with the gimbal, these errors were minimized, with most discrepancies being below 0.10 cm. Although some errors ranging from 10 to 20 cm were present, the root mean square error (RMSE) for smartphone-derived vector data ranged between 15 to 20 cm. In comparison, the RMSE for the total station and photogrammetry was measured at 2 mm and 1.5 cm, respectively. While the accuracy of this data is lower, it is suitable for medium-accuracy indoor building surveys, though it is less reliable for engineering projects requiring very high precision.

کلیدواژه‌ها [English]

• Smartphone
• 3D scanner
• photogrammetry
• building information model
• 3D cadastre

مراجع

[1]   C., Oluwadare and M., Salami,"Comparative Analysis of Smartphones and Survey-Grade GNSS Receivers for Parcel Boundary Determination", Journal of Geoinformatics & Environmental Research, 3(01), Pp. 10–22. (2022).

[2]    S.D.G., Arabinda, "Smartphone as a Real-time and Participatory Data Collection Tool for Civil Engineers", International Journal of Modern Computer Science. (2014).

[3]   K. J. W., McCaffrey, R. R., Jones, R. E., Holdsworth, R. W., Wilson, P., Clegg, J., Imber, N., Holliman and I.,Trinks, "Unlocking the spatial dimension: Digital technologies and the future of geoscience fieldwork", Journal of the Geological Society, 162(6), 927–938. https://doi.org/10.1144/0016-764905-017, (2005).

[4]   S., Tavani, A., Billi, A., Corradetti, M., Mercuri, A., Bosman, M., Cuffaro, T., Seers and E.,Carminati, "Smartphone assisted fieldwork: Towards the digital transition of geoscience fieldwork using LiDAR-equipped iPhones", Earth-Science Reviews, 227, 103969. https://doi.org/10.1016/J.EARSCIREV .2022.103969, (2022).

[5]   K., Khoshelham, H., Tran and D., Acharya, "Indoor mapping eyewear: Geometric evaluation of spatial mapping capability of hololens", International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 42(2/W13), 805–810. https://doi.org/10.5194/ISPRS-ARCHIVES-XLII-2-W13-805-2019, (2019).

[6]   H., Patrick, S., Landgraf, W., Martin and S., Wursthorn, "Evaluation of the Microsoft HoloLens for the Mapping of Indoor Building Environments", Conference: Dreiländertagung Der DGPFDer OVG Und Der SGPFAt: Wien., (2019).

[7]   L., Díaz-Vilariño, H., Tran, E., Frías, J., Balado and K., Khoshelham, "3D MAPPING OF INDOOR AND OUTDOOR ENVIRONMENTS USING APPLE SMART DEVICES", International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 43(B4-2022), 303–308. (2022). https://doi.org/10.5194/ISPRS-ARCHIVES-XLIII-B4-2022-303-2022

[8]   S., Xia, D., Chen, R., Wang, J., Li and X., Zhang, "Geometric Primitives in LiDAR Point Clouds: A Review", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, Pp. 685–707. https://doi.org/10.1109/JSTARS.2020.2969119, (2020).

[9]   A., Murtiyoso, P., Grussenmeyer, T., Landes and H., Macher, "First assessments into the use of commercial-grade solid state lidar for low cost heritage documentation", International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 43(B2-2021), Pp. 599–604, (2021).

[10] M., Reynolds, J., Doboš, L., Peel, T., Weyrich and G. J., Brostow, "Capturing Time-of-Flight data with confidence", Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 945–952. (2011). https://doi.org/10.1109/CVPR.2011.5995550

[11] A., Prusak, O., Melnychuk, H., Roth, I., Schiller and R., Koch, "Pose estimation and map building with a Time-Of- Flight-camera for robot navigation", International Journal of Intelligent Systems Technologies and Applications, 5(3–4), 355–364. (2008). https://doi.org/10.1504/IJISTA.2008.021298

[12] S., May, D., Dröschel, D., Holz, F., Iais, S., Fuchs and  A., Nüchter, "Robust 3D-Mapping with Time-of-Flight Cameras", (2009).

[13] S., Agnes, B., Liu, J., Penne, O., Jesorsky and R., Kompe, "A Comprehensive System for 3D Modeling from Range Images Acquired from a 3D ToF Sensor", 5th International Conference on Computer Vision Systems (ICVS 2. (2007).

[14] J., Feulner, J., Penne, E., Kollorz and J., Hornegger, "Robust Real-Time 3D Modeling of Static Scenes Using Solely a Time-of-Flight Sensor", In 6th IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum,  (2009).

[15] D., Costantino, G., Vozza, M., Pepe and V. S. , Alfio, "Smartphone LiDAR Technologies for Surveying and Reality Modelling in Urban Scenarios: Evaluation Methods, Performance and Challenges", Applied System Innovation 2022, Vol. 5, Page 63, 5(4), 63. https://doi.org/10.3390/ASI5040063, (2022).

[16] N., Bursztyn, B., Shelton, A., Walker and J., Pederson, "Increasing undergraduate interest to learn geoscience with GPS-based augmented reality field trips on students’ own smartphones", GSA Today, 27(6), 4–10. https://doi.org/10.1130/GSATG304A.1, (2017).

[17] D. G., De Paor, "Virtual Rocks", GSA Today, 26(8), 4–11. (2016). https://doi.org/10.1130/GSATG257A.1

[18] A. F., Glazner and J., Douglas Walker, "StraboTools: A mobile app for quantifying fabric in geology", GSA Today, 30(8), 1– 8, (2020). https://doi.org/10.1130/GSATG454A.1

[19] T. L., Pavlis, R., Langford, J., Hurtado and L., Serpa, "Computer-based data acquisition and visualization systems in field geology: Results from 12 years of experimentation and future potential", Geosphere, 6(3), 275–294., (2010). https://doi.org/10.1130/GES00503.1

[20] J. D., Walker, B., Tikoff, J., Newman, R., Clark, J., Ash, J., Good, E. G., Bunse, A., Möller, M., Kahn, R. T., Williams, Z., Michels, J. E., Andrew and C., Rufledt, "StraboSpot data system for structural geology,ˮ Geosphere, 15(2), 533–547. (2019). https://doi.org/10.1130/GES02039.1

[21] S. J., Whitmeyer, E. J., Pyle, T. L., Pavlis, W., Swanger and L., Roberts, Modern approaches to field data collection and mapping: Digital methods, crowdsourcing, and the future of statistical analyses", Journal of Structural Geology, 125, 29–40. (2019). https://doi.org/10.1016/J.JSG.2018.06.023

[22]R. W., Allmendinger, C. R., Siron and C. P., Scott, "Structural data collection with mobile devices: Accuracy, redundancy, and best practices", Journal of Structural Geology, 102, 98–112. (2017). https://doi.org/10.1016/J.JSG.2017.07.011,

[23] L., Novakova and T. L., Pavlis, "Modern methods in structural geology of twenty-first century: Digital mapping and digital devices for the field geology", Springer Geology, 43–54. (2019). https://doi.org/10.1007/978-981-13-2781-0_3/COVER

[24] F., Zangenehnejad and Y., Gao, "GNSS smartphones positioning: advances, challenges, opportunities, and future perspectives", Satellite Navigation, 2(1), 1–23. (2021). https://doi.org/10.1186/S43020-021-00054-Y/TABLES/5

[25] M., Amooshahi, A., Milan and Y., jamour, "Feasibility of using smartphones in the reconstruction of the interior architecture of the building without using interior control points", JGST, 12(2):9, (2023). (In Persian) http://jgst.issgeac.ir/article-1-1104-fa.html

[26] M. I., Razali, A. N., Idris, M. H., Razali and W. M., Syafuan, "Quality Assessment of 3D Point Clouds on the Different Surface Materials Generated from iPhone LiDAR Sensor", International Journal of Geoinformatics, 18(4), 51-59. (2022). https://doi.org/10.52939/ijg.v18i4.2259

[27] P. P. C., Chase, K. H., Clarke, A. J., Hawkes, S., Jabari and J. S., Jakus, "Apple IPhone 13 Pro LiDAR Accuracy Assessment for Engineering Applications", Transforming Construction with Reality Capture Technologies. CloudCompare User manual (2.6.1). (n.d.), (2022). https://doi.org/10.57922/TCRC.645

[28] A., Spreafico, F., Chiabrando, L., Teppati Losè and  F., Giulio Tonolo, "The Ipad Pro Built-in LIDAR Sensor: 3D Rapid Mapping Tests and Quality Assessment", The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B1-2021(B1-2021), 63–69. (2021). https://doi.org/10.5194/ISPRS-ARCHIVES-XLIII-B1-2021-63-2021

[29] J., Zaczek, "Evaluation of the LiDAR in the Apple iPhone 13 Pro for use in Inventory Works", FIG Congress, (2022).

[30] G., Luetzenburg, A., Kroon and A. A., Bjørk, "Evaluation of the Apple iPhone 12 Pro LiDAR for an Application in Geosciences", Scientific Reports 2021 11:1, 11(1), 1–9. (2021). https://doi.org/10.1038/s41598-021-01763-9

[31] M., Torkan, M., Janiszewski, L., Uotinen and  M., Rinne, "Method to obtain 3D point clouds of tunnels using smartphone LiDAR and comparison to photogrammetry", IOP Conference Series: Earth and Environmental Science, 1124(1), 012016. (2023). https://doi.org/10.1088/1755-1315/1124/1/012016

[32] B. E., Heinrichs and M., Yang, "Bias and Repeatability of Measurements from 3D Scans Made Using iOS-Based Lidar", SAE International Journal of Advances and Current Practices in Mobility, 3(5), 2219–2226. (2021). https://doi.org/10.4271/2021-01-0891

[33] A. Sh., Amini, M., Varshusaz, M. S., Sarasht, "Investigating the influence of parameters of the basic relationship of network design on the final accuracy of short-range photogrammetry", Geomatic Conference and the 4th Conference on Unification of Geographical Names, https://civilica.com/doc/37106, (2008).

[34] G., Vacca, "3D Survey with Apple LiDAR Sensor—Test and Assessment for Architectural and Cultural Heritage", Heritage 2023, Vol. 6, Pp. 1476-1501, 6(2), 1476–1501. (2023). https://doi.org/10.3390/ HERITAGE6020080

[35] S., Rusinkiewicz and M., Levoy, "Efficient variants of the ICP algorithm", Proceedings of International Conference on 3-D Digital Imaging and Modeling, 3DIM, 145–152. (2001). https://doi.org/10.1109/IM.2001.924423

[36] T. O., Hodson, "Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not", Geosci. Model Dev, 15, 5481–5487. (2022). https://doi.org/10.5194/gmd-15-5481-2022