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Akıllı Telefon iPhone LiDAR Tarayıcısının Altyapı Çalışmalarında Uygulanabilirliği

Year 2024, , 1 - 9, 30.06.2024
https://doi.org/10.51946/melid.1402883

Abstract

Son zamanlarda ışık algılama ve mesafe ölçme (LiDAR) sensörlerinin akıllı telefonlara entegre edilmesi, fotoğraf odak uzaklığının iyi ayarlanmasının yanı sıra üç boyutlu (3B) iç ve dış mekân haritalama için yepyeni bir alternatif ölçme aracı olarak yerini almıştır. Bu yeni sistem sayesinde tarama teknolojisi farklı disiplinlerde sivil kullanıma kapılarını aralasa da veri kalitesinin jeodezik LiDAR ölçme seviyesi için henüz oldukça erken. Küçük detayların ölçülmesini gerektiren işlemlerde sistem tamamen güvenilir olmayabileceği daha önceki çalışmalarda gösterilmiştir. Ancak, bu durum, akıllı telefon LiDAR’larının harita yapımında kullanımına tamamen engel değildir. Bu makale, Apple 14 Pro akıllı cihazının dış ortamlarda, özellikle altyapı çalışma kanallarının 3B modellemesinde belirli seviyelerde haritalandırılmasına imkân verip veremeyeceğini tartışmaktadır. Özellikle, kanalizasyon, içme suyu gibi altyapı tesislerine ait 3B haritaları kanal yapı ortamlarının yeniden yapılandırılması, daha sonra yapılması planlanan bakım ve onarım çalışmaları için önemli bir konudur. Bu konuyla ilgili örnek çalışma alanı, Selçuk Üniversitesi Güneysınır Meslek Yüksekokulu doğal gaz bağlantı hattı olarak belirlenmiştir. Hatta ait geometrik yapı ve rölatif konum belirleme çalışması yapılmıştır. Altyapı çalışmaları sırasında farklı yapılar ve sistemler tespit edilmiştir. Bu katmanların belirlenmesi, sonraki kazı aşamalarında sağlayacağı bilgiler açısından önemli olduğu düşünülmektedir.

References

  • 3DReshaper (2024). “Leica Cyclone 3DR - All-in-One Deliverable Solution”. Geliş tarihi 12 Mart 2024 (https://leica-geosystems.com/products/laser-scanners/software/leica-cyclone/leica-cyclone-3dr).
  • 3DScanner App. (2023). “3D Scanner App.” Geliş tarihi 07 Aralık 2023 (https://3dscannerapp.com/).
  • Akay, A. E., Oğuz, H., Karas, I. R., & Aruga, K. (2009). Using LiDAR technology in forestry activities. Environmental monitoring and assessment, 151, 117-125.
  • Apple (2020). “iPhone 12 Pro - Teknik Özellikler (TR)”. Geliş tarihi 06 Aralık 2023 (https://support.apple.com/kb/SP831?locale=tr_TR).
  • Apple (2023). “iPhone 14 Pro - Teknik Özellikler (TR)”. Geliş tarihi 07 Aralık 2023 (https://support.apple.com/kb/SP875?viewlocale=tr_TR&locale=tr_TR).
  • Benvenuto, L., Cosso, T., & Delzanno, G. (2022). An adaptive algorithm for multipath mitigation in GNSS positioning with Android smartphones. Sensors, 22(15), 5790.
  • Besl, P. J., & McKay, N. D. (1992, April). Method for registration of 3-D shapes. In Sensor fusion IV: control paradigms and data structures, 1611, 586-606.
  • Bolles, R. C., & Fischler, M. A. (1981, August). A RANSAC-based approach to model fitting and its application to finding cylinders in range data. In IJCAI, 1981, 637-643.
  • CloudCompare (2023). “CloudCompare - Open Source project”. Geliş tarihi 09 Aralık 2023 (https://www.danielgm.net/cc/).
  • Díaz Vilariño, L., Tran, H., Frías Nores, E., Balado Frías, J., & Khoshelham, K. (2022). 3D mapping of indoor and outdoor environments using Apple smart devices. ISPRS-International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, XLIII-B4-2022, 303–308,
  • GIM, International (2022). “Using Lidar Software for Energy Infrastructure Mapping-Web of Science Core Collection”. Geliş tarihi 06 Aralık 2023 (https://www.webofscience.com/wos/woscc/full-record/WOS:000787750100012).
  • Gollob, C., Ritter, T., Kraßnitzer, R., Tockner, A., & Nothdurft, A. (2021). Measurement of forest inventory parameters with Apple iPad pro and integrated LiDAR technology. Remote Sensing, 13(16), 3129.
  • Günen, M. A., Erkan, İ., Aliyazıcıoğlu, Ş., & Kumaş, C. (2023). Investigation of geometric object and indoor mapping capacity of Apple iPhone 12 Pro LiDAR. Mersin Photogrammetry Journal, 5(2), 82-89.
  • Huang, X., Gong, J., Chen, P., Tian, Y., & Hu, X. (2021). Towards the adaptability of coastal resilience: Vulnerability analysis of underground gas pipeline system after hurricanes using LiDAR data. Ocean & Coastal Management, 209, 105694.
  • Kaartinen, E., Dunphy, K., & Sadhu, A. (2022). LiDAR-based structural health monitoring: Applications in civil infrastructure systems. Sensors, 22(12), 4610.
  • Killinger, D. K. (2014). Lidar (light detection and ranging). In Laser spectroscopy for sensing, 2014, 292-312. Woodhead Publishing.
  • Kottner, S., Thali, M. J., & Gascho, D. (2023). Using the iPhone's LiDAR technology to capture 3D forensic data at crime and crash scenes. Forensic Imaging, 32, 200535.
  • Kuçak, R. A., Erol, S., & Alkan, R. M. (2023). iPad Pro LiDAR sensörünün profesyonel bir yersel lazer tarayıcı ile karşılaştırmalı performans analizi. Geomatik, 8(1), 35-41.
  • Luetzenburg, G., Kroon, A., & Bjørk, A. A. (2021). Evaluation of the Apple iPhone 12 Pro LiDAR for an application in geosciences. Scientific reports, 11(1), 1-9.
  • Lukács, G., Marshall, A. D., & Martin, R. R. (1997). Geometric least-squares fitting of spheres, cylinders, cones and tori. RECCAD, Deliverable document, 1197, 2.
  • Monsalve, A., Yager, E. M., & Tonina, D. (2023). Evaluating Apple iPhone LiDAR measurements of topography and roughness elements in coarse bedded streams. Journal of Ecohydraulics, 8(1) 1-11.
  • Rabbani, T., & Van Den Heuvel, F. (2005). Efficient hough transform for automatic detection of cylinders in point clouds. Isprs Wg Iii/3, Iii/4, 3, 60-65.
  • Sevgen, S. C. (2019). Airborne lidar data classification in complex urban area using random forest: a case study of Bergama, Turkey. International Journal of Engineering and Geosciences, 4(1), 45-51.
  • Sevgen, S. C., & Karsli, F. (2020). Automatic ground extraction for urban areas from airborne lidar data. Turkish Journal of Engineering, 4(3), 113-122.
  • Seyfeli, S., & Ok, A. O. (2021, November). Classification of Mobile Laser Scanning Point Cloud in an Urban Environment Using kNN and Random Forest. In The Proceedings of the International Conference on Smart City Applications 5, 963-973.
  • Sharifisoraki, Z., Dey, A., Selzler, R., Amini, M., Green, J. R., Rajan, S., & Kwamena, F. A. (2022). Monitoring critical infrastructure using 3d lidar point clouds. IEEE Access, 11, 314-336.
  • Shen, Z., Wang, J., Pang, C., Lan, Z., & Fang, Z. (2024). A LiDAR-IMU-GNSS fused mapping method for large-scale and high-speed scenarios. Measurement, 225, 113961.
  • Soilán, M., Sánchez-Rodríguez, A., del Río-Barral, P., Perez-Collazo, C., Arias, P., & Riveiro, B. (2019). Review of laser scanning technologies and their applications for road and railway infrastructure monitoring. Infrastructures, 4(4), 58.
  • Suleymanoglu, B., Gurturk, M., Yilmaz, Y., Soycan, A., & Soycan, M. (2023). Comparison of unmanned aerial vehicle-LiDAR and image-based mobile mapping system for assessing road geometry parameters via digital terrain models. Transportation Research Record, 2677(8), 617-632.
  • Suleymanoglu, B., Soycan, M., & Toth, C. (2024). 3D Road Boundary Extraction Based on Machine Learning Strategy Using LiDAR and Image-Derived MMS Point Clouds. Sensors, 24(2), 503.
  • Teo, T. A., & Yang, C. C. (2023). Evaluating the accuracy and quality of an iPad Pro's built-in lidar for 3D indoor mapping. Developments in the Built Environment, 14, 100169.
  • Vacca, G. (2023). 3D Survey with Apple LiDAR Sensor—test and assessment for architectural and cultural heritage. Heritage, 6(2), 1476-1501.
  • Yiğit, A. Y., Gamze Hamal, S. N., Ulvi, A., & Yakar, M. (2023). Comparative analysis of mobile laser scanning and terrestrial laser scanning for the indoor mapping. Building Research & Information, 52(4), 1-16.
  • Zeybek, M. (2021). Extraction of road lane markings from mobile LiDAR data. Transportation research record, 2675(5), 30-47.
  • Zeybek, M., Şanlıoğlu, İ., & Genç, A. (2015). Yüksek çözünürlüklü yersel lazer tarama verilerinin filtrelenmesi ve filtrelemelerin heyelan izlemeye etkisi. Doğal Afetler ve Çevre Dergisi, 1(1-2), 11-20.

Applicability of Smartphone Iphone Lidar Scanner in Infrastructure Studies

Year 2024, , 1 - 9, 30.06.2024
https://doi.org/10.51946/melid.1402883

Abstract

The recent integration of light detection and ranging (LiDAR) sensors into smartphones has provided a brand new alternative surveying tool for three-dimensional (3D) indoor and outdoor mapping, as well as fine-tuning photo focal length. Thanks to this new system, scanning technology opens the doors to civilian use in different disciplines, but it is still too early for the data quality to reach the level of geodetic LiDAR surveying. Prior research has demonstrated that the system might not be totally dependable for procedures requiring the measurement of minute details. This does not, however, preclude the creation of maps using smartphone LiDAR. This paper discusses whether the Apple 14 Pro smart device can enable certain levels of mapping in outdoor environments, especially 3D modeling of infrastructure working channels. In particular, 3D maps of infrastructure facilities such as sewerage and drinking water are important for reconstructing canal building scenes and for subsequent maintenance and repair works. The case study area is the natural gas connection line of Selcuk University Guneysinir Vocational School. The geometric structure and relative positioning of the line were determined. Different structures and systems were identified during the infrastructure works. The identification of these layers is considered to be important in terms of the information they will provide in the following excavation phases.

References

  • 3DReshaper (2024). “Leica Cyclone 3DR - All-in-One Deliverable Solution”. Geliş tarihi 12 Mart 2024 (https://leica-geosystems.com/products/laser-scanners/software/leica-cyclone/leica-cyclone-3dr).
  • 3DScanner App. (2023). “3D Scanner App.” Geliş tarihi 07 Aralık 2023 (https://3dscannerapp.com/).
  • Akay, A. E., Oğuz, H., Karas, I. R., & Aruga, K. (2009). Using LiDAR technology in forestry activities. Environmental monitoring and assessment, 151, 117-125.
  • Apple (2020). “iPhone 12 Pro - Teknik Özellikler (TR)”. Geliş tarihi 06 Aralık 2023 (https://support.apple.com/kb/SP831?locale=tr_TR).
  • Apple (2023). “iPhone 14 Pro - Teknik Özellikler (TR)”. Geliş tarihi 07 Aralık 2023 (https://support.apple.com/kb/SP875?viewlocale=tr_TR&locale=tr_TR).
  • Benvenuto, L., Cosso, T., & Delzanno, G. (2022). An adaptive algorithm for multipath mitigation in GNSS positioning with Android smartphones. Sensors, 22(15), 5790.
  • Besl, P. J., & McKay, N. D. (1992, April). Method for registration of 3-D shapes. In Sensor fusion IV: control paradigms and data structures, 1611, 586-606.
  • Bolles, R. C., & Fischler, M. A. (1981, August). A RANSAC-based approach to model fitting and its application to finding cylinders in range data. In IJCAI, 1981, 637-643.
  • CloudCompare (2023). “CloudCompare - Open Source project”. Geliş tarihi 09 Aralık 2023 (https://www.danielgm.net/cc/).
  • Díaz Vilariño, L., Tran, H., Frías Nores, E., Balado Frías, J., & Khoshelham, K. (2022). 3D mapping of indoor and outdoor environments using Apple smart devices. ISPRS-International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences, XLIII-B4-2022, 303–308,
  • GIM, International (2022). “Using Lidar Software for Energy Infrastructure Mapping-Web of Science Core Collection”. Geliş tarihi 06 Aralık 2023 (https://www.webofscience.com/wos/woscc/full-record/WOS:000787750100012).
  • Gollob, C., Ritter, T., Kraßnitzer, R., Tockner, A., & Nothdurft, A. (2021). Measurement of forest inventory parameters with Apple iPad pro and integrated LiDAR technology. Remote Sensing, 13(16), 3129.
  • Günen, M. A., Erkan, İ., Aliyazıcıoğlu, Ş., & Kumaş, C. (2023). Investigation of geometric object and indoor mapping capacity of Apple iPhone 12 Pro LiDAR. Mersin Photogrammetry Journal, 5(2), 82-89.
  • Huang, X., Gong, J., Chen, P., Tian, Y., & Hu, X. (2021). Towards the adaptability of coastal resilience: Vulnerability analysis of underground gas pipeline system after hurricanes using LiDAR data. Ocean & Coastal Management, 209, 105694.
  • Kaartinen, E., Dunphy, K., & Sadhu, A. (2022). LiDAR-based structural health monitoring: Applications in civil infrastructure systems. Sensors, 22(12), 4610.
  • Killinger, D. K. (2014). Lidar (light detection and ranging). In Laser spectroscopy for sensing, 2014, 292-312. Woodhead Publishing.
  • Kottner, S., Thali, M. J., & Gascho, D. (2023). Using the iPhone's LiDAR technology to capture 3D forensic data at crime and crash scenes. Forensic Imaging, 32, 200535.
  • Kuçak, R. A., Erol, S., & Alkan, R. M. (2023). iPad Pro LiDAR sensörünün profesyonel bir yersel lazer tarayıcı ile karşılaştırmalı performans analizi. Geomatik, 8(1), 35-41.
  • Luetzenburg, G., Kroon, A., & Bjørk, A. A. (2021). Evaluation of the Apple iPhone 12 Pro LiDAR for an application in geosciences. Scientific reports, 11(1), 1-9.
  • Lukács, G., Marshall, A. D., & Martin, R. R. (1997). Geometric least-squares fitting of spheres, cylinders, cones and tori. RECCAD, Deliverable document, 1197, 2.
  • Monsalve, A., Yager, E. M., & Tonina, D. (2023). Evaluating Apple iPhone LiDAR measurements of topography and roughness elements in coarse bedded streams. Journal of Ecohydraulics, 8(1) 1-11.
  • Rabbani, T., & Van Den Heuvel, F. (2005). Efficient hough transform for automatic detection of cylinders in point clouds. Isprs Wg Iii/3, Iii/4, 3, 60-65.
  • Sevgen, S. C. (2019). Airborne lidar data classification in complex urban area using random forest: a case study of Bergama, Turkey. International Journal of Engineering and Geosciences, 4(1), 45-51.
  • Sevgen, S. C., & Karsli, F. (2020). Automatic ground extraction for urban areas from airborne lidar data. Turkish Journal of Engineering, 4(3), 113-122.
  • Seyfeli, S., & Ok, A. O. (2021, November). Classification of Mobile Laser Scanning Point Cloud in an Urban Environment Using kNN and Random Forest. In The Proceedings of the International Conference on Smart City Applications 5, 963-973.
  • Sharifisoraki, Z., Dey, A., Selzler, R., Amini, M., Green, J. R., Rajan, S., & Kwamena, F. A. (2022). Monitoring critical infrastructure using 3d lidar point clouds. IEEE Access, 11, 314-336.
  • Shen, Z., Wang, J., Pang, C., Lan, Z., & Fang, Z. (2024). A LiDAR-IMU-GNSS fused mapping method for large-scale and high-speed scenarios. Measurement, 225, 113961.
  • Soilán, M., Sánchez-Rodríguez, A., del Río-Barral, P., Perez-Collazo, C., Arias, P., & Riveiro, B. (2019). Review of laser scanning technologies and their applications for road and railway infrastructure monitoring. Infrastructures, 4(4), 58.
  • Suleymanoglu, B., Gurturk, M., Yilmaz, Y., Soycan, A., & Soycan, M. (2023). Comparison of unmanned aerial vehicle-LiDAR and image-based mobile mapping system for assessing road geometry parameters via digital terrain models. Transportation Research Record, 2677(8), 617-632.
  • Suleymanoglu, B., Soycan, M., & Toth, C. (2024). 3D Road Boundary Extraction Based on Machine Learning Strategy Using LiDAR and Image-Derived MMS Point Clouds. Sensors, 24(2), 503.
  • Teo, T. A., & Yang, C. C. (2023). Evaluating the accuracy and quality of an iPad Pro's built-in lidar for 3D indoor mapping. Developments in the Built Environment, 14, 100169.
  • Vacca, G. (2023). 3D Survey with Apple LiDAR Sensor—test and assessment for architectural and cultural heritage. Heritage, 6(2), 1476-1501.
  • Yiğit, A. Y., Gamze Hamal, S. N., Ulvi, A., & Yakar, M. (2023). Comparative analysis of mobile laser scanning and terrestrial laser scanning for the indoor mapping. Building Research & Information, 52(4), 1-16.
  • Zeybek, M. (2021). Extraction of road lane markings from mobile LiDAR data. Transportation research record, 2675(5), 30-47.
  • Zeybek, M., Şanlıoğlu, İ., & Genç, A. (2015). Yüksek çözünürlüklü yersel lazer tarama verilerinin filtrelenmesi ve filtrelemelerin heyelan izlemeye etkisi. Doğal Afetler ve Çevre Dergisi, 1(1-2), 11-20.
There are 35 citations in total.

Details

Primary Language Turkish
Subjects Photogrammetry and Remote Sensing
Journal Section Research Articles
Authors

Mustafa Zeybek 0000-0001-8640-1443

Publication Date June 30, 2024
Submission Date December 10, 2023
Acceptance Date May 6, 2024
Published in Issue Year 2024

Cite

APA Zeybek, M. (2024). Akıllı Telefon iPhone LiDAR Tarayıcısının Altyapı Çalışmalarında Uygulanabilirliği. Türkiye Lidar Dergisi, 6(1), 1-9. https://doi.org/10.51946/melid.1402883

Türkiye LiDAR Dergisi