scholarly journals Novel Approach for Three-Dimensional Integral Documentation of Machine Rooms in Hospitals Using Portable Mobile Mapping System

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 79200-79210 ◽  
Author(s):  
Manuel Rodriguez-Martin ◽  
Pablo Rodriguez-Gonzalvez ◽  
Diego Gonzalez-Aguilera ◽  
Erica Nocerino
Keyword(s):  
Three Dimensional ◽  
Mobile Mapping ◽  
Novel Approach ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Dimensional Integral

scholarly journals Three-dimensional mobile mapping system and its use in road engineering

2018 ◽  
Vol 196 ◽  
pp. 04082
Author(s):  
Zuzana Florkova ◽  
Lukas Duris ◽  
Michal Veselovsky ◽  
Stefan Sedivý ◽  
Dasa Kovalova
Keyword(s):  
Data Collection ◽  
Field Data ◽  
Three Dimensional ◽  
Research Paper ◽  
Mobile Mapping ◽  
Road Engineering ◽  
Mapping System ◽  
Field Data Collection ◽  
Mapping Technology ◽  
Mobile Mapping System

The paper focuses on the issue of the use of three-dimensional mobile mapping system and the following processing of obtained data. The first part is devoted to the description of the three-dimensional mobile mapping technology using LiDAR, specifically to the mobile three-dimensional scanner - Lynx SG1 from Teledyne OPTECH. It describes into more details the process of works from the field data collection to their so called "postprocessing" as well as a variety of output options and interpretations of results obtained in the measurements. Advantages of the system together with its limits of use are summarized in the conclusion of the research paper.

scholarly journals Validation of Portable Mobile Mapping System for Inspection Tasks in Thermal and Fluid–Mechanical Facilities

2019 ◽  
Vol 11 (19) ◽  
pp. 2205 ◽  
Author(s):  
Rodríguez-Martín ◽  
Rodríguez-Gonzálvez ◽  
Ruiz de Oña Crespo ◽  
González-Aguilera
Keyword(s):  
Three Dimensional ◽  
Laser Scanner ◽  
Ground Truth ◽  
Mobile Mapping ◽  
Industrial Facilities ◽  
Starting Point ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Machine Room ◽  
Inspection Tasks

The three-dimensional registration of industrial facilities has a great importance for maintenance, inspection, and safety tasks and it is a starting point for new improvements and expansions in the industrial facilities context. In this paper, a comparison between the results obtained using a novel portable mobile mapping system (PMMS) and a static terrestrial laser scanner (TLS), widely used for 3D reconstruction in civil and industrial scenarios, is carried out. This comparison is performed in the context of industrial inspection tasks, specifically in the thermal and fluid-mechanics facilities in a hospital. The comparison addresses the general reconstruction of a machine room, focusing on the quantitative and qualitative analysis of different elements (e.g., valves, regulation systems, burner systems and tanks, etc.). The validation of the PMMS is provided considering the TLS as ground truth and applying a robust statistical analysis. Results come to confirm the suitability of the PMMS to perform inspection tasks in industrial facilities.

scholarly journals Novel Approach to Automatic Traffic Sign Inventory Based on Mobile Mapping System Data and Deep Learning

2020 ◽  
Vol 12 (3) ◽  
pp. 442 ◽  
Author(s):  
Jesús Balado ◽  
Elena González ◽  
Pedro Arias ◽  
David Castro
Keyword(s):  
False Positive Rate ◽  
Good Condition ◽  
Point Clouds ◽  
Traffic Sign ◽  
Mobile Mapping ◽  
Traffic Signs ◽  
Novel Approach ◽  
Mapping System ◽  
Positive Rate ◽  
Mobile Mapping System

Traffic signs are a key element in driver safety. Governments invest a great amount of resources in maintaining the traffic signs in good condition, for which a correct inventory is necessary. This work presents a novel method for mapping traffic signs based on data acquired with MMS (Mobile Mapping System): images and point clouds. On the one hand, images are faster to process and artificial intelligence techniques, specifically Convolutional Neural Networks, are more optimized than in point clouds. On the other hand, point clouds allow a more exact positioning than the exclusive use of images. The false positive rate per image is only 0.004. First, traffic signs are detected in the images obtained by the 360° camera of the MMS through RetinaNet and they are classified by their corresponding InceptionV3 network. The signs are then positioned in the georeferenced point cloud by means of a projection according to the pinhole model from the images. Finally, duplicate geolocalized signs detected in multiple images are filtered. The method has been tested in two real case studies with 214 images, where 89.7% of the signals have been correctly detected, of which 92.5% have been correctly classified and 97.5% have been located with an error of less than 0.5 m. This sequence, which combines images to detection–classification, and point clouds to geo-referencing, in this order, optimizes processing time and allows this method to be included in a company’s production process. The method is conducted automatically and takes advantage of the strengths of each data type.

scholarly journals Deep Learning Based Pavement Inspection Using Self-Reconfigurable Robot

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2595
Author(s):  
Balakrishnan Ramalingam ◽  
Abdullah Aamir Hayat ◽  
Mohan Rajesh Elara ◽  
Braulio Félix Gómez ◽  
Lim Yi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Semantic Segmentation ◽  
High Accuracy ◽  
Experimental Results ◽  
Mobile Mapping ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Reconfigurable Robot ◽  
Nvidia Gpu ◽  
Inspection Task

The pavement inspection task, which mainly includes crack and garbage detection, is essential and carried out frequently. The human-based or dedicated system approach for inspection can be easily carried out by integrating with the pavement sweeping machines. This work proposes a deep learning-based pavement inspection framework for self-reconfigurable robot named Panthera. Semantic segmentation framework SegNet was adopted to segment the pavement region from other objects. Deep Convolutional Neural Network (DCNN) based object detection is used to detect and localize pavement defects and garbage. Furthermore, Mobile Mapping System (MMS) was adopted for the geotagging of the defects. The proposed system was implemented and tested with the Panthera robot having NVIDIA GPU cards. The experimental results showed that the proposed technique identifies the pavement defects and litters or garbage detection with high accuracy. The experimental results on the crack and garbage detection are presented. It is found that the proposed technique is suitable for deployment in real-time for garbage detection and, eventually, sweeping or cleaning tasks.

A Mobile Mapping System for road data capture based on 3D road model

2006 ◽  
Author(s):  
Kiichiro Ishikawa ◽  
Jun-ichi Takiguchi ◽  
Yoshiharu Amano ◽  
Takumi Hashizume
Keyword(s):  
Data Capture ◽  
Mobile Mapping ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Road Data

Stereopolis II: A multi-purpose and multi-sensor 3D mobile mapping system for street visualisation and 3D metrology

2014 ◽  
pp. 69-79
Author(s):  
Nicolas Paparoditis ◽  
Jean-Pierre Papelard ◽  
Bertrand Cannelle ◽  
Alexandre Devaux ◽  
Bahman Soheilian ◽  
...  
Keyword(s):  
Software As A Service ◽  
Mobile Mapping ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Grand Public ◽  
3D Metrology

Nous présentons dans cet article un système de numérisation mobile 3D hybride laser-image qui permet d'acquérir des infrastructures de données spatiales répondant aux besoins d'applications diverses allant de navigations multimédia immersives jusqu'à de la métrologie 3D à travers le web. Nous détaillons la conception du système, ses capteurs, son architecture et sa calibration, ainsi qu'un service web offrant la possibilité de saisir en 3D via un outil de type SaaS (Software as a Service), permettant à tout un chacun d'enrichir ses propres bases de données à hauteur de ses besoins.Nous abordons également l'anonymisation des données, à savoir la détection et le floutage de plaques d'immatriculation, qui est est une étape inévitable pour la diffusion de ces données sur Internet via des applications grand public.

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