A Study on Potential of Big Visual Data Analytics in Construction Arena

In most construction and Infrastructure management projects, it is important to ensure and maintain the performance, safety as well as quality in the work to execute the construction in expected period , for monitoring the above parameters i.e. Performance, Safety, Quality and as well as Security, requires data to analyze, determine and test the algorithms, due to eternal increase amount of captured data thorough modern improvements in technology i.e. devices, camera equipped vehicles, Sensors, etc. accommodates an innovative scope to capture present status of construction sites at a less cost analogized to more alternative techniques such as laser scanning technique. Vast endeavours on documenting as-built status, nevertheless, stay at retrieving the visual data and updating Building Information Model (BIM). Hundreds of images and videos are captured but most of the data becomes scrap without proper localize with plan document and time. To take full benefits of visual data for construction status analytics where performance analytics is also included in it, three aspects (reliable, relevance and speed) of capturing, analysing and reporting visual data are captious and tracking development in construction sites needs two direction communication between field crew and management so that performances and changes issues related to task management, completion and outlook can be convey effectively. This paper deals with the investigation of current techniques for influence with help of arising BIM and big data in performance monitoring at construction from reliable, relevance and speed.

[1]  David Arditi,et al.  Time-Lapse Digital Photography Applied to Project Management , 2002 .

[2]  SangUk Han,et al.  A vision-based motion capture and recognition framework for behavior-based safety management , 2013 .

[3]  Mani Golparvar-Fard,et al.  Visual monitoring of civil infrastructure systems via camera-equipped Unmanned Aerial Vehicles (UAVs): a review of related works , 2016 .

[4]  Mani Golparvar-Fard,et al.  Potential of big visual data and building information modeling for construction performance analytics: An exploratory study , 2017 .

[5]  Frédéric Bosché,et al.  Plane-based registration of construction laser scans with 3D/4D building models , 2012, Adv. Eng. Informatics.

[6]  Seokho Chi,et al.  Automated Object Identification Using Optical Video Cameras on Construction Sites , 2011, Comput. Aided Civ. Infrastructure Eng..

[7]  Jun Wang,et al.  Geotechnical and safety protective equipment planning using range point cloud data and rule checking in building information modeling , 2015 .

[8]  Burcu Akinci,et al.  Characterization of Laser Scanners and Algorithms for Detecting Flatness Defects on Concrete Surfaces , 2011, J. Comput. Civ. Eng..

[9]  Changyoon Kim,et al.  4D CAD model updating using image processing-based construction progress monitoring , 2013 .

[10]  Chih-Chen Chang,et al.  A framework for dimensional and surface quality assessment of precast concrete elements using BIM and 3D laser scanning , 2015 .

[11]  Hye-Chung Kum,et al.  Establishing a National Consortium for Data Science , 2012 .

[12]  Jie Li,et al.  Rethinking big data: A review on the data quality and usage issues , 2016 .

[13]  Seokho Chi,et al.  Image-Based Safety Assessment: Automated Spatial Safety Risk Identification of Earthmoving and Surface Mining Activities , 2012 .