Session 1.5
Digitising the built environment more efficiently with new mobile scanning and software workflows
Synopsis:
Innovations in point cloud collection through laser scanning continue to improve year on year. We have reached an inflection point where mobile scanning using SLAM algorithms has reached a level of progress where data is now accurate and optimised for BIM applications. But what does more data, faster mean?
Learning Objectives:
1. Be aware of the current and future state of mobile point cloud data acquisition technologies.
2. Understand the implications of more point cloud data in-field means to working with mass data in relevant software
3. Provide demonstrations of software workflows that aid the scan to BIM process
Body:
Innovations in point cloud collection through laser scanning continue to improve year on year. New data collection methods are increasingly efficient via mobile and automated methods and thus result in the ability to collect more data. Software workflows will be key in the design professional’s ability to manage and get the most out of large point cloud data sets.
This presentation will look at the current and future state of mobile point cloud data acquisition technologies making it easier to collect data more frequently and at a larger scale. Highlighting what instruments best apply to certain applications. Why switch to mobile scanning? Does static still have a place? Will robots take over scanning? If so, when?
Secondly, explore the implications of larger point cloud data sets collected in-field means to working with this mass data in relevant software, touching on tools such as feature classification and automatic feature extraction in a built environment context. How effective is automated feature extraction today? And look at future possibilities and applications.
Finally live demonstrations of relevant software workflows will be presented to highlight benefits to industry professionals.
Synopsis:
Innovations in point cloud collection through laser scanning continue to improve year on year. We have reached an inflection point where mobile scanning using SLAM algorithms has reached a level of progress where data is now accurate and optimised for BIM applications. But what does more data, faster mean?
Learning Objectives:
1. Be aware of the current and future state of mobile point cloud data acquisition technologies.
2. Understand the implications of more point cloud data in-field means to working with mass data in relevant software
3. Provide demonstrations of software workflows that aid the scan to BIM process
Body:
Innovations in point cloud collection through laser scanning continue to improve year on year. New data collection methods are increasingly efficient via mobile and automated methods and thus result in the ability to collect more data. Software workflows will be key in the design professional’s ability to manage and get the most out of large point cloud data sets.
This presentation will look at the current and future state of mobile point cloud data acquisition technologies making it easier to collect data more frequently and at a larger scale. Highlighting what instruments best apply to certain applications. Why switch to mobile scanning? Does static still have a place? Will robots take over scanning? If so, when?
Secondly, explore the implications of larger point cloud data sets collected in-field means to working with this mass data in relevant software, touching on tools such as feature classification and automatic feature extraction in a built environment context. How effective is automated feature extraction today? And look at future possibilities and applications.
Finally live demonstrations of relevant software workflows will be presented to highlight benefits to industry professionals.