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Lamsal Lab
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A lab that advances DX at construction sites from the perspectives of both architecture and information technology.
AboutAbout the lab
Connecting architecture and information technology on site.
The Lamsal Lab researches the development of technologies actually used in the construction industry, from the perspectives of both architecture and information technology.
The lab works on indoor self-localization where GPS signals do not reach, technology that assesses workers' health using only a smartphone camera, and the use of 3D printers at construction sites.
By linking architecture and information science, the lab aims to advance construction DX, which solves problems at construction sites.
Key terms
- Self-localization
- The process by which a machine or person works out where it currently is from sensor information.
- Computer vision
- Technology that lets a computer read objects and situations from images taken by a camera.
- Construction DX
- An effort to use digital technology to change the way construction work itself is done.
ResearchResearch themes
The lab aims to develop technologies that are actually used in the construction industry, from the perspectives of both architecture and information technology. Built on three pillars (indoor self-localization, assessment of workers' health, and the use of 3D printers at construction sites), it works in the field of architectural informatics.
*Illustrative imagePositioning Indoors Where GPS Cannot Reach
This is a system that works out position and movement from the sensors and radio signals built into a smartphone, in places where GPS signals do not reach, such as construction sites and large buildings. Because it needs no dedicated equipment, it is inexpensive and can be widely used.
*Illustrative imageSite Photo Management with Location Information
This is an app that takes site photos while automatically attaching indoor location information. It builds a database of organized photos, making it easier to grasp construction progress, check workmanship, and manage records.
*Illustrative imageFace Detection Methods
The lab develops a robust face detection method using the unscented Kalman filter. Combined with research on detecting drowsiness from how the eyes appear, it is advancing applications in human-computer interaction.
*Illustrative imageAI for Assessing Health Condition
The lab builds an AI model that assesses the health condition of construction workers from facial photos, skin color, eye color, blinking, and questionnaire responses. It aims to make health management on site more efficient and to prevent occupational accidents.
MembersFaculty
The members of the Lamsal Lab consist of faculty and master's and undergraduate students.As of 2026
- Associate ProfessorBikash Lamsal
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “3D-Druck-Haus Wallenhausen 01” Looniverse / CC BY-SA 4.0 (cropped)
- Positioning Indoors Where GPS Cannot Reach: “Scan-to-BIM Mechanical Room” Oregon State University / CC BY-SA 2.0 (cropped)
- Site Photo Management with Location Information: “INTERIORS construction site - geograph.org.uk - 8131996” DS Pugh / CC BY-SA 2.0 (cropped)
- Face Detection Methods: “Iris of human male” Osmo Lundell / CC BY-SA 4.0 (cropped)
- AI for Assessing Health Condition: “Safety Helmets ( )” Michael Coghlan from Adelaide, Australia / CC BY-SA 2.0 (cropped)
- Related lab (吉村研究室): “Tiny house, Portland” Tammy / CC BY 2.0 (cropped)
- Related lab (有賀研究室): “Old Merchant District of Little Edo IMG 0323” Dandy1022 / CC BY-SA 4.0 (cropped)
- Related lab (渡邊研究室): “Mangrove roots in the Laguna de La Restinga” Wilfredor / CC0 (cropped)
- Related lab (宮本研究室): “Government Center Study models ( )” City of Boston Archives from West Roxbury, United States / CC BY-SA 2.0 (cropped)
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