AI-Driven Occupant Behavior Analysis for Enhanced Building Performance - INTERN | Institut royal d'architecture du Canada

AI-Driven Occupant Behavior Analysis for Enhanced Building Performance - INTERN

Référence: CE2024CONF20

AI-Driven Occupant Behavior Analysis for Enhanced Building Performance

This webinar is part of the RAIC 2024 Conference on Architecture, now available to stream!

Topics: Innovation in Materials, Technology and Construction

Length: 1 hour | What's Included: Video, Quiz, and Certificate of Completion 

Explore a strategic implementation of artificial intelligence non-Player Characters in video game engines as an opportunity to enhance energy efficiency and occupant comfort across diverse architectural contexts. Discover an innovative workflow that employs AI behaviour trees, perception algorithms, and environmental queries in non-Player Characters (NPCs) within video game engines, providing valuable insights into occupant behaviour. Through a case study using Dunton Tower of Carleton University in Ottawa, learn to implement user-defined AI-driven NPCs to assess occupant comfort under varying conditions and quantify results using a scoring mechanism. Gain practical skills to configure Unreal Engine projects, expand behaviour trees, formulate quantitative assessments, and troubleshoot AI Bot functionalities. Join us in this engaging session to shape a more sustainable, empathetic architecture for the future.

By the end of this session, participants will be able to:
  • Construct an Unreal Engine project primed for AI Bot integration using external data sources and BIM Models, showcasing proficiency in project configuration.
  • Discuss and expand upon behaviour trees for AI Bots, seamlessly integrating them into projects via environmental queries, demonstrating advanced understanding and practical application.
  • Formulate a quantitative scoring mechanism based on rigorously reviewed methodologies, enabling the comprehensive evaluation of AI Bots within their designated environments.
  • Describe how to effectively troubleshoot and debug AI Bot functionalities and their corresponding environments prior to execution, and to produce detailed diagnostic reports, reflecting a high level of expertise in quality assurance.

Subject Matter Expert:

Joey Doherty
M.Arch
RAIC, OAQ Intern Architect, HOK, CIMS & Figurr Architects Collective

Joey Doherty earned a B.A. (Hon) in Architectural Studies from the University of Toronto and an M.Arch from Carleton University and an architectural technologist DEC at Vanier College, Quebec. During his M.Arch, he was a team lead on various projects at the Carleton Immersive Media Studio (CIMS), focusing on Architectural visualization, digitally assisted storytelling, and interactive digital tools. Additionally, Joey pursued research grants, exploring innovative digital tools for the architecture, engineering, construction, and operations (AECO) industry, gaining insights from HOK’s Research and Development department and the Universitat Politècnica de València. Post-M.Arch, Joey joined Epic Games as an interoperability quality assurance specialist for Twinmotion and Unreal   Engine software. Currently, Joey is an Intern Architect with 3 years of experience at In Situ Atelier D'Architecture and Figurr Architects Collective in Montreal, Quebec.

Pricing A-La-Carte 

$50.00
Prix catalogue: $50.00
Prix membres: 
$35.00