May 22 2019
10:30 am - 12:00 pm
Artificial Intelligence / Machine Learning Approaches
Track Names: AEC Next, AIA Accredited
Session Date: May 22 2019 10:30 am - 12:00 pm
Session Credits: 1.5 AIA LU
Enhanced Life and Safety through Artificial Intelligence
After the harrowing current events detailing deaths from fires, shootings, and otherwise dangerous circumstances, it is up to engineers and architects to create a device that drastically improves security in buildings. Husband and wife duo, Rajesh and Meghana Joshi will be presenting their latest invention, one that revolutionizes life safety by immediately alerting first responders to a potentially life threatening situation, as well as giving them a firsthand view to plan out the most appropriate, efficient exiting course of action. The session will commence outlining the current life and safety devices and their extent of usage. The presentation will then delve into the new invention, and how to revolutionize life and safety and directional exiting based on the decisions made by Artificial Intelligence, and Internet of Things. Instead of treating emergencies as "closed door" surprises, first responders will be able to know the details of the emergency as well as the dangers to life and safety. The session will proceed to on-screen simulation of an emergency situation with the device helping save lives. The fourth part of the presentation will include the directional signage changes based on the emergency assessment made by Internet of Things devices to help occupants safely discharge before emergency responders arrive at scene. The presentation will conclude with a Q&A session allowing Architects and Building Code Experts interacting with the presenters.
Artificial Intelligence For MEP Engineering
AEA Integration is a revolutionary new software technology that completely automates the design of MEP systems for buildings. AEA Integration not only automates the design process, it optimizes the designs to find the most energy efficient, material efficient and cost effective solution to any design condition. The software performs countless design simulations in a quest to find the most cost effective solution that meets all of the established design parameters for the project. The most cost effective solution also results in the most energy efficient and sustainable solution, saving both energy and natural resources, reducing transportation costs and even reducing construction waste. The speed at which AEA Integration is able to render the most cost effective solution is remarkable. It is simply not possible to design to the optimized solution using conventional engineering methods due to the time and labor effort it would require to accomplish the level of automation that AEA Integration provides. It is truly a revolution for the MEP design industry. More information and a brief video can be found on our website at www.schnackel.com.
Schnackel Engineers, Inc.
Increasing BIM Effectiveness with Artificial Intelligence
The concept of Building Information Modeling promises high-fidelity virtual representations of building designs. This promise extends ultimately to the automated extraction of high-quality elevation, section and detail views that reflect the potential built environment in exquisite detail. In practice, however, the technical labor required to bring an entire BIM to this ultimate level of detail is tedious and error-prone. Secondly, and perhaps more importantly from the designer’s point of view, creating a BIM with high enough fidelity to allow for design intent evaluation requires a huge manual “lift” of information into the model. This is a limitation of today’s conventional BIM approach. These issues lie in direct opposition to the value proposition promised by the concept of Building Information Modeling. At Bricsys, we are focused on the development of machine learning / machine intelligence methodologies designed to assist BIM users in creating high level-of-detail (LOD) BIM models with high-fidelity and minimum manual effort. We are developing these tools for two reasons: first, to reduce the time required to add effective detail to a BIM and second, to allow project teams to evaluate, check and confirm that the design intent covers all conditions. This visibility can significantly reduce the potential for errors and change orders. Our work to date in the machine intelligence research arena has focused on several areas: • Automated classification of building elements, determined purely on the basis of geometry. This methodology allows imported geometry to be classified as accurately as native. • Automated propagation of building details, and connections. In this scenario, modeling a single connection trains the system to find similar connections across the entire BIM. A simple, visual selection schema allows the user to control the propagation of the building element(s). This mechanism can perform multiple duties, from the trimming of composition plies to the placement of window patterns / curtain wall elements. We will demonstrate these tools in the context of a live BIM, discuss the next generation of these features and deliver additional insights into the development of a smart BIM workflow.
Utilizing Artificial Intelligence in Construction Planning and Scheduling
Rene Morkos, CEO of ALICE Technologies, who received his Ph.D. from Stanford in Artificial Intelligence applications for construction, will share the planning and scheduling challenges facing construction today and why artificial intelligence is perfect to solve some of the biggest planning and scheduling issues. Rene will go into the challenges with the current CPM method of scheduling, what AI is, and how AI is being applied to solve challenges that have plagued the construction planning process for decades and how AI can astronomically increase the ability to explore millions of construction scenarios in just minutes; a feat that would take a human being decades by comparison. This session is appropriate for construction executives and professionals who are responsible for increasing the efficiency of their organizations, heads of innovation, or who are responsible for project planning and scheduling.