I haven’t written many updates about my research as of late, but that doesn’t mean I haven’t been hard at work. Below you’ll find a couple of time lapse videos of the latest prototypes (some I’ve built, others are Grasshopper models of prototypes that have been temporarily shelved), as well as some low-fi paper prototypes of an iOS Home Automation App that I’ve been working on.
Active Prototype 1
Active Prototype 2
Passive Facade Prototype (Unbuilt)
Hybrid/Heliostat Facade Prototype (Unbuilt)
Active Facade Prototype
Low Fidelity Paper Prototypes of iOS Home Automation App
Written for the ARCC 2013 Conference: The Visibility of Research
(pending acceptance for publication)
ABSTRACT: Energy consumption by buildings, especially high-rise buildings, has increased to the point that it has overtaken the industrial and transportation sectors. This unsustainable phenomenon has prompted research into intelligent and adaptive building systems (IABS) for more energy-efficient buildings that current architectural practice and building operations overlook. IABS are bottom-up strategies that provide energy consumption and comfort solutions at any scale of the built environment. In addition to the benefit of reduced energy consumption, occupant physiological and psychological well-being can also be addressed through better control and feedback mechanisms. These improvements can be made through the widespread application of systems that blend many different and readily attainable components. This research seeks to address these issues through the development and study of IABS prototypes, virtual models, and material/component libraries that address the needs of all stakeholders. Prototypes that form contextually aware and flexible agent networks will be presented, along with the results of those that have been completed, and suggestions for design and interfacing. Controlled environments are constructed in and around physical prototypes to carefully observe performance results. Also discussed is how high-rise buildings are ideal candidates for IABS integration.
Link to full paper.
To date, I have created two applications to run on iOS6. The first was for an assignment, and is a relatively simple calculator app. The second is the basis for the end-user control and feedback applications that I mention in my research on Intelligent and Adaptive Building Systems.
The Mulit-Calculator app was my first iOS app. It behaves like any other simple calculator, but has a toggle switch that can put it into “accounting” mode where a previous result can be calculated into the next mathematical operation. Any negative results in this mode appear in red text. The app can also me switched to the “tip” function where the tip for a bill of a user determined amount can be calculated by altering the percentage that the tip will be of the original amount with a slider.
The Room Report app is a decidedly more complicated iOS application. Rooms are created by the user, then Room Reports consisting of the user’s perceived room qualities are created and sorted by date. The application interface, and front-end functionality are relatively simple. However, beneath it all is a persistent SQLite store and Core Data Model. This data storage framework will be the framework for future applications that I will be developing for the purpose of building control and feedback.
Core Data Model Diagram showing aBi-Directional To-Many relationship from rooms to reports.
Very encouraging considering Google’s track record for making these kinds of things opensource. Having this tool should help to integrate Neural Networking into Intelligent Building Systems.
Average features: This composite image represents the ideal stimulus for Google’s software to detect a human face in a photo.
From MIT’s Technology Review: This summer Google set a new landmark in the field of artificial intelligence with software that learned how to recognize cats, people, and other things simply by watching YouTube videos (see “Self-Taught Software“). That technology, modeled on how brain cells operate, is now being put to work making Google’s products smarter, with speech recognition being the first service to benefit.