Propositional Architecture using Induced Representation
Paper in proceeding, 2014
The paper describes a method and an approach to using sensor data, machine-learning and pattern recognition for proposing and guiding immediate modifications to the existing built environment. The proposed method; Induced Representation, consists of a few steps which we have identified as crucial for such an approach. The steps are A: data collection from the environment, B: machine cognition, learning, prediction, and, c: proposition, visualization, and embodied representations for quick implementation. In the paper we outline the factual and theoretical basis for this approach, and we present and discuss three experiments that each deal with the steps A, B and C.
Prediction
Machine Learning
Architecture
Proposition
Sensors
Cognition
Induced Representation
Embodiment
Representation.
Sensor Fusion
Author
Stig Anton Nielsen
Chalmers, Architecture
Alexandru Dancu
Chalmers, Applied Information Technology (Chalmers)
What’s the Matter? Materiality and Materialism at the Age of Computation
297-312
978-960-89320-6-7 (ISBN)
Subject Categories
Architectural Engineering
Interaction Technologies
Embedded Systems
Other Civil Engineering
Robotics
Signal Processing
Computer Systems
Areas of Advance
Information and Communication Technology
Building Futures (2010-2018)
Driving Forces
Sustainable development
ISBN
978-960-89320-6-7