Ambient Intelligence for Scientific Discovery

Foundations, Theories, and Systems

  • Yang Cai

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3345)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 3345)

Table of contents

  1. Front Matter
  2. New Paradigms in Scientific Discovery

    1. Judith E. Devaney, S. G. Satterfield, J. G. Hagedorn, J. T. Kelso, A. P. Peskin, W. L. George et al.
      Pages 1-24
    2. Madhavi Ganapathiraju, Narayanas Balakrishnan, Raj Reddy, Judith Klein-Seetharaman
      Pages 25-47
    3. Andy Pryke, Russell Beale
      Pages 48-65
    4. Andrew J. Cowell, Sue Havre, Richard May, Antonio Sanfilippo
      Pages 66-80
  3. Ambient Cognition

    1. Michael Leyton
      Pages 81-103
    2. Geoffrey S. Hubona, Gregory W. Shirah
      Pages 104-128
    3. David Kaufer, Cheryl Geisler, Suguru Ishizaki, Pantelis Vlachos
      Pages 129-151
    4. Peter H. Jones, Christopher P. Nemeth
      Pages 152-183
  4. Ambient Intelligence Systems

    1. Elena V. Zudilova, Peter M. A. Sloot
      Pages 184-201
    2. Jonathan Farringdon, Sarah Nashold
      Pages 202-223
    3. Yang Cai, Gregory Li, Teri Mick, Sai Ho Chung, Binh Pham
      Pages 224-247
    4. Ophir Tanz, Jeremy Shaffer
      Pages 248-262
    5. Julio Abascal, Elena Lazkano, Basilio Sierra
      Pages 263-285
    6. Gregory M. P. O’Hare, M. J. O’Grady, R. Collier, S. Keegan, D. O’Kane, R. Tynan et al.
      Pages 286-310
  5. Back Matter

About this book


Many difficult scientific discovery tasks can only be solved in interactive ways, by combining intelligent computing techniques with intuitive and adaptive user interfaces. It is inevitable to use human intelligence in scientific discovery systems: human eyes can capture complex patterns and relationships, along with detecting the exceptional cases in a data set; the human brain can easily manipulate perceptions to make decisions.

Ambient intelligence is about this kind of ubiquitous and autonomous human interaction with information. Scientific discovery is a process of creative perception and communication, dealing with questions like: how do we significantly reduce information while maintaining meaning, or how do we extract patterns from massive data and growing data resources.

Originating from the SIGCHI Workshop on Ambient Intelligence for Scientific Discovery, this state-of-the-art survey is organized in three parts: new paradigms in scientific discovery, ambient cognition, and ambient intelligence systems. Many chapters share common features such as interaction, vision, language, and biomedicine.


3D Ambient Intelligence Monitor Navigation ambient intelligence systems cognition cognitive skills data anlysis data mining data visualization discovery science human perception intelligence scientific discovery visualization

Editors and affiliations

  • Yang Cai
    • 1
  1. 1.Ambient Intelligence Lab, CIC-2218Carnegie Mellon UniversityPittsburghUSA

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