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Massachusetts Institute of Technology

End-user modification and correction of home activity recognition

Abstract

dc:description.abstract

Sensor-enabled computer systems capable of recognizing specific activities taking place in the home may enable a host of "context-aware" applications such as health monitoring, home automation, remote presence, and on-demand information and learning, among others. Current state-of-the-art systems can achieve close to 90% accuracy in certain situations, but the decision processes involved in this recognition are too complex for the end-users of the home to understand. Even at 90% accuracy, errors are inevitable and frequent, and when they do occur the end-users have no tools to understand the cause of errors or to correct them. Instead of such complex approaches, this work proposes and evaluates a simplified, user-centric activity recognition system that can be understood, modified, and improved by the occupants of a context-aware home. The system, named Distinguish, relies on high-level, common sense information to construct activity models used in recognition. These models are transferable between homes and can be modified on a mobile phone-sized screen. Observations are reported from a pilot evaluation of Distinguish on naturalistic data gathered continuously from an instrumented home over a period of a month. Without any knowledge of the target home or its occupant's behaviors and no training data other than common sense information contributed by web users, the system achieved a baseline activity recognition accuracy of 20% with 51 target activities. A user test with 10 participants demonstrated that end-users were able to not only understand the cause of the errors, but with a few minutes of effort were also able to improve the system's accuracy in recognizing a particular activity from 12.5% to 52.3%. Based on the user study, 5 design recommendations are presented.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Architecture. Program in Media Arts and Sciences.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2010

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Burns, Edward E. (Edward Eugene)
Advisor dc:contributor.advisor
  • Kent Larson.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/61941
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/61941

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Burns, Edward E. (Edward Eugene). End-user modification and correction of home activity recognition. Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61941