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Evaluating semi-automatic annotation of domestic energy consumption as a memory aid

Evaluating semi-automatic annotation of domestic energy consumption as a memory aid
Evaluating semi-automatic annotation of domestic energy consumption as a memory aid
Frequent feedback about energy consumption can help conservation, one of the current global challenges. Such feedback is most helpful if users can relate it to their own day-to-day activities. In earlier work we showed that manual annotation of domestic energy consumption logs aids users to make such connection and discover patterns they were not aware of. In this poster we report how we augmented manual annotation with machine learning classification techniques. We propose the design of a lab study to evaluate the system, extending methods used to evaluate context aware memory aids, and we present the results of a pilot with 5 participants.
613-614
Richardson, Darren P.
f55f06e8-4f92-4399-b365-558b4e64d65d
Costanza, Enrico
0868f119-c42e-4b5f-905f-fe98c1beeded
Ramchurn, Sarvapali D.
1d62ae2a-a498-444e-912d-a6082d3aaea3
Richardson, Darren P.
f55f06e8-4f92-4399-b365-558b4e64d65d
Costanza, Enrico
0868f119-c42e-4b5f-905f-fe98c1beeded
Ramchurn, Sarvapali D.
1d62ae2a-a498-444e-912d-a6082d3aaea3

Richardson, Darren P., Costanza, Enrico and Ramchurn, Sarvapali D. (2012) Evaluating semi-automatic annotation of domestic energy consumption as a memory aid. UbiComp '12. Proceedings of the 2012 ACM Conference on Ubiquitous Computing, Pittsburgh, United States. 05 - 08 Sep 2012. pp. 613-614 . (doi:10.1145/2370216.2370330).

Record type: Conference or Workshop Item (Poster)

Abstract

Frequent feedback about energy consumption can help conservation, one of the current global challenges. Such feedback is most helpful if users can relate it to their own day-to-day activities. In earlier work we showed that manual annotation of domestic energy consumption logs aids users to make such connection and discover patterns they were not aware of. In this poster we report how we augmented manual annotation with machine learning classification techniques. We propose the design of a lab study to evaluate the system, extending methods used to evaluate context aware memory aids, and we present the results of a pilot with 5 participants.

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Published date: September 2012
Venue - Dates: UbiComp '12. Proceedings of the 2012 ACM Conference on Ubiquitous Computing, Pittsburgh, United States, 2012-09-05 - 2012-09-08
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 349083
URI: http://eprints.soton.ac.uk/id/eprint/349083
PURE UUID: 8b7601a0-b34c-455c-aa7c-3c28e96e5393
ORCID for Sarvapali D. Ramchurn: ORCID iD orcid.org/0000-0001-9686-4302

Catalogue record

Date deposited: 21 Feb 2013 19:04
Last modified: 15 Mar 2024 03:22

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Contributors

Author: Darren P. Richardson
Author: Enrico Costanza
Author: Sarvapali D. Ramchurn ORCID iD

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