A hybrid rule and machine learning based generic alerting platform for smart environments

J. Rafferty; J. Synnott; C. Nugent

doi:10.1109/EMBC.2016.7591949

A hybrid rule and machine learning based generic alerting platform for smart environments

J. Rafferty
, J. Synnott
, C. Nugent

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

Existing smart environment based alert solutions have adopted a relatively complex and tailored approach to supporting individuals. These solutions have involved sensor based monitoring, activity recognition and assistance provisioning. Traditionally they have suffered from a number of issues, rooted in scalability and performance, associated with complex activity recognition processes. This paper introduces a generic approach to realizing an alerting platform within a smart environment. The core concept of this approach is presented and placed within the context of related work. A description of the approach is provided, followed by an evaluation. This evaluation shows the approach offers reasonable accuracy, future work will increase accuracy.

Original language	English
Title of host publication	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Publisher	IEEE
Pages	5405-5408
DOIs	https://doi.org/10.1109/EMBC.2016.7591949
Publication status	Published (in print/issue) - 16 Aug 2016

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10.1109/EMBC.2016.7591949

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title = "A hybrid rule and machine learning based generic alerting platform for smart environments",

abstract = "Existing smart environment based alert solutions have adopted a relatively complex and tailored approach to supporting individuals. These solutions have involved sensor based monitoring, activity recognition and assistance provisioning. Traditionally they have suffered from a number of issues, rooted in scalability and performance, associated with complex activity recognition processes. This paper introduces a generic approach to realizing an alerting platform within a smart environment. The core concept of this approach is presented and placed within the context of related work. A description of the approach is provided, followed by an evaluation. This evaluation shows the approach offers reasonable accuracy, future work will increase accuracy.",

author = "J. Rafferty and J. Synnott and C. Nugent",

year = "2016",

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doi = "10.1109/EMBC.2016.7591949",

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A hybrid rule and machine learning based generic alerting platform for smart environments. / Rafferty, J.; Synnott, J.; Nugent, C.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. IEEE, 2016. p. 5405-5408 7591949.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Nugent, C.

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AB - Existing smart environment based alert solutions have adopted a relatively complex and tailored approach to supporting individuals. These solutions have involved sensor based monitoring, activity recognition and assistance provisioning. Traditionally they have suffered from a number of issues, rooted in scalability and performance, associated with complex activity recognition processes. This paper introduces a generic approach to realizing an alerting platform within a smart environment. The core concept of this approach is presented and placed within the context of related work. A description of the approach is provided, followed by an evaluation. This evaluation shows the approach offers reasonable accuracy, future work will increase accuracy.

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EP - 5408

BT - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

PB - IEEE

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A hybrid rule and machine learning based generic alerting platform for smart environments

Abstract

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