Artificial immune system – a new approach for the long-term data monitoring in ambient assisted living

Sebastian Bersch; Djamel Azzi; Rinat Khusainov

doi:10.1007/978-3-319-17136-4_5

Artificial immune system – a new approach for the long-term data monitoring in ambient assisted living

Sebastian Bersch, Djamel Azzi, Rinat Khusainov

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

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Abstract

This paper makes a case for the use of Artificial Immune Systems (AIS) in the area of Ambient Assisted Living (AAL) for anomaly detection and long-term data monitoring. The literature review of relevant solutions developed for AAL and the use of AIS in other fields is presented. It is further highlighted that so far AIS have not been used in the area of AAL. To advocate the use of AIS in this area, the authors compare the accuracy rate of detecting abnormal activity between a simple Signal Vector Magnitude (SVM)-based threshold algorithm, two Artificial Immune System (AIS)-based monitoring algorithms, and four supervised classification algorithms (KNN, J48, Naïve Bayes, and SMO). The results of the comparison, using precision, recall, and fmeasure, showed good results for the two different AIS-based monitoring algorithms, warranting current and future work.

Original language	English
Title of host publication	Sensor Systems and Software
Subtitle of host publication	5th International Conference, S-CUBE 2014, Coventry, UK, October 6-7, 2014, revised selected papers
Editors	Eiman Kanjo, Dirk Trossen
Publisher	Springer
Pages	41-50
Number of pages	10
ISBN (Electronic)	9783319171364
ISBN (Print)	9783319171357
DOIs	https://doi.org/10.1007/978-3-319-17136-4_5
Publication status	Published - 6 May 2015
Event	5th International Conference on Sensor Systems and Software - Coventry, United Kingdom Duration: 6 Oct 2014 → 7 Oct 2014

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Publisher	Springer International Publishing
Volume	143
ISSN (Print)	1867-8211

Conference

Conference	5th International Conference on Sensor Systems and Software
Abbreviated title	S-CUBE 2014
Country/Territory	United Kingdom
City	Coventry
Period	6/10/14 → 7/10/14

Keywords

artificial immune system
AIS
fall detection
abnormality detection
supervised classifier
unsupervised classifier

Access to Document

10.1007/978-3-319-17136-4_5

bersch_scube14_ais
This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-319-17136-4_5.
Accepted author manuscript (Post-print), 1.07 MB

Cite this

Bersch, S., Azzi, D., & Khusainov, R. (2015). Artificial immune system – a new approach for the long-term data monitoring in ambient assisted living. In E. Kanjo, & D. Trossen (Eds.), Sensor Systems and Software: 5th International Conference, S-CUBE 2014, Coventry, UK, October 6-7, 2014, revised selected papers (pp. 41-50). (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Vol. 143). Springer. https://doi.org/10.1007/978-3-319-17136-4_5

Bersch, Sebastian ; Azzi, Djamel ; Khusainov, Rinat. / Artificial immune system – a new approach for the long-term data monitoring in ambient assisted living. Sensor Systems and Software: 5th International Conference, S-CUBE 2014, Coventry, UK, October 6-7, 2014, revised selected papers. editor / Eiman Kanjo ; Dirk Trossen. Springer, 2015. pp. 41-50 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering).

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title = "Artificial immune system – a new approach for the long-term data monitoring in ambient assisted living",

abstract = "This paper makes a case for the use of Artificial Immune Systems (AIS) in the area of Ambient Assisted Living (AAL) for anomaly detection and long-term data monitoring. The literature review of relevant solutions developed for AAL and the use of AIS in other fields is presented. It is further highlighted that so far AIS have not been used in the area of AAL. To advocate the use of AIS in this area, the authors compare the accuracy rate of detecting abnormal activity between a simple Signal Vector Magnitude (SVM)-based threshold algorithm, two Artificial Immune System (AIS)-based monitoring algorithms, and four supervised classification algorithms (KNN, J48, Na{\"i}ve Bayes, and SMO). The results of the comparison, using precision, recall, and fmeasure, showed good results for the two different AIS-based monitoring algorithms, warranting current and future work.",

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Bersch, S, Azzi, D & Khusainov, R 2015, Artificial immune system – a new approach for the long-term data monitoring in ambient assisted living. in E Kanjo & D Trossen (eds), Sensor Systems and Software: 5th International Conference, S-CUBE 2014, Coventry, UK, October 6-7, 2014, revised selected papers. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 143, Springer, pp. 41-50, 5th International Conference on Sensor Systems and Software, Coventry, United Kingdom, 6/10/14. https://doi.org/10.1007/978-3-319-17136-4_5

Artificial immune system – a new approach for the long-term data monitoring in ambient assisted living. / Bersch, Sebastian; Azzi, Djamel ; Khusainov, Rinat.
Sensor Systems and Software: 5th International Conference, S-CUBE 2014, Coventry, UK, October 6-7, 2014, revised selected papers. ed. / Eiman Kanjo; Dirk Trossen. Springer, 2015. p. 41-50 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Vol. 143).

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

TY - GEN

T1 - Artificial immune system – a new approach for the long-term data monitoring in ambient assisted living

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N2 - This paper makes a case for the use of Artificial Immune Systems (AIS) in the area of Ambient Assisted Living (AAL) for anomaly detection and long-term data monitoring. The literature review of relevant solutions developed for AAL and the use of AIS in other fields is presented. It is further highlighted that so far AIS have not been used in the area of AAL. To advocate the use of AIS in this area, the authors compare the accuracy rate of detecting abnormal activity between a simple Signal Vector Magnitude (SVM)-based threshold algorithm, two Artificial Immune System (AIS)-based monitoring algorithms, and four supervised classification algorithms (KNN, J48, Naïve Bayes, and SMO). The results of the comparison, using precision, recall, and fmeasure, showed good results for the two different AIS-based monitoring algorithms, warranting current and future work.

AB - This paper makes a case for the use of Artificial Immune Systems (AIS) in the area of Ambient Assisted Living (AAL) for anomaly detection and long-term data monitoring. The literature review of relevant solutions developed for AAL and the use of AIS in other fields is presented. It is further highlighted that so far AIS have not been used in the area of AAL. To advocate the use of AIS in this area, the authors compare the accuracy rate of detecting abnormal activity between a simple Signal Vector Magnitude (SVM)-based threshold algorithm, two Artificial Immune System (AIS)-based monitoring algorithms, and four supervised classification algorithms (KNN, J48, Naïve Bayes, and SMO). The results of the comparison, using precision, recall, and fmeasure, showed good results for the two different AIS-based monitoring algorithms, warranting current and future work.

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Bersch S, Azzi D , Khusainov R. Artificial immune system – a new approach for the long-term data monitoring in ambient assisted living. In Kanjo E, Trossen D, editors, Sensor Systems and Software: 5th International Conference, S-CUBE 2014, Coventry, UK, October 6-7, 2014, revised selected papers. Springer. 2015. p. 41-50. (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering). doi: 10.1007/978-3-319-17136-4_5

Artificial immune system – a new approach for the long-term data monitoring in ambient assisted living

Abstract

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Keywords

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