AARCTIC: Autonomic Analytics Research for Corrections Technology, Institutional and in the Community

Catherine McFarland, Roy Sterritt, David Bustard, Sally McClean, Patricia O'Hagan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work is essentially concerned with PredictiveIntelligence for Corrections. The best predictor of futurebehaviour is past behavior, and is the premise behind predictiveanalytics. In essence it involves identifying predictors andpatterns that can suggest a possible outcome. In human-activitysituations prediction can be more difficult due to the inherentfickleness of human behaviour. However, in controlledenvironments such as correctional facilities a fairly consistentcommonality in predictors exists that could be mapped to acomputer system. The vision for corrections is to harness allexisting electronic data available in a given facility and employpredictive analytics to successfully identify hotspots and preemptdisturbances and incidents. The research hypothesis behindthis research project is to adapt the techniques of data fusion andpredictive analytics with the concepts surround big data velocityand autonomics to facilitate near real-time automated predictiveintelligence, that being Autonomic Analytics.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages6
Publication statusPublished - Sep 2014
Event11th IEEE International Conference and Workshops on the Engineering of Autonomic & Autonomous - APL, Laurel, Maryland, USA
Duration: 1 Sep 2014 → …

Conference

Conference11th IEEE International Conference and Workshops on the Engineering of Autonomic & Autonomous
Period1/09/14 → …

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Data fusion
Big data

Cite this

McFarland, Catherine ; Sterritt, Roy ; Bustard, David ; McClean, Sally ; O'Hagan, Patricia. / AARCTIC: Autonomic Analytics Research for Corrections Technology, Institutional and in the Community. Unknown Host Publication. 2014.
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abstract = "This work is essentially concerned with PredictiveIntelligence for Corrections. The best predictor of futurebehaviour is past behavior, and is the premise behind predictiveanalytics. In essence it involves identifying predictors andpatterns that can suggest a possible outcome. In human-activitysituations prediction can be more difficult due to the inherentfickleness of human behaviour. However, in controlledenvironments such as correctional facilities a fairly consistentcommonality in predictors exists that could be mapped to acomputer system. The vision for corrections is to harness allexisting electronic data available in a given facility and employpredictive analytics to successfully identify hotspots and preemptdisturbances and incidents. The research hypothesis behindthis research project is to adapt the techniques of data fusion andpredictive analytics with the concepts surround big data velocityand autonomics to facilitate near real-time automated predictiveintelligence, that being Autonomic Analytics.",
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McFarland, C, Sterritt, R, Bustard, D, McClean, S & O'Hagan, P 2014, AARCTIC: Autonomic Analytics Research for Corrections Technology, Institutional and in the Community. in Unknown Host Publication. 11th IEEE International Conference and Workshops on the Engineering of Autonomic & Autonomous, 1/09/14.

AARCTIC: Autonomic Analytics Research for Corrections Technology, Institutional and in the Community. / McFarland, Catherine; Sterritt, Roy; Bustard, David; McClean, Sally; O'Hagan, Patricia.

Unknown Host Publication. 2014.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - McFarland, Catherine

AU - Sterritt, Roy

AU - Bustard, David

AU - McClean, Sally

AU - O'Hagan, Patricia

PY - 2014/9

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N2 - This work is essentially concerned with PredictiveIntelligence for Corrections. The best predictor of futurebehaviour is past behavior, and is the premise behind predictiveanalytics. In essence it involves identifying predictors andpatterns that can suggest a possible outcome. In human-activitysituations prediction can be more difficult due to the inherentfickleness of human behaviour. However, in controlledenvironments such as correctional facilities a fairly consistentcommonality in predictors exists that could be mapped to acomputer system. The vision for corrections is to harness allexisting electronic data available in a given facility and employpredictive analytics to successfully identify hotspots and preemptdisturbances and incidents. The research hypothesis behindthis research project is to adapt the techniques of data fusion andpredictive analytics with the concepts surround big data velocityand autonomics to facilitate near real-time automated predictiveintelligence, that being Autonomic Analytics.

AB - This work is essentially concerned with PredictiveIntelligence for Corrections. The best predictor of futurebehaviour is past behavior, and is the premise behind predictiveanalytics. In essence it involves identifying predictors andpatterns that can suggest a possible outcome. In human-activitysituations prediction can be more difficult due to the inherentfickleness of human behaviour. However, in controlledenvironments such as correctional facilities a fairly consistentcommonality in predictors exists that could be mapped to acomputer system. The vision for corrections is to harness allexisting electronic data available in a given facility and employpredictive analytics to successfully identify hotspots and preemptdisturbances and incidents. The research hypothesis behindthis research project is to adapt the techniques of data fusion andpredictive analytics with the concepts surround big data velocityand autonomics to facilitate near real-time automated predictiveintelligence, that being Autonomic Analytics.

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