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.
|Title of host publication||Unknown Host Publication|
|Publisher||IEEE Computer Society|
|Number of pages||6|
|Publication status||Published - Sep 2014|
|Event||11th IEEE International Conference and Workshops on the Engineering of Autonomic & Autonomous - APL, Laurel, Maryland, USA|
Duration: 1 Sep 2014 → …
|Conference||11th IEEE International Conference and Workshops on the Engineering of Autonomic & Autonomous|
|Period||1/09/14 → …|
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 IEEE Computer Society.