Mining Patterns from 9-1-1 Calls Dataset
Athithyaa Selvam, Balasubramanian Thiagarajan and Thivakaran T K.. Mining Patterns from 9-1-1 Calls Dataset. International Journal of Applied Information Systems 11(7):35-40, December 2016. URL, DOI BibTeX
@article{10.5120/ijais2016451632, author = "Athithyaa Selvam and Balasubramanian Thiagarajan and Thivakaran T. K.", title = "Mining Patterns from 9-1-1 Calls Dataset", journal = "International Journal of Applied Information Systems", issue_date = "December 2016", volume = 11, number = 7, month = "Dec", year = 2016, issn = "2249-0868", pages = "35-40", numpages = 6, url = "http://www.ijais.org/archives/volume11/number7/953-2016451632", doi = "10.5120/ijais2016451632", publisher = "Foundation of Computer Science (FCS), NY, USA", address = "New York, USA" }
Abstract
Everybody encounters different kinds of emergency circumstances in their day-to-day life. A 9-1-1 call may be a consequence of a natural disaster, emergency medical need, fire attack, crime or an individual or group of persons needing some form of immediate assistance. Strategy makers are faced with difficult decisions of providing resources to handle these emergencies, and due to lack of data, they face many problems. In this paper, a model is developed using data mining techniques for identifying patterns based on an analysis of the characteristics of 9-1-1 call activity from Montgomery County 9-1-1 calls dataset. This analysis is useful for allocating emergency responders and helps them take proactive steps in their response efforts. The model will also help strategy makers anticipate the occurrences of emergencies and enable them to effectively handle the emergency by appropriate allocation of resources.
Reference
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Keywords
Pre-processing, K-means Clustering, Visualization, 9-1-1 Dataset