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14.1 - A Predictive Analytics Framework for Spatio-Temporal Hotspots

Project - Summary


The objective of this project is to develop a framework for hotspot analysis. To accomplish this, we (a) created a new approach to detect hotspots from point data, (b) developed a MapReduce approach to improve scalability of hotspot detection, © created a new ensemble-based approach to hotspot prediction and (d) designed a MapReduce framework for ensemble-based prediction.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Jian Chen PI Not available Not available UL Lafayette
Ryan Benton Co-PI Not available Not available UL Lafayette
Raju Gottumukkala Co-PI (337) 482-0632 UL Lafayette
Xiaohua Tony Hu Co-PI (215) 895-0551 Drexel University
Vijay Raghavan Co-PI (337) 482-6603 UL Lafayette
Satya Katragadda Graduate Student (337) 482-0625 UL Lafayette
Shaaban Abbady Graduate Student Not available Not available UL Lafayette

Project - Impact and Uses/Benefits

Early hotspots detection and precise prediction are important in many disciplines. This project provides scalable spatio-temporal hotspot detection and prediction approaches which are well engineered for big data. The approaches are general and can be applied in various application domains with minimal customizations.

This system can be beneficial in several applications such as epidemiology, public health, law enforcement, anti-terrorism, marketing (Merging markets, cross selling, and advertisement optimization), etc.

Project - Deep Dive

Project - Documents

FilenameFilesizeLast modified
14.1_year_3_cvdi_ip_letter_combined.pdf769.4 KiB2019/08/22 11:26
14.1_year_3_presentation.pptx3.0 MiB2019/08/22 11:26
14.1_year_3_executive_summaries_combined.pdf441.9 KiB2019/08/22 11:26
14.1_year_3_final_report.pdf2.1 MiB2019/08/22 10:21
projects/year3/14.1.txt · Last modified: 2021/06/02 15:50 by sally.johnson