Purdue Research Foundation

Arizona State University

Ross Maciejewski

David Scott Ebert

Abish Malik

William Cleveland

David H Frakes

Ryan P Hafen

Mark Spano

Yun Jang

Timothy Collins

Jonah Thomas

Sherry Towers

Alison Van Putten

Sandra Amass

Nathaniel Kirkpatrick

Dustin Plaas

Joseph Sansone

Stephen Rudolph

Matthew Mortensen

Benjamin N Tyner

Disclosed herein is a visual analytics system and method that provides a proactive and predictive environment in order to assist decision makers in making effective resource allocation and deployment decisions. The challenges involved with such predictive analytics processes include end-users' understanding, and the application of the underlying statistical algorithms at the right spatiotemporal granularity levels so that good prediction estimates can be established. In the disclosed approach, a suite of natural scale templates and methods are provided allowing users to focus and drill down to appropriate geospatial and temporal resolution levels. The disclosed forecasting technique is based on the Seasonal Trend decomposition based on Loess (STL) method applied in a spatiotemporal visual analytics context to provide analysts with predicted levels of future activity. A novel kernel density estimation technique is also disclosed, in which the prediction process is influenced by the spatial correlation of recent incidents at nearby locations.

Proactive spatiotemporal resource allocation and predictive visual analytics system

Some systems include a memory, and a processor coupled to the memory, wherein the processor is configured to: identify one or more spatial markers in a medical data-based image of a patient, identify one or more spatial markers in a real-time perceived image of the patient, wherein the one or more spatial markers in the medical data-based image correspond to an anatomical feature of the patient and the one or more spatial markers in the real-time perceived image correspond to the anatomical feature of the patient, superimpose the medical data-based image of the patient with the real-time perceived image of the patient, and align the one or more spatial markers in the medical data-based image with the respective one or more spatial markers in the real-time perceived image.

Real-time medical image visualization systems and related methods

A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

Forecasting hotspots using predictive visual analytics approach

A system and method for visually displaying and analyzing public health data for geospatial and/or time variations, including the collection of symptom data coupled with geographic and time data, filtering the symptom data based upon a selected time period and geographic range, and creating a visual result based upon statistical modeling including power transform and/or data normalization. According to at least one embodiment, the system for visually displaying and analyzing includes selecting and performing at least one aberration detection method such as applying CUSUM analysis, quantile measures, and/or bootstrapping analysis, and displaying the result to a user via a visual analytics arrangement.

Animal symptom visual analytics

A system and method for visually displaying and analyzing criminal and/or public health and safety data for geospatial and/or time variations, including the collection of incident data coupled with geographic and time data, filtering the symptom data based upon a selected time period and geographic range, and creating a visual result based upon statistical modeling including power transform and/or data normalization. According to at least one embodiment, the system for visually displaying and analyzing includes selecting and performing at least one aberration detection method and displaying the result to a user via a visual analytics arrangement.

Visual analytics law enforcement tools

Growing community of inventors

Phoenix, AZ, United States of America

Ross Maciejewski