Browse Prior Art Database

Location and Image Analytics Based Decision Making

IP.com Disclosure Number: IPCOM000241987D
Publication Date: 2015-Jun-11
Document File: 5 page(s) / 187K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a method for smarter decision-making based on the superimposition of a user location-based map and an analytics-based processed image. The method is relevant to a plurality of applications.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 51% of the total text.

Page 01 of 5

Location and Image Analytics Based Decision Making

Global Positioning Systems (GPS) and signal triangulation based location methods are accurate and useful in many applications, and are widespread in consumer applications. Image analytics and processing is an emerging field wherein, based on certain filters or parameters, an image can be processed to suit a needed functionality.

The novel contribution is a method for smarter decision-making based on a combination of the superimposition of a user location-based map and an analytics-based processed image. The said method is relevant to a plurality of applications.

A user location-based map is created using any of the known location detection methods. The said locations can thereby be marked and saved. An image is captured and the said image is processed based on a certain set of input filter parameters. The processed image, post filter processing, is again marked at relevant locations and this image is then superimposed upon the first map to provide a map to assist decision- makers.

Figure 1: Method flow

Method Flow:


S1: A user carries a certain location tracking enabled device and subsequently the system records the real time location, last known location, or a path followed on a map with coordinates, and subsequently marks it. The said layout map is then saved. For example, the described map can be that of particular block in the city, of a particular region in the forest, and multiple other scenarios conceivable.

1


Page 02 of 5

S2: The system captures an overhead image using a device like drone, unmanned aerial vehicle (UAV), satellite etc. The system then runs image analytics on a captured image containing the same subset of region as described in [S1], with a plurality of other features. The image analytics filters the image based on a predetermined set of user-defined inputs, and then marks certain locations with coordinates post processing based on the input filters. For example, a captured overhead image can be processed to locate and mark only skyscrapers and cancel/blur out all other buildings such as homes, shops etc.

S3: The system superimposes the location map from [S1] and the processed image from [S2] to provide the filtered image-map with markers. The said final image-map can then be analyzed to make a decision. Note that steps [S1] and [S2] can be repeated a plurality of times and subsequently the map and processed image can be superimposed.

Example Embodiment: Determining Search & Rescue Operation Locations post large- scale natural disasters

Due to a natural disaster (e.g., earthquake, tornado, tsunami, etc.), all structures in a certain area have been destroyed. There is an urgent need to find people trapped in the rubble. However, if the affected area is large, searching through all the rubble is a time consuming process. The novel solution can determine the most possible locations of people trapped under debris using a comb...