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Method and System for Detecting Presence of a Living Object in a Stationary Car by a Self-Cognitive Analysis

IP.com Disclosure Number: IPCOM000238069D
Publication Date: 2014-Jul-30
Document File: 2 page(s) / 68K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system is disclosed for detecting presence of a living object in a stationary car by a self-cognitive analysis.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 52% of the total text.

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Method and System for Detecting Presence of a Living Object in a Stationary Car by a Self-

-Cognitive Analysis

Cognitive Analysis

Disclosed is a method and system for detecting presence of a living object in a stationary car by a self-cognitive analysis. The self-cognitive analysis utilizes a digital image recognition approach. The method and system can be used to dynamically detect any number of living objects left in the hot stationary car and is not limited to a pre-defined set of living objects to be monitored.

In one implementation, the system includes a monitoring module, a database of digital images history and a detection module as illustrated in the figure .

Figure

The monitoring module is utilized for one or more of , but not limited to, obtaining a digital video image of the inside of a car from time to time , motion detection to detect if car is moving, sound level detection to detect if there are any activities inside the car and temperature inside of the car. The detection module determines a confidence level of a child being left behind in the car based on image history .

In an implementation of the method and system , a detection unit is installed inside a car to obtain a desired view of an empty dome. Thereafter, the detection unit starts detecting with the empty dome as the basis. The detection unit subsequently learns and stores the digital images of a plurality of object states . The detection unit stores

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the images when the objects to be monitored are in the car over a period of time .

The detection unit determines the confidence level of a living object left in a stationary car based on comparing digital images snapped from time to time with the digital images in the image database and the car temperature . If the confidence level is greater than 70% means that the system is 70% confident that there is a living object in the car which was also learned to be there before. The detection unit accordingly generates critical level electronic alert signals until physically reset at the unit. The alert can be used to perform actions such as, but not limited to, automatically wind down

windows, text pre-defined contacts, blare car alarms and text...