Methods and systems for monitoring human body weight with vehicle sensors and big data AI analytics

Patent metadata

Field	Value
Publication number	US-11625937-B2
Application number	US-202016840571-A
Country	US
Kind code	B2
Filing date	Apr 6, 2020
Priority date	Apr 6, 2020
Publication date	Apr 11, 2023
Grant date	Apr 11, 2023

Abstract

A weight management system for managing vehicle seat occupant body weight by using vehicle cameras and weight sensors of a plurality of vehicles having onboard communication modules. Each vehicle is equipped to analyze and compare weight changes of the vehicle seat occupant over time. Based on the weight status, a weight management recommendation can be transmitted to the vehicle seat occupant. Each vehicle is operatively connected to a weight management application in a data center. The weight management application includes a registration module which registers each vehicle. Additionally, a vehicle seat occupant may register with the weight management application to have his/her weight analyzed when travelling in any of the plurality of vehicles. The weight management application requests a search of a data lake and analysis of search results by a weight data artificial intelligence analytics program to improve the weight management recommendation.

First claim

The invention claimed is:

1. A method for managing a weight of a vehicle seat occupant using vehicle cameras and vehicle weight sensors, comprising:
detecting an approach of the vehicle seat occupant to the vehicle and generating a presence signal;
performing a body scan of the vehicle seat occupant upon receiving the presence signal;
timestamping and storing the body scan in a vehicle memory;
determining a set of body scan parameters from the body scan of the vehicle seat occupant, wherein the set of body scan parameters includes apparent weight, height, body mass index (BMI), and waist thickness;
recording a sensor signature of the vehicle seat occupant;
identifying the vehicle seat occupant by matching the sensor signature to a set sensor signatures of registered vehicle seat occupants stored in the vehicle memory;
measuring a current body weight of the vehicle seat occupant;
timestamping and storing the current body weight in the vehicle memory;
determining changes between the current body weight and at least one stored body weight of the vehicle seat occupant having a timestamp recorded during an earlier time period;
accessing GPS records regarding venues visited by the vehicle seat occupant during the earlier time period;
associating each of the venues with a level of caloric intake based on a type of the venue, wherein the venues include restaurants, fast food restaurants, fitness centers, and grocery stores;
generating a weight analysis by (i) correlating the weight changes of the vehicle seat occupant with the level of the caloric intake associated with the venues visited by the vehicle seat occupant, and (ii) correlating the weight changes, the set of body scan parameters and the GPS records of venues visited with weight information stored in the vehicle memory;
generating a weight management recommendation from the weight analysis;
notifying the vehicle seat occupant of the weight management recommendation;
updating the vehicle memory with the weight management recommendation; and
transmitting the body weight changes and the body scan parameters to a data lake.

2. The method of claim 1 , further comprising:
determining changes between the current body weight and at least one stored body weight of the vehicle seat occupant having a timestamp recorded during an earlier time period selected from at least one of:
greater than two weeks and less than five years before the current body weight;
greater than one month and less than three months before the current body weight; and
greater than six months and less than one year before the current body weight.

3. The method of claim 1 , further comprising:
comparing the current body weight with each body weight from an earlier time period until one of a change is detected and all body weights having earlier timestamps have been compared to the current body weight.

4. The method of claim 1 , further comprising:
recording the sensor signature by at least one of an internal vehicle camera, an audio sensor, a fingerprint sensor, and a retinal sensor.

5. The method of claim 1 , further comprising:
registering the vehicle with a weight management application by creating public and private pair keys in a vehicle computing system of the vehicle;
transmitting the public key to the weight management application;
creating a user profile for each vehicle seat occupant including at least a facial image, an age, a height, a weight, a gender, an ethnic group, an address, a credit card number and medical diseases of the vehicle seat occupant; and
providing lists of preferred medical practitioners, dieticians, weight management centers, fitness centers and scalp care professionals and retail outlets of each vehicle seat occupant.

6. The method of claim 5 , further comprising:
combining the vehicle seat occupant identification, the body weight changes, the set of body scan parameters and the GPS records of venues visited into a data packet;
transmitting the data packet to the weight management application.

7. The method of claim 6 , further comprising:
receiving, by the weight management application, the data packet;
requesting, by the weight management application, a search related to the vehicle seat occupant body weight changes, the set of body scan parameters and the GPS records of venues visited;
receiving the request by a weight data artificial intelligence (AI) analytics circuitry module;
querying the data lake for information relating to the vehicle seat occupant body weight changes, the set of body scan parameters and the GPS records of venues visited;
searching, by the data lake, unstructured data and structured databases for matches to the query;
receiving, by the weight data AI analytics circuitry module, the matches to the query;
analyzing, by the weight data AI analytics circuitry module, the matches to determine weight conditions, treatment options for the weight conditions and at least one of weight loss or weight gain product information related to the weight conditions;
generating, by the weight data AI analytics circuitry module, a weight report;
providing the weight report to the weight management application for correlation with the vehicle seat occupant user profile;
generating a weight management recommendation;
transmitting the weight management recommendation to the vehicle;
updating the vehicle memory; and
delivering the weight management recommendation to the vehicle seat occupant.

8. The method of claim 6 , further comprising:
registering a smart device of the vehicle seat occupant with the weight management application by:
creating public and private pair keys with a smart device of the vehicle seat occupant;
transmitting the public key to the weight management application;
creating a vehicle seat occupant user profile including at least a facial image, an age, a height, a weight, a gender, an ethnic group, an address, a credit card number and previous weight and medical diseases of the vehicle seat occupant; and
providing a list of preferred weight management professionals, dieticians, weight management centers, fitness centers and retail outlets.

9. The method of claim 8 , further comprising:
receiving, by the weight management application, the data packet;
requesting, by the weight management application, a search related to the vehicle seat occupant weight information record;
receiving the request by a weight data artificial intelligence (AI) analytics circuitry module;
querying the data lake for information relating to the vehicle seat occupant body weight changes, the set of body scan parameters and the GPS records of venues visited;
searching, by the data lake, unstructured data and structured databases for matches to the query;
receiving, by the weight data AI analytics circuitry module, the matches to the query;
analyzing, by the weight data AI analytics circuitry module, the matches to determine weight conditions, treatment options for the weight conditions and at least one of weight loss or weight gain product information related to the weight conditions;
generating, by the weight data AI analytics circuitry module, a weight report;
providing the weight report to the weight management application for correlation with the vehicle seat occupant user profile;
generating a weight management recommendation;
transmitting the weight management recommendation to the smart device of the registered vehicle seat occupant.

10. The method of claim 7 , wherein the weight management recommendation comprises at least one of:
recommending a medical practitioner based on a home location or a current location of the vehicle seat occupant;
recommending a weight management

Assignees

• Toyota Eng & Mfg North America

Inventors

• Pham Alexander T

Classifications

• B60N2230/20

  Wireless data transmission · CPC title

• B60N2210/24

  Cameras · CPC title

• B60N2230/30

  Signal processing of sensor data · CPC title

• B60N2/0025

  by using weight measurement · CPC title

• B60N2/0022

  for sensing anthropometric parameters, e.g. heart rate or body temperature · CPC title