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Method and System for Predicting Lifestyle Impact Based on Data Gathered Using Social Networks and Internet of Things

IP.com Disclosure Number: IPCOM000244862D
Publication Date: 2016-Jan-22
Document File: 3 page(s) / 71K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system is disclosed for predicting impact on lifestyle of a user relocating to a new location based on data gathered from Internet of Things (IoT) and one or more social networking sites.

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Method and System for Predicting Lifestyle Impact Based on Data Gathered Using Social Networks and Internet of Things

Disclosed is a method and system for predicting impact on lifestyle of a user relocating to a new location based on data gathered from Internet of Things (IoT) and one or more social networking sites.

The method and system gathers the data describing the user's lifestyle using several

wearable or instrumented devices such as, but not limited to, cellphones, fitness monitoring devices and devices using Global Positioning System (GPS).

Similarly, a lot of data can be gathered about the user's lifestyle from the one or more social networking sites such as, but not limited to, the user's demographics, age, hobbies, types of events the user and the user's family likes to attend and so on.

Once the data is gathered, the method and system uses the gathered data to build a model of the user's lifestyle. For example, the user's lifestyle can be modelled as, but need not be limited to, the following.

The user may jog everyday on the jogging tracks around the user's house. Also, the GPS data may suggest that the user goes to a gym. Further, the user may take the user's son for piano lessons or the user may shop at an ethnic Asian grocery store.

The method and system also derive trends from the gathered data. The trends can be used to set weights or preferences of "what matters most" vs "what can be sacrificed by

the user", and "which part of the user's current lifestyle needs improvement". For example, the user may go to a place of worship very infrequently/inconsistently such as once in three months. On the other hand, the user may jog almost every day and go to the gym at least four times a week. Further, the user may live in a big house with a basement and bonus room but hardly spends time at the house and spends lot of time outdoors. Thus, the user's lifestyle consists of activities in multiple categories.

In an embodiment, the user's lifestyle model is used to aid the user in searching for houses.

Consider two houses namely house A and house B, wherein house A is better in some

categories and house B is better in some other categories. In this case, the method and system uses the additional information derived from trends to compare the lifestyle impacts of the two houses
The figure below illustrates weights associated with the user's preferences in searching for houses.

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Figure

As illustrated in the figure, a list of home-buyer's house search results are shown by orange and blue lines taking into account the lifestyle impact. Each axis of the spider graph shows the top relevant categories for a user such as Gym, Temple etc and the impact for that category. Yellow lines shows the user's current home in comparison to the two searched results. A net weighted average can then be determined to compare

lifestyle impact of houses.

In the above example, both houses A and B are close to the user's work location so...