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Predictive Analytics for Exceeding Desired Limits

IP.com Disclosure Number: IPCOM000249011D
Publication Date: 2017-Jan-25
Document File: 1 page(s) / 20K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed are a system and method to apply Internet of Things (IoT) technology and predictive analytics to identify actions that are likely to lead to an individual exceeding desired limits (e.g., eating too much, drinking in excess, or over-spending money), and then automatically recommend alternatives to help the user avoid excessive behavior.

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Predictive Analytics for Exceeding Desired Limits

Individuals, if not paying attention to the current situation, can often exceede a desired limit for an activity such as eating, drinking, or spending money. This can be triggered by spending time with a particular individual or group or going to certain locations.

The novel contribution is a system and method for identifying actions that are likely to lead to an individual exceeding desired limits (e.g., eating too much, drinking in excess, or over-spending money). The system tracks items that an individual wants to monitor and then associates that item or action with the combination of people and/or locations that cause the person to exceed desired limits.

The system uses sensor data and predictive analytics to learn where and with whom an individual is likely to exceed a limit that needs to be kept in control. When the system detects a high probability of excessive behavior, it automatically recommends possible alternatives or actions to the individual, which the user can select to strengthen the will power to avoid the behavior.

At a high level, to implement this solution in a preferred embodiment, the system: 1. Receives as input configurations for the limits the user wants to control 2. Accesses the user’s electronic calendar and Internet of Things (IoT) sensors to

identify whom a person is associating or spending time 3. Uses the electronic calendar and global positioning system (GPS) sensors to

identify the user’s l...