Memorable Event Detection and Recall System

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Solution Overview

Problem

Users often fail to record memorable events due to surprise or tediousness, leading to a lack of documentation of emotionally significant experiences.

Innovation Solution

A system comprising an event detection server and user profile database that collects emotional reaction information and event data, applies rules to determine emotions and events, and characterizes events as memorable based on predetermined thresholds, storing and later recalling these events to encourage delightful experiences or engage users in conversation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If users manually record events, then memory retention is improved, but user burden and tediousness increase

Engineering Contradiction:

Improvememory retentionVSAvoiduser burden

Core Design Contradiction:

Loss of informationVSEase of operation

Solution Approach 1:

The system performs automatic event detection and recording without requiring user intervention. Sensors continuously monitor user state and environment, automatically identifying memorable events and storing them in the database, eliminating the need for manual user action while preserving memory retention

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The manual mechanical act of recording is replaced by an automated electronic system using sensors, processors, and databases. The system substitutes human effort with automated detection algorithms that analyze sensor data to identify and record memorable events

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of information

If users record all events, then completeness is improved, but data volume and processing complexity increase

Engineering Contradiction:

Improveevent completenessVSAvoidprocessing complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The system extracts only the essential and memorable events from the continuous stream of sensor data, rather than recording all events. By applying detection algorithms to identify emotionally significant moments, the system separates valuable information from unnecessary data, maintaining completeness of important events while reducing overall data volume

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system applies different processing quality levels to different types of data. Memorable events receive detailed processing and storage, while non-memorable events are either summarized or discarded. This localized quality approach ensures complete recording of important events without the processing overhead of uniformly high-quality recording

Inventive Principle:

Principle #3Local quality

3Measurement precision

If the system monitors continuously, then detection accuracy is improved, but energy consumption increases

Engineering Contradiction:

Improvedetection accuracyVSAvoidenergy consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

Instead of continuous high-intensity monitoring, the system uses periodic sampling of sensor data at strategically determined intervals. The monitoring intensity is adjusted based on detected patterns and user state, maintaining detection accuracy for memorable events while reducing overall energy consumption through intermittent rather than constant operation

Inventive Principle:

Principle #19Periodic action

Data Source

PatentUS11625622B2Memorable event detection, recording, and exploitation

Publication Date: 2023.04.11 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

Aspects of the present disclosure provide systems and methods for detecting memorable events of a user, storing those memorable events in a user profile, and leveraging those events to the user. In so doing, memorable events with positive emotional weight may be recalled to encourage delightful experiences. Alternatively or additionally, memorable events with negative emotional weight may be recalled to increase user engagement for conversational systems.