Intelligent Sensor Data Retention for Event Detection
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Solution Overview
Problem
In materials handling facilities, managing large volumes of sensor data acquired for event detection and inventory management is challenging due to the need to store relevant data for varying durations, while retaining all data indefinitely is not feasible.
Innovation Solution
A system that determines which sensor data to store for a default period and which to store for longer, using automated processes and user input to identify and tag data based on complexity scores, interestingness, and specific events, allowing for intelligent data retention and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all sensor data is stored indefinitely, then complete event detection and analysis capability is maintained, but storage costs and data management complexity become unmanageable
Solution Approach 1:
The patent segments sensor data into different retention categories based on event type and importance. Different data segments are retained for different durations - high-value data (e.g., safety incidents, theft) is retained indefinitely, while routine data is retained for shorter periods. This segmentation resolves the contradiction by maintaining only the necessary portion of data indefinitely rather than all data.
Solution Approach 2:
The system dynamically changes the retention parameter (storage duration) based on the characteristics of the sensor data and events detected. Retention periods are adjusted according to data importance, event severity, and business requirements. This parameter change approach allows the system to maintain high reliability for critical events while reducing overall storage volume by not indefinitely retaining all data types.
2Loss of information
If sensor data is retained for longer periods, then historical analysis and audit capabilities are improved, but storage costs and system complexity increase
Solution Approach 1:
The patent implements dynamic data retention policies where the retention period is not fixed but adapts based on event characteristics, data type, and business needs. The system automatically adjusts which data is retained longer and which is deleted sooner, making the retention strategy flexible and adaptive rather than static and uniform.
Solution Approach 2:
The system automatically classifies sensor data into retention categories based on predefined criteria and event detection, eliminating the need for manual review and decision-making for each data set. The automated classification and retention management reduce operational complexity while ensuring historical data is preserved according to business requirements.
3Reliability
If all sensor data is retained, then comprehensive security and compliance requirements are met, but storage resources are wasted on low-value data
Solution Approach 1:
The patent applies different retention qualities to different portions of sensor data based on their specific characteristics and compliance requirements. Critical data related to safety, security, and compliance is retained with high quality and indefinitely, while routine operational data is retained for shorter periods or with reduced quality. This local quality approach ensures compliance is met for necessary data without wasting resources on all data.
Data Source
AI summary
This disclosure describes techniques for utilizing sensor data to automatically determine the results of events within a system. Upon receiving sensor data indicative of an event, the techniques may analyze the sensor data to determine a result of the event, such as that a particular user associated with a user identifier selected a particular item associated with an item identifier. The techniques described herein may determine when sensor data is to be stored for a default amount of time, and when sensor data is to be stored for a greater amount of time. By retaining data in an intelligent manner, the system is able to function accurately without unduly taxing storage constraints.