Sensor Event Relevance Filtering for IoT Data Overload
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Solution Overview
Problem
The proliferation of sensor data from Internet of Things and Ubiquitous Computing systems poses a challenge in determining the relevance of sensor events, leading to information overload.
Innovation Solution
An apparatus comprising processors and memory configured to obtain sensor events, determine their relevance, and output only those that meet predetermined criteria, utilizing an output interface to prioritize and rank sensor events based on their significance to specific tasks or conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all sensor events are transmitted without filtering, then complete information is provided, but information overload and communication capacity waste occur
Solution Approach 1:
The system performs preliminary relevance determination and filtering of sensor events before transmission. The processor evaluates each sensor event against stored relevance criteria and pre-determines which events are relevant, filtering out irrelevant events before they consume communication bandwidth. This preliminary action prevents information overload while ensuring relevant information is transmitted.
Solution Approach 2:
The system extracts and transmits only the relevant subset of sensor events from the complete set of sensor data. By applying relevance criteria, the system separates relevant events from irrelevant ones, transmitting only the necessary information while discarding redundant data, thus resolving the contradiction between information completeness and data volume.
2Reliability
If all sensor events are processed and transmitted, then no relevant information is lost, but communication capacity and user inspection efficiency decrease
Solution Approach 1:
The system performs preliminary filtering of sensor events based on stored relevance criteria before transmission. By pre-evaluating each event's relevance and removing irrelevant events, the system maintains accuracy of transmitted information while significantly improving communication efficiency and reducing the burden on users to inspect unnecessary data.
3Loss of information
If relevance determination is performed on all sensor events, then information quality is improved, but processing complexity increases
Solution Approach 1:
The system uses self-service by storing relevance criteria in its memory and automatically evaluating sensor events against these criteria. The processor autonomously determines relevance without requiring external intervention or complex external processing systems, improving information quality while managing processing complexity through self-contained operations.
Data Source
AI summary
Relevance determination of sensor event is disclosed. An apparatus obtains a sensor event created on the basis of sensor data generated by one or more sensors, determines relevance of the sensor event, and if the relevance of the sensor event fulfills a predetermined relevance condition, outputs, with the output interface, the sensor event according to its determined relevance.