IoT Edge Analytics Filtering for Data Volume Reduction
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Solution Overview
Problem
The increasing amount of sensory data from Internet of Things (IoT) devices overwhelms storage capacity and bandwidth, with much raw data being discarded due to inefficiencies in processing and storage, leading to the loss of valuable information.
Innovation Solution
An analysis device is introduced to collect, analyze, and filter sensory data using analytic filters, compressing and reducing the data while retaining fidelity, and enabling mobile devices to manage and update data storage, allowing for efficient data management and migration to cloud storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all raw sensory data from IoT devices is stored and transmitted, then complete information is preserved, but storage capacity and bandwidth are overwhelmed
Solution Approach 1:
The patent applies preliminary action by performing data analysis and filtering at the edge device (IoT device or gateway) before data is transmitted to the cloud. Analytic filters are executed locally to pre-process sensory data, identifying and retaining only relevant information while discarding redundant data beforehand. This prevents unnecessary data from consuming storage and bandwidth resources during transmission and cloud storage.
Solution Approach 2:
The patent extracts valuable information from raw sensory data by applying analytic filters that identify and separate relevant data points from the overwhelming volume of raw sensor readings. The filters extract only the meaningful patterns and anomalies, discarding the rest. This extraction process reduces the data quantity to be stored and transmitted while preserving the essential information content.
2Productivity
If analytic filters are applied to filter and compress data, then storage and bandwidth are optimized, but processing complexity increases
Solution Approach 1:
The patent segments the data processing function into multiple analytic filters that can be independently configured and executed. Each filter handles specific types of analysis (e.g., threshold-based filtering, pattern recognition, anomaly detection), allowing the complex processing task to be divided into manageable, modular components. This segmentation makes the system more manageable and allows selective application of different filter types based on data characteristics.
Solution Approach 2:
The patent introduces an intermediary processing layer (analytic filter engine) between the IoT sensor devices and the cloud storage system. This intermediary performs the complex filtering and compression operations, acting as a mediator that reduces data volume before cloud ingestion. The intermediary handles the processing complexity locally, preventing it from propagating to both the sensor devices and the cloud infrastructure.
3Loss of information
If more data is retained for analysis, then better insights are obtained, but storage costs increase
Solution Approach 1:
The patent changes the parameters of data representation through compression and filtering operations. By transforming raw sensory data into filtered, aggregated, or compressed formats, the system retains the essential information content while reducing the storage space required. Parameter changes in data format, precision, and granularity allow the system to maintain analytical value with reduced storage requirements.
Data Source
AI summary
A system, computer program product, and computer-executable method for managing data from an Internet of Things (IoT) Device, the system, computer program product, and computer-executable method comprising receiving data from the IoT Device, analyzing the data using an analytic filter, and updating a mobile device based on the analyzing.