Domain-Agnostic Sensor Data Aggregation System
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Solution Overview
Problem
Current data warehousing solutions require significant investment in time and resources for designing ETL modules and purchasing specialized hardware, and are often tied to specific domains, making it costly and complex to extract and transform data from complex domains for analysis.
Innovation Solution
A domain-agnostic system and method that uses a system server as a central data collection point to capture, store, and analyze sensor readings from various gauges, allowing for unified storage and aggregation of data across different domains, eliminating the need for expensive ETL modules and specialized hardware by using an API for gauge readings and supporting formulas for data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional data warehousing solutions are used to extract and transform data from complex domains, then data can be stored and analyzed, but significant investment in time and resources is required for designing ETL modules and purchasing specialized hardware
Solution Approach 1:
The patent applies universality by creating a domain-agnostic system that can handle multiple data types and domains through a single unified architecture. The system uses generic sensor models, configurable data sources, and standardized processing pipelines that can accommodate various domains (industrial, environmental, healthcare, etc.) without requiring domain-specific ETL modules or specialized hardware, thus resolving the contradiction between reliable data storage and system complexity
2Productivity
If domain-specific data warehousing approaches are used, then data extraction and transformation can be performed, but it becomes costly and complex to extract and transform data from complex domains for analysis
Solution Approach 1:
The patent applies dynamics by implementing a flexible, configurable system where data sources, processing parameters, and analysis methods can be dynamically adjusted based on the specific domain and data characteristics. The system allows runtime configuration of data pipelines, dynamic schema adaptation, and flexible query processing, enabling high productivity across diverse domains without requiring separate domain-specific implementations
Solution Approach 2:
The system achieves versatility through universal components that can handle multiple domains. It uses domain-agnostic data models, standardized interfaces for various data sources (sensors, databases, APIs), and configurable processing pipelines that can be adapted to different domains through configuration rather than code changes, thus maintaining high productivity while enabling cross-domain functionality
Data Source
AI summary
Domain agnostic systems and methods for the capture, storage, and analysis of sensor readings including: collecting gauge readings from a plurality of gauges; storing the gauge readings in a database; normalizing select gauge readings in near-real time at the server from the database of the server in response to a user query; and generating a relationship among the select gauge readings in response to the user query; generating information for configuring an entity that provides feedback in a domain agnostic system, based on said relationship among the select gauge readings; and generating an alert in response to the select gauge readings satisfying a certain condition.