IoT Analytics Engine Semantic Reasoning for Procedural Evaluation
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Solution Overview
Problem
Traditional IoT analytics systems are limited by their reliance on quantitative analysis and manual intervention due to differences in programming languages, lacking support for procedural evaluations and obsolete or false facts, which restricts their reasoning capabilities.
Innovation Solution
A method and system that dynamically create and integrate procedural functions from multiple programming languages to extend reasoning capabilities, using semantic rules and Uniform Resource Identifiers (URIs) to execute data analytics tasks, and represent control flow codes in vector space for real-time semantic rule extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional quantitative analysis methods are used for IoT data analytics, then the analysis can be performed using existing tools, but the reasoning capability is limited and manual intervention is required
Solution Approach 1:
The patent introduces an intermediary layer (analytics engine with semantic reasoning capabilities) that sits between the IoT data sources and the analysis tools. This intermediary automatically performs procedural evaluations and reasoning tasks, reducing the need for manual intervention while managing complexity through modular architecture.
Solution Approach 2:
The patent replaces manual mechanical analysis processes with automated semantic reasoning mechanisms. The system uses semantic rules, ontologies, and procedural functions to automatically perform data analytics tasks that previously required human analysts, thereby increasing automation while encapsulating complexity within the system.
2Adaptability or versatility
If analytics tasks are implemented in different programming languages, then flexibility in tool selection is improved, but manual intervention and asynchronous sequential analysis are required
Solution Approach 1:
The patent creates a universal analytics engine that can process analytics tasks from multiple programming languages simultaneously. The system uses a common semantic framework and procedural function registry that accepts inputs from different language platforms, enabling parallel processing and eliminating the need for sequential manual intervention between different language environments.
3Reliability
If the system supports procedural evaluations and dynamic fact checking, then reasoning capability is enhanced, but the system complexity increases
Solution Approach 1:
The patent segments the reasoning system into distinct modular components: procedural function registry, semantic rule engine, ontology repository, and fact verification module. Each component handles specific aspects of procedural evaluation and fact checking independently, which enhances reasoning capability while managing complexity through clear separation of concerns and reusable modules.
4Speed
If pre-defined procedural functions are used, then execution speed is improved, but adaptability to new analytics tasks is reduced
Solution Approach 1:
The patent implements a dynamic procedural function registry that allows the system to adapt to new analytics tasks while maintaining execution speed. The registry can load pre-defined functions for immediate execution and dynamically register new procedural functions from different programming languages as needed. This dynamic architecture enables the system to switch between using existing optimized functions and adapting to new requirements, balancing speed and versatility.
Data Source
AI summary
Systems and methods for extending reasoning capability for data analytics in Internet of Things (IoT) platform(s) are provided. Traditional systems and methods for executing IoT analytics tasks suffer as IoT analytics techniques are generated in different programming language platforms, and this leads to a manual intervention or an asynchronous and sequential analysis of IoT analytics task(s). Embodiments of the method disclosed provide for overcoming the limitations faced by the traditional systems and methods by dynamically creating procedural functions from a plurality of programming languages upon determining an absence of pre-defined procedural functions, and extracting, using the dynamically created procedural functions, one or more semantic rules in a real-time, wherein the one or more semantic rules extend a reasoning capability for executing the one or more data analytics tasks in a plurality of IoT platforms.