Declarative Framework for IoT Event Throttling
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Solution Overview
Problem
Current IoT applications are complex and require substantial programming expertise, making them inaccessible to non-technical users who need to harness and analyze big data for real-time insights, and existing data analytics tools are not engineered to handle machine-generated events effectively.
Innovation Solution
A declarative framework that implements a state machine for multi-step entity interaction, providing a simple rule-based authoring tool for specifying state definitions, transition triggers, and actions, allowing non-technical users to create workflows that handle machine-generated events without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a complex state machine framework is used to handle machine-generated events, then the system can effectively process and analyze big data from IoT devices, but the framework becomes inaccessible to non-technical users who lack programming expertise
Solution Approach 1:
The patent introduces a declarative framework that acts as an intermediary layer between non-technical users and the complex state machine processing system. Users define workflows using simple, readable statements in a declarative language, which are then automatically translated into the complex state machine logic required for handling machine-generated events from IoT devices. This mediator layer shields users from complexity while maintaining full processing capability.
Solution Approach 2:
The patent replaces the traditional mechanical approach of manually programming state machines with complex code with an automated translation system. The declarative workflow definitions are automatically converted into executable state machine logic, eliminating the need for users to manually construct complex processing frameworks. This substitution transforms a manually-intensive, expertise-requiring process into an automated, accessible operation.
2Reliability
If existing data analytics tools are used, then they can process structured data, but they fail to effectively handle machine-generated events from IoT devices
Solution Approach 1:
The patent implements a dynamic workflow execution engine that can adapt to different types of machine-generated events from IoT devices. The system dynamically translates declarative workflow definitions into appropriate state machine logic based on the specific event types and data sources being processed. This dynamic adaptation allows the same framework to reliably handle diverse event streams from various IoT devices without requiring separate specialized tools for each device type.
3Ease of operation
If a declarative framework with automatic state machine generation is implemented, then non-technical users can easily create workflows, but the system complexity increases in the background translation and execution layer
Solution Approach 1:
The patent implements a self-service translation engine that automatically generates the necessary state machine logic from declarative workflow definitions without requiring manual intervention from users or system administrators. The translation engine autonomously analyzes the workflow definitions, identifies required state transitions and event handlers, and generates the appropriate processing logic. This self-service approach masks the underlying complexity while providing simple user-facing workflow creation capabilities.
Data Source
AI summary
The disclosed declarative framework implements a machine for multi-step progression of interaction with an entity. The framework is usable for a broad range of applications—providing a simple rule-based authoring tool for specifying elements and components of a complex state machine, including state definitions, state transition triggers, state transition conditions and state transition actions. Case-status states, a first filtering condition, and a count parameter that specifies a limit on a number of times within a time period in excess of which additional events with characteristics that match will be ignored or discarded are usable to determine whether to ignore or process an incoming event—throttling the rate at which certain actions occur. A workflow engine gets loaded with instructions derived from the states and event filtering conditions, for handling incoming machine-generated events. Once defined, the state machine is automatically generated and implemented based on the declarative input provided.