Unified Events Framework for IoT Anomaly Detection
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Solution Overview
Problem
Current IoT systems lack an efficient mechanism for processing and managing timeseries data from IoT networks, particularly in identifying anomalies and generating customized events and workflows to react to changes in these environments.
Innovation Solution
A unified events framework is introduced that allows for the definition and configuration of customized events, tasks, requests, and event workflows, enabling the processing of timeseries data by receiving data from IoT networks, applying rule sets to detect anomalies, and generating events with customizable configurations, which can transition through states and send responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a unified events framework is implemented to enable customized event processing and anomaly detection in IoT systems, then the system's ability to monitor and react to changes is improved, but the device complexity increases due to the need for managing event configurations, rule sets, and workflow transitions
Solution Approach 1:
The patent introduces an event framework as an intermediary layer between raw IoT data and application responses. This framework includes event subscriptions, rule engines, and workflow managers that mediate the processing of timeseries data, enabling sophisticated anomaly detection without requiring complex logic in individual applications or devices.
Solution Approach 2:
The system segments event processing into distinct modular components: event subscriptions that define what to monitor, rule sets that determine anomaly conditions, event workflows that manage state transitions, and event responses that handle outcomes. This segmentation allows each component to be independently configured and managed, reducing overall system complexity.
2Adaptability or versatility
If customized event configurations and industry-specific workflows are added to handle diverse IoT scenarios, then the adaptability of the system is improved, but the ease of operation deteriorates due to the increased complexity of configuring and managing events
Solution Approach 1:
The event framework provides universal, reusable components that can be applied across different industries and use cases. Event subscriptions, rule templates, and workflow patterns are designed to be generic yet configurable, allowing the same framework to handle diverse IoT scenarios from manufacturing to healthcare without requiring complete customization.
Solution Approach 2:
The system provides pre-configured event templates, rule sets, and workflow patterns that can be deployed immediately for common scenarios. Users can start with predefined configurations and then customize them as needed, rather than building everything from scratch, which significantly reduces the operational complexity for new deployments.
Data Source
AI summary
Methods, systems, and computer-readable storage media for detecting and managing events from data of an Internet-of-Things (IoT) network, and actions can include receiving a first call from a first application, the first call including timeseries data from one or more IoT devices in a first IoT network, retrieving a rule set for processing the timeseries data, and determining that an anomaly is represented in the timeseries data based on the rule set, and in response, generating an event, the event having a configuration that is customized by an enterprise associated with the first application, executing an event workflow to transition the event between states, and transmitting an event response to the first application.