Dynamically Updatable Rules Engine for Real-Time Sensor Processing
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Solution Overview
Problem
Existing IoT devices face limitations in processing high volumes of sensor data due to complexity, leading to reduced transaction rates and inefficient management of sensor data, especially when computational resources are not co-located with sensors.
Innovation Solution
A dynamically updatable rules engine that selectively prioritizes the application of rules relevant to identified events and conditions, processing sensor data through a system comprising sensors, a data processing apparatus, and a dynamically updateable rules engine that optimizes rule evaluation based on operational relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a rules engine evaluates all rules for sensor data processing, then comprehensive coverage of event conditions is achieved, but processing speed decreases due to high transaction rates
Solution Approach 1:
The system performs preliminary actions by pre-evaluating and prioritizing rules based on event conditions before actual data processing occurs. Rules are ranked in advance according to their relevance and urgency, allowing the rules engine to execute only the most critical rules first when sensor data arrives, thus maintaining comprehensive coverage while improving processing speed.
Solution Approach 2:
The rules engine dynamically adjusts its behavior based on incoming sensor data and event conditions. Instead of statically evaluating all rules, the system dynamically prioritizes and selects which rules to execute based on the current context, ensuring that processing speed adapts to the complexity and urgency of each specific event while maintaining reliable coverage.
2Productivity
If computational resources are co-located with sensors, then real-time processing capability is improved, but system flexibility and deployment flexibility are reduced
Solution Approach 1:
The system segments the computational architecture into distributed components. The rules engine is separated from the sensors and can be deployed independently on different computational resources. This segmentation allows real-time processing capability to be maintained through efficient communication protocols while providing flexibility in deployment, as the rules engine can be co-located with sensors when needed or deployed remotely when flexibility is required.
Solution Approach 2:
An intermediary communication layer is introduced between sensors and computational resources. This intermediary enables efficient data transfer and rule evaluation regardless of physical proximity, allowing real-time processing capability to be maintained while providing deployment flexibility. The intermediary abstracts the physical location details, enabling the system to adapt to different deployment scenarios.
3Reliability
If complex rules are used to process sensor data, then management effectiveness is improved, but processing time increases
Solution Approach 1:
Complex rules are broken down into preliminary actions and prioritized steps. The rules engine evaluates and executes rules in a prioritized sequence, performing simple preliminary actions first and reserving complex rule evaluations for when necessary. This approach maintains management effectiveness through comprehensive rule coverage while reducing processing time by avoiding unnecessary complex evaluations for simple events.
Solution Approach 2:
The system dynamically adjusts the complexity of rule evaluation based on the specific sensor data and event conditions. For simple events, only simple rules are evaluated, minimizing processing time. For complex events requiring detailed analysis, the full complex rule set is evaluated, maintaining management effectiveness. This dynamic adaptation ensures optimal balance between processing speed and management effectiveness for each specific case.
Data Source
AI summary
A system for automatic and dynamic control of machine operations includes a connection to a machine external to the system; sensors configured and deployed to monitor an operation of the external machine and to generate sensor records; a sensor data processing apparatus configured and deployed to receive sensor records from the sensors, and to identify, based on the received sensor records, events and corresponding event conditions affecting an operation of the machine. The processing apparatus is further configured to identify a rule set that, when applied to the machine, alters the operation of the machine by the processing apparatus selectively prioritizing application of the rules to the machine by using only those rules that are operationally relevant to identified events and corresponding event conditions affecting the operation of the machine.