Neuromorphic Experiential System for Sensor Data Analysis
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Solution Overview
Problem
Distributed sensor systems face challenges in data collection due to divergent sensor behaviors, network latency, and intermittent network availability, making it complex to analyze sensor data across multiple sources effectively.
Innovation Solution
A neuromorphic experiential analysis system that utilizes a Communitive Replicated Data Type (CRDT) protocol for sensor and data communication, combined with software transformers for Change Data Capture and hardware transformers for physical sensor systems, to convert sensor emissions into a unified format for processing and storage in an episodic memory inspired by human memory, enabling efficient data processing and storage across various platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If distributed sensor systems are used to collect data from multiple sources, then data coverage and monitoring capability are improved, but system complexity and difficulty of data analysis increase due to divergent sensor behaviors and network issues
Solution Approach 1:
The patent segments the distributed sensor system into independent modular units, each capable of autonomous operation and data processing. Sensors are organized into discrete functional blocks that can be individually managed, reducing overall system complexity while maintaining broad coverage.
Solution Approach 2:
The patent introduces intermediary components including event sources, event stores, and query processors that act as mediators between diverse sensors and analysis systems. These intermediaries standardize data formats and behaviors, enabling seamless integration of multiple sensor types without increasing complexity.
2Reliability
If data is collected from multiple distributed sensors with different output rates and behaviors, then monitoring capability is improved, but data processing complexity increases
Solution Approach 1:
The patent implements a universal event store and query processing system that can handle multiple sensor types, output rates, and data formats through a single standardized interface. This multi-functional architecture processes diverse sensor data uniformly, improving monitoring capability without proportionally increasing processing complexity.
Solution Approach 2:
The patent dynamically adjusts processing parameters such as sampling rates, buffer sizes, and query thresholds based on sensor characteristics and data importance. This adaptive parameter adjustment optimizes processing efficiency for different sensor types while maintaining reliable monitoring across all sources.
3Speed
If real-time sensor data processing is implemented, then responsiveness is improved, but computational resource requirements and system complexity increase
Solution Approach 1:
The patent implements periodic event processing and batch query execution mechanisms that balance real-time responsiveness with computational efficiency. Events are processed at optimized intervals based on their urgency and importance, reducing continuous computational overhead while maintaining appropriate responsiveness.
Solution Approach 2:
The patent applies partial processing strategies where only critical or high-priority sensor events trigger full processing pipelines, while less important events receive simplified or deferred processing. This selective approach maintains responsiveness for important events without requiring full computational resources for all data.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for neuromorphic experiential analysis of sensor data. The methods, systems, and apparatus include actions of obtaining sensor emissions from multiple sensors, generating monotonic data that indicates an orientation of the sensor emissions in respect to time, determining that the monotonic data matches a registered query, and in response to determining that the monotonic data matches a registered query, invoking an executor.