Local Data Processing Monitor Device for Utility Systems
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Solution Overview
Problem
Existing monitoring systems for utility systems, such as water distribution, rely heavily on cloud-based services for data processing, which can lead to network dependency, increased processing loads, and reduced autonomy, especially during connectivity issues or high processing demands.
Innovation Solution
A monitor device that performs local data processing by receiving sensor data, comparing it to parameter data stored locally, and taking actions autonomously, such as sending notifications or controlling system responses, without relying on continuous network connectivity to a remote service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If cloud-based services are used for data processing, then centralized analysis capability is improved, but network dependency increases and processing speed decreases
Solution Approach 1:
The patent divides the data processing system into two segments: local processing at the monitor device for real-time anomaly detection, and centralized cloud processing for aggregate analysis and parameter updates. This segmentation allows the system to maintain centralized analysis capabilities while reducing network dependency for time-critical operations.
Solution Approach 2:
The system performs preliminary data processing and anomaly detection locally at the monitor device before potentially transmitting data to the cloud. This preliminary action enables the system to respond to anomalies immediately without waiting for cloud processing, thereby reducing network dependency while maintaining centralized analysis capabilities.
2Reliability
If all data processing is performed locally, then network independence is improved, but processing power requirements increase
Solution Approach 1:
The monitor device performs only essential processing locally - comparing sensor data against stored parameters to detect anomalies. More computationally intensive tasks such as aggregate data analysis, parameter optimization, and long-term trend analysis are performed in the cloud. This partial local action achieves network independence for critical functions without requiring excessive local processing power.
3Loss of information
If sensor data is transmitted to remote services, then centralized analysis is improved, but network bandwidth usage increases
Solution Approach 1:
The system extracts only the essential anomaly detection function to be performed locally, transmitting only anomaly events and aggregated statistics to the cloud rather than all raw sensor data. This extraction approach maintains centralized analysis capability for aggregate data while minimizing network bandwidth consumption.
Solution Approach 2:
The monitor device performs preliminary filtering and aggregation of sensor data locally, transmitting only relevant anomaly information and summarized statistics to the cloud service. This preliminary processing reduces the volume of data requiring network transmission while preserving the ability to perform centralized aggregate analysis.
Data Source
AI summary
A monitor device is configured to monitor a system, such as a utility system and/or appliance. The monitor device includes sensor(s) that measure characteristic(s) of the system, and data storage that stores parameter data that is provided from a remote service. The parameter data includes thresholds, signatures, and/or other information that describes a typical operational state of the system. The monitor device includes software that executes locally to compare current sensor data to the parameter data and determine whether the current operational state of the system is within the bounds of the typical state as defined by the parameter data. In instances where the current state is atypical, indicating a possible problem with the system, a notification can be sent describing the anomaly. The monitor device can also perform other action(s) to correct the problem or mitigate possible damage, and can operate autonomously if a network connection is unavailable.