Utility Usage Profiling for Abnormal Consumption Detection
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Solution Overview
Problem
Existing systems lack an efficient method to monitor and manage utility usage patterns, leading to potential misuse or equipment malfunctions, as they fail to detect abnormal usage and respond accordingly.
Innovation Solution
A network device compiles historical and current usage data to generate profiles, compares them to determine abnormal usage, and triggers actions such as deactivation or notifications based on predefined thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing systems monitor utility usage without dynamic profile updates, then system simplicity is maintained, but detection precision of abnormal usage deteriorates
Solution Approach 1:
The system dynamically updates usage profiles by comparing historical usage data with current usage patterns. The profile evolves over time to adapt to changing normal usage behaviors, enabling the system to detect abnormalities more accurately without requiring manual reconfiguration or complex threshold settings.
2Speed
If the system responds immediately to threshold exceedances, then response speed is improved, but reliability deteriorates due to false alarms from temporary spikes
Solution Approach 1:
The system performs preliminary analysis by comparing current usage against dynamically updated profiles that incorporate historical patterns. This preliminary assessment distinguishes between temporary spikes and genuine abnormalities, allowing the system to respond only to confirmed issues and avoid false alarms while maintaining rapid response times.
3Measurement precision
If comprehensive usage data is collected and analyzed, then detection accuracy is improved, but loss of time in data processing increases
Solution Approach 1:
The system extracts only the essential features from comprehensive usage data that are relevant for detecting abnormalities. By focusing on key patterns and deviations from the dynamic profile rather than processing all raw data, the system maintains high detection accuracy while significantly reducing processing time and computational resources required.
Data Source
AI summary
The present disclosure relates to using sensors and measurements from sensors to trigger actions within a network. Specifically, various techniques and systems are provided for measuring usage or measurements, using sensors, of utilities or other environmental factors, generating profiles based on the usage or measurements, and triggering actions within a network device based on the usage, measurements and profiles. Embodiments of the present invention may include, for example, compiling historical usage based on the use or measurements detected by a network device and generating a usage profile based on that use or measurements. The normal usage profile may be compared with the usage over a certain predetermined period of time to detect any abnormal use or measurements from the network device, and an action may be taken as a result of an abnormality.