Acoustic Sump Pump Detection in Sewer Systems
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Solution Overview
Problem
Current methods for detecting and locating illegal sump pumps connected to public sewer systems are inefficient and do not provide accurate information necessary for precise location without additional equipment and labor.
Innovation Solution
A system and method that utilize audio data collected from sewer systems, analyzed using machine learning to detect sump pump sound signatures, and geolocation algorithms to accurately determine the location of illegal sump pumps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to detect and locate illegal sump pumps, then detection can be performed, but the methods are inefficient and do not provide accurate location information without additional equipment and labor
Solution Approach 1:
The patent replaces traditional mechanical detection methods with acoustic sensing technology. Audio sensors capture sound waves generated by sump pump operations, and signal processing algorithms analyze these acoustic signals to detect and locate illegal sump pumps. This substitution of mechanical inspection with acoustic field analysis improves detection efficiency and location accuracy while reducing the need for additional physical equipment and manual labor.
2Reliability
If audio data is collected and analyzed using machine learning to detect sump pump sound signatures, then detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system implements machine learning algorithms that automatically analyze audio data and identify sump pump sound signatures without requiring manual intervention or expert analysis. The automated detection system processes acoustic signals, extracts relevant features, and classifies them to detect illegal sump pumps. This self-service approach improves detection reliability while the automation actually reduces operational complexity despite the sophisticated algorithms involved.
Solution Approach 2:
The patent transforms physical acoustic parameters (sound frequency, amplitude, temporal patterns) into detectable electrical signals through audio sensors, then processes these signals through multiple parameter transformations including Fourier transforms and feature extraction. These parameter changes enable the system to convert complex acoustic information into actionable detection data, improving reliability through comprehensive signal analysis.
3Measurement precision
If geolocation algorithms are used to determine the location of illegal sump pumps, then location precision is improved, but computational requirements and processing time increase
Solution Approach 1:
The system pre-establishes a network of audio sensors at known locations throughout the sewer system, each with precisely recorded coordinates. When illegal sump pumps are detected, the system uses pre-computed algorithms to rapidly calculate locations based on sound propagation models and sensor network geometry. This preliminary setup of sensor positions and pre-computed detection algorithms enables fast geolocation processing without requiring complex real-time calculations, thus improving location precision while minimizing processing time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient detection and accurate location of illegal sump pumps, reducing unnecessary operational costs and wear and tear on sewer systems by providing precise information for authorized users.
Implementation Method 1
monitors the sounds travelling through the sewer system which are analyzed to detect illegal sump pumps
Data Source
AI summary
A system and a method for monitoring and detecting an illegal sump pump in a sewer system is used to accurately detect and locate sump pumps that are illegally connected to the sewer system. Actual audio profiles are collected and timestamped with audio-recording devices. The actual audio profiles from the audio-recording devices are relayed to the remote server. The remote server compares each actual audio profile to a baseline audio profile to identify at least one matching audio profile. If the matching audio profile is identified amongst the actual audio profiles, the remote server geolocates a potential location for an illegal sump pump based on the sewer location of the corresponding audio-recording device for the matching audio profile. The remote server compiles the potential location of an illegal sump pump into a summarization report. The sewer system is continuously monitored by executing several iterations of the overall process.