Utility Bill Resolution With Peak-Shaving Consumption Scheduling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional utility bill management systems in industrial environments are inadequate for handling complex billing structures, manual data entry leads to inefficiency and errors, and lack real-time analysis capabilities for ToD pricing and peak shaving strategies, leading to overpayment, compliance issues, and missed cost-saving opportunities.
Innovation Solution
A utility bill resolution system and consumption optimization system that automate bill detection, parsing, anomaly detection, and optimization using machine learning models, integrating real-time consumption data and sophisticated monitoring to ensure accuracy and cost-effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual data entry is used for utility bill management, then system complexity is reduced, but efficiency and accuracy deteriorate due to inefficiency and errors
Solution Approach 1:
The patent replaces manual mechanical data entry operations with automated optical character recognition (OCR) and image processing systems. The system captures utility meter images, automatically extracts numerical readings through OCR technology, and processes billing information without human intervention, thereby eliminating the trade-off between simplicity and efficiency.
Solution Approach 2:
The system enables self-service automation where the utility bill management system automatically detects, extracts, and processes billing data from images. The automated system serves itself by performing data entry, validation, and anomaly detection without requiring manual operation, resolving the contradiction between system simplicity and operational efficiency.
2Extent of automation
If manual data entry is used for utility bill management, then automation resources are reduced, but accuracy deteriorates due to errors
Solution Approach 1:
The patent implements feedback mechanisms where the system validates extracted data against expected patterns, ranges, and historical information. Anomaly detection algorithms provide feedback to identify potential errors in automated extraction, and the system can flag or correct inconsistencies, thereby maintaining high accuracy while utilizing automation.
Solution Approach 2:
The system performs preliminary validation and anomaly detection during the automated extraction process itself, rather than relying on post-processing manual review. By built-in verification steps that check data consistency and detect anomalies before final processing, the system ensures high accuracy while maintaining automation.
3Loss of energy
If real-time analysis capabilities are added for ToD pricing and peak shaving strategies, then cost-saving opportunities are improved, but device complexity worsens
Solution Approach 1:
The patent integrates multiple functions into a single unified system: image capture, OCR processing, data extraction, anomaly detection, and energy optimization analysis all occur within one system. This multi-functionality enables real-time analysis for time-of-day pricing and peak shaving strategies without requiring separate complex systems for each function.
Solution Approach 2:
The system merges billing management and energy optimization functions into an integrated platform. By combining utility bill processing with real-time consumption analysis and optimization recommendations, the system achieves cost-saving capabilities through a unified architecture rather than separate systems, managing complexity through integration.
4Productivity
If automated bill detection and parsing are implemented, then productivity is improved, but device complexity worsens
Solution Approach 1:
The patent segments the automated bill processing system into distinct functional modules: image capture module, OCR processing module, data extraction module, validation module, and anomaly detection module. This segmentation allows each component to perform its specific function independently, improving overall productivity while managing complexity through modular design that can be implemented and maintained separately.
Data Source
AI summary
Approaches for managing utility bills and optimizing utility consumption in industrial environments are described. A utility bill resolution system automates extraction, parsing, analysis, and resolution of utility bills from utility providers. The system detects anomalies within bills using machine learning models and verifies bill authenticity using real-time consumption data. A utility consumption optimization system analyzes historical consumption data and utility rate information to generate optimized operation schedules for utility-intensive equipment and processes. The optimization system considers time-of-day pricing structures and implements peak shaving strategies to reduce costs. Both systems leverage advanced technologies including optical character recognition, natural language processing, and Internet of Things (IoT) devices to enhance accuracy and efficiency. The integrated approach enables industrial consumers to ensure billing accuracy, proactively optimize utility consumption patterns, and achieve significant cost savings while improving operational efficiency across multiple utility consumption sites.