Automated Utility Issue Detection via Social Media and Weather Data
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Solution Overview
Problem
Utility service providers face challenges in efficiently identifying and responding to operational and customer issues due to reliance on manual, telephonic interactions, limited data sharing, and lack of utilization of social media and online news feeds for real-time issue detection and prediction.
Innovation Solution
An automated method that collects and filters data from online sources using keyword association, classifies utility issues, and provides actionable solutions, leveraging social media, news, and weather data to identify and respond to issues in real-time, regardless of language, and coordinates responses across various stakeholders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual telephonic interactions are used to identify and respond to utility issues, then human interaction and language understanding are improved, but processing time and operational costs increase
Solution Approach 1:
The patent replaces manual telephonic interactions with an automated computer-based system that collects data from multiple sources (social media, news feeds, weather data, utility systems) and uses natural language processing to identify and categorize utility issues. This substitution eliminates the need for human operators to manually process each customer call while maintaining the ability to understand and respond to customer needs through automated text analysis.
Solution Approach 2:
The system enables self-service by automatically monitoring and analyzing data from diverse sources to identify utility issues without requiring human intervention. The computer-based system autonomously processes information from social media posts, news feeds, and weather data to detect outages, service disruptions, and customer concerns, then automatically generates notifications and responses.
2Reliability
If proprietary data formats are used for outage data, then data security and control are improved, but data sharing and coordination with third parties deteriorate
Solution Approach 1:
The patent creates a universal data collection and processing system that can handle multiple data formats and sources simultaneously. The computer-based system is designed to ingest, standardize, and process data from diverse proprietary formats including social media platforms, news feeds, weather services, and utility systems, converting them into a common format that enables seamless sharing and coordination among utility providers, first responders, and other stakeholders while maintaining data integrity.
3Device complexity
If traditional OMS tools with GIS-based guessing are used to predict outages, then system infrastructure is utilized, but prediction accuracy in dynamic environments deteriorates
Solution Approach 1:
The patent implements preliminary action by continuously collecting and analyzing data from multiple external sources (social media, news feeds, weather services) before outages occur. The system monitors real-time conditions and identifies potential issues by detecting patterns and anomalies in the data, enabling early warning and prediction of outages before they impact customers, thus improving prediction accuracy beyond traditional GIS-based methods.
Solution Approach 2:
The system incorporates feedback mechanisms by continuously monitoring data from diverse sources and using this information to refine and improve prediction accuracy. The computer-based system analyzes patterns in social media posts, news reports, and weather data to learn from past events and adjust prediction models, creating a feedback loop that enhances the accuracy of outage predictions in dynamic environments.
Data Source
AI summary
An automated method of customer engagement and issue location, prediction, and response that utilizes disparate data sources including social media, weather, news, real estate information, customer account information, and/or asset information to locate and categorize issues, to predict the occurrence of such issues, and to determine/automate operational and customer-related responses to such issues.