AI-Powered Digital Solution for Utility Marketing Services: Integrating Image Recognition and Intelligent Response Systems
Description: Patent No.: ZL 2021 1 0970658.5、ZL 202110970659.X、ZL 202110969030.3、ZL 2021 1 0970622.7、ZL 202110970634.X
Introduction： This invention develops a set of AI-based intelligent front-end operation assistance tools for the electricity marketing business domain. Through image recognition, voice interaction, and other methods, it realizes functions such as text information recognition (e.g., business licenses), voice recording of on-site marketing operations, and intelligent line loss investigation. This further extends intelligent capabilities to the field to assist or replace manual operations, enhancing human-machine collaboration and comprehensively elevating the specialization, standardization, informatization, and intelligence levels of grassroots power supply offices. I. Novelty and Practicality 1.Novelty This project demonstrates significant innovation in the integration of technology application and business scenarios, mainly reflected in the following aspects: 1.1 Technological Integration Innovation: The project deeply integrates image recognition, speech recognition, and intelligent response technologies, constructing a complete "perception-understanding-response" intelligent closed loop for electricity marketing operations within power supply offices for the first time. For example, dedicated OCR algorithms (e.g., combining Faster R-CNN and YOLOv3 object detection techniques) were developed for industry-specific documents like certificates and forms, addressing the pain points of low accuracy and insufficient structured output of generic OCR in power business scenarios. For voice interaction, the BERT-BiLSTM-CRF model is used for entity relationship extraction in the power domain, optimized with a self-built industry corpus, significantly improving the precision of semantic understanding. 1.2 Business Scenario Innovation: Traditional electricity marketing operations rely heavily on manual processes, suffering from issues like redundant data entry and inconsistent standards. This project automates business process restructuring through intelligent tools (e.g., intelligent line loss investigation, intelligent response for business expansion). For instance, the transformer area line loss rate anomaly investigation application uses AI algorithms to analyze line loss distribution and automatically generates loss reduction plans, filling an industry gap in intelligent line loss management. 1.3 Intellectual Property Layout: The project has applied for 7 invention patents (e.g., "An Intelligent Interaction Method and Device Applicable to Voice Information", "An OCR Classification Method and System"), covering core algorithms and application scenarios to establish technical barriers. Among these, the multi-model fusion method for power entity recognition and the end-to-end relationship extraction technology based on attention mechanism are industry firsts. 2. Practicality The project has been piloted at Zhaoqing Power Supply Bureau of Guangdong Power Grid, verifying its efficiency and scalability: Efficiency Improvement: In the intelligent business expansion review scenario, document recognition accuracy increased from 70% (using generic OCR) to 95%, reducing single transaction processing time from 40 minutes to 15 minutes. During the pilot of the transformer area line loss investigation application, line loss anomaly localization efficiency improved by 60%, saving approximately 1.2 million yuan in annual labor costs. Standardization and Normalization: Through unified data models and intelligent review rules, data error rates caused by manual operations were reduced (data consistency improved by 80% during the pilot), enabling cross-system linkage of marketing and distribution network business data. User Experience Optimization: The intelligent response system supports natural language interaction, reducing average customer inquiry response time from 5 minutes to real-time feedback, increasing customer satisfaction to 98%.
Organisation: Guangdong Power Grid Corporation Zhaoqing Power Supply Bureau
Innovator(s): Wu Yanfang, Zhang Yincui, He Junchi, Chen Guansheng, Liang Zhiyong, Jiang Nan; Zhaoqing Power Supply Bureau, Guangdong Power Grid Co., Ltd.
Category: Information Technology, AI and ML
Country: China