IoT Device Knowledge Graph for Real-Time Customer Service Diagnostics
Solution Overview
Problem
Existing online customer service systems lack the ability to precisely locate device-related problems in real-time and fail to automatically explore new knowledge paths, leading to inefficiencies and uncertainties in user interactions.
Innovation Solution
An IoT-based system that collects and stores real-time device status information, queries a device knowledge graph to identify issues, and provides solutions to users, supporting voice requests through recognition and semantic analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing online customer service systems use knowledge indexing and voice interaction, then user interaction capability is improved, but problem location accuracy deteriorates due to lack of real-time device status access
Solution Approach 1:
The patent introduces a knowledge graph as an intermediary layer between the user interaction interface and the device status data. The knowledge graph models device structures, fault patterns, and diagnostic rules, enabling the system to translate user descriptions into precise device status queries and automatically locate problems by matching real-time sensor data with known fault patterns.
Solution Approach 2:
The patent replaces the traditional mechanical approach of manual problem description and empirical diagnosis with an automated information processing system. The system substitutes human expert analysis with algorithmic processing of device status data, using the knowledge graph to automatically infer problems from sensor readings and device metadata without requiring user expertise.
2Device complexity
If existing systems rely on empirical knowledge and manual customer service, then system complexity is reduced, but productivity deteriorates due to limited service availability and high training costs
Solution Approach 1:
The patent implements a self-service diagnostic system where the knowledge graph automatically analyzes device status information and identifies problems without human intervention. The system autonomously queries device sensors, processes the data through diagnostic rules encoded in the knowledge graph, and provides troubleshooting guidance, eliminating the need for manual customer service representatives and enabling 24/7 service availability.
Solution Approach 2:
The patent performs preliminary action by pre-building the knowledge graph with device specifications, operational parameters, and fault diagnostic rules before deployment. This advance preparation of diagnostic knowledge enables the system to immediately analyze device status and locate problems without requiring real-time human expert input, significantly improving service response time and efficiency.
3Reliability
If existing customer service systems use manual intervention, then handling of complex cases is improved, but loss of time increases due to high flow rates and limited service hours
Solution Approach 1:
The patent implements a dynamic diagnostic system where the knowledge graph adapts its query strategies based on real-time device status data and the specific characteristics of each reported problem. The system dynamically adjusts its analysis depth and scope, automatically exploring relevant device components and parameters based on the knowledge graph's understanding of device architecture and fault patterns, thereby reducing unnecessary analysis steps and response time.
Data Source
AI summary
Disclosed are an Internet of Things (IoT) based method and system for interacting with users. The intelligent customer service system collects and stores real-time status information of at least one device in an IoT; receives a request of a user; queries a device knowledge graph according to content of the request, and invoke the real-time status information of a related IoT device to acquire a corresponding request result, wherein the device knowledge graph is established according to usage information and/or maintenance information of one or more IoT devices; and return the request result to the user.