AI Charging Pile Monitoring for Early Hazard Detection

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Solution Overview

Problem

Existing charging pile safety systems fail to provide timely early warnings for environmental hazards at unmanned public charging stations, leading to potential serious accidents.

Innovation Solution

A monitoring system for charging piles that utilizes an image capture module and artificial intelligence to analyze environmental images, detecting abnormal conditions and controlling the power module accordingly.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional power detection systems are used for charging pile safety monitoring, then the system structure remains simple, but the system cannot detect environmental hazards such as fire, collision, or other safety threats

Engineering Contradiction:
Improvesafety monitoring capabilityVSAvoidsystem structure
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent combines multiple monitoring functions (power detection, environmental monitoring via image capture, and AI analysis) into an integrated charging pile safety monitoring system. The control module coordinates all subsystems including image capture modules, power detection systems, and communication modules to work together, achieving comprehensive safety monitoring while managing system complexity through unified control.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The charging pile safety monitoring system is designed to perform multiple functions: detecting power anomalies, capturing environmental images, analyzing safety threats using AI, and communicating warnings. This multi-functional approach allows a single system to address various safety hazards (fire, collision, theft, etc.) rather than requiring separate dedicated systems for each threat.

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Measurement precision

If AI-based image analysis is implemented for environmental hazard detection, then detection accuracy and speed improve, but system complexity and computational requirements increase

Engineering Contradiction:
Improvehazard detection accuracyVSAvoidcomputational complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by continuously capturing environmental images and pre-processing them through AI analysis before actual hazards fully develop. The control module is configured to analyze images in real-time during charging operations, identifying potential threats (smoke, fire, collision) at early stages when they can still be prevented or mitigated.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary communication module that bridges the AI analysis process and the control actions. This module receives analysis results from the control module and transmits warnings to external devices or authorities, simplifying the overall system architecture by creating a dedicated communication layer that handles the complexity of data transmission and alert generation.

Inventive Principle:
Principle #24Intermediary (Mediator)

3Loss of time

If real-time monitoring and early warning systems are deployed at public charging stations, then safety response time improves, but operational costs and system resource requirements increase

Engineering Contradiction:
Improveresponse timeVSAvoidsystem energy consumption
Core Design Contradiction:
Loss of timeVSUse of energy by stationary object

Solution Approach 1:

The system implements periodic action by continuously capturing images at scheduled intervals during the charging process rather than attempting constant uninterrupted monitoring. The control module is configured to capture environmental images at specific moments (e.g., periodically during charging sessions), which reduces computational load and energy consumption while still maintaining effective real-time monitoring capabilities.

Inventive Principle:
Principle #19Periodic action

Solution Approach 2:

The patent incorporates feedback mechanisms where the system continuously monitors charging conditions and adjusts its monitoring intensity based on detected anomalies. When the system detects normal charging conditions, it maintains standard monitoring levels; when anomalies are detected (through power detection or image analysis), the system increases monitoring frequency and triggers warning protocols, optimizing energy usage based on actual safety needs.

Inventive Principle:
Principle #23Feedback

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

Enhances detection speed and accuracy of environmental hazards, preventing larger accidents by taking proactive actions at the initial stages of abnormal situations.

Implementation Method 1

an image capture module, configured to capture at least one environmental image signal related to the electric vehicle

Methodology Applied
Scientific EffectImage capture: Photography

Implementation Method 2

a control module, coupled to the image capture module, configured to apple an artificial intelligence technology to analyze the at least one environmental image signal, to generate an analysis result

Methodology Applied
Scientific EffectArtificial intelligence image analysis: Image Processing

Data Source

PatentEP4678465A1Monitoring system and method for charging pile
Publication Date: 2026.01.14 CARININTERNATIONALCO LTD
  • EP4678465A1 patent drawingFigure 1
  • EP4678465A1 patent drawingFigure 2
  • EP4678465A1 patent drawingFigure 3A

AI summary

A monitoring system (1), for a charging pile (2), wherein the charging pile (2) charges an electric vehicle (3) through a power module (20), includes an image capture module (10), configured to capture at least one environmental image signal (IMG) related to the electric vehicle (3); and a control module (16), coupled to the image capture module (10), configured to apple an artificial intelligence technology to analyze the at least one environmental image signal (IMG), to generate an analysis result, and control the power module (20) according to the analysis result.