Distributed edge computing architecture of emotion cockpit and intelligent cockpit

Through the distributed edge computing architecture, low latency, privacy protection and efficient computing of the on-board emotion recognition system are achieved, and the problems of privacy leakage, high latency and high computing resource demand in the existing technology are solved, and personalized emotional response strategies are provided to improve driving safety and user experience.

CN120449132APending Publication Date: 2025-08-08SHANGHAI PUFAFEN ELECTRONIC TECH CO LTD
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Patent Information

Application Number
CN202510566052.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-30
Publication Date
2025-08-08

AI Technical Summary

Technical Problem

The existing on-board emotion recognition system has problems such as insufficient privacy protection, high delay and high demand for computing resources. It is especially difficult to achieve real-time feedback in emergency driving scenarios, and the multimodal data fusion algorithm cannot adapt to the emotional recognition needs of different users or environments.

Method used

The distributed edge computing architecture is adopted, including the local edge node layer, the regional coordination point layer and the central control unit layer, and the acquisition, fusion and policy response of multimodal emotional data are achieved through low-latency communication interfaces. The original data is preprocessed locally and only structured results are uploaded. Combined with a lightweight model and a modal fusion mechanism, it supports the generation of personalized emotional response strategies.

Benefits of technology

Effectively protect occupant privacy, reduce system delays, improve the efficiency and consistency of multimodal data fusion, realize personalized emotional soothing and guidance, and improve driving safety and user experience.

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Abstract

The invention provides a distributed edge computing architecture of an emotion cockpit and an intelligent cockpit, and the distributed edge computing architecture comprises a local edge node layer, a regional coordination node layer and a central control unit layer which are connected through low-delay communication interfaces, and cooperatively achieve the collection, fusion, judgment and strategy response of multi-modal emotion data. Wherein the local edge node layer comprises a plurality of intelligent terminals deployed near passengers in a vehicle, and each terminal comprises a modal sensing module and a feature extraction module; the area coordination node layer comprises a plurality of area processing units, and each unit comprises an area fusion module; the central control unit layer comprises an emotion map module, an emotion decision module and a strategy response module. By adopting an edge-region-center three-level collaborative architecture, the method has low delay, high robustness and privacy protection capability, can realize emotion-driven in-vehicle environment intelligent linkage control, and improves driving safety and user experience.
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