SYSTEM AND METHOD FOR AIR QUALITY MONITORING THROUGH REINFORCEMENT LEARNING
The system addresses HVAC inefficiencies by using reinforcement learning to manage air quality and reduce CO2 levels through optimized airflow, enhancing safety and energy efficiency in vehicles.
DE102024137802A1Pending Publication Date: 2026-06-11MERCEDES BENZ GROUP AG
Patent Information
- Authority / Receiving Office
- DE · DE
- Patent Type
- Applications
- Current Assignee / Owner
- MERCEDES BENZ GROUP AG
- Filing Date
- 2024-12-14
- Publication Date
- 2026-06-11
AI Technical Summary
Technical Problem
Existing HVAC systems in vehicles fail to provide comprehensive management of air quality, leading to increased CO2 concentrations that impair occupant health and efficiency, and consume excessive energy when switching to fresh air mode.
Method used
A system using reinforcement learning to monitor air quality by adjusting airflow through a dual-head hybrid neural network, optimizing flap angles to minimize energy consumption and maintain safe CO2 levels.
Benefits of technology
Reduces CO2 concentration and energy consumption by implementing partial air recirculation, ensuring occupant safety and comfort through precise airflow control.
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Smart Images
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Abstract
The present disclosure provides a system (106) and a method (800) for air quality monitoring using reinforcement learning. The system (106) receives one or more parameters associated with the environment of the vehicle (102) and one or more occupants of the vehicle (102). The system (106) determines a state of the environment based on the one or more parameters. Using a reinforcement learning technique, the system (106) calculates a required amount of airflow into the environment for a predetermined period under one or more predetermined time intervals based on the determined state. The system (106) then generates the required amount of airflow for the predetermined period using the reinforcement learning technique based on a variation of the state, thus providing safety for one or more occupants of the vehicle (102).
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