Transport Cabin Environment Control Using Occupant Behavior Modes
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Solution Overview
Problem
Existing transport systems lack automated adjustment of environmental settings based on occupant preferences, requiring manual or driver intervention for adjustments such as lighting, temperature, and seat positions.
Innovation Solution
A system utilizing a blockchain-based decentralized database to monitor occupant data, determine preferences, and adjust transport environments automatically based on destination, departure time, and occupant behavior using smart contracts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual or driver intervention is used to adjust environmental settings, then the occupant can control the environment, but the process is time-consuming and requires human intervention
Solution Approach 1:
The system performs preliminary actions by determining the occupant's destination and departure time before the occupant enters the transport. Environmental settings are pre-adjusted based on predicted occupant preferences and historical data, so that when the occupant arrives, the environment is already optimized for their needs without requiring real-time manual adjustment.
Solution Approach 2:
The transport system serves itself by automatically monitoring occupant behavior data, analyzing preferences, and adjusting environmental settings without human intervention. The system uses smart contracts on a blockchain to autonomously execute environmental adjustments based on detected occupant modes (e.g., work mode, relaxation mode), eliminating the need for manual control.
2Productivity
If environmental settings are adjusted manually, then the occupant has control, but the adjustment process is slow and inefficient
Solution Approach 1:
The system determines destination and departure time in advance, and pre-adjusts environmental settings before the occupant enters the transport. This eliminates the time loss associated with manual adjustment during the journey, as the environment is already optimized when the occupant boards.
Solution Approach 2:
The system continuously monitors occupant behavior data (e.g., eye tracking, posture, device usage) and uses this feedback to dynamically adjust environmental settings in real-time. This closed-loop feedback mechanism ensures the environment remains optimized without requiring manual intervention, significantly improving adjustment efficiency.
3Extent of automation
If the system monitors and analyzes occupant behavior data, then automated adjustment is achieved, but data processing complexity increases
Solution Approach 1:
The data processing system is segmented into modular components: data collection modules (sensors, cameras), data analysis modules (behavior pattern recognition), and execution modules (environmental control). Each module operates independently but communicates through standardized interfaces, reducing overall system complexity while enabling comprehensive automated adjustment.
Solution Approach 2:
A blockchain-based smart contract system acts as an intermediary between data collection and environmental control. The smart contracts automatically process occupant behavior data and execute environmental adjustments without requiring complex centralized processing, distributing the computational load and simplifying the overall system architecture.
Data Source
AI summary
An example operation may include one or more of monitoring, by a transport, data related to behavior of an occupant of the transport, determining, by the transport, a mode of the occupant based on the data, and adjusting, by the transport, an environment of the transport based on the mode of the occupant.