Elevator Dispatching With Passenger Preference Grouping
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Solution Overview
Problem
Elevator systems lack passenger control over multimedia content and passenger grouping, leading to negative ride experiences due to mismatched interests and content preferences.
Innovation Solution
An intelligent building system uses passenger identification to select and provide multimedia content and group passengers based on their preferences derived from social network data, optimizing content relevance and passenger pairing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If destination dispatching systems optimize service speed by assigning passengers to elevators using algorithms, then service efficiency is improved, but passenger choice and content relevance deteriorate
Solution Approach 1:
The elevator dispatching system dynamically adjusts between two modes: a first mode that optimizes for service efficiency using traditional algorithms, and a second mode that optimizes for passenger preference matching. The system can switch between modes based on real-time conditions such as elevator availability, passenger load, and time of day, allowing it to adapt the degree of optimization applied to different situations rather than using a fixed algorithmic approach
Solution Approach 2:
The system changes the optimization parameters used for elevator assignment based on the selected mode. In the first mode, parameters include waiting time, round trip time, and number of stops. In the second mode, parameters are shifted to prioritize passenger preference matching and content relevance. This parameter switching allows the system to balance efficiency and adaptability without requiring complete system redesign
2Device complexity
If pre-selected content is provided in elevators without regard to passenger identity, then system complexity is reduced, but content relevance and passenger satisfaction deteriorate
Solution Approach 1:
The system uses passenger identification data and preference profiles stored in the database to automatically select and provide relevant content without requiring manual intervention from building operators or complex real-time analysis. The elevator controller autonomously queries the database using passenger IDs and retrieves pre-configured content preferences, allowing the system to provide personalized content while maintaining relatively simple architecture
Solution Approach 2:
A database acts as an intermediary between the elevator control system and content delivery mechanism. The database stores passenger preference profiles and content metadata, allowing the controller to efficiently query and retrieve relevant content without direct complex processing. This intermediary layer simplifies the control logic while enabling personalized content delivery based on passenger identification
3Loss of time
If passengers are assigned to elevators based on optimization algorithms, then waiting time is reduced, but passenger grouping by preference deteriorates
Solution Approach 1:
The dispatching system dynamically adjusts between optimizing for service efficiency (reducing waiting time) and optimizing for passenger preference matching (grouping likeminded passengers). The system can switch between these optimization goals based on real-time conditions such as peak hours, elevator availability, and passenger load, allowing flexible balancing of time efficiency and social preferences without being locked into a single algorithmic approach
Data Source
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AI summary
The disclosure herein includes a method (200) for controlling elevators by an intelligent building system. The method (200) includes receiving, by the intelligent building system, elevator calls initiated by passengers (210). Each elevator call can include a passenger identification corresponding to a passenger initiating the elevator call. The method further includes procuring passenger preference information based on the passenger identifications in response to the elevator calls (220) and grouping the passengers with respect to the passenger preference information to produce passenger groups (233). The method further includes controlling the elevators to collect the passenger groups (240).