Dynamic Location Guidance for Interior Density Management
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Solution Overview
Problem
Conventional remote appointment scheduling applications fail to account for interior conditions and social distancing requirements at locations offering both automated and in-person services, leading to overcrowding and inefficiencies, especially during the COVID-19 pandemic.
Innovation Solution
A system that provides location-based guidance based on interior density conditions, recommending locations with lower user density for services by retrieving and analyzing queuing area densities across multiple locations and adjusting recommendations in real-time to ensure social distancing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional remote appointment scheduling applications are used to schedule appointments, then users can book services in advance, but the system cannot account for interior conditions and social distancing requirements leading to overcrowding
Solution Approach 1:
The system continuously monitors interior conditions (density, wait times, service status) at locations and uses this feedback to dynamically adjust appointment recommendations and real-time guidance, allowing the scheduling system to respond to actual conditions rather than relying solely on static appointment bookings
Solution Approach 2:
The patent introduces an intermediary layer between the appointment scheduling application and the physical location that monitors and reports interior conditions, enabling the system to mediate between scheduled appointments and actual service capacity to prevent overcrowding
2Adaptability or versatility
If users visit locations with mixed automated and in-person services, then users can access multiple service types, but different social distancing requirements create complexity in managing user flow
Solution Approach 1:
The system segments users into different groups based on their service needs (automated vs. in-person) and assigns them to appropriate queues and locations, managing social distancing by separating user flows rather than mixing them, while still providing access to all service types
3Productivity
If conventional appointment systems are used, then users can schedule services, but walk-in users and users arriving outside appointment windows cause increased queuing and social distancing issues
Solution Approach 1:
The system transitions from static appointment scheduling to dynamic real-time guidance that adapts to current conditions at locations, allowing users to be directed to appropriate services based on live density data and service availability rather than fixed time slots, thereby reducing wait times for walk-in users
Data Source
AI summary
Methods and systems are discussed for location-based guidance based on interior conditions at a plurality of locations. For example, the system may receive, from a user device of a user, a user request to access a first service. The system may retrieve a plurality of locations that provide the first service. The system may retrieve an average density for respective first queuing areas at each of the plurality of locations at a first time interval. The system may, in response to determining a subset of the plurality of locations where the average density for the respective first queuing areas at the first time interval exceed the threshold average density, generate for display, on the user device, a recommendation for a location from the subset at which to access the first service at the first time interval.