Conference Room Presence Detection for Next-Available Booking

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Solution Overview

Problem

Conventional buildings lack automation, leading to inefficiencies and increased costs due to difficulties in locating resources such as parking spots and conference rooms, as well as inadequate security and energy management.

Innovation Solution

The implementation of a computer-implemented method and system for building automation, utilizing machine learning, computer vision, and artificial intelligence to detect room presence, manage resources, and enhance security through automated visitor check-in, multi-factor authentication, and real-time parking dispatch.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If conventional building management systems are used, then building operations can be maintained, but automation is lacking leading to inefficiencies in resource location, energy consumption, and security

Engineering Contradiction:
Improvebuilding management automationVSAvoidsystem complexity
Core Design Contradiction:
Extent of automationVSDevice complexity

Solution Approach 1:

The patent introduces a chatbot as an intermediary interface that connects users to building management functions. The chatbot handles user requests for room booking, parking space location, and other building services through natural language communication, eliminating the need for users to directly interact with complex building management systems while maintaining full automation capabilities.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The building management system is designed to perform multiple functions through a single integrated platform. The system simultaneously handles room presence detection, conference room booking, parking space management, lighting control, and security monitoring, allowing one system to replace multiple separate management tools and reduce overall complexity.

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Productivity

If machine learning models are deployed for room presence detection, then resource allocation is improved, but computing resources and system complexity increase

Engineering Contradiction:
Improveresource allocation efficiencyVSAvoidcomputing energy consumption
Core Design Contradiction:
ProductivityVSUse of energy by moving object

Solution Approach 1:

The system employs machine learning models selectively rather than continuously. The chatbot activates and processes requests only when users need building management services, such as booking rooms or locating parking spaces. This partial action approach maintains high resource allocation efficiency when needed while minimizing computing energy consumption during idle periods.

Inventive Principle:
Principle #16Partial or excessive action

3Ease of operation

If integrated building management functionality is added to communication platforms, then user experience is enhanced, but system complexity increases

Engineering Contradiction:
Improveuser experienceVSAvoidsystem integration complexity
Core Design Contradiction:
Ease of operationVSDevice complexity

Solution Approach 1:

The chatbot serves as an intermediary layer between the communication platform and the building management system. Users interact with familiar messaging interfaces while the chatbot translates these interactions into building management commands, handling the integration complexity on the backend while maintaining simplicity for end users.

Inventive Principle:
Principle #24Intermediary (Mediator)

Data Source

PatentUS12230136B2Room presence methods and systems
Publication Date: 2025.02.18 CDW LLC
  • US12230136B2 patent drawing
  • US12230136B2 patent drawing
  • US12230136B2 patent drawing

AI summary

A method for delegating conference rooms using room presence detection includes identifying a human in a digital image using a trained machine learning model; updating room presence information; and determining a next-available conference room. A room presence computing system includes a processor; and a memory storing instructions that, when executed by the processor, cause the system to: identify a human in a digital image using a trained machine learning model; update room presence information; and determine, by analyzing the room presence information, a next-available conference room. A non-transitory computer readable medium includes program instructions that when executed, cause a computer to: identify a human in a digital image using a trained machine learning model update room presence information; and determine, by analyzing the room presence information, a next-available conference room.