Conversational Facility Monitoring Bot for Building System Control
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Solution Overview
Problem
Current building maintenance systems require intensive training and rely on skilled labor, leading to high operational costs and a high attrition rate, while also lacking efficient data analytics and easy interaction with building systems for facility managers and owners.
Innovation Solution
A bot framework with a reusable voice- and chat-based engine that interacts with supervisory systems, utilizing machine learning and cognitive analytics to predict user behavior and provide real-time data and control, reducing the need for multiple apps and minimizing training costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a traditional BMS system with multiple screens and dashboards is used, then comprehensive building monitoring is achieved, but intensive training is required and operational costs increase
Solution Approach 1:
A chatbot intermediary is introduced between the user and the complex BMS system. The chatbot translates natural language queries into system commands and presents information in an easily digestible format, eliminating the need for users to navigate complex dashboards or undergo intensive training while maintaining full access to building monitoring capabilities.
Solution Approach 2:
The patent replaces the mechanical interaction model (navigating physical or graphical interfaces with multiple screens and dashboards) with a natural language processing system. Users can query building systems using conversational language, and the chatbot processes these queries through NLP to retrieve and present relevant information, significantly reducing the operational complexity.
2Reliability
If skilled labor is used for facility management, then system operation reliability is improved, but operational costs and attrition rate increase
Solution Approach 1:
The chatbot system enables facility management operations to be performed through automated natural language interactions, reducing dependency on highly skilled human operators. The system handles routine monitoring and control tasks autonomously, allowing less trained staff to effectively manage building systems while maintaining operational reliability.
Solution Approach 2:
The system incorporates feedback mechanisms where the chatbot continuously learns from user interactions and system responses, improving its ability to handle complex facility management tasks. This feedback loop enables the system to progressively reduce its dependency on skilled human intervention while maintaining or improving operational reliability.
3Adaptability or versatility
If multiple apps are used for building system interaction, then comprehensive control is achieved, but system complexity and training requirements increase
Solution Approach 1:
The chatbot is designed as a universal interface that can handle multiple building system control functions through a single platform. It can query HVAC systems, lighting, security, and other building systems using natural language, consolidating the functionality of multiple specialized apps into one versatile tool that reduces overall system complexity.
Data Source
AI summary
A self-guided robot (bot) mechanism. An example bot may have a channel having an input for users, a cloud platform connected to the channel, a bot framework connected to the cloud platform, a web services module connected to the bot framework, and one or more drivers connected to the web services module. The one, the bot framework, the web services module and the drivers may be electronic hardware devices that effect their respective functions with a level of software managed and manipulated by the devices according to their respective algorithms.