Behavior-Aware Chatbot Conversation Using Sensors and State Machines
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Solution Overview
Problem
Conventional chatbots lack the ability to actively provide human-computer interaction and fail to engage in meaningful conversations without user input.
Innovation Solution
An active chatbot system with behavioral awareness and on-demand conversation, utilizing sensors to sense physiological states, facial expressions, and body movements, combined with a server-end host that generates precise question messages through finite state machines and a large language model to provide tailored responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional chatbot uses passive chat mode to reply only when user asks questions, then system complexity is low, but the chatbot cannot actively provide human-computer interactive chatting
Solution Approach 1:
The system performs preliminary actions by continuously sensing user behavior states (physiological state, facial expressions, body movements) and pre-generating potential conversation topics based on browsing records and user profiles before the user initiates a conversation. This allows the chatbot to be ready to engage actively when appropriate moments arise.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring user behavior states through sensors and using this information to adjust conversation strategies. The chatbot receives feedback from user responses and modifies its active conversation approach accordingly, creating a closed-loop system that improves over time.
2Extent of automation
If conventional chatbot uses browsing records to actively ask questions, then the chatbot can actively reply messages, but the interactive manner is rigid and not humanized
Solution Approach 1:
The system changes parameters by incorporating multiple dimensions of user state information (physiological state, facial expressions, body movements) in addition to browsing records. This multi-parameter approach enables the chatbot to adjust conversation tone, timing, and content to match the user's current emotional and physical state, making interactions more natural and humanized.
Solution Approach 2:
The system applies dynamics by making conversation behavior adaptive and flexible rather than static and rigid. The chatbot dynamically adjusts its active conversation strategies based on real-time user behavior state changes, allowing it to respond naturally to different situations and maintain humanized interaction throughout the conversation.
3Measurement precision
If the chatbot continuously monitors user behavior through sensors, then behavioral awareness is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic action by continuously sensing user behavior states through sensors and periodically processing this information to generate conversation topics. Rather than continuously processing all sensor data in real-time, the system samples user behavior at appropriate intervals and triggers conversation generation based on significant state changes or predefined time intervals, reducing energy consumption while maintaining behavioral awareness.
Data Source
AI summary
An active chatbot system with behavioral awareness and on-demand conversation and a method thereof are disclosed. In the active chatbot system, a client-end host continuously senses a client behavior state, and transmits the sensed client behavior state and an on-demand conversation setting to a server-end host to generate a rough question message having a natural language structure, and input the rough question message to a plurality of finite state machines to generate a precise question message. The server-end host transmits the precise question message to an artificial intelligence platform to obtain a corresponding answer message, stores the answer message to an answer list, filters out an answer message matching the on-demand conversation setting as an on-demand conversation message, transmits the on-demand conversation message to the client-end host for output. Therefore, the technical effect of improving human-computer interaction and initiative of chatbot can be achieved.