User Feedback System for Delivery Devices
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Solution Overview
Problem
Current delivery devices, such as e-cigarettes, lack responsiveness to the user's state, including mood and subjective needs, which can affect the interaction and perceived utility of the device.
Innovation Solution
A user feedback system that includes an estimation processor to identify behavioral feedback actions based on user factors, such as neurological, physiological, contextual, and use-based data, and a feedback processor to modify device operations to alter the user's state, enhancing the device's responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the delivery device operates with fixed parameters, then the device structure is simple, but the device cannot respond to user state changes
Solution Approach 1:
The patent implements feedback loops where sensors continuously monitor user state (physiological signals, usage patterns) and transmit this information to processors that analyze the data and adjust delivery parameters in real-time. This creates a closed-loop system where the device responds dynamically to user needs, resolving the contradiction between adaptability and complexity by making the complexity serve the feedback function.
Solution Approach 2:
The delivery device autonomously monitors its own operation and the user's state through integrated sensors and processors, automatically adjusting parameters without external intervention. The system serves itself by collecting, analyzing, and acting on its own operational data and user feedback, reducing the need for manual control while enhancing adaptability.
2Adaptability or versatility
If the device collects and analyzes user data, then the personalization improves, but the data processing requirements increase
Solution Approach 1:
The data processing function is segmented into multiple components: sensors collect raw data, local processors perform initial analysis and filtering, and cloud-based systems handle complex pattern recognition and long-term trend analysis. This segmentation distributes the processing burden across different levels, enabling comprehensive personalization without overwhelming a single processing unit.
Solution Approach 2:
The system performs preliminary data processing and filtering at the sensor level before transmitting data to central processors. Basic analytics and feature extraction are conducted locally to reduce data volume and prepare information for higher-level analysis, reducing the overall processing burden while maintaining personalization capability.
3Ease of operation
If the device adjusts delivery parameters dynamically, then the user experience improves, but the control complexity increases
Solution Approach 1:
The delivery device autonomously monitors its own operation and the user's state through integrated sensors and processors, automatically adjusting parameters without external intervention. The system serves itself by collecting, analyzing, and acting on its own operational data and user feedback, reducing the need for manual control while enhancing adaptability.
Solution Approach 2:
The patent implements feedback loops where sensors continuously monitor user state (physiological signals, usage patterns) and transmit this information to processors that analyze the data and adjust delivery parameters in real-time. This creates a closed-loop system where the device responds dynamically to user needs, resolving the contradiction between adaptability and complexity by making the complexity serve the feedback function.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system improves the delivery device's responsiveness to the user's state, potentially leading to a more personalized and effective delivery of active ingredients, such as nicotine, by adjusting parameters like vaporization temperature and active ingredient concentration based on user feedback and data analysis.
Implementation Method 1
electrical power is supplied to the heating element to vaporize the aerosol source (a portion of the payload) in the vicinity of the heating element, to generate an aerosol for inhalation by the user
Implementation Method 2
a heater having a heating element arranged to receive source liquid from the reservoir, for example through wicking / capillary action
Data Source
AI summary
A user feedback system for a user of a delivery device within a delivery ecosystem includes an estimation processor adapted to identify at least a first feedback action based upon one or more user factors, the at least first feedback action including a behavioral feedback action for affecting at least a first behavior of the user, the feedback action being expected to alter a state of the user as indicated at least in part by the one or more user factors; and a feedback processor adapted to select at least a first identified feedback action, and to cause a modification of one or more operations of at least a first device within the delivery ecosystem, according to the selected at least first feedback action.