Questionnaire Data Acquisition Module Auto-Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing questionnaire generation methods require significant time and labor to input question content, options, and types, leading to low efficiency and poor user experience.
Innovation Solution
A method and system for automatically generating a data acquisition module that includes an input terminal, conversion terminal, and data generation end, which identify and convert input data into target data for questionnaire format, using identification information and conversion strategies to enhance efficiency and compatibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual configuration of data acquisition modules is used, then flexibility and adaptability are maintained, but time consumption and labor requirements increase significantly
Solution Approach 1:
The patent uses template-based copying to generate data acquisition modules. A template contains predefined acquisition parameters and configuration structures, and the system automatically copies and instantiates this template for each data acquisition task, eliminating manual configuration while maintaining consistency and reducing errors
Solution Approach 2:
The system automatically modifies template parameters based on detected data types and acquisition requirements. When data is detected, the system changes parameters such as sampling rate, data types, and acquisition duration to match the specific detection needs, enabling adaptive automated configuration
2Loss of time
If automated module generation is implemented, then time consumption is reduced, but system complexity and automation requirements increase
Solution Approach 1:
The data acquisition system performs self-configuration by automatically detecting data types, determining acquisition parameters, and generating modules without external intervention. The system monitors its own state and autonomously adjusts configuration settings based on detected conditions, reducing the need for complex external automation systems
Solution Approach 2:
The template is prepared in advance with predefined acquisition parameters and configuration structures. This preliminary preparation allows the system to quickly instantiate modules by simply filling in detected data values, significantly reducing configuration time without requiring complex real-time decision-making systems
3Reliability
If standardized templates are used for module generation, then consistency and reliability are improved, but adaptability to different data types may be reduced
Solution Approach 1:
The template is designed as a universal structure that can accommodate multiple data types through parameter substitution. The same template framework can be used for detecting various data types (temperature, pressure, flow rate, etc.) by simply changing the parameter values and data type specifications, achieving both consistency and versatility
Data Source
Figure 1~2
Figure 3~4
Figure 5
AI summary
Embodiments of the application disclose a method and a system for automatically generating a data acquisition module. The method for automatically generating a data acquisition module includes that: an input terminal inputs at least one piece of data to be converted, and sends the at least one piece of data to be converted to a conversion terminal, herein each of the at least one piece of data to be converted includes at least one piece of identification information; the conversion terminal identifies the at least one piece of identification information according to the received data to be converted to obtain an identification result; the at least one piece of data to be converted is converted into target data according to the identification result; and a data generation end at least generates a data acquisition module based on the target data. According to the application, the plurality of pieces of data to be identified may be converted into the question content in a questionnaire survey format by identifying the identification information in the plurality of pieces of data to be identified and determining the contents included in the question type, question content and question options of each of a plurality of questions, which can improve the efficiency of entering questionnaire questions and user experience.