One-Handed Service Evaluation via Gesture Recognition
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Solution Overview
Problem
The efficiency of evaluating service quality in Online to Offline (O2O) applications is low due to the need for users to operate mobile devices with both hands to provide descriptive text evaluations, which is inefficient and inconvenient.
Innovation Solution
A service quality evaluation method that uses a terminal device to obtain and display candidate evaluation phrases based on analyzed data, allowing users to select and submit evaluations with one hand by determining action types from device movements, thereby improving efficiency and accuracy of service quality assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users provide descriptive text evaluations by operating mobile devices with both hands, then evaluation content can be detailed and specific, but evaluation efficiency becomes low and operation becomes inconvenient
Solution Approach 1:
The system pre-provides a plurality of candidate evaluation phrases related to the target service before the user needs to evaluate. These candidate phrases are prepared in advance based on the service type and context, so when the user needs to evaluate, they can directly select from pre-prepared options rather than typing from scratch, thus improving efficiency while maintaining evaluation quality
Solution Approach 2:
The system uses gesture recognition to copy the user's natural hand movements and translates them into evaluation selections. By capturing the gesture trajectory and matching it with predefined gesture patterns, the system converts simple hand gestures into meaningful evaluation actions, allowing one-handed operation while maintaining detailed evaluation capability
2Loss of information
If users manually enter text for service quality evaluation, then personalized information content can be provided, but the operation requires both hands and reduces efficiency
Solution Approach 1:
Candidate evaluation phrases are pre-generated and stored in the system before evaluation is needed. These phrases contain personalized information content relevant to different service types (e.g., taxi service, food delivery). When evaluation is required, users can quickly select from these pre-prepared personalized phrases without manually typing, thus preserving information quality while reducing time consumption
Solution Approach 2:
The system replaces the mechanical text input process (typing with keyboard) with gesture-based selection. By using acceleration sensors and gyroscopes to detect hand gestures, the system translates physical gestures into digital selection actions, substituting the manual typing mechanism with a more efficient gesture recognition mechanism that preserves one-handed operation capability
3Productivity
If traditional text entry method is used for evaluation, then users can provide detailed feedback, but the process becomes monotonous and time-consuming
Solution Approach 1:
The system copies the user's natural gesture movements and interprets them as evaluation selections. By recording the gesture trajectory (starting point, ending point, intermediate points) and matching it with predefined gesture templates, the system converts simple physical gestures into complex evaluation actions, reducing operational complexity while maintaining evaluation efficiency
Solution Approach 2:
The system introduces gesture recognition technology as an intermediary between the user's hand movement and the evaluation selection. The acceleration sensor, gyroscope, and gesture recognition algorithm act as intermediaries that translate physical gestures into digital commands, simplifying the user's interaction while maintaining system intelligence and evaluation quality
Data Source
AI summary
A service quality evaluation method and a terminal device for a communications field includes obtaining a candidate evaluation phrase set including at least one first candidate evaluation phrase, where the at least one first candidate evaluation phrase is obtained by analyzing to-be-analyzed evaluation data of a target service using a target analysis model, wherein the at least one first candidate evaluation phrase includes an evaluation phrase having personalized information content to evaluate service quality of the target service, displaying the at least one first candidate evaluation phrase and a first to-be-selected evaluation phrase, determining a first action type according to an obtained first moving track, determining a target evaluation phrase from the at least one first candidate evaluation phrase and the first to-be-selected evaluation phrase according to the first action type, and sending service quality evaluation content including the target evaluation phrase.