Meeting Activity Detection for Mobile Sales Timing Control
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Solution Overview
Problem
Customers often do not purchase predicted commodities if they are not offered at the right time, and existing technologies do not address mobile sales in meeting rooms.
Innovation Solution
An information processing device that estimates the activity state of a meeting room using sensors and determines the optimal timing for mobile sales by a self-propelled robot to approach participants, ensuring timely and appropriate sales opportunities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mobile sales are performed in meeting rooms, then sales opportunities can be captured, but the timing may disrupt the meeting flow
Solution Approach 1:
The system performs preliminary detection of meeting state using sensors (camera, microphone, motion detectors) to assess whether the meeting is in a suitable state for sales intervention. This preliminary assessment allows the system to prepare sales actions only when the meeting is in an appropriate state, preventing premature disruptions.
Solution Approach 2:
The system continuously monitors meeting state through sensors and uses this feedback to dynamically adjust sales timing decisions. The detection unit provides real-time information about meeting activity level, speaker identification, and participant engagement, which feeds back to the control unit to determine the optimal moment to initiate sales without disrupting the meeting flow.
2Productivity
If sales timing is determined without considering meeting activity state, then sales can be performed more frequently, but the effectiveness of sales decreases
Solution Approach 1:
The system dynamically adjusts sales timing based on the detected meeting activity state rather than using fixed intervals. The control unit modifies sales execution decisions in real-time according to detected parameters such as meeting intensity, participant engagement, and speaker transitions, making the sales process adaptive to the evolving meeting context.
Solution Approach 2:
The system changes the operational parameters of sales execution based on detected meeting state parameters. When the meeting is in a high-activity state, the system delays or cancels sales actions; when the meeting enters a lower-activity state or natural transition points, the system initiates sales. This parameter-based control optimizes both frequency and effectiveness.
3Measurement precision
If the meeting state is continuously monitored, then sales timing can be optimized, but the system complexity increases
Solution Approach 1:
The detection system is segmented into multiple independent sensor units (camera for visual detection, microphone for audio detection, motion detectors for movement detection) that each monitor specific aspects of the meeting. This segmentation allows the system to gather comprehensive meeting state information through multiple simple, specialized sensors rather than one complex all-in-one detection device.
Solution Approach 2:
The sensor units serve multiple functions: the camera detects both speaker identity and participant engagement, the microphone captures both speech content and meeting intensity, and motion detectors track both individual movement and overall activity level. This multi-functionality reduces the number of separate detection devices needed while maintaining comprehensive monitoring capability.
Data Source
AI summary
The information processing device 1D mainly includes a state-of-activity estimation unit 31D and a timing determination unit 32D. The state-of-activity estimation unit 31D estimates, based on information detected in a meeting room in which a meeting is being held, a state of activity of the meeting. The timing determination unit 32D determines a timing of mobile sales of a commodity to one or more participants of the meeting based on the state of activity estimated by the state-of-activity estimating unit 31D.