Smart workstation method and system
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Solution Overview
Problem
Existing workstations lack efficient systems for powering sensors integrated within furniture affordances, such as task chairs and workstation tables, and fail to provide effective feedback and encouragement for healthy behaviors.
Innovation Solution
The integration of on-board power systems in furniture, including inductive coupling antennas and electrical mats, to efficiently power sensors, combined with sensor placement strategies and automated charging mechanisms that respect user privacy, and the implementation of systems that provide real-time feedback and encouragement for healthy behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are integrated within furniture affordances (task chairs, workstation tables), then physiological parameters and behavioral data can be collected, but the furniture requires reliable power sources to operate these sensors
Solution Approach 1:
The furniture is equipped with self-charging capabilities through regenerative mechanisms. When the furniture is used (e.g., sitting on the chair), the user's movement or weight automatically generates electrical energy through piezoelectric or electromagnetic induction, which is stored in onboard batteries to power the integrated sensors without requiring external power sources or user intervention for charging
Solution Approach 2:
The furniture serves multiple functions: it provides mechanical support (seating/table surface), collects physiological and behavioral data through integrated sensors, and generates/stores electrical energy through regenerative power systems. This multi-functionality eliminates the need for separate power stations or frequent battery replacements
2Reliability
If on-board power systems are integrated in furniture, then sensors can be continuously powered, but the device complexity increases
Solution Approach 1:
The power generation, energy storage, and sensor operation systems are merged into a single integrated furniture unit. The regenerative power system combines mechanical energy harvesting (from user movement), electrical energy storage (through onboard batteries), and power management circuitry into one cohesive system that automatically powers the sensors without requiring separate power infrastructure
Solution Approach 2:
A power management system acts as an intermediary between the regenerative power generation mechanisms and the sensors. This intermediary component regulates energy flow, manages battery charging/discharging cycles, and ensures stable power delivery to sensors while protecting the system from energy fluctuations
3Ease of operation
If automated charging mechanisms are implemented, then power management becomes user-friendly, but the manufacturing complexity increases
Solution Approach 1:
The furniture automatically manages its own power needs through integrated sensing of user presence and activity. The system self-regulates power consumption by activating sensors only when needed (when a user is detected), automatically charges energy storage devices during periods of non-use or through regenerative mechanisms, and requires no user intervention for power management operations
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
This solution enables reliable data collection of physiological parameters and behavioral data within workspaces, promotes healthy behaviors by providing timely feedback, and ensures efficient and user-friendly power management for integrated sensors.
Implementation Method 1
The base assembly includes an inductive coupling antenna
Implementation Method 2
The button includes a piezoelectric element that transforms mechanical energy to electrical energy
Data Source
AI summary
A system and method establishing control of affordances at a workstation. The method includes the steps of storing affordance preferences in a database for a plurality of portable affordance settings that may be present at a workstation, detecting a subset of affordances present within a first zone associated with the workstation, for each detected affordance in the subset, identifying an affordance setting in the database indicating a user preference, and automatically controlling settings of at least each of the detected affordances in the subset to match the user preferences for the detected affordances.