Crowd-Based Haptics for Live Event Ambience
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Solution Overview
Problem
Existing haptic systems fail to fully replicate the ambience of live events for remote attendees, providing only partial sensory experiences through haptic sensations, as they lack the immersive feedback of being physically present.
Innovation Solution
A haptic system that captures and re-renders crowd and event data, including crowd mood, intensity, and key elements, using input from personal devices and sensors to generate targeted haptic feedback, allowing remote users to feel the ambience of live events through haptic effects such as vibrations, deformations, and audio cues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional haptic systems are used to deliver haptic effects for remote events, then basic haptic feedback can be provided, but the full ambience and immersive experience of live events cannot be replicated
Solution Approach 1:
The system segments the crowd into multiple groups distributed across different geographic locations, with each group capturing local haptic data through their personal devices. This segmentation allows the system to collect diverse haptic information from various perspectives and locations, thereby more accurately reconstructing the overall event ambience without losing critical atmospheric details.
Solution Approach 2:
The system merges haptic data from multiple crowd members' personal devices, combining accelerometer, gyroscope, and other sensor data to create a comprehensive haptic profile of the event. By integrating data from numerous sources, the system reconstructs the full ambience and crowd energy that would otherwise be lost in traditional single-point haptic systems.
2Measurement precision
If haptic data is collected from multiple personal devices in the crowd, then more accurate event ambience can be captured, but data collection and processing complexity increases
Solution Approach 1:
The system leverages the existing multi-functional capabilities of personal devices (smartphones, tablets, wearables) that already contain accelerometers, gyroscopes, and other sensors. By utilizing these universally available devices for haptic data collection, the system achieves high measurement precision without adding dedicated complex collection infrastructure, as each personal device serves multiple functions including navigation, communication, and now haptic sensing.
Solution Approach 2:
The system implements feedback mechanisms where haptic data from personal devices is continuously collected, processed, and used to adjust and refine the haptic effects delivered to remote users in real-time. This feedback loop enables the system to maintain high measurement precision while managing data complexity through adaptive processing that focuses on relevant haptic patterns and crowd responses.
3Adaptability or versatility
If haptic effects are generated based on crowd-caused event elements, then more authentic event experience is provided, but processing and identifying relevant elements becomes more difficult
Solution Approach 1:
The system dynamically adapts to crowd behavior by continuously analyzing haptic data patterns from personal devices and adjusting the identification of crowd-caused event elements in real-time. Rather than using fixed thresholds or predetermined criteria, the system evolves its detection algorithms based on observed crowd responses, enabling it to authentically capture varying event dynamics while managing the complexity of element identification through adaptive pattern recognition.
Solution Approach 2:
The system utilizes mechanical vibration patterns detected by sensors in personal devices as key indicators of crowd-caused event elements. By focusing on vibration characteristics (frequency, amplitude, duration) that naturally occur during crowd responses such as cheering, standing ovations, or reactions to event moments, the system can identify authentic crowd-driven events more easily, transforming the complexity of element detection into a more manageable vibration analysis task.
Data Source
AI summary
A system produces haptic effects. The system receives input data associated with an event, identifies an element of the event in the input data, generates the haptic effects based on the element of the event, and produces the haptic effects via a haptic output device. In one embodiment, the haptic effects are generated by haptifying the element of the event. In one embodiment, the haptic effects are designed haptic effects and are adjusted based on the element of the event. In one embodiment, the input data is associated with a crowd that attends the event, and the element of the event is caused by the crowd. In one embodiment, the input data includes haptic data collected by one or more personal devices associated with the crowd. In one embodiment, the input data is indicative of a location of the one or more personal devices associated with the crowd.