Spatial Asset Orchestration Using LiDAR and Gesture Recognition
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Solution Overview
Problem
Current digital asset management systems lack real-time monitoring, integration, and collaboration capabilities, leading to inefficiencies, security vulnerabilities, and non-compliance issues, especially in large organizations with dynamic user roles and remote work environments.
Innovation Solution
A system integrating LiDAR face detection, gesture recognition, and augmented reality to provide real-time asset management, including heatmap visualization, collaborative networking, and context-aware provisioning using spatial computing devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual asset management methods are used, then system complexity is reduced, but real-time monitoring capability and productivity are significantly degraded
Solution Approach 1:
The spatial computing device serves multiple functions: LiDAR-based user identification, gesture recognition for asset manipulation, augmented reality visualization for monitoring, and integration with asset management systems. This multi-functional approach consolidates what would otherwise require separate systems into a single device, achieving real-time monitoring without proportionally increasing overall system complexity.
Solution Approach 2:
The patent replaces manual mechanical asset management processes with automated optical and computational systems. LiDAR replaces manual identification, gesture recognition replaces physical interaction with interfaces, and augmented reality replaces traditional display mechanisms. This substitution enables real-time monitoring capability while the integration architecture manages the resulting complexity.
2Measurement precision
If comprehensive asset tracking is implemented, then measurement precision and reliability are improved, but loss of time and operational complexity increase
Solution Approach 1:
The system implements continuous real-time monitoring of digital assets through the spatial computing device. Instead of periodic manual audits, the LiDAR and sensor systems continuously track user identities, asset locations, and compliance status. This continuous action maintains high measurement precision while eliminating the time loss associated with intermittent manual reconciliation processes.
Solution Approach 2:
The spatial computing device acts as an intermediary between physical assets and the asset management system. It captures data through LiDAR and sensors, processes it through gesture recognition and spatial mapping, and transmits it to the centralized system. This intermediary role enables accurate tracking while automating the data collection process, reducing the time manual reconciliation would require.
3Loss of information
If integrated asset management system is deployed, then information completeness and reliability are improved, but device complexity and initial time investment increase
Solution Approach 1:
The patent merges multiple asset management functions into a single integrated system. The spatial computing device combines LiDAR scanning, gesture recognition, augmented reality display, and communication interfaces into one unified platform. This consolidation provides complete information about digital assets while managing complexity through integration rather than proliferation of separate systems.
Solution Approach 2:
The spatial computing device is designed as a universal platform that performs identification, tracking, visualization, and communication functions. This multi-functionality ensures complete information capture across all asset management needs while avoiding the complexity of coordinating multiple specialized systems. The device's integrated architecture handles diverse tasks through unified processing.
4Ease of operation
If advanced LiDAR and gesture recognition technology is used, then user interaction ease and measurement precision are improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The LiDAR system automatically performs user identification without requiring manual input. The gesture recognition system interprets natural hand movements directly, eliminating the need for traditional interfaces. The augmented reality display presents information autonomously based on spatial context. These self-service capabilities provide intuitive interaction while the integrated system manages the underlying complexity of multiple advanced technologies.
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
Enables efficient, secure, and responsive digital asset management with real-time updates, intuitive user interaction, and proactive threat detection, enhancing compliance and reducing vulnerabilities.
Implementation Method 1
identifying a user by using a LiDAR face detection system integrated with a spatial computing device
Data Source
AI summary
An intelligent method for managing and orchestrating digital assets leveraging spatial computing devices is disclosed. The method enables real-time identification and extraction of user digital asset details, including software and hardware assets, using a LiDAR-based face detection system integrated with spatial computing devices. The invention includes a spatial scanning engine, user asset extraction engine, and spatial anchor programming engine, allowing asset management associates to annotate, alter, and manipulate user assets via an interactive spatial interface. Gesture recognition capabilities enable intuitive control of digital assets, while deep learning modules enhance accuracy in user and asset identification. The method supports the formation of local area networks for collaborative asset management and real-time provisioning of digital assets based on spatial and geolocation data. An asset anomaly event engine detects and reports compliance issues, ensuring security and efficient management of digital assets. The homomorphic encryption layer secures data during processing, maintaining privacy.