Distributed Stage Data Mining System for Real-Time Control
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Solution Overview
Problem
The complexity of controlling and managing stage equipment and personnel in large performances has increased due to the richness of sci-tech elements, leading to manual control challenges, independent subsystems that are hard to coordinate, data scrambling for bandwidth, and potential safety hazards that are difficult to detect in a timely manner.
Innovation Solution
An intelligently distributed stage data mining system that includes an intelligent central server, WLAN and ZigBee receiving and transmitting units, a self-adaptive multi-dimensional transmission processing unit, and a distributed data extraction unit, which dynamically acquires and transmits real-time data from stage equipment and personnel, improving data traffic control and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual control mode is used for stage equipment and personnel, then operation simplicity is maintained, but control accuracy and safety monitoring capability deteriorate
Solution Approach 1:
The system enables automated data collection, transmission, and analysis without manual intervention. Sensors and embedded systems automatically monitor equipment status, personnel positions, and environmental parameters, eliminating the need for manual control while maintaining operational simplicity through centralized intelligent management.
Solution Approach 2:
Manual mechanical control is replaced by an intelligent automated system comprising sensors, embedded controllers, and a central server. The system substitutes human operators with automated detection and control mechanisms that continuously monitor and adjust stage parameters, significantly improving control accuracy.
2Reliability
If wired control mode is used for stage subsystems, then connection reliability is improved, but system complexity and coordination difficulty increase
Solution Approach 1:
The system adopts a unified wireless communication protocol that can accommodate multiple types of stage equipment and subsystems. The standardized protocol enables different devices (lighting, sound, special effects, personnel trackers) to communicate through a common interface, reducing system complexity while maintaining reliable connections.
Solution Approach 2:
The system transitions from wired physical connections to wireless electromagnetic communication, changing the transmission medium parameter. This transformation reduces physical complexity and improves coordination capability while maintaining connection reliability through error correction protocols and automatic reconnection mechanisms.
3Ease of manufacture
If independent subsystems are used for stage equipment, then subsystem independence and ease of maintenance are improved, but data coordination and overall control capability deteriorate
Solution Approach 1:
The system merges data from independent subsystems into a unified data framework managed by the central server. Each subsystem maintains its independence for manufacturing and maintenance, but all subsystems contribute data to the centralized platform that coordinates overall stage control, preventing information loss through comprehensive data aggregation.
Solution Approach 2:
The embedded control systems act as intermediaries between independent subsystems and the central server. They collect data from local equipment, preprocess information, and transmit coordinated data to the central platform, ensuring seamless data integration while preserving subsystem independence.
4Quantity of substance
If multiple independent subsystems collect data separately, then data collection coverage is improved, but bandwidth utilization and data evaluation accuracy deteriorate
Solution Approach 1:
The system performs preliminary data filtering, compression, and prioritization at the source before transmission. Embedded controllers pre-process data to remove redundant information and encode critical parameters efficiently, reducing bandwidth consumption while maintaining comprehensive data coverage from all subsystems.
Solution Approach 2:
The system transitions from separate independent data transmission channels to a multi-dimensional integrated data architecture. Data from multiple subsystems is organized in a hierarchical structure with different priority levels and transmission protocols, enabling efficient bandwidth utilization through dimensional optimization of data flow.
Data Source
AI summary
An intelligently distributed stage data mining system is disclosed herein, including an intelligent central server, a first WLAN receiving and transmitting unit, a local cluster control unit, a second WLAN receiving and transmitting unit, a third WLAN receiving and transmitting unit, a self-adaptive multi-dimensional transmission processing unit, a plurality of ZigBee receiving and transmitting units and a distributed data extraction unit. The intelligent central server is used for sending data acquisition and stage correction instruction to the local cluster control unit, and for receiving the stage real-time data uploaded by the self-adaptive multi-dimensional transmission processing unit. The local cluster control unit is used for receiving the data acquisition instruction sent by the intelligent central server, and forwarding instructions to the self-adaptive multi-dimensional transmission processing unit.