View source for Unknown Organization (20240256905). Internet Of Things (IOT) Big Data Artificial Intelligence Expert System Information Management And Control Systems And Methods simplified abstract

=Internet Of Things (IOT) Big Data Artificial Intelligence Expert System Information Management And Control Systems And Methods=


==Organization Name==

[[:Category:Unknown Organization|Unknown Organization]]


[[Category:Unknown Organization]]

==Inventor(s)==

[[:Category:Robert D. Pedersen of Dallas TX (US)|Robert D. Pedersen of Dallas TX (US)]][[Category:Robert D. Pedersen of Dallas TX (US)]]

==Internet Of Things (IOT) Big Data Artificial Intelligence Expert System Information Management And Control Systems And Methods - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240256905 titled 'Internet Of Things (IOT) Big Data Artificial Intelligence Expert System Information Management And Control Systems And Methods

The patent application describes a system for managing and controlling IoT big data information, focusing on distributed performance monitoring and critical network fault detection.

* IoT data collection sensor stations receive sensor input signals and are connected to monitor units that communicate with other units and cloud resources through IoT telecommunication links.
* The system includes expert predesignated network elements such as sensor stations, monitor units, and telecommunications equipment for performance and fault monitoring based on criticality to operations.
* Performance and fault monitoring signals are analyzed using artificial intelligence and hierarchical expert system algorithms to generate warning and control signals.

Potential Applications:
- Industrial IoT systems for real-time monitoring and control of critical operations.
- Smart city infrastructure for efficient management of resources and services.
- Healthcare systems for remote patient monitoring and emergency response.

Problems Solved:
- Enhancing the reliability and efficiency of IoT networks.
- Improving response times to network faults and performance issues.
- Enabling proactive maintenance and management of interconnected IoT devices.

Benefits:
- Increased operational efficiency and reliability.
- Enhanced network security and data protection.
- Cost savings through optimized resource utilization.

Commercial Applications:
Title: "Advanced IoT Performance Monitoring and Fault Detection System"
This technology can be applied in industries such as manufacturing, energy, transportation, and healthcare for optimizing operations and ensuring continuous connectivity.

Questions about IoT Big Data Information Management and Control Systems:
1. How does the system prioritize critical network elements for monitoring?
The system uses expert predesignated network elements based on criticality to operations to prioritize monitoring.
2. What are the key advantages of using artificial intelligence in performance and fault monitoring?
Artificial intelligence enables advanced analysis of monitoring signals and the generation of proactive warning and control signals.


==Original Abstract Submitted==

iot big data information management and control systems and methods for distributed performance monitoring and critical network fault detection comprising a combination of capabilities including: iot data collection sensor stations receiving sensor input signals and also connected to monitor units providing communication with other monitor units and/or cloud computing resources via iot telecommunication links, and wherein a first data collection sensor station has expert predesignated other network elements comprising other data collection sensor stations, monitor units, and/or telecommunications equipment for performance and/or fault monitoring based on criticality to said first data collection sensor station operations, thereby extending monitoring and control operations to include distributed interdependent or critical operations being monitored and analyzed throughout the iot network, and wherein performance and/or fault monitoring signals received by said first data collection sensor station are analyzed with artificial intelligence, hierarchical expert system algorithms for generation of warning and control signals.



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