Energy Optimization of Wireless Sensor Embedded Cloud Computing Data Monitoring System in 6G Environment

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Smart cities generate massive data, straining traditional processing platforms.
• Current surveillance systems require efficient data handling in 6G networks.
• Wireless sensor networks face challenges with energy supply and consumption.

Purpose of the Study:

• To propose a data governance solution for 6G environments.
• To optimize wireless sensor networks for efficient data processing in monitoring systems.
• To address energy limitations and enhance the reliability of sensor networks.

Main Methods:

• ZigBee energy optimization for wireless sensor networks.
• An improved routing algorithm combined with embedded cloud computing.
• Development of a data governance framework for 6G monitoring systems.

Main Results:

• ZigBee-optimized wireless sensor networks demonstrate reduced energy consumption.
• The optimized network increases the service life of the sensor network.
• The integrated system ensures efficient data processing, security, and reliability.

Conclusions:

• The proposed data governance solution effectively manages large-scale data in 6G environments.
• ZigBee energy optimization and embedded cloud computing enhance wireless sensor network performance.
• The system provides a secure, reliable, and efficient monitoring solution for smart cities.