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    Distributed event-triggered estimation conserves resources in sensor networks by reducing data transmission. This survey explores recent advances in this efficient, resource-aware monitoring solution.

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    Area of Science:

    • Control Systems
    • Networked Systems
    • Signal Processing

    Background:

    • Resource constraints in sensor networks necessitate efficient data handling.
    • Distributed estimation allows collaborative state calculation using limited sensor data.
    • Event-triggered mechanisms reduce unnecessary sampling and transmission, saving power and bandwidth.

    Purpose of the Study:

    • To survey recent advancements in distributed event-triggered estimation for resource-constrained sensor networks.
    • To detail fundamental design issues and recent developments in event-triggered estimation.
    • To highlight practical applications and future research directions.

    Main Methods:

    • Discussion of fundamental issues in distributed estimator design (structures, communication, methods).
    • Categorization of recent event-triggered estimation results based on triggering conditions.
    • Review of applications in grid-connected generation and target tracking systems.

    Main Results:

    • Event-triggered mechanisms significantly reduce sensor sampling and network bandwidth usage.
    • Distributed event-triggered estimation offers a resource-aware approach for monitoring systems.
    • Recent developments show promise for various practical applications.

    Conclusions:

    • Distributed event-triggered estimation is a key technology for efficient sensor network monitoring.
    • Further research is needed to address challenging issues in the field.
    • The surveyed methods provide a foundation for developing advanced resource-aware estimation systems.