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Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework.
Kaushik Sathupadi1, Sandesh Achar2, Shinoy Vengaramkode Bhaskaran3
1Google LLC, Sunnyvale, CA 94089, USA.
Sensors (Basel, Switzerland)
|January 8, 2025
Summary
This study introduces an edge-cloud hybrid framework for real-time predictive maintenance, significantly reducing latency, energy use, and bandwidth needs for sensor networks.
Area of Science:
- Computer Science
- Electrical Engineering
- Industrial Engineering
Background:
- Sensor networks generate large real-time data volumes, straining traditional predictive maintenance due to latency, energy, and bandwidth constraints.
- Existing cloud-only frameworks struggle with the demands of high-velocity data processing in industrial environments.
Purpose of the Study:
- To propose and evaluate an edge-cloud hybrid framework for efficient real-time predictive maintenance.
- To address the limitations of latency, energy consumption, and bandwidth in sensor network data analysis.
Main Methods:
- Implemented a K-Nearest Neighbors (KNNs) model on edge devices for real-time anomaly detection.
- Utilized a Long Short-Term Memory (LSTM) model in the cloud for in-depth time-series failure prediction.
- Developed a dynamic workload management algorithm to optimize resource distribution between edge and cloud.
Main Results:
- Achieved a 35% reduction in latency compared to cloud-only solutions.
- Demonstrated a 28% decrease in energy consumption.
- Reduced bandwidth usage by 60%.
Conclusions:
- The proposed edge-cloud hybrid framework offers a scalable and efficient solution for real-time predictive maintenance.
- This approach is highly suitable for resource-constrained, data-intensive environments.
- Optimized task distribution enhances operational efficiency and maintenance scheduling.
Keywords:
K-nearest neighbors (KNN)bandwidth reductiondynamic workload managementenergy efficiencyhybrid edge-cloud frameworklatency optimizationlong short-term memory (LSTM) networkpredictive maintenancesensor networksensor networksMore Related Videos
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