Scalable Cloud-Native Architectures for Intelligent PMU Data Processing

Phasor Measurement Units (PMUs) generate high-frequency, time-synchronized data essential for real-time power grid monitoring, yet the growing scale of PMU deployments creates significant challenges in latency, scalability, and reliability. Conventional centralized processing architectures are increasingly unable to handle the volume and velocity of PMU data, particularly in modern grids with dynamic operating conditions. This paper presents a scalable cloud-native architecture for intelligent PMU data processing that integrates artificial intelligence with edge and cloud computing. The proposed framework employs distributed stream processing, containerized microservices, and elastic resource orchestration to enable low-latency ingestion, real-time anomaly detection, and advanced analytics. Machine learning models for time-series analysis are incorporated to enhance grid observability and predictive capabilities. Analytical models are developed to evaluate system latency, throughput, and reliability, showing that the architecture can achieve sub-second response times while scaling to large PMU deployments. Security and privacy mechanisms are embedded to support deployment in critical infrastructure environments. The proposed approach provides a robust and flexible foundation for next-generation smart grid analytics.

A quantitative comparison of plantar soft tissue strainability distribution and homogeneity between ulcerated and non-ulcerated patients using strain elastography

The primary objective of this study was to develop a method that allows accurate quantification of plantar soft tissue stiffness distribution and homogeneity. The secondary aim of this study is to investigate if the differences in soft tissue stiffness distribution and homogeneity can be detected between ulcerated and non-ulcerated foot. Novel measures of individual pixel stiffness, named as quantitative strainability (QS) and relative strainability (RS) were developed. SE data obtained from 39 (9 with active diabetic foot ulcers) patients with diabetic neuropathy. The patients with active diabetic foot ulcer had wound in parts of the foot other than the first metatarsal head and the heel where the elastography measures were conducted. RS was used to measure changes and gradients in the stiffness distribution of plantar soft tissues in participants with and without active diabetic foot ulcer. The plantar soft tissue homogeneity in superior-inferior direction in the left forefoot was significantly (p<0.05) higher in ulcerated group compared to non-ulcerated group. The assessment of homogeneity showed potentials to further explain the nature of the change in tissue that can increase internal stress . This can have implications in assessing the vulnerability to soft tissue damage and ulceration in diabetes.