edge computing

T1DM personalized care insights through machine and deep learning models: A comprehensive survey

Type 1 Diabetes Mellitus (T1DM) is a lifelong condition defined by the immune system's beating on and eradication of the insulin-generating beta cells within the pancreas. The reasoning for this review is that it not only synthesizes an existing finding, but also provides a practical implication for how ML, and DL, can...

Adaptive resource scheduling for hierarchical edge intelligence via self-attention and self-supervised deep reinforcement learning

An SS-DDPG-based task scheduling framework for a collaborative robot-UAV-MEC architecture that achieves lower service delay, better workload distribution, and stronger robustness than conventional reinforcement-learning-based scheduling approaches is presented.

lctriage — experiment outputs for "Persistence, Not Consensus" (TESS sectors 1, 2, 13)

Experiment outputs behind every table and figure of Persistence, Not Consensus: Measured Triage of Unsupervised Anomaly Rankings of TESS Light Curves, produced with lctriage 1.1.0 on TESS sectors 1, 2 and 13. Kept apart from the catalogue so that scores computed on synthetically modified light curves cannot be mistaken...

Transient Events: A Rapid-Response, Multi-Platform Observing Strategy for Detecting and Understanding Abrupt Change in Aquatic Ecosystems

Extremes, not average conditions, increasingly govern the state of aquatic ecosystems and the risks they carry for people. Events far outside normal variability can reshape ecosystem structure and function within hours to weeks, and both the observational record and climate projections indicate such extremes are growin...

somamaley-ux/non-degenerate-construction-kernel-admissibility: Kernel Reference v0.3.0 — Constructed necessity and exact realization

v0.3.0 — Constructed necessity and exact original realization Lean companion to the v51 reference edition of Non-Degenerate Construction and the Kernel of Admissibility. This release checks the mathematical necessity chain developed around Proposition 2.4. Independently specified original subjects, complete uses, depen...

Synergy of Artificial Intelligence, Blockchain, Internet of Things, Digital Twin, with Edge Computing (ABIDE)

The Guarino Infrastructure Dependency Metric: Buffered Edges as a Complete Dimensionless Basis for Interdependent Infrastructure

Paper I of the Guarino Infrastructure Dependency Metric (GIDM). Infrastructure fails in chains. The February 2021 freeze in Texas began at frozen wellheads, ran through load-shed gas processing plants, took 61,800 MW of generation offline, and ended in boil-water notices for almost 18 million people. Existing resilienc...

An Explainable Multimodal AI Software Framework for 36-Month MCI-to-Alzheimer’s Disease Progression Prediction: A Methodological Evaluation

The complexity involved in predicting the progression of Alzheimer’s Disease (AD) occurs because of differences in neuroimaging data and the many inconsistencies in biomarker data and cognitive data alike. The current research examined an AI model that uses deep learning, organized data preprocessing, and post-experime...

Exploring Smart Infrastructure Development through IIOT, Cloud Computing and Big Data Analytics

The rapid expansion of the Industrial Internet of Things (IIoT) has revolutionized modern technological infrastructure, generating unprecedented volumes of data through massive sensor deployments. However, extracting actionable value from this data remains a critical challenge due to the computational, networking, and...

Design and Real-Time Analytics of a Digital Twin-Based Framework for Intelligent Mobility Management

Digital Twin ranks amongst the disruptive digital transformation technologies that permit the modeling of complex systems and their management by creating digital replicas of real-world environments. Digital Twins such as smart city, autonomous car and intelligent transport network operate for real-time monitoring, sim...

Semantic-Aware Edge Intelligence for Cooperative Perception in UAV–V2X Mobility

This chapter presents a semantic-aware edge intelligence framework for cooperative perception in UAV–V2X mobility. It addresses the limitations of continuous raw-data sharing among vehicles, UAVs, roadside units, MEC servers, and cloud platforms under bandwidth, latency, energy, synchronization, and computing constrain...

Group Distillation for Semi-supervised Federated Learning in Heterogeneous Edge Computing