edge computing

Digital Twin-Based Predictive Maintenance in 6G Smart Stadiums Using Standardized AI-Driven Models

The future of smart stadiums lies in highly connected, intricate systems that must respond instantly and maintain smooth operations. When it comes to handling the operational complexity of such dynamic infrastructures, traditional maintenance strategies — whether time-based or reactive — are rapidly falling short. A ga...

Artificial Intelligence-Empowered “Walking Hospitals”: A Narrative Review of Innovative Models and Ecosystem Construction in Rural Healthcare

An AI-empowered “Walking Hospitals” represent a paradigm shift from hardware distribution to capability enhancement, and future research must prioritize resolving domain shift through techniques like Federated Learning, establishing sustainable reimbursement models, and developing community-level data governance framew...

Playing with Kruskal: A State-of-the-Art Report on Watershed Cuts

This article presents a detailed end-to-end pipeline of algorithms to compute (hierarchical) watershed segmentations, starting from the computation of graph-based image representations, up to the computation of connected components of the final (hierarchical) segmentation.

Clinical risk-aware reinforcement learning for latency-constrained healthcare IoT scheduling

CRAI-LCS, a clinical risk-aware Reinforcement learning (RL) framework for latency-constrained scheduling in HIoT systems, combines data-driven clinical risk estimation, deadline-violation prediction, and RL-based scheduling to dynamically prioritize high-risk tasks while efficiently managing system resources.

An Edge-Computing UAV Architecture for GPS-Denied Structural Inspection in Reinforced-Concrete Environments: A Prototype-Based Proof-of-Concept Evaluation

While there are evident advantages to deploying UAVs for structural inspection applications within reinforced-concrete structures where human access may be hazardous or restricted, UAV deployment is still inhibited within structures due to a lack of GPS, payload and power limitations, signal attenuation, limited transm...

Approximate Equilibrium Play in 4-Max Shove-or-Fold Poker: A Delayed-Linear Weighted-Averaging MCCFR Study at 8BB Effective Stacks

This technical note presents validated shove and call ranges for 4-player all-in-or-fold poker at 8 big-blind effective stacks. The strategy was produced using delayed-linear weighted-averaging Monte Carlo Counterfactual Regret Minimization (MCCFR), trained from iteration zero to 4,000,000 across two independent seeds...

GT-PPO: Graph Attention-Based and Sequence-Aware Deep Reinforcement Learning for Adaptive SFC Orchestration in SAGIN-MEC

GT-PPO is proposed, a deep reinforcement learning (DRL)-based approach for online SFC orchestration designed to maximize network profit while minimizing end-to-end (E2E) delay and capturing global dependencies among virtual network functions (VNFs).

On Overcoming Compute and Memory Constraints for Distributed Machine Learning at the IoT Edge

Applied Identity Physics: Adaptive Predictive Pattern Assistant-APPA

-- ============================================================-- Applied Identity Physics — Combined Lean 4 Compilation Unit-- Released by SNSFT Foundation · Soldotna, Alaska-- ============================================================---- Architect: HIGHTISTIC (Russell Trent)-- Corpus: Substrate-Neutral Structural...

Cosmology from a Three-Bit Seed

Author's note. This monograph consolidates the program corpus listed at the foot of this description. As the program has grown, each new result was propagated across an expanding set of documents, and the set became unmanageable. Consolidation also surfaced inconsistencies between documents written at different stages...

WatchEDGE Smart Cameras: Real-Time Wildlife Detection at the Far Edge

This conference poster presents WatchEDGE smart cameras for real-time wildlife detection at the far edge. Animals can severely affect crops, making continuous monitoring important for both farm management and wildlife protection. The work investigates deep-learning-based animal detection on resource-constrained far-edg...

ARTIFICIAL INTELLIGENCE-DRIVEN QUALITY CONTROL IN MODERN MANUFACTURING SYSTEMS

AI should not be viewed simply as a replacement for human inspection but as an intelligent layer that augments engineering knowledge and enables manufacturing systems to anticipate, diagnose and correct quality problems, a critical review of recent literature concludes.