Service Continuity in Healthcare Internet of Things (HIoT): An Architectural Solution
In the Healthcare IoT (HIoT), wearables often depend on companion devices for data handling, which risks service disruption during connectivity or resource failures. To address this, a new HIoT architecture is proposed that supports continuous data collection, dynamic device association, and hybrid device–edge–cloud processing. Leveraging wearables and cloud services (e.g., AWS), it ensures fault tolerance, high availability, security compliance, and continuous healthcare services under dynamic conditions.
Jun 9, 2025
Edge AI in the computing continuum: Consistency and Availability at Early Design Stages
This paper integrates Edge Intelligence (EI) with the coordination language Lingua Franca (LF), using the Consistency-Availability-Latency (CAL) theorem to optimize Cyber-Physical Systems (CPS). We demonstrate an Emergency Vehicle Detection (EVD) system that prioritizes emergency vehicles through multimodal detection and LF’s deterministic coordination. Two deployment scenarios are evaluated—cloud-assisted and fully edge-based—guided by CAL tradeoffs. Experiments show that the edge-based solution reduces inference-to-actuation latency by 2.8x and energy consumption by 10.26%, while eliminating cloud bandwidth overhead.
Jun 3, 2025
A Generative AI-Driven Architecture for Intelligent Transportation Systems
This paper addresses the need for intelligent transportation systems (ITS) by proposing an innovative architecture for vehicle trajectory prediction. It integrates a Long Short-Term Memory (LSTM) module with a generative AI component, specifically the RoBERTa Transformer model. The LSTM network with a recursive decoder outperforms a teacher forcing decoder on clean datasets, demonstrating higher robustness in time-series predictions. When video data is partially missing, performance drops, but RoBERTa-based data reconstruction significantly improves results (from 37% to 92%). These findings emphasize the importance of data reconstruction in handling incomplete information in real-world ITS scenarios.
Oct 11, 2024
Towards an Edge Intelligence-Based Traffic Monitoring System
This paper explores urban changes necessitating digital transformation, proposing an Edge Intelligence (EI)-based Traffic Monitoring System (TMS) for smart cities. It advocates for placing intelligence near data sources, showcasing early benefits like enhanced performance and reduced resource usage compared to cloud-centric methods.
Oct 1, 2023