The ASSIST-IoT journal paper entitled “In-cabin and outdoor environmental monitoring in vehicular scenarios with distributed computing”, is now available! The paper has been accepted in the context of ELSEVIER Internet of Things Magazine.
Fotis Konstantinidis from ISenseGroup presented the ASSIST-IoT conference paper entitled ‘Mixed reality applications for health and safety monitoring’, at the IEEE IST- International Conference on Imaging Systems and Techniques (October 17-19, 2023) in the DTU – Technical University of Denmark.
Continuous, real-time monitoring of occupational health and safety in high-risk workplaces such as construction sites can substantially improve the safety of workers. However, introducing such systems in practice is associated with a number of challenges, such as scaling up the solution while keeping its cost low. In this context, this work investigates the use of an off-the-shelf, low-cost smartwatch to detect health issues based on heart rate monitoring in a privacy-preserving manner.
ASSIST-IoT paper “A fuzzy knowledge-based system for UV exposure management” presentation at IEEE 8th World Forum Georgios Stavropoulos (CERTH) presented the ASSIST-IoT paper “A fuzzy knowledge-based system for UV exposure management” at IEEE 8th World Forum on Internet of Things (WF-IoT), ASSIST-IoT Special Session: Future Platforms for Edge-Cloud Continuum–Theoretical Foundations and Practical Considerations, on Monday 31st October 2022, in Yokohama, Japan.
Artificial intelligence (AI) algorithms can provide an effective solution for dynamic and automated network resource management in Software Defined Networking (SDN). In this contribution, we propose an auto-configuration enabler inside the next-generation Internet of Things (IoT) architecture proposed in the ASSIST-IoT project, for network resource allocation. The AI algorithm is responsible for controlling intent-based routing in an SDN network. This paper focuses on the problem of optimal intent switching between two designated paths using a Deep-Q-Learning approach based on an artificial neural network. Read more “AI Application in Next Generation Programmable Networks”→
AIOTI White Paper. This document provides an analysis on the integration of IoT and edge computing in data spaces. It explains the context, defines data spaces, enumerates the challenges of data spaces, as well as the positioning of data spaces in the AIOTI high-level architecture (HLA).Read more ““Guidance for the Integration of IoT and Edge Computing in Data Spaces” Report”→
ASSIST-IoT Technical Report #10, entitled “Implementation of UI methods and UX in VR in case of 3D printer tutorial”, by Andrzej PASZKIEWICZ, Mateusz SALACH, Maria GANZHA, Marcin PAPRZYCKI, Marek BOLANOWSKI, Grzegorz BUDZIK, Hubert WÓJCIK, Fotios KONSTANTINIDIS, and Carlos E. PALAU, accepted at SOMET 2022 conference, KitaKyushu, Japan (20-22 September 2022). Read more “ASSIST-IoT Technical Report #10”→
ASSIST-IoT partner Ioardanis Papoutsoglou (CERTH) will take part and present “DLT-enabled security for IoT infrastructures” in the NGIoT Training Workshop: Decentralizing IoT Intelligence using Distributed Ledger Technologies on February 7, 2022.
A Vision on Smart, Decentralised Edge Computing Research Directions White paper. The EU-IoT White paper entitled “A Vision on Smart, Decentralised Edge Computing Research Directions” is now available! You may also find information about ASSIST-IoT project in page 15.
ASSIST-IoT Technical Report #6, entitled “From OBD to Connected Diagnostics: A Game Changer at Fleet, Vehicle and Component Level.”, by: ASIST-IoT partners C Guardiola, C Vigild, F de Smet and K Schusteritz has been published. Early on-board diagnostics (OBD) standards were enforced in 1988 and, by the beginning of the XXI century, all major automotive markets require some sort of OBD. Over the years, the diagnostics software layer has grown in complexity, yet robust fault detection remains a challenging task: insufficient memory and computation power, suboptimal calibration, and the lack of sufficient real-life operation data for model development are some of the limiting factors. Read more “Technical Report #6”→