[HTML][HTML] A comprehensive survey on an IoT-based smart public street lighting system application for smart cities

S Khemakhem, L Krichen - Franklin Open, 2024 - Elsevier
The swift advancement and updating of urban lighting systems, along with the incorporation
of smart and Internet of Things (IoT) infrastructure, have opened up numerous opportunities …

[HTML][HTML] The CrowdHEALTH project and the hollistic health records: Collective wisdom driving public health policies

D Kyriazis, S Autexier, M Boniface, V Engen… - Acta Informatica …, 2019 - ncbi.nlm.nih.gov
Aim: The aim of the CrowdHEALTH approach, is to introduce a new paradigm of Holistic
Health Records (HHRs) that include all health determinants defining health status by using …

IoT in healthcare: Achieving interoperability of high-quality data acquired by IoT medical devices

A Mavrogiorgou, A Kiourtis, K Perakis, S Pitsios… - Sensors, 2019 - mdpi.com
It is an undeniable fact that Internet of Things (IoT) technologies have become a milestone
advancement in the digital healthcare domain, since the number of IoT medical devices is …

CDP-UA: Cognitive data processing method wearable sensor data uncertainty analysis in the internet of things assisted smart medical healthcare systems

G Manogaran, M Alazab, H Song… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Internet of Medical Things (IoMT) platform serves as an interoperable medium for healthcare
applications by connecting wearable sensors, end-users, and clinical diagnosis centers …

[PDF][PDF] Batch and streaming data ingestion towards creating holistic health records

A Mavrogiorgou, A Kiourtis, G Manias… - Emerging Science …, 2023 - researchgate.net
The healthcare sector has been moving toward Electronic Health Record (EHR) systems
that produce enormous amounts of healthcare data due to the increased emphasis on …

An autoscaling platform supporting graph data modelling big data analytics

A Kiourtis, P Karamolegkos… - … and Technology in …, 2022 - ebooks.iospress.nl
Big Data has proved to be vast and complex, without being efficiently manageable through
traditional architectures, whereas data analysis is considered crucial for both technical and …

Interpretable stroke risk prediction using machine learning algorithms

N Zafeiropoulos, A Mavrogiorgou, S Kleftakis… - … : Selected Papers of …, 2023 - Springer
Stroke is the second most common cause of death globally according to the World Health
Organization (WHO). Information Technology (IT), and especially Machine Learning (ML) …

A catalogue of machine learning algorithms for healthcare risk predictions

A Mavrogiorgou, A Kiourtis, S Kleftakis, K Mavrogiorgos… - Sensors, 2022 - mdpi.com
Extracting useful knowledge from proper data analysis is a very challenging task for efficient
and timely decision-making. To achieve this, there exist a plethora of machine learning (ML) …

Automated rule-based data cleaning using NLP

K Mavrogiorgos, A Mavrogiorgou… - … 32nd Conference of …, 2022 - ieeexplore.ieee.org
Data Cleaning is a subfield of Data Mining that is thriving in the recent years. Ensuring the
reliability of data, either when generated or received, is of vital importance to provide the …

A computer vision-based IoT data ingestion architecture supporting data prioritization

A Kiourtis, A Mavrogiorgou, D Kyriazis - Health and Technology, 2023 - Springer
Abstract Purpose As Internet of Things (IoT) evolves, additional focus should be provided in
aggregating and ingesting the most valuable data. Several techniques aim to identify the …