AI-Powered Communication for Health Crisis Management

Project AICom4Health
Project Key Information

Project Status: running

Start Date: January 2022

End Date: May 2025

Budget (total): 5114.94 K€

Effort:  73.52 PY

Project-ID: C2021/1-7

Project Coordinator

Name: Elio Saltalamacchia

Company: SII Concatel S. L.

Country: Spain

E-mail: moc.letacnoc@aihccamalatlas.oile

Project Consortium

Luda Partners S.A., Spain

NETCHECK S.A., Spain

SII Concatel S. L., Spain

Bewell Technology Industry & Trade Inc., Turkey

ETIYA, Turkey

NETAS Telecommunications A.S., Turkey

Turk Telekom, Turkey

Not yet active:

Beia SRL, Belgium

ECITelecom, Israel

Abstract

The objective of AIcom4Health project is to offer an innovative solution towards recovering the pandemics negative impacts on public health ,healthcare access and socioeconomics through remote monitoring -AI based platform’s integration to the public’s daily life whereas employing healthier citizens for smart cities s in the area of 5G and beyond, network slicing, edge computing, artificial intelligence and machine learning based on feasible use cases including both medical and non-medical sensors for making accurate decisions and predicting risks against contagion in the future. The use cases include integration of an IoT platform with various types of sensors to monitor physiological, behavioral and environmental data from natural indoors and outdoors environments.

From a research perspective, AICom4Health aims to bring together data processing, AI and data communication techniques. Edge computing paradigm is a key enabler that integrates data processing and artificial intelligence algorithms within data communication, 5G, network slicing and IoT domains in order to provide reliability and timeliness in the system. Use cases within the AICom4Health project will provide continuous monitoring of individuals and crowds through multivariate analysis, fast response and action to health deterioration of individuals or health threats within a crowd. It also deals with big data collection from several measurement surveillance cameras and also air quality monitoring capabilities. This will require real-time, fast and intelligent data processing techniques, while providing highly reliable communication through network slicing.

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