Remote Monitoring of Human’s Activities and Health


Case Study Team

Coordinators

Id Name Institution (type*) Contact e-mail Related WG Role in the team
1 Sabri Pllana Linnaeus University, SE (A) sabri.pllana@lnu.se  WG2 Coordinator
2 Dragan Sotjanovic University of Nis, RS  (A) dragan.stojanovic@elfak.ni.ac.rs WG1 Vice-Coordinator

Team members

Id Name Institution (type*) Contact e-mail Related WG
1  Siegfried Benkner  University of Vienna, AT  (A)  siegfried.benkner@univie.ac.at)  WG2
2  Daniel Grzonka  Cracow University of Technology, PL (A)  grzonka.daniel@gmail.com  WG1
3 Farhoud Hosseinpour University of Turku, FI  (A) Farhood.h@gmail.com  WG1
4  Agnieszka Jakóbik  Cracow University of Technology, PL (A)  agneskrok@gmail.com  WG1
5 Helen Karatza  University of Thessaloniki, GR (A)  karatza@csd.auth.gr WG2
6 Joanna Kolodziej  NASK , PL (I) jokolodziej@pk.edu.pl  WG1
7 Mateusz Krzyszton NASK, PL (I) mateusz.krzyszton@gmail.com WG1
8 Zuzana Kominkova-Oplatkova Tomas Bata University of Zlin , CZ  (A) zuzka.oplatkova@gmail.com)  WG4
9 Francesco Masulli University of Genoa, IT (A)  Francesco.masulli@unige.it  WG4
10  Ilias Mavridis  University of Thessaloniki, GR (A)  imavridis@csd.auth.gr  WG2
11 Jose Manuel Molina Lopez Universidad Carlos III de Madrid, ES (A)  molina@ia.uc3m.es WG2
12 Michal Marks Warsaw University of Technology (A), NASK, PL (I) mmarks@elka.pw.edu.pl WG1
13 Ewa Niewiadomska-Szynkiewicz Warsaw University of Technology, PL (A) ens@ia.pw.edu.pl WG1
14  Ana Respicio University of Lisbon,  PT  (A)  alrespicio@fc.ul.pt  WG4
15 Andrzej Sikora Warsaw University of Technology (A), NASK, PL (I) A.Sikora@elka.pw.edu.pl WG1
16 George Suciu  BEIA Consult International, RO (A)  george@beia.ro  WG1
 17 Salvatore Vitabile  University of Palermo, IT (A), MIRC s.r.l. (I)  salvatore.vitabile@unipa.it  WG3
18 Ioan Salomie Technical University of Cluj-Napoca, RO (A) ioan.salomie@cs.utcluj.ro WG1

*A-academia, I-industry


Addressed Problem(-s)

The Topics we focus on

  • Remote monitoring of health conditions of the patients – Body Area Networks (small area sensor networks)
  • Remote monitoring of the human’s activities – sensor-based monitoring systems, support in emergency situations, situated awareness
  • Cloud support systems for processing and analytics of the data generated by the above sensor-based monitoring systems

Main Problems related to the topics

Individual monitoring

  • Security and privacy
  • Data ownership
  • Individual (personal) data analytics
  • Data fusion
  • Edge-Cloud trade-off for processing/analysis sensor data

Crowd modelling and monitoring

  • Collective data analytics
  • Data fusion
  • Security and privacy
  • Data ownership

Existing Solution(-s) (Models, Tools)

  • Heterogeneous data fusion
  • Deep learning in e-health
  • Virtual layer for medical data abstraction/anonymization
  • Thinger.io open source Cloud IoT framework; sensors and actuators (https://thinger.io)
  • Containers technology
  • Existing data: crowdsignals.io, www.physionet.org
  • Situated MAS (crowd or individual modeling)
  • Private Cloud clusters for medical data storage and analytics (Comarch, Philips)
  • FIWARE (www.fiware.org) processing sensor data

Proposed Solution(-s) (Models, Tools)

Data mining

  • High-performance data analysis
  • Context-aware data fusion & processing 
  • Incremental clustering of data streams
  • Adaptive [edge vs cloud] processing of sensor data

Methods and models

  • Artificial Intelligence models and methods
    • Artificial Neural Networks
    • Fuzzy logic
    • Machine learning
    • Bioinspired methods
  • Blockchain
  • Intelligent agents
  • Modelling, simulation and optimisation

Tools, devices and platforms

  • Sensors & actuators
  • IoT platform 
  • Cloud, Fog/Edge computing
  • Smart dust computing
  • Wearable computing
  • Simulators

Practical Scenarios (-s)

  • Remote monitoring of the heart condition of the taxi drivers in Cracow (Comarch)
  • Remonte monitoring of the chemical engineers in the dangerous environments (ABB)
  • Smart Phone Ad hoc Network (SPAN) for e-health application (NASK)
  • Machine learning for daily living activities of people with dementia

Supplementary Material