Paper Info
Title
Challenges in data collection in real-world environments for activity recognition
Abstract
Detecting and recognizing activities of daily living is an important part of ambient assisted living (AAL) systems. This part of the system has the highest impact on the overall system efficiency because it directly provides insights into the user's health state. One of the main challenges that AAL systems are facing are the privacy concerns and the intrusiveness of the sensors that are being deployed. In an ideal scenario, an aged person should be able to continue his or her normal life without noticing that they are being monitored. Another issue for such systems is the data collection. The current approaches usually use data generated in labs and data from end-users users is usually unavailable due to ethical concerns and the inability to deploy them in their living environments. Publications that rely on real-life scenario data are scarce. In this paper, we present the challenges one faces when trying to produce a sound dataset for further analysis and suggest ideas for overcoming them.
Year
DOI
Venue
2019
10.1109/EUROCON.2019.8861964
IEEE EUROCON 2019 -18th International Conference on Smart Technologies
Keywords
Field
DocType
ambient assisted living,daily activity recognition,data collection,field conditions
Data science,Data collection,Activities of daily living,Activity recognition,Computer science,Intelligent sensor,Intrusiveness
Conference
ISBN
Citations 
PageRank 
978-1-5386-9302-5
0
0.34
References 
Authors
10
5
Name
Order
Citations
PageRank
Petre Lameski16113.84
Ace Dimitrievski232.12
Eftim Zdravevski35716.51
Vladimir Trajkovik44717.70
Saso Koceski5308.82