Fuzzy-as-a-service for real-time human activity recognition using IEEE 1855-2016 Standard

Pandya, B., Pourabdollah, A. ORCID: 0000-0001-7737-1393 and Lotfi, A. ORCID: 0000-0002-5139-6565, 2020. Fuzzy-as-a-service for real-time human activity recognition using IEEE 1855-2016 Standard. In: 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): 2020 conference proceedings. Piscataway, NJ: IEEE. ISBN 9781728169323

Full text not available from this repository.

Abstract

Fuzzy Logic Systems (FLSs) have shown their potentials in Ambient Intelligence (AmI) applications. However, the implementation of FLSs is typically linked to dedicated and non-scalable hardware/software systems. As a result, some specific AmI requirements such as web communications and Service-Oriented Architecture (SOA), which can be found in many modern systems, are rarely adapted for FLSs. Sharing FLSs accessibility as web services (called fuzzy-as-a-service), in which the service is developed independently from a specific FLS, allows for system autonomy, openness, load balancing, efficient resource allocation and eventually cost-efficiency, particularly for computationally intense FLSs. In a wider context, such features can open new dimensions for FLSs’ applicability in Cloud Computing and Internet of Things devices. Recent advances in standardising Fuzzy Mark-up Language (IEEE 1855-2016) and its associated software libraries (such as JFML) has made this even more achievable. This paper proposed fuzzy-as-a-service architecture based on IEEE 1855-2016, JFML and SOA. Through a simulated experiment, this paper concerned the collection, processing and monitoring the distributed data over the web, thus a real-time human activity recognition simulated scenario using a rule based FLS is demonstrated.

Item Type: Chapter in book
Description: Paper presented at the 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Glasgow, Scotland, 19-24 July 2020.
Creators: Pandya, B., Pourabdollah, A. and Lotfi, A.
Publisher: IEEE
Place of Publication: Piscataway, NJ
Date: 2020
ISBN: 9781728169323
Identifiers:
NumberType
10.1109/fuzz48607.2020.9177781DOI
1358645Other
Divisions: Schools > School of Science and Technology
Record created by: Jonathan Gallacher
Date Added: 01 Sep 2020 10:24
Last Modified: 01 Sep 2020 10:24
URI: http://irep.ntu.ac.uk/id/eprint/40604

Actions (login required)

Edit View Edit View

Views

Views per month over past year

Downloads

Downloads per month over past year