Fuzzy-as-a-Service for Real-Time Human Activity Recognition Using IEEE 1855-2016 Standard

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.