  Internet of things is growing with a large number of diverse objects which
generate billions of data streams by sensing, actuating and communicating.
Management of heterogeneous IoT objects with existing approaches and processing
of myriads of data from these objects using monolithic services have become
major challenges in developing effective IoT applications. The heterogeneity
can be resolved by providing interoperability with semantic virtualization of
objects. Moreover, monolithic services can be substituted with modular
microservices. This article presents an architecture that enables the
development of IoT applications using semantically interoperable microservices
and virtual objects. The proposed framework supports analytic features with
knowledge-driven and data-driven techniques to provision intelligent services
on top of interoperable microservices in Web Objects enabled IoT environment.
The knowledge-driven aspects are supported with reasoning on semantic ontology
models and the data-driven aspects are realized with machine learning pipeline.
The development of service functionalities is supported with microservices to
enhance modularity and reusability. To evaluate the proposed framework a proof
of concept implementation with a use case is discussed.
