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Interoperability remains a significant burden to the developers of Internet of Things’ Systems. This is due to the fact that the IoT devices are highly heterogeneous in terms of underlying communication protocols, data formats, and technologies. Secondly due to lack of worldwide acceptable standards, interoperability tools remain limited. In this paper, we proposed an IoT based Semantic Interoperability Model (IoT-SIM) to provide Semantic Interoperability among heterogeneous IoT devices in healthcare domain. Physicians communicate their patients with heterogeneous IoT devices to monitor their current health status. Information between physician and patient is semantically annotated and communicated in a meaningful way. A lightweight model for semantic annotation of data using heterogeneous devices in IoT is proposed to provide annotations for data. Resource Description Framework (RDF) is a semantic web framework that is used to relate things using triples to make it semantically meaningful. RDF annotated patients’ data has made it semantically interoperable. SPARQL query is used to extract records from RDF graph. For simulation of system, we used Tableau, Gruff-6.2.0, and Mysql tools.

The concept of smart home is widely favored, as it enhances the lifestyle of the residents involving multiple disciplines, i.e., lighting, security, and much more. As the smart home networks continue to grow in size and complexity, it is essential to address a handful among the myriads of challenges related to data loss due to the interference and efficient energy management. In this paper, we propose a smart home control system using a coordinator-based ZigBee networking. The working of the proposed system is three fold: 1) smart interference control system controls the interference caused due to the co-existence of IEEE 802.11x-based wireless local area networks and wireless sensor networks; 2) smart energy control system is developed to integrate sunlight with light source and optimizes the energy consumption of the household appliances by controlling the unnecessary energy demands; and 3) smart management control system to efficiently control the operating time of the electronic appliances. The performance of the proposed smart home is testified through computer simulation. Simulation results show that the proposed smart home system is less affected by the interference and efficient in reducing the energy consumption of the appliances used in a smart home.

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