Maximizing the interoperability of smart space devices

Smart spaces can range from a building with networked temperature and motion sensors to a vehicle that constantly reports its location, performance, and maintenance needs. They offer great benefits, among others, for the environment: they reduce energy costs through real-time adjustments of heating, cooling, and lighting based on changes in weather and building occupancy.

As they can be monitored and adjusted remotely, smart spaces reduce carbon footprints while saving money in the process. They can also ensure that dangerous situations are avoided: the monitoring and remote-control capabilities of smart spaces allow supervisors to catch problems early and often help prevent them before they start. Given their ability to elevate people's living standards, intensive research is being conducted on real-life applications of smart spaces.

How well a smart space functions depends largely on the degree of interoperability and cooperation between its various components (also known as "nodes"). Supporting interoperability is an absolute necessity for the design of smart space architectures.

The ability to communicate meaningful information (semantics) across nodes and share a common understanding is referred to as semantic interoperability. For his PhD thesis, Sachin Bhardwaj focused his research precisely on improving that semantic interoperability.

A first step

To address the challenge of semantic interoperability in smart spaces in a generic manner, the first essential step is to provide a precise smart space definition that clearly describes its fundamental concepts and properties.

Prior to Bhardwaj’s thesis work, such a detailed formal definition of a smart space was non-existent. This set a barrier in terms of achieving a technological breakthrough in generic smart space design. 

Bhardwaj formally and rigorously defined general smart space concepts and discussed related architectural components (both hardware and software) in detail. He proposed centralized, decentralized, and distributed smart space architecture options to choose from. Finally, he proposed a semantic interoperability architecture for smart spaces. 

Smart lighting model and applications

Following the definition phase, Bhardwaj introduced an innovative smart lighting model designed for the continuous monitoring and control of illumination in an activity space through sensing and actuation. 

This model served as the foundation for implementing the proposed semantic interoperability architecture. In his study, Bhardwaj used a gateway approach to seamlessly integrate resource-poor nodes (e.g., sensors, actuators) into a smart space. 

The gateway node performs complex tasks on their behalf, facilitating their semantic interactions with each other and with other resource-rich nodes.
 

Versatile thus broadly applicable

While extensively tested in the context of lighting applications, the semantic interoperability architecture proved to be versatile and offers a competitive solution for implementing smart space applications beyond just smart lighting applications.

By maximizing interoperability, the impact of smart spaces on users' daily lives can become even greater - resulting, for example, in optimized energy consumption, increased sense of security or productivity, or an even more personalized user experience of devices.

Title of PhD thesis: Semantic interoperability architecture for smart spaces
Supervisors: prof.dr. Johan Lukkien, dr.Tanir Ozcelebi