The Internet of Things (IoT) services are typically delivered based on the interaction and information exchange between numerous heterogeneous Internet-connected devices, as well as the orchestration of the services that they provide. Therefore, integrators of large scale IoT solutions have to deal with a very complex and highly heterogeneous landscape of sensors, devices, networks, services, data formats, data analytics algorithms and application logic components.
Since the very early days of IoT (e.g., the era of the first WSN (Wireless Sensor Networks) and RFID (Radio Frequency Identification) systems) IoT platform providers and application builders have devised ways for ensuring interoperability across the different elements that comprise IoT applications. Early interoperability techniques included the use of common (virtualized) models of all sensors, as well as the use of common standards-based models for representing sensor and IoT data. However, these techniques used to be ad-hoc and limited to the scope of specific problems, such as WSN based energy management or RFID-based supply chain management applications.
Nowadays, more than ten years after the introduction of the term Internet of Things, the issues of interoperability across sensors, devices, things and whole IoT systems has become more topical than ever.
This is due to three main reasons:
- First, the different types of devices and things are proliferating and increasingly used by end-users. For example, in the consumer IoT space, end-users are nowadays likely to use multiple devices such as various smart phones, Tablets and wearable, which are barely interoperable unless they all come from the same vendor.
- Second, a large number of IoT deployments are already available. Interoperability is the missing ingredient for interconnecting already deployed systems, as a means of enabling new applications and added-value functionalities. As a prominent example, the interoperability of IoT systems in the areas of smart energy, urban transport and electromobility can enable the development of holistic sustainability strategies, beyond the capabilities of each individual system in the above areas. As another example, novel fitness and personalised lifestyle management applications could be implemented by considering interactions and interoperability across all the smart devices of a user, regardless of their vendor and type.
- Third, the advent of Cloud computing and Big Data technologies provides more opportunities for data exchange, data processing and services interactions across inter-operable IoT systems at a large scale. The unified and inter-operable processing of IoT data collected from diverse IoT systems can nowadays be performed in a scalable and high-performance way, as a result of IoT’s integration with Cloud and Big Data systems.
Overall, IoT interoperability is an enabler for a range of novel applications and solutions, beyond the capabilities offered by a single device or system. It could also act as a catalyst for increasing Return-on-Investment (ROI) on IoT infrastructure investments, through reusing data and services from IoT systems within a broader set of applications, which shall increase their business value and utility. Moreover, interoperability across diverse IoT devices and services is a prerequisite for implementing large scale dynamic IoT solutions, which dynamically discover and use devices and services. Relevant discovery mechanisms should be able to interact in a uniform way with models of different objects, regardless of their type, vendor and status.
The business potential of IoT interoperability has been acknowledged in a recent report by McKinsey & Co., which concluded that interoperability will be driving nearly 40% of IoT’s business value in the coming years[1]. This figure is expected to be higher in certain application settings such as smart cities, where entirely new opportunities could be generated based on the interconnection of existing deployments that still remain fragmented.
The IoT interoperability challenge has different flavors including:
- Technical interoperability between the hardware or software components that comprise an IoT application. Use of platforms and protocols for objects’ identification and machine-to-machine communication is required towards ensuring technical interoperability.
- Syntactic interoperability which refers to the use of common formats for data processing and data exchange. Simple, easy to process and developer-friendly formats such as JSON (JavaScript Object Notation) and XML (eXtensible Markup Language) are used as a basis for a common syntax between IoT systems.
- Semantic interoperability focuses on the ability of two IoT systems to understand the semantics of the data or services that they exchange. It is a higher-level problem aiming to ensure a common way for interpreting IoT data and services across different IoT systems. Common interpretations are usually empowered by the use of ontologies, which provide a basis for knowledge representation and reasoning.
- Business interoperability of IoT systems refers to interoperability across different IoT business processes supported by these systems. This requires a common model for the business semantics of the processes, rather than a mere representation of domain knowledge via one or more ontologies.
The multiple facets of IoT interoperability have given rise to many different frameworks and technologies for addressing interoperability issues in the IoT space. Several frameworks make use of ontologies such as W3C SSN (Semantic Sensor Networks) ontology[2] and the oneM2M ontologies[3] as a common model for IoT knowledge representation. The IoTDB.org project[4] is specifying and developing a semantic layer for IoT, in order to decouple developers from the need to acquaint themselves with the low-level details and functionalities of various things.
As another example, the Hypercat consortium has developed a framework for secure, standards-based and inter-operable access to IoT resources in order to facilitate dynamic discovery of assets over the web[5]. Hypercat is very popular in the UK and has been deployed in both industrial and smart city applications. Beyond these examples there are numerous other solutions to IoT interoperability, which render the technical solution less important when compared to the organisational, regulatory and governance challenges of IoT interoperability. The latter include for example the establishment of the proper incentives and regulatory frameworks for sharing and reusing data from IoT systems that are operated by different administrative entities.
This touches on privacy and data protection issues as well, which are worked out in parallel to the technical solutions. Despite the complexity of the IoT interoperability landscape, IoT stakeholders should get prepared for the IoT interoperability era, which will break the boundaries of existing silo applications, leading to a global IoT.
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[1] “Unlocking the potential of the Internet of Things”, McKinsey Global Institute June 2015, available at: http://www.mckinsey.com/business-functions/business-technology/our-insights/the-internet-of-things-the-value-of-digitizing-the-physical-world
[2] https://www.w3.org/2005/Incubator/ssn/ssnx/ssn
[3] http://www.onem2m.org/technical/onem2m-ontologies
[4] https://iotdb.org
[5] http://www.hypercat.io/
John Soldatos is an Internet of Things, Cloud Computing, JavaEE Consultant, Writer and published author.
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