Interoperability in IoT

Interoperability in IoT

Regel Gonzalez-Usach (Universitat Politecnica de Valencia, Spain), Diana Yacchirema (Escuela Politécnica Nacional, Ecuador), Matilde Julian (Universitat Politecnica de Valencia, Spain) and Carlos E. Palau (Universitat Politècnica de València, Spain)
Copyright: © 2019 |Pages: 25
DOI: 10.4018/978-1-5225-7432-3.ch009
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Interoperability refers to the ability of IoT systems and components to communicate and share information among them. This crucial feature is key to unlock all of the IoT paradigm´s potential, including immense technological, economic, and social benefits. Interoperability is currently a major challenge in IoT, mainly due to the lack of a reference standard and the vast heterogeneity of IoT systems. IoT interoperability has also a significant importance in big data analytics because it substantively eases data processing. This chapter analyzes the critical importance of IoT interoperability, its different types, challenges to face, diverse use cases, and prospective interoperability solutions. Given that it is a complex concept that involves multiple aspects and elements of IoT, for a deeper insight, interoperability is studied across different levels of IoT systems. Furthermore, interoperability is also re-examined from a global approach among platforms and systems.
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Interoperability is defined as the ability of different technology systems, system components or software applications to establish communication between them, exchange data, and interpret properly the received information for its use (ETSI, 2013). This property applies to interactions within a system (i.e. the internal communication of its different components), but also to the interaction between two or more systems.

In IoT interoperability plays an essential role; there is probably no other technology area in which interoperability becomes as critical and relevant as in the case of IoT (World Economic Forum, 2015). Interoperability is the key that allows any set of devices to exchange information and work together in concert, acting as an actual IoT system. For example, without interoperability lights would not respond to remote switches, sensors could not be read by smartphones, and devices in general would be unable to connect to accessible networks. Moreover, according to a study by the McKinsey Global Institute in 2015 (Mckinsey Global Institute, 2015), without interoperability, at least 40% of the potential benefits of IoT cannot be achieved. This is evident considering that a transparent integration and interconnection of different IoT systems and system components would critically simplify their implementation, maximize performance and facilitate their operation with other systems. This interconnection of systems propitiates to share relevant data and to establish significant synergies, improving the quality of the information, the quality of service and the experience provided to the user. Moreover, interoperability enriches Big Data analytics using 3v model (Tanque, M., & Foxwell, 2014) through the integration of a variety of data formats, models and definitions, in a common data model to increase its effectiveness. Indeed, one of the main challenges in Big Data is to handle this data diversity properly (Chen et al., 2014).

To highlight the aforementioned advantages, let us consider an application of a bus company that calculates its optimal route. This application could benefit from interoperability with other transportation services. For instance, it could consider links with trains using the real time information that they provide. The application could also benefit from the interoperation with the traffic monitoring service of the city, capable of indicating the less congested routes. Thus, the service provided by the bus application would be more precise, complete and useful for the user.

Let us also consider some examples of IoT systems in the e-Health domain. In this area, interoperability among sensors and medical devices permit the remote monitoring of different bodily vital signals such as heart rate, blood pressure or breath rate using wearable sensors. Through this monitoring, it is possible for an IoT health system to detect any abnormality of vital signals remotely, at any moment, and automatically alert health services and caregivers. In both examples, it is necessary the interconnection and integration of systems in order to collect, analyse and use big amounts of data from heterogeneous sources.

To achieve a high degree of interoperability in an IoT system is therefore desirable, but regrettably it is still one of the most difficult and important challenges to solve in IoT. As a matter of fact, currently the different IoT systems are typically unable to communicate with each other or to interoperate in general (Diallo, Herencia-zapana, Padilla, & Tolk, 2011). The main cause of this lack of interoperability is the highly heterogeneous nature of IoT systems. The Internet of things covers a wide range of devices, protocols, technologies, networks, middleware, applications, systems and data that present a vast diversity. The heterogeneity of the underlying technologies can prevent the interoperation of smart objects and systems, as they follow different rules and standards. This diversity also affects the process of extracting value from the IoT Big Data due to its inherent heterogeneity, variety of data formats, and rapid growth (Chen et al., 2014). In this sense, the existence of a global reference standard for IoT would notably facilitate interoperability by giving rules and certain homogeneity to this heterogeneous universe. Though, currently there is no de facto reference standard, posing a significant problem when designing new IoT systems (Ganzha, Paprzycki, Pawlowski, Szmeja, & Wasielewska, 2016).

Key Terms in this Chapter

IoT Platform: Is the infrastructure and middleware that allow end users and applications to successfully interact with sensors and actuators.

M2M or Machine-to-Machine Communication: Direct exchange of information or communication between two remote machines (e.g., dispositions, tablets, PCs, etc.) without the manual assistance of humans.

Ontology: Is a vocabulary that contains the formal naming of concepts, and the definition of their types, properties, and interrelations. It enables a common interpretation of semantic metadata, which allows systems to understand the actual meaning and context of exchanged data.

Interoperability: Is the ability to exchange data and use the information across systems, applications, or system components.

Syntactic Interoperability: Is the ability of systems of correctly interpreting the message structure of exchanged information, and thus, of being capable to read its content, although they may not being aware of the meaning of this information.

Constrained Device: Is a device with sensing capabilities, which presents limited CPU, energy resources, and memory.

Smart Gateway: Is a gateway specifically designed for the connection of IoT devices. These gateways offer additional functionality in comparison to traditional gateways such as data aggregation and data pre-processing. Also, they usually provide low-power connectivity through typical IoT technologies such as ZigBee or Bluetooth.

Technical Interoperability: Refers to the ability of systems, system components or applications to establish communication and share messages, without necessarily understanding their content.

E-Health: It is also called health information technology refers to the use of information and communications technologies like to the internet to store and manage the medical records, instead of paper files in healthcare industry.

Semantic Interoperability: Ability of systems of understanding the meaning and context of the information exchanged among them. Ontologies, semantic technologies and knowledge management systems are means to facilitate semantic interoperability.

Smart Object or Smart Device: Refers to any sensor, actuator and/or virtual device connected within an IoT system.

Vertical Silo: System that is unable to communicate or interoperate with others.

Smart City: City that employs digital technology to enhance the quality and performance of urban services (such as transportation, energy, environment, etc.) through the leverage of modern technologies such as IoT.

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