Martin Serrano

Amelie Gyrard, Martin Serrano, Pankesh Patel

The Web of Things (WoT) is rapidly growing in popularity getting the interest of not only technologist and scientific communities but industrial, system integrators and solution providers. The key aspect of the WoT to succeed is the relatively, easy-to-build ecosystems nature inherited from the web and the capacity for building end-to-end solutions. At the WoT connecting physical devices such as sensors, RFID tags or any devices that can send data through the Internet using the Web is almost automatic. The WoT shared data can be used to build smarter solutions that offer business services in the form of IoT applications. In this chapter, we review the main WoT challenges, with particular interest on highlighting those that rely on combining heterogeneous IoT data for the design of smarter services and applications and that benefit from data interoperability. Semantic web technologies help for overcoming with such challenges by addressing, among other ones the following objectives: 1) semantically annotating and unifying heterogeneous data, 2) enriching semantic WoT datasets with external knowledge graphs, and 3) providing an analysis of data by means of reasoning mechanisms to infer meaningful information. To overcome the challenge of building interoperable semantics-based IoT applications, the Machine-to-Machine Measurement (M3) semantic engine has been designed to semantically annotate WoT data, build the logic of smarter services and deduce meaningful knowledge by linking it to the external knowledge graphs available on the web. M3 assists application and business developers in designing interoperable Semantic Web of Things applications. Contributions in the context of European semantic-based WoT projects are discussed and a particular use case within FIESTA-IoT project is presented.

Amelie Gyrard, Pankesh Patel, Amit Sheth et al.

The Internet of Things (IoT) is experiencing fast adoption in the society, from industrial to home applications. The number of deployed sensors and connected devices to the Internet is changing our perspective and the way we understand the world. The development and generation of IoT applications is just starting and they will modify our physical and virtual lives, from how we control remotely appliances at home to how we deal with insurance companies in order to start insurance schemes via smart cards. This massive deployment of IoT devices represents a tremendous economic impact and at the same time offers multiple opportunities. However, the potential of IoT is underexploited and day by day this gap between devices and useful applications is getting bigger. Additionally, the physical and cyber worlds are largely disconnected, requiring a lot of manual efforts to integrate, find, and use information in a meaningful way. To build a connection between the physical and the virtual, we need a knowledge framework that allow bilateral understandings, devices producing data, information systems managing the data and applications transforming information into meaningful knowledge. The first column in this series in the previous issue of this magazine titled "Internet of Things to Smart IoT Through Semantic, Cognitive, and Perceptual Computing," reviews IoT growth and potential that have energized research and technology development, centered on aspects of Artificial Intelligence to build future intelligent system. This column steps back and demonstrates the benefits of using semantic web technologies to get meaningful knowledge from sensor data to design smart systems.