Introduction to Smart Environments

Now the Internet of Things (IoT) is growing fast into a large industry with huge potential economic impact expected in near future. The IoT technology evolves to a substrate for resource interconnection and convergence. The users' needs go beyond the existing web-like services, which do not provide satisfactory coupling and automatic composition when the user tries to solve tasks from her/his everyday life. New generation of services (named “smart services”) emerges. In this chapter, we introduce the problem of effective use of the multitude of IoT-enabled devices and other digital resources that now surround our lives. The devices support and assist human by provision of digital services. This is the key objective of a smart environment. Our focus is on such a particular class of smart environments as smart spaces. This class targets IoT-enabled computing environments, where a smart space is created and then provides an infrastructure for applications to construct and deliver value-added services based on cooperative activity of environment participants, either human or machines.

Smart-M3 Techniques

The previous chapters elaborated the design principles that guide the development of smart spaces-based applications using the Smart-M3 platform. The principles aim at such properties for applications as (i) interoperability for a multitude of participated heterogeneous devices, services, and users localized in the physical surrounding and (ii) context-aware, situational, and personalized service construction and delivery. In this chapter, we present selected ontology-oriented modeling techniques for applying the principles. The aspect of shared semantic information management becomes essential for service construction. We describe techniques how implement this management in a smart space. A question of what is a smart service compared with regular service is still debatable. We describe techniques how implement various intelligence attributes in services constructed and delivered in M3 spaces.

M3 Spaces in Internet of Things Environments

As we showed in the previous chapter, the M3 architecture supports the Smart Spaces concept with localization and interconnection of available resources, their semantics, and information-driven programming over this dynamic knowledge corpus (in the form of a semantic network). In this chapter, we consider the settings of IoT environments. The settings play an essential practical role, influencing the way how an M3 space and its applications are deployed on the existing networked equipment of a given IoT environment. Basically, IoT refers to the connection of physical objects. IoT technologies make all the devices of a spatial-limited physical computing environment interconnected as well as connected to the Internet. This ability leads to the consideration of notion of localized IoT-environments which now appears in many places of everyday life. Software agents running on devices turn the latter into “smart objects” that are visible in our daily lives as real participating entities. As a result, the next generation of software applications (smart applications) can be deployed in localized IoT-environments in the form of M3 spaces.

The M3 Architecture for Smart Spaces

In accordance with the previous chapter, a particular class of smart environments is created by Smart Spaces, where many devices participate using information-driven and ontology-oriented interaction. In this case, a smart space is developed based on models from multi-agent systems and knowledge manipulation technologies from the Semantic Web. In this chapter, we consider this particular approach for creating such smart environments. The M3 architecture (multidevice, multivendor, multidomain) aims at development of smart spaces that host advanced service-oriented applications. We introduce the theoretical background of the M3 architecture in respect to its open source implementation—the Smart-M3 platform. The latter forms a technology for creating M3-based smart spaces (M3 spaces) as heterogeneous dynamic multi-agent systems with multi-device, multi-vendor, multi-domain devices and services. We further consider the concept models of space computing that enable the studied class of smart spaces, derive the generic properties that an M3 space design requires, and describe the basic software components of M3 architecture that realize the generic design properties in accordance with the concept models.

Application Case Studies

The previous chapters showed theoretical foundations and development techniques for the Smart Spaces concept. This chapter presents appraisal of the M3-based smart spaces for Internet of Thing application development. Six topical application domains has been chosen: collaborative work environments, social networking, transport logistics, mobile e-Tourism services, mobile health, and industrial Internet. Existing pilot implementations of applications for these domains show that M3 space is useful for smart services collaboration since it provides possibilities of semantic-based information sharing between services using the publish / subscribe mechanism.