Matti Eteläperä

Enabling Semantic Technology Empowered Smart Spaces

It has been proposed that Semantic Web technologies would be key enablers in achieving context-aware computing in our everyday environments. In our vision of semantic technology empowered smart spaces, the whole interaction model is based on the sharing of semantic data via common blackboards. This approach allows smart space applications to take full advantage of semantic technologies. Because of its novelty, there is, however, a lack of solutions and methods for developing semantic smart space applications according to this vision. In this paper, we present solutions to the most relevant challenges we have faced when developing context-aware computing in smart spaces. In particular the paper describes (1) methods for utilizing semantic technologies with resource restricted-devices, (2) a solution for identifying real world objects in semantic technology empowered smart spaces, (3) a method for users to modify the behavior of context-aware smart space applications, and (4) an approach for content sharing between autonomous smart space agents. The proposed solutions include ontologies, system models, and guidelines for building smart spaces with the M3 semantic information sharing platform. To validate and demonstrate the approaches in practice, we have implemented various prototype smart space applications and tools.

A Cognitive Management Framework for Empowering the Internet of Things

This work presents a Cognitive Management framework for empowering the Internet of Things (IoT). This framework has the ability to dynamically adapt its behaviour, through self-management functionality, taking into account information and knowledge (obtained through machine learning) on the situation (e.g., internal status and status of environment), as well as policies (designating objectives, constraints, rules, etc.). Cognitive technologies constitute a unique and efficient approach for addressing the technological heterogeneity of the IoT and obtaining situation awareness, reliability and efficiency. The paper also presents a first indicative implementation of the proposed framework, comprising real sensors and actuators. The preliminary results of this work demonstrate high potential towards self-reconfigurable IoT.

Feasibility Evaluation of M3 Smart Space Broker Implementations

In this paper we evaluate two M3 smart space information broker implementations -- Smart-M3 and RIBS. M3 is a semantic interoperability architecture for both local and Internet connected smart environments and it utilizes RDF databases in similar fashion as does the Semantic Web. The implementations compared in this paper have similar functionality, but their design philosophies are very different. Smart-M3 is an open source reference architecture for M3 and RIBS is a solution for devices with restricted computational capabilities. Our evaluation is based on both qualitative evaluation and quantitative measurements. A measurement and testing tool for M3 smart environment databases was built during the work. Measurement based analysis shows that the RIBS implementation is 6.7-237 times faster than Smart-M3 over an Ethernet network, but RIBS is usable only in a limited number of use cases. The work also shows that there is a need for new M3 database solutions which are usable for more generic use cases.

Opening information of low capacity embedded systems for Smart Spaces

Smart Spaces are an emerging computing paradigm in which various devices of our everyday environment share information autonomously with each other in order to provide services to people in the environment. Achieving reliable way to share information between heterogeneous devices is not an easy process however. Solutions that are independent of application domain and that provide interoperability for the devices of the Smart Space are needed. This paper presents a new application domain independent approach for low capacity embedded systems to be part of applications and use cases based on semantic information interoperability. The approach uses NoTA and Smart-M3 solutions to open embedded information for devices in the Smart Space. A reference implementation of smart greenhouse is used to demonstrate the approach in practice.

Enabling End-Users to Configure Smart Environments

Our everyday living environments are inhabited by a huge and constantly increasing number of electronic devices. Smart Environment is a common name for a physical place where these various devices interact with each other in order to provide useful services for the end-user. Because different people usually have different kind of needs it is important that the user is able to configure the Smart Environment so that the services provided to individual user are in fact useful. In this paper, we present an approach for enabling end-user to configure how the Smart Environments functions. In our approach we utilize Semantic Web technologies and publish/subscribe based architecture for providing semantic interoperability in the Smart Environment. As a proof of concept, we present a reference implementation of a tool that can be used to configure Smart Environments and a case study in a smart greenhouse domain.

Open-M3: smart space with COTS devices

Support of legacy devices and services is crucial for the adoption of new smart space technologies. We present two technologies which enable the formation of local ad-hoc smart spaces with commercial off-the-shelf (COTS) devices. First of these technologies is NoTA, which is a service oriented architecture enabling networks of devices with different physical transports. Second one is Smart-M3, which is a semantic information sharing architecture for smart spaces. It aims at opening physical world information for the use of services and applications in the information world, thus enabling new types of mash-up applications. In our demonstration - Open-M3 - we show how these technologies are used to build a small, yet extendable smart space for sensor monitoring using COTS devices.

Validating Applicability of Smart-M3 Platform for a Multi-vendor Micropayment System in the Context of Small Business

To be economically feasible, micropayment systems are expected to be efficient, with low transaction and computing costs and light security protection. In addition, a micropayment system is a networked good involving both consumers and merchants subject to positive network effects: the value of the system to consumers depends on the number of merchants adopting the system and vice versa. The objective of this study was to implement a micropayment system pilot for small business with restricted resources, scarce labor force and growing number of products and vendors. Based on the results of a literature review conducted in this study, an account-based system was considered an appropriate starting point for the pilot. Further, applicability of Smart-M3 platform for the system was validated. The results of the study show that the implemented system provides small business with opportunities of additional services and products, cost savings, and inclusion of new vendors.

Virtual Prototypes in Developing Mobile Software Applications and Devices

The goal of this paper is to study how software based virtual prototypes and hardware simulation tools can be combined. By combining these tools and techniques we can shorten the time to market with parallel concurrent design and more importantly, we can provide a real-time simulation environment for virtual prototypes. Application designers get access to a simulated realistic real-time mobile device well before the first prototypes are available from the device manufacturer. The research work was done in two cases. In the first case the virtual prototypes were used to illustrate and help to select new mobile application concepts and to test new applications usability. In the second case the virtual prototypes were used for modelling the product platforms, e.g. the computer system and the simulation of the complete system including both hardware and software. Our approach facilitates early simulation and testing of the final user experience and system behaviour in cases where they are heavily dependent on the characteristics and performance of the underlying computer platform.