Future Smart Products Systems Engineering

Future Smart Products Systems Engineering

Julia Kantorovitch (VTT Technical Research Centre of Finland, Finland)
Copyright: © 2015 |Pages: 12
DOI: 10.4018/978-1-4666-5888-2.ch375
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Introduction

The increased availability, robustness, and moderate cost of sensors; the increased capacity of computer chips; and the wide spread of Internet and wireless connectivity are adding a new dimension to models of human living and working.

Embedding machine intelligence into the working environment, tools, and processes can make even routine tasks easier. A smart vehicle may eventually suggest using a different type of fuel, knowing the expected temperatures and location of the vehicle during the upcoming trip. Analyzing how a repair procedure is created, a smart vehicle may instruct its owner or technician about the repair procedure, mounting of the snow-chains, or changing the oil. Assembly tools such as a smart wrench may link real-time measurements with actions performed to advise further steps in the assembly process, thanks to the advanced computing and communication technologies available in the surrounding environment and other products.

A combination of several elements brings intelligence to smart products. Sensors measure the environment and the activity of the user, actuators act on the environment or perform functions on behalf of the user, and communication means connect the smart product to other products and the rest of the world. The core of the smart product’s intelligence is a knowledge technology combined with the ability to comprehend the user and surrounding environment (i.e. context), coming from reasoning software and intelligent decision rules.

It is widely recognized that additional methods and techniques should be established to meet the needs of the development of future smart products systems. The current research is advancing in several complementary directions, such as 1) clarifying the concept of a smart product from business and technical points of view; 2) implementing various dimensions of smart products systems, including situation awareness, autonomy, and personalization; 3) researching and developing the enabling technologies to implement the functions of smart products; and finally 4) proposing novel support tools to ease the smart product developer’s work (see Figure 1).

Figure 1.

Research direction in the area of smart products engineering

This article presents a systematic review of existing research in the previously identified domains, providing an analysis of an up-to-date set of technologies that play a critical role in the realization of intelligence and in the sophisticated proactive behavior of smart products. The requirements for the tools facilitating the rapid prototyping of contextual applications and services based on future smart products systems are, in particular, highlighted. The objective of this review is to summarize the existing research in the domain of smart products engineering, to discuss the future trends in the development of smart products systems, and to identify further research needed to ensure the practical execution and success of future smart products systems.

Key Terms in this Chapter

Developer Support Tools: The tools that are designed to facilitate the work of the service developer. Examples are simulators, modelers, visualizers, and code generators.

Reasoning about Knowledge: A method of thinking about knowledge models using logic, deduction, and induction as tools, with the objective of deriving new knowledge and overall understanding of the context.

Machine Intelligence: The ability of original objects (i.e. machines) to accomplish specific tasks in the presence of uncertainty and variability, using sensing and reasoning capabilities.

Knowledge Model: A computer interpretable description of a product and related processes. some knowledge representation language or data structure that enables the knowledge to be interpreted by software and to be stored in a database or data exchange file.

Middleware: A software layer that is built to hide the heterogeneity of hardware and software from applications.

Resource Constrained Device: A device that has limited processing and storage capabilities, and that often runs on batteries.

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