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In this paper, we attempted to address this research gap by proposing an evaluation
framework for IE methodologies. The framework has been defined through studying,
abstracting and unifying systems engineering lifecycle models as well as considering
best practices from systems engineering (SE) [13]. The rest of the paper is organized as
follows: Section 2 discusses the engineering challenges for IEs, Section 3 explains the
rationale for choosing systems engineering, Section 4 presents our proposed framework,
Section 5 describes application of the User-Centred Intelligent Environments
Development Process (UC-IEDP) to build a smart irrigation system, Section 6 reports on
an initial evaluation of UC-IEDP against the evaluation framework and Section 7
highlights the study limitations. The paper is concluded in Section 8 with some directions
for current and future work respectively.
2. Background
IEs emphasize developing systems that incorporate both a smart environment and
ambient intelligence and are based on the ubiquitous availability of services that will
enhance occupants’ experiences [2]. Accordingly, every IE should be able to satisfy
certain basic design goals [2]. IE projects are inherently complex; both from a technical
and management perspective. Moreover, according to a landmark study carried by [12],
the development of intelligent systems poses a number of challenges as a result of
increasing complexity. While these systems are often multidisciplinary, they require
involvement of diverse stakeholders during the entire systems development process.
Therefore, it is imperative to have proper communication and cooperation beyond the
limits of individual specialist disciplines. This infers that ensuring a standard system
understanding represents a key challenge. Moreover, according to [20], these systems
require compliance to numerous quality attributes such as robustness, availability,
extensibility, safety, security, timeliness and efficiency. This further reinforces careful
management of systems requirements during the systems development process and
beyond.
IEs also consist of numerous components or sub-systems interfacing with each other.
Only complete control over the interfaces enables successful system integration. The
increased interactions and interfaces between the individual components further
enhances the design complexity of the overarching system to deliver the emergent effect
that each individual component cannot provide on its own. To this end, human machine
interfaces are also of particular concerns. In [22], the author asserts that testing alone is
not sufficient for these systems due to their complexity level and the consequences of
their failure. As a result, integration of suitable verification and validation methods is
critical for truly dependable systems. As such, system architecting and engineering tools
must be adopted to manage the level of complexity in these types of systems.
3. Why Systems Engineering?
According to the International Council on SE [16], “Systems Engineering is an
interdisciplinary approach and means to enable the realization of successful systems ...
Systems Engineering considers both the business and the technical needs of all customers
with the goal of providing a quality product that meets the user needs.” This implies that
SE addresses both the system to be developed and the associated project [12]. It is
A.Santokheeetal. /TowardsaGeneralFramework forEvaluating
IEs’Methodologies18
Intelligent Environments 2019
Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Title
- Intelligent Environments 2019
- Subtitle
- Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Authors
- Andrés Muñoz
- Sofia Ouhbi
- Wolfgang Minker
- Loubna Echabbi
- Miguel Navarro-CĂa
- Publisher
- IOS Press BV
- Date
- 2019
- Language
- German
- License
- CC BY-NC 4.0
- ISBN
- 978-1-61499-983-6
- Size
- 16.0 x 24.0 cm
- Pages
- 416
- Category
- Tagungsbände