Zohreh Pourzolfaghar

Investigating HCI Challenges for Designing Smart Environments

With the advancement of technologies related to ‘Internet of Things’, we are moving towards environments characterised by full integration and semantics. Various environments are often summarized with terms such as ‘Smart City’, ‘Smart Home’, ‘Smart Buildings’ or ‘Smart Commerce’. In the meantime, technologies and standards for interoperability have been developed. However, to realise the full potential one remaining challenge is the design, integration and interoperability of many elements into a smart environment. In order to address this challenge, researchers have proposed concepts for Information Systems Design and Enterprise Architectures. By inspecting interaction challenges -in particular activities in which Humans are involved- during the design process, we endeavour in this paper to identify key challenges for designing smart environments. In order to address the challenges we propose a conversational approach that supports the main design phases and allows professionals to interact during the design phases for smart environments.

A technique to capture multi-disciplinary tacit knowledge during the conceptual design phase of a building project

The construction industry is suffering from incomplete knowledge flow that results in time and cost over-runs. Many researchers believe that a large part of this problem is related to the design phase being a tacit knowledge-dominated area. Since tacitness of knowledge contributes to incomplete flow of knowledge, we posit that facilitating the conversion of tacit knowledge to explicit knowledge can improve the overall knowledge flow. Within this context, this paper analyses recognised knowledge-capturing techniques and compares them in view of the operating characteristics of the conceptual design phase. This paper proposes a new tacit knowledge-capturing technique for this phase. The outcomes include a new knowledge-capturing technique, a method for validation of the proposed technique, and recommendations on how to deal with the challenges concomitant with the application and utilisation of the proposed technique in the building industry. By proposing a combinational tacit knowledge-capturing technique, this study attempts to mitigate the impact of the potential incomplete knowledge flow during the conceptual design phase in building projects.

A Comparison of Smart City Development and Big Data Analytics Adoption Approaches.

This paper intends to elucidate the similarities between smart city development and big data analytics adoption. Both concepts promise new opportunities: smart cities to improve citizens’ life quality and big data analytics to drive companies towards the competitive edge. Consequently, the number of organisational big data initiatives and efforts to implement smart city concepts are increasing. In the context of big data analytics adoption, it could be shown that there are two distinct approaches companies follow. They either focus on the search for potential use cases or on the development of a technology infrastructure. Based on a comparison of various smart city and big data analytics use cases, this paper discloses that both of these approaches either concentrate on developing new service development or providing the required infrastructures for future

Utilising Latent Data in Smart Buildings: A Process Model to Collect, Analyse and Make Building Data Accessible for Smart Industries

Smart buildings are embedded with large amounts of latent data from different sources, e.g. IoT devices, sensors, and the like. Integration of this latent data with the buildings information can highly impact efficiency services provided by various industries such as facility management companies, utility companies, smart commerce, and so forth. To enable the integration of buildings information, diverse technologies such as Building Information Modelling (BIM) have been developed and changed the traditional approaches. Notwithstanding a plethora of research in this area, potential users of this information such as facility management companies are still unable to fully benefit from the building information. This is due to this fact that various information and data have been heterogeneously scattered across various sources. To overcome this challenge, this research follows the design science approach to propose a process model to address facility management concerns in terms of the ability to access the combination of building information with live data captured from various sources. The presented process model is introduced thoroughly by explaining the required steps to collect and integrate this information with the live data. The Artifact evaluation of the process model was undertaken via the employment of a focus group session with the construction professionals, the IoT experts, and the data analysts. Also, this paper elaborates on two industrial use-cases to demonstrate how having access to the building information effectively affects the other industries. The outcome of this research provides an open access to the integrated building information and live data for diverse range of users.

Integration of Buildings Information with Live Data from IoT Devices

Information generated by smart buildings is a valuable asset that can be utilised by various groups of stakeholders in smart cities. These stakeholders can benefit from such information in order to provide additional valuable services. The added value is achievable if there is access to buildings information integrated with the live data being generated and collected from smart devices and sensors residing within the Internet of Things (IoT) environment. Notwithstanding the prominence of this combination, there are some barriers relating to the integration of buildings information with the live data. With the aim of examining such barriers, this chapter primarily focuses on information exchanges between various domains in smart cities. It also provides a vision on specific domains that can benefit from integration of buildings information with other live data. This can impact and improve the quality of various e-services. This chapter describes the barriers and suggests solutions to realise these visions. At the end of this chapter, a summary of the barriers is provided and discussed followed by proposals for future research topics to provide solutions to the inherent barriers.

A Meta-Level Design Science Process for Integrating Stakeholder Needs - Demonstrated for Smart City Services

Currently there is an issue in the design process of smart city services, where citizens as the main stakeholders are not involved enough in requirements engineering. In this paper, we present a meta-level design science process, based on an extended version of design science research methodology, that can be used to create requirements engineering frameworks to inform smart city service requirements engineering processes. The introduced meta-level process is beneficial as it can be used to ensure that design guideline research processes are rigorous, just as design science process ensures scientific rigor in design research. Additionally, we present a previous case study and frame it using the new meta-level design science process.

Explicating Mechanical and Electrical Knowledge for Design Phase of Green Building Projects

Construction projects usually encompass numerous disciplines, requiring the integration of knowledge from civil, mechanical, electrical and other engineering domains. Some researchers contend that the integration of construction knowledge and experience at the early design phase would improve the overall project performance. Domination of tacit knowledge during design phase of building projects is the major source of knowledge flow problems between involved professionals. Therefore, this study intends to explicate the required mechanical and electrical knowledge which has to be considered during the conceptual design phase of a green building project. To fulfil this goal, a case study has been conducted to specify the entity of the required mechanical and electrical knowledge. The primary method for the data collection here is observation. Furthermore, this study employs the triangulation method in order to validate the collected data. The results contain the required mechanical and electrical knowledge which has to be considered during the conceptual design phase of a green building project.