Investigating HCI Challenges for Designing Smart Environments

Pourzolfaghar, Zohreh; Helfert, Markus

doi:10.1007/978-3-319-39399-5_8

Cited by 7 publications

(4 citation statements)

References 28 publications

(32 reference statements)

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“…In general, there are various studies of HCI that can be applied in the context of SMS. For example, in [20], general guidelines for creating smart environments are shown, which can be easily adapted to SMS environments.…”

Section: State Of the Artmentioning

confidence: 99%

Towards human-computer interaction on smart metering systems

et al. 2020

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New technologies associated with the fourth industrial revolution are transforming the world in which we live, and the power grid is no exception since it has been provided with intelligence. One of its best-known applications is smart metering systems that allow real-time energy consumption/production to be known, as well as other benefits such as outages and reconnections automatically. The new generations of smart meters have more computing capacity allowing new applications. This work shows some considerations in the design of smart meters using human-computer interaction techniques. The results aim to improve the end-user’s experience and satisfaction and can help to mitigate the reluctance to use smart metering systems in Mexico.;

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Section: State Of the Artmentioning

confidence: 99%

Towards human-computer interaction on smart metering systems

et al. 2020

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“…With respect to learning capabilities the key enablers identified are the city stakeholders who regularly hone their skills; while with respect to cultural capabilities the key enablers identified are the city structure and history. Learning Capability The importance of knowledge transfer amongst city actors during the design phase of smart city environments is emphasised by [37]. The authors state that the exchange of domain knowledge is highly tacit in nature; which, at times leads to loss of valuable information.…”

Section: Learning and Cultural Capabilitiesmentioning

confidence: 99%

Towards a Capabilities Approach to Smart City Management

Gupta

Panagiotopoulos

Bowen

2017

Lecture Notes in Computer Science

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Smart cites are rapidly gaining momentum but our understanding of their underlying management framework has to a large extent been unexplored. Under the different initiatives within the label of smart cities, there is no systematic understanding of how city decision makers manage the configuration of resources and processes within the dynamic urban environment. This research in progress paper develops a research agenda on the capabilities of smart city management by synthesising the findings of 72 papers. Further to consolidating the enabling aspects of technology and data as key resources is smart city development, the review leads to the identification of dynamic, operational, cultural and management capabilities. The paper concludes by discussing the value of this approach for future work in the area of smart cities.

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“…For instance, utility companies can utilise building information to estimate energy consumption and promote energy saving [20]. For this purpose, they need the cumulative information of electrical devices, while detailed buildings information may not be accessible.…”

Section: Process Model For Building Information and Live Data Intmentioning

confidence: 99%

“…For this purpose, they need the cumulative information of electrical devices, while detailed buildings information may not be accessible. Similarly, other industries such as retailers can predict and manage market demands with regard to the technical specification for building components and materials [20]. However, building information is not openly available for these typical potential industry users.…”

Section: Process Model For Building Information and Live Data Intmentioning

confidence: 99%

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

Pourzolfaghar

Helfert

2017

Annals of Computer Science and Information Systems

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Abstract-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 of the services provided by various industries, e.g. facility management companies, utility companies, smart commerce, and so forth. To manage buildings information, diverse technologies such as Building Information Modelling (BIM) technology 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 the 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 enable facility management industry to access the integration of buildings information with live data. The presented process model is introduced thoroughly by explaining the required steps to collect and integrate and preserve the integrated information and data. The 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 integration of building information and live data for diverse range of users.

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Investigating HCI Challenges for Designing Smart Environments

Cited by 7 publications

References 28 publications

Towards human-computer interaction on smart metering systems

Towards human-computer interaction on smart metering systems

Towards a Capabilities Approach to Smart City Management

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

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