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A Study on Visual Representations for Active Plant Wall Data Analysis
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Science and Technology, Physics, Electronics and Mathematics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5742-1266
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Centre for Climate Science and Policy Research, CSPR.
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2019 (English)In: DATA, E-ISSN 2306-5729, Vol. 4, no 2, article id 74Article in journal (Refereed) Published
Abstract [en]

The indoor climate is closely related to human health, well-being, and comfort. Thus, an understanding of the indoor climate is vital. One way to improve the indoor climates is to place an aesthetically pleasing active plant wall in the environment. By collecting data using sensors placed in and around the plant wall both the indoor climate and the status of the plant wall can be monitored and analyzed. This manuscript presents a user study with domain experts in this field with a focus on the representation of such data. The experts explored this data with a Line graph, a Horizon graph, and a Stacked area graph to better understand the status of the active plant wall and the indoor climate. Qualitative measures were collected with Think-aloud protocol and semi-structured interviews. The study resulted in four categories of analysis tasks: Overview, Detail, Perception, and Complexity. The Line graph was found to be preferred for use in providing an overview, and the Horizon graph for detailed analysis, revealing patterns and showing discernible trends, while the Stacked area graph was generally not preferred. Based on these findings, directions for future research are discussed and formulated. The results and future directions of this research can facilitate the analysis of multivariate temporal data, both for domain users and visualization researchers.

Place, publisher, year, edition, pages
MDPI, 2019. Vol. 4, no 2, article id 74
Keywords [en]
visualization; qualitative evaluation; temporal multivariate data; active plant walls
Keywords [sv]
Visualisering; kvalitativ utvärdering; tidsvarierande multivariate data; active plant walls
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:liu:diva-157027DOI: 10.3390/data4020074ISI: 000475303500028OAI: oai:DiVA.org:liu-157027DiVA, id: diva2:1317560
Available from: 2019-05-23 Created: 2019-05-23 Last updated: 2019-08-21Bibliographically approved
In thesis
1. A Data-centric Internet of Things Framework Based on Public Cloud
Open this publication in new window or tab >>A Data-centric Internet of Things Framework Based on Public Cloud
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The pervasive application of Internet of Things (IoT) has been seen in many aspects in human daily life and industrial production. The concept of IoT originates from traditional machine-to-machine (M2M) communications which aimed at solving domain-specific and applicationspecific problems. Today, the rapid progress of communication technologies, the maturation of Internet infrastructures, the continuously reduced cost of sensors, and emergence of more open standards, have witnessed the approaching of the expected IoT era, which envisions full connectivity between the physical world and the digital world via the Internet protocol. The popularity of cloud computing technology has enhanced this IoT transform, benefiting from the superior computing capability and flexible data storage, let alone the security, reliability and scalability advantages.

However, there are still a series of obstacles confronted by the industry in deployment of IoT services. First, due to the heterogeneity of hardware devices and application scenarios, the interoperability and compatibility between link-layer protocols, sub-systems and back-end services are significantly challenging. Second, the device management requires a uniform scheme to implement the commissioning, communication, authorization and identity management to guarantee security. Last, the heterogeneity of data format, speed and storage mechanism for different services pose a challenge to further data mining.

This thesis aims to solve these aforementioned challenges by proposing a data-centric IoT framework based on public cloud platforms. It targets at providing a universal architecture to facilitate the deployment of IoT services in massive IoT and broadband IoT categories. The framework involves three representative communication protocols, namely WiFi, Thread and Lo-RaWAN, to enable support for local, personal, and wide area networks. A security assessment taxonomy for wireless communications in building automation networks is proposed as a tool to evaluate the security performance of adopted protocols, so as to mitigate potential network flaws and guarantee the security. Azure cloud platform is adopted in the framework to provide device management, data processing and storage, visualization, and intelligent services, thanks to the mature cloud infrastructure and the uniform device model and data model. We also exhibit the value of the study by applying the framework into the digitalization procedure of the green plant wall industry. Based on the framework, a remote monitoring and management system for green plant wall is developed as a showcase to validate the feasibility. Furthermore, three specialized visualization methods are proposed and a neuron network-based anomaly detection method is deployed in the project, showing the potential of the framework in terms of data analytics and intelligence.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 43
Series
Linköping Studies in Science and Technology. Licentiate Thesis, ISSN 0280-7971 ; 1850
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-159770 (URN)10.3384/lic.diva-159770 (DOI)9789175190136 (ISBN)
Presentation
2019-09-13, K3, Kåkenhus, Campus Norrköping, Norrköping, 10:15 (English)
Opponent
Supervisors
Available from: 2019-08-21 Created: 2019-08-21 Last updated: 2019-08-26Bibliographically approved

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