MODULARITY Applied to SMART HOME

Ursuțiu, Doru; Neagu, Andrei; Samoilă, Cornel; Jinga, Vlad

doi:10.1007/978-3-319-64352-6_6

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…"Modularization of Smart Home Products" consists of six items which draw lessons from previous research on modular product development of the smart home [18,66]. Modularization can expand functions through wireless connection [66]. Modularity can complete more complex functions by adding products [18].…”

Section: Questionnaire Designmentioning

confidence: 99%

Services on Platform Ecosystems in the Smart Home 2.0 Era: Elements Influencing Consumers’ Value Perception for Smart Home Products

Tang

Inoue

2021

Sensors

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Recently, smart home products have shown signs of rapid development and increasing awareness of smart home platforms. In order to make smart home enterprises enter the era of Smart Home 2.0, it is necessary to consider the elements related to smart home platforms. This study examines the relationship between consumers’ value perception and the platform ecosystem theory and how this relationship contributes to their perception of smart home products’ value. This study aims to reveal the influence of smart home platform elements on the value perception of consumers regarding consumers’ perception of the smart home products’ value. To achieve this goal, an online survey (n = 595) was implemented to collect data from Japanese respondents. The analytical results presented in this study indicated that consumers, who sense the value of modularization of smart home products and inter-consumer connectivity, can sense the value of smart home products. In addition, consumers who can perceive the value of a platform service can indirectly feel the value of smart home products through modularity and inter-consumer connectivity. The results presented in this study provide new insights into product development in Smart Home 2.0.

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Section: Questionnaire Designmentioning

confidence: 99%

Services on Platform Ecosystems in the Smart Home 2.0 Era: Elements Influencing Consumers’ Value Perception for Smart Home Products

Tang

Inoue

2021

Sensors

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“…The maximum number of nodes in one IQRF R network is 240 devices, including the coordinator [7,28]. In the article [29] which deals about smart home monitoring system, they use XBee technology for individual sensors. At the end of this article, the authors argue that by replacing this communication technology with IQRF R technology, they have managed to reduce the power consumption of each wireless sensor node by 20% at the same coverage.…”

Section: Carbon Dioxide Measurement Devicementioning

confidence: 99%

Design, Implementation and Data Analysis of an Embedded System for Measuring Environmental Quantities

Pies

Hajovsky

Velicka

2020

Sensors

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The article describes the development and implementation of a complex monitoring system for measuring the concentration of carbon dioxide, ambient temperature, relative humidity and atmospheric pressure. The presented system was installed at two locations. The first was in the rooms at the Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VŠB-Technical University of Ostrava. The second was in the classrooms of the Grammar School and Secondary School of Electrical Engineering and Computer Science in Frenštát pod Radhoštěm. The article contains a detailed description of the entire measurement network, whose basic component was a device for measuring carbon dioxide concentration, temperature and relative humidity in ambient air and atmospheric pressure via wireless data transmission using IQRF® technology. Measurements were conducted continuously for several months. The data were archived in a database. The article also describes the methods for processing the data with statistical analysis. Carbon dioxide concentration was selected for data analysis. Data were selected from at least two different rooms at each location. The processed results represent the time periods for the given carbon dioxide concentrations. The graphs display in percent how much of the time students or employees spent exposed to safe or dangerous concentrations of carbon dioxide. The collected data were used for the future improvement of air quality in the rooms.

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“…IQRF is a cost-effective IoT wireless technology that enables low-power connectivity. Its efficiency in IoT applications has been addressed by many studies in the literature [11][12][13][14][15][16]. Additionally, its usability in smart city applications is discussed by evaluating its network coverage performance in outdoor environments [17].…”

Section: Introductionmentioning

confidence: 99%

Indoor Propagation Analysis of IQRF Technology for Smart Building Applications

et al. 2022

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Owing to its efficiency in the Internet of Things (IoT) applications in terms of low-power connectivity, IQRF (Intelligent Connectivity using Radio Frequency) technology appears to be one of the most reasonable IoT technologies in the commercial market. To realize emerging smart building applications using IQRF, it is necessary to study the propagation characteristics of IQRF technology in indoor environments. In this study, preliminary propagation measurements are conducted using IQRF transceivers that operate on the 868 MHz band in a peer-to-peer (P2P) configured system. The measurements are conducted both in a single corridor of a building in a Line-of-Sight (LoS) link and two perpendicular corridors in a Non-Line-of-Sight (NLoS) with one single knife-edge link. Moreover, the measured path loss values are compared with the predicted path loss values in order to comparatively assess the prediction accuracy of the well-known empirical models, such as log-distance, ITU, and WINNER II. According to the results, it is concluded that the ITU-1 path loss model agrees well with the measurements and could be used in the planning of an IQRF network deployment in a typical LoS corridor environment. For NLoS corridors, both ITU-3 and WINNERII-2 models could be used due to their higher prediction accuracy. We expect that the initial results achieved in this study could open new perspectives for future research on the development of smart building applications.

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MODULARITY Applied to SMART HOME

Cited by 5 publications

References 2 publications

Services on Platform Ecosystems in the Smart Home 2.0 Era: Elements Influencing Consumers’ Value Perception for Smart Home Products

Services on Platform Ecosystems in the Smart Home 2.0 Era: Elements Influencing Consumers’ Value Perception for Smart Home Products

Design, Implementation and Data Analysis of an Embedded System for Measuring Environmental Quantities

Indoor Propagation Analysis of IQRF Technology for Smart Building Applications

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