Toward Self-monitoring Smart Cities: the OpenSense2 Approach

Calbimonte, Jean-Paul; Eberle, Julien; Aberer, Karl

doi:10.1007/s00287-016-1009-y

Cited by 12 publications

(4 citation statements)

References 19 publications

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“…People live in Smart Homes equipped with the latest high-tech gadgets for more comfortable and efficient living, while digital entertainment, information, and communication are permanently available via global data networks [18,19]. Municipalities are developing fully networked cities based on the example of Industry 4.0 [20], where full automation with sensor networks and intelligent control algorithms has proven to be advantageous for many reasons [21]. This makes the entire supply system of a city, as well as its mobility structure, just as smart as the intelligent vehicles that move in it [22].…”

Section: Introductionmentioning

confidence: 99%

Modern Technology in Geography Education—Attitudes of Pre-Service Teachers of Geography on Modern Technology

Bengel

Peter

2021

Education Sciences

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In this study, we focus on teachers’ attitudes to compare and evaluate their ability and readiness to implement technology education in geography lessons. First, the lack of suitable measuring instruments for our intent was identified, and we thus attempted to develop the Modern Technology Attitude Index (MTAI) for remedy. An exploratory factor analysis helped to identify three distinguishable dimensions that depict areas of intimidation (INT), loss of control (LOC), and benefits and easement (BAE), with or through modern technology. The scales were then applied to German university students (n = 357). As a result, the pre-service geography teachers (n = 72) showed higher scores on the affinity scale than on the two aversion scales. Their subject-specific interest correlated negatively with intimidation and positively with the perceived benefits and easements of modern technology, while the perceived loss of control showed no significant correlation. This allows for the conclusion that the subject’s technology-related interest has an influence on cognitive and behavioral attitudes, while this is not the case for affective ones. Further, there are indications that the much-discussed gender gap in technology topics might particularly be related to people’s affective attitudes, while cognitive and behavioral dimensions seem not to be affected. Differing results in other studies on whether the gender gap still exists or not could be due to the fact that, in addition to growing social awareness and a generational change, the measuring tools used may have not yet been able to depict a sufficiently diverse range of attitudes.

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Section: Introductionmentioning

confidence: 99%

Modern Technology in Geography Education—Attitudes of Pre-Service Teachers of Geography on Modern Technology

Bengel

Peter

2021

Education Sciences

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“…Challenges and solutions associated with implementing a semantic data management system for air quality monitoring in smart cities are the main focus of the OpenSense project [61]. This project aims to provide transparent access to air quality data by generating meaningful and semantically understandable data.…”

Section: Related Workmentioning

confidence: 99%

SEDIA: A Platform for Semantically Enriched IoT Data Integration and Development of Smart City Applications

Lymperis,

Goumopoulos

2023

Future Internet

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The development of smart city applications often encounters a variety of challenges. These include the need to address complex requirements such as integrating diverse data sources and incorporating geographical data that reflect the physical urban environment. Platforms designed for smart cities hold a pivotal position in materializing these applications, given that they offer a suite of high-level services, which can be repurposed by developers. Although a variety of platforms are available to aid the creation of smart city applications, most fail to couple their services with geographical data, do not offer the ability to execute semantic queries on the available data, and possess restrictions that could impede the development process. This paper introduces SEDIA, a platform for developing smart applications based on diverse data sources, including geographical information, to support a semantically enriched data model for effective data analysis and integration. It also discusses the efficacy of SEDIA in a proof-of-concept smart city application related to air quality monitoring. The platform utilizes ontology classes and properties to semantically annotate collected data, and the Neo4j graph database facilitates the recognition of patterns and relationships within the data. This research also offers empirical data demonstrating the performance evaluation of SEDIA. These contributions collectively advance our understanding of semantically enriched data integration within the realm of smart city applications.

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“…Many authors [6,19,[65][66][67][68] suggest that it is essential to implement a valid monitoring system in order to be able to identify in advance the flaws in the complex urban system. Risk mitigation depends on the internal capacity of the system to identify the risk promptly and implement proactive measures.…”

Section: Literature Reviewmentioning

confidence: 99%

A Partially Non-Compensatory Method to Measure the Smart and Sustainable Level of Italian Municipalities

2021

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A smart sustainable city (SSC) is a paradigm that encapsulates the latest lines of development in multiple fields of research. The attempt to converge towards a model of sustainable urban life, made difficult by increasing anthropic pressure and polluting activities conducted by man, is also reflected in the intentions of public institutions to take measures of environmental risk mitigation. The change towards more liveable cities must also include the adoption of more far-reaching measures in various sectors. The objective of our work was to provide an analysis in order to assess which of the Italian provincial municipalities were most closely related to the paradigm of SSCs. This aim was pursued through a comparison based on the results of a partially non-compensatory quantitative method, known as the Pena’s Distance method (DP2). The smartest and most sustainable cities, such as Siena, Milan and Padua, were not identified on the basis of common urban characteristics but rather derived from the combination of distinctive and functional elements in the pursuit of a strategic approach aimed at fully exploiting the resources of each area. Moreover, at a macro-geographical level, from the analysis emerged the presence of contiguous clusters, i.e., areas in which a major concentration of smart sustainable municipalities tended to form.

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Toward Self-monitoring Smart Cities: the OpenSense2 Approach

Cited by 12 publications

References 19 publications

Modern Technology in Geography Education—Attitudes of Pre-Service Teachers of Geography on Modern Technology

Modern Technology in Geography Education—Attitudes of Pre-Service Teachers of Geography on Modern Technology

SEDIA: A Platform for Semantically Enriched IoT Data Integration and Development of Smart City Applications

A Partially Non-Compensatory Method to Measure the Smart and Sustainable Level of Italian Municipalities

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