scholarly journals Towards a Consistent Measurement Stream Processing from Heterogeneous Data Sources

2017 ◽  
Vol 7 (6) ◽  
pp. 3164 ◽  
Author(s):  
Mario Diván ◽  
María de los Ángeles Martín
Keyword(s):  
Stream Processing ◽  
Heterogeneous Data ◽  
Geographic Information ◽  
Context Information ◽  
Practical Case ◽  
Information Need ◽  
Concept Model ◽  
Heterogeneous Data Sources ◽  
Measurement And Evaluation ◽  
Consistent Measurement

<span>In this work an updating of the C-INCAMI (Context-Information Need, Concept model, Attribute, Metric and Indicator) conceptual framework for Measurement and Evaluation projects was proposed. The updating incorporated better supporting for the measures stream processing. Therefore, a new version of the measurement interchange schema based on the updated C-INCAMI framework was introduced. This new schema incorporated the concept of “complementary data” linking them with geographic information. The complementary data could be associated with the measures and allowed us incorporating video, geographic information, text plain, audio or pictures with the quantitative measures (deterministic or estimated) jointly. A practical case associated with the Weather Radar of the Experimental Agricultural Station (EAS) INTA Anguil (Province of La Pampa, Argentina) was shown, indicating the advantages of the new schema.</span>

scholarly journals Air Quality Context Information Model for Ubiquitous Public Access to Geographic Information

2018 ◽  
Vol 7 (8) ◽  
pp. 316 ◽  
Author(s):  
Sungchul Hong
Keyword(s):  
Information System ◽  
Air Quality ◽  
Information Model ◽  
Heterogeneous Data ◽  
Geographic Information ◽  
Information Services ◽  
Public Access ◽  
Quality Information ◽  
Context Information ◽  
New Paradigm

The advance in Information Communication Technology (ICT) has contributed to global challenges of improving urban air quality. Ubiquitous computing technology enables citizens to easily access air quality information services without spatial or temporal limitations. Citizens are also encouraged to participate in air quality assessment and environmental governance. These societal and technical changes require a new paradigm to develop an air quality information system and its services. An air quality information system needs to integrate varied types of air quality information from heterogeneous data sources as well as allow citizens to express their concerns about air quality. Thus, a standardized manner is necessary to develop an air quality information system. In this regard, an air quality context information model was designed according to the Ubiquitous Public Access (UPA) context information model defined in the International Organization for Standard (ISO) 19154. For validation and verification purposes, the air quality context information model was implemented in a geographic information system (GIS)-based air quality information system. Implementation results showed that spatially relevant air quality information services were generated from the system, depending on the location and air quality situations near a specific user. Also, citizens can contribute air quality information at their current regions.

scholarly journals Accessible Routes Integrating Data from Multiple Sources

2020 ◽  
Vol 10 (1) ◽  
pp. 7
Author(s):  
Miguel R. Luaces ◽  
Jesús A. Fisteus ◽  
Luis Sánchez-Fernández ◽  
Mario Munoz-Organero ◽  
Jesús Balado ◽  
...  
Keyword(s):  
Information System ◽  
Data Model ◽  
Large Scale ◽  
Heterogeneous Data ◽  
Multiple Sources ◽  
Heterogeneous Data Sources ◽  
Different Types ◽  
Software Sensors ◽  
The City

Providing citizens with the ability to move around in an accessible way is a requirement for all cities today. However, modeling city infrastructures so that accessible routes can be computed is a challenge because it involves collecting information from multiple, large-scale and heterogeneous data sources. In this paper, we propose and validate the architecture of an information system that creates an accessibility data model for cities by ingesting data from different types of sources and provides an application that can be used by people with different abilities to compute accessible routes. The article describes the processes that allow building a network of pedestrian infrastructures from the OpenStreetMap information (i.e., sidewalks and pedestrian crossings), improving the network with information extracted obtained from mobile-sensed LiDAR data (i.e., ramps, steps, and pedestrian crossings), detecting obstacles using volunteered information collected from the hardware sensors of the mobile devices of the citizens (i.e., ramps and steps), and detecting accessibility problems with software sensors in social networks (i.e., Twitter). The information system is validated through its application in a case study in the city of Vigo (Spain).

scholarly journals Improving Sustainability of Smart Cities through Visualization Techniques for Big Data from IoT Devices

2020 ◽  
Vol 12 (14) ◽  
pp. 5595 ◽  
Author(s):  
Ana Lavalle ◽  
Miguel A. Teruel ◽  
Alejandro Maté ◽  
Juan Trujillo
Keyword(s):  
Big Data ◽  
Smart City ◽  
Smart Cities ◽  
Fire Department ◽  
Heterogeneous Data ◽  
Fire Extinguishing ◽  
Heterogeneous Data Sources ◽  
Iot Devices ◽  
Visualization Techniques ◽  
The Impact

Fostering sustainability is paramount for Smart Cities development. Lately, Smart Cities are benefiting from the rising of Big Data coming from IoT devices, leading to improvements on monitoring and prevention. However, monitoring and prevention processes require visualization techniques as a key component. Indeed, in order to prevent possible hazards (such as fires, leaks, etc.) and optimize their resources, Smart Cities require adequate visualizations that provide insights to decision makers. Nevertheless, visualization of Big Data has always been a challenging issue, especially when such data are originated in real-time. This problem becomes even bigger in Smart City environments since we have to deal with many different groups of users and multiple heterogeneous data sources. Without a proper visualization methodology, complex dashboards including data from different nature are difficult to understand. In order to tackle this issue, we propose a methodology based on visualization techniques for Big Data, aimed at improving the evidence-gathering process by assisting users in the decision making in the context of Smart Cities. Moreover, in order to assess the impact of our proposal, a case study based on service calls for a fire department is presented. In this sense, our findings will be applied to data coming from citizen calls. Thus, the results of this work will contribute to the optimization of resources, namely fire extinguishing battalions, helping to improve their effectiveness and, as a result, the sustainability of a Smart City, operating better with less resources. Finally, in order to evaluate the impact of our proposal, we have performed an experiment, with non-expert users in data visualization.

scholarly journals A multi-agent conversational system with heterogeneous data sources access

2016 ◽  
Vol 53 ◽  
pp. 172-191 ◽  
Author(s):  
Eduardo M. Eisman ◽  
María Navarro ◽  
Juan Luis Castro
Keyword(s):  
Heterogeneous Data ◽  
Data Sources ◽  
Heterogeneous Data Sources ◽  
Multi Agent
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