scholarly journals Towards an Open Data Framework for Body Sensor Networks Supporting Bluetooth Low Energy

2016 ◽  
Author(s):  
Ninoshka K. Singh ◽  
Darrell O Ricke
Keyword(s):  
Health Status ◽  
New Technologies ◽  
Emotional Health ◽  
Open Data ◽  
Data Access ◽  
Heterogeneous Data ◽  
Low Energy ◽  
Easy Access ◽  
Bluetooth Low Energy ◽  
Data Framework

AbstractMajor companies, healthcare professionals, the military, and other scientists and innovators are now sensing that fitness and health data from wearable biosensors will likely provide new discoveries and insights into physiological, cognitive, and emotional health status of an individual. Having the ability to collect, process, and correlate data simultaneously from a set of heterogonous biosensor sources may be a key factor in informing the development of new technologies for reducing health risks, improving health status, and possibly preventing and predicting disease. The challenge in achieving this is getting easy access to heterogeneous data from a set of disparate sensors in a single, integrated wearable monitoring system. Often times, the data recorded by commercial biosensing devices are contained within each manufacturer’s proprietary platform. Summary data is available for some devices as free downloads or included only in annual premium memberships. Access to raw measurements is generally unavailable, especially from a custom developed application that may include prototype biosensors. In this paper, we explore key ideas on how to leverage the design features of Bluetooth Low Energy to ease the integration of disparate biosensors at the sensor communication layer. This component is intended to fit into a larger, multi-layered, open data framework that can provide additional data management and analytics capabilities for consumers and scientists alike at all the layers of a data access model which is typically employed in a body sensor network system.

scholarly journals A Framework Uniting Ontology-Based Geodata Integration and Geovisual Analytics

2020 ◽  
Vol 9 (8) ◽  
pp. 474
Author(s):  
Linfang Ding ◽  
Guohui Xiao ◽  
Diego Calvanese ◽  
Liqiu Meng
Keyword(s):  
Data Integration ◽  
Visual Analysis ◽  
Open Data ◽  
Data Access ◽  
Heterogeneous Data ◽  
Geospatial Data ◽  
Making Sense ◽  
Research Areas ◽  
Geovisual Analytics ◽  
Integration Techniques

In a variety of applications relying on geospatial data, getting insights into heterogeneous geodata sources is crucial for decision making, but often challenging. The reason is that it typically requires combining information coming from different sources via data integration techniques, and then making sense out of the combined data via sophisticated analysis methods. To address this challenge we rely on two well-established research areas: data integration and geovisual analytics, and propose to adopt an ontology-based approach to decouple the challenges of data access and analytics. Our framework consists of two modules centered around an ontology: (1) an ontology-based data integration (OBDI) module, in which mappings specify the relationship between the underlying data and a domain ontology; (2) a geovisual analytics (GeoVA) module, designed for the exploration of the integrated data, by explicitly making use of standard ontologies. In this framework, ontologies play a central role by providing a coherent view over the heterogeneous data, and by acting as a mediator for visual analysis tasks. We test our framework in a scenario for the investigation of the spatiotemporal patterns of meteorological and traffic data from several open data sources. Initial studies show that our approach is feasible for the exploration and understanding of heterogeneous geospatial data.

scholarly journals Handling qualitative preferences in SPARQL over virtual ontology-based data access

Semantic Web ◽  
2022 ◽  
pp. 1-24
Author(s):  
Marlene Goncalves ◽  
David Chaves-Fraga ◽  
Oscar Corcho
Keyword(s):  
Open Data ◽  
Scoring Function ◽  
Data Access ◽  
Heterogeneous Data ◽  
Database Management System ◽  
Query Complexity ◽  
Distribution Data ◽  
Preference Queries ◽  
Preference Criteria ◽  
Qualitative Preferences

With the increase of data volume in heterogeneous datasets that are being published following Open Data initiatives, new operators are necessary to help users to find the subset of data that best satisfies their preference criteria. Quantitative approaches such as top-k queries may not be the most appropriate approaches as they require the user to assign weights that may not be known beforehand to a scoring function. Unlike the quantitative approach, under the qualitative approach, which includes the well-known skyline, preference criteria are more intuitive in certain cases and can be expressed more naturally. In this paper, we address the problem of evaluating SPARQL qualitative preference queries over an Ontology-Based Data Access (OBDA) approach, which provides uniform access over multiple and heterogeneous data sources. Our main contribution is Morph-Skyline++, a framework for processing SPARQL qualitative preferences by directly querying relational databases. Our framework implements a technique that translates SPARQL qualitative preference queries directly into queries that can be evaluated by a relational database management system. We evaluate our approach over different scenarios, reporting the effects of data distribution, data size, and query complexity on the performance of our proposed technique in comparison with state-of-the-art techniques. Obtained results suggest that the execution time can be reduced by up to two orders of magnitude in comparison to current techniques scaling up to larger datasets while identifying precisely the result set.

scholarly journals Open Government Data: Fostering Innovation

2014 ◽  
Vol 6 (1) ◽  
pp. 69-79 ◽  
Author(s):  
Ivan Bedini ◽  
Feroz Farazi ◽  
David Leoni ◽  
Juan Pane ◽  
Ivan Tankoyeu ◽  
...  
Keyword(s):  
Diffusion Of Innovation ◽  
New Technologies ◽  
Open Data ◽  
Public Information ◽  
Heterogeneous Data ◽  
Data Reuse ◽  
Operational Mode ◽  
Open Government Data ◽  
Government Data ◽  
The Government

The provision of public information contributes to the enrichment and enhancement of the data produced by the government as part of its activities, and the transformation of heterogeneous data into information and knowledge. This process of opening changes the operational mode of public administrations, leveraging the data management, encouraging savings and especially in promoting the development of services in subsidiary and collaborative form between public and private entities. The demand for new services also promotes renewed entrepreneurship centred on responding to new social and territorial needs through new technologies. In this sense we speak of Open Data as an enabling infrastructure for the development of innovation and as an instrument to the development and diffusion of Innovation and Communications Technology (ICT) in the public system as well as creating space for innovation for businesses, particularly SMEs, based on the exploitation of information assets of the territory. The Open Data Trentino Project has initiated and fosters the process of opening of public information and develops as a natural consequence of this process of openness, the creation of innovative services for and with the citizens. In this paper we present how our project acts on long-chain, from raw data till reusable meaningful and scalable knowledge base that leads to the production of data reuse through the implementation of services that will enhance and transform the data into information capable of responding to specific questions efficiency and innovation.

The Factors of the Holistic Health Status of Thai Elders in the 21st Century

2020 ◽  
Vol 13 ◽  
Author(s):  
Manyat Ruchiwit ◽  
Kanjanee Phanphairoj ◽  
Tipsuda Sumneangsanor ◽  
Jinpitcha Mamom
Keyword(s):  
Health Status ◽  
21St Century ◽  
Emotional Health ◽  
Holistic Health ◽  
Alpha Coefficient ◽  
Factors Affecting ◽  
Stress Prevention ◽  
The Social ◽  
Whole Person

Background: Holistic health is important to life, perhaps especially for elders. Focus should not only be placed on illness or the physical part of their lives, but the whole person should also be considered, emphasizing the connection of their mind, body, and the environment. Objective: The aims of this research were to study the factors of the holistic health status (HHS) of the Thai elderly in the 21st century, and to predict the factors affecting the development of HHS in 3 aspects; physical health status, mental and emotional health status, and the social and environmental health status. Method: The data were collected from 928 Thai elderly aged 60 and over in the central part of Thailand. The research instrument was a questionnaire whose reliability was confirmed using a Cronbach alpha coefficient of .904. Multiple regression analysis was used for predicting the factors of HHS. Results: The results indicated that stress, increased age, gender, and social participation can predict the HHS of Thai elders, and stress can predict each 3 aspects. Therefore, stress prevention activities are very important for enhancing the HHS of Thai elders. Conclusion: The findings of this research can be used to improve the quality of life of elders in the 21st century.

RFID, NFC, Beacons, and the Infrastructures of Logistical Locative Media

2020 ◽  
pp. 474-486
Author(s):  
Jordan Frith
Keyword(s):  
Internet Of Things ◽  
Radio Frequency Identification ◽  
Near Field ◽  
Low Energy ◽  
Near Field Communication ◽  
Rfid Tags ◽  
Bluetooth Low Energy ◽  
Locative Media ◽  
Frequency Identification ◽  
Machine Readable

The phrase the Internet of things was originally coined in a 1999 presentation about attaching radio frequency identification (RFID) tags to individual objects. These tags would make the objects machine-readable, uniquely identifiable, and, most importantly, wirelessly communicative with infrastructure. This chapter evaluates RFID as a piece of mobile communicative infrastructure, and it examines two emerging forms: near-field communication (NFC) and Bluetooth low-energy beacons. The chapter shows how NFC and Bluetooth low-energy beacons may soon move some types of RFID to smartphones, in this way evolving the use of RFID in payment and transportation and enabling new practices of post-purchasing behaviors.

Bluetooth Low Energy-based Angle of Arrival Estimation in Presence of Rayleigh Fading

2020 ◽  
Author(s):  
Zohreh Hajiakhondi-Meybodi ◽  
Mohammad Salimibeni ◽  
Arash Mohammadi ◽  
Konstantinos N. Plataniotis
Keyword(s):  
Rayleigh Fading ◽  
Low Energy ◽  
Angle Of Arrival ◽  
Bluetooth Low Energy
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