scholarly journals SPATIAL DATA INTEGRATION USING ONTOLOGY-BASED APPROACH

2015 ◽  
Vol XL-1-W5 ◽  
pp. 293-296 ◽  
Author(s):  
S. Hasani ◽  
A. Sadeghi-Niaraki ◽  
M. Jelokhani-Niaraki
Keyword(s):  
Data Integration ◽  
Real Time ◽  
Spatial Data ◽  
Service Oriented Architecture ◽  
Low Cost ◽  
Time Integration ◽  
Semantic Heterogeneity ◽  
Sources Of Information ◽  
Time Data ◽  
Service Oriented

In today's world, the necessity for spatial data for various organizations is becoming so crucial that many of these organizations have begun to produce spatial data for that purpose. In some circumstances, the need to obtain real time integrated data requires sustainable mechanism to process real-time integration. Case in point, the disater management situations that requires obtaining real time data from various sources of information. One of the problematic challenges in the mentioned situation is the high degree of heterogeneity between different organizations data. To solve this issue, we introduce an ontology-based method to provide sharing and integration capabilities for the existing databases. In addition to resolving semantic heterogeneity, better access to information is also provided by our proposed method. Our approach is consisted of three steps, the first step is identification of the object in a relational database, then the semantic relationships between them are modelled and subsequently, the ontology of each database is created. In a second step, the relative ontology will be inserted into the database and the relationship of each class of ontology will be inserted into the new created column in database tables. Last step is consisted of a platform based on service-oriented architecture, which allows integration of data. This is done by using the concept of ontology mapping. The proposed approach, in addition to being fast and low cost, makes the process of data integration easy and the data remains unchanged and thus takes advantage of the legacy application provided.

scholarly journals Development of geoportal for landslide monitoring

2012 ◽  
Vol 92 (4) ◽  
pp. 63-78
Author(s):  
Dubravka Sladic ◽  
Milan Vrtunski ◽  
Ivan Alargic ◽  
Aleksandra Ristic ◽  
Dusan Petrovacki
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
Service Oriented Architecture ◽  
Reference Value ◽  
Landslide Monitoring ◽  
Alert System ◽  
Service Oriented ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures

The paper presents the implementation of geoportal for landslide monitoring which which includes two subsystems: a system for acquisition, storage and distribution of data on landslides and real time alert system. System for acquisition, storage and distribution of data on landslides include raster and vector spatial data on landslides affected areas, as well as metadata. Alert system in real time is associated with a sensor for detecting displacement, which performs constant measurements and signals in case of exceeding the reference value. The system was developed in accordance with the standards in the field of GIS: ISO 19100 series of standards and OpenGIS Consortium and is based on service-oriented architecture and principles of spatial data infrastructures.

scholarly journals An adaptive and real-time based architecture for financial data integration

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Noussair Fikri ◽  
Mohamed Rida ◽  
Noureddine Abghour ◽  
Khalid Moussaid ◽  
Amina El Omri
Keyword(s):  
Data Integration ◽  
Data Processing ◽  
Real Time ◽  
Reporting Quality ◽  
Financial Data ◽  
Semantic Heterogeneity ◽  
Time Data ◽  
Analysis Process ◽  
Short Time ◽  
Time Frames

Abstract In this paper we are proposing an adaptive and real-time approach to resolve real-time financial data integration latency problems and semantic heterogeneity. Due to constraints that we have faced in some projects that requires real-time massive financial data integration and analysis, we decided to follow a new approach by combining a hybrid financial ontology, resilient distributed datasets and real-time discretized stream. We create a real-time data integration pipeline to avoid all problems of classic Extract-Transform-Load tools, which are data processing latency, functional miscomprehensions and metadata heterogeneity. This approach is considered as contribution to enhance reporting quality and availability in short time frames, the reason of the use of Apache Spark. We studied Extract-Transform-Load (ETL) concepts, data warehousing fundamentals, big data processing technics and oriented containers clustering architecture, in order to replace the classic data integration and analysis process by our new concept resilient distributed DataStream for online analytical process (RDD4OLAP) cubes which are consumed by using Spark SQL or Spark Core basics.

Preventing Health Risks Caused by Unhealthy Air Quality Using a CEP-Based SOA 2.0

2017 ◽  
pp. 170-196
Author(s):  
Juan Boubeta-Puig ◽  
Guadalupe Ortiz ◽  
Inmaculada Medina-Bulo
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Health Risks ◽  
Service Oriented Architecture ◽  
Life Quality ◽  
End Users ◽  
Quality Information ◽  
Time Data ◽  
Service Oriented ◽  
User Friendly

Air quality has been a recurrent issue in recent years since it can seriously impact citizens' health and their life quality. Nowadays, the different ways to provide end users with air quality information do not provide real-time data and lack accessibility. Besides, they do not automatically adapt to the particular circumstances of each citizen. In this chapter, an event-driven service-oriented architecture is proposed for detecting air quality changes in real time as well as making this information available to end users in a user-friendly way, notifying them with customized alerts upon detecting any potentially hazardous level for their health, thereby helping to prevent health risks.

scholarly journals PEMODELAN INTEGRASI NEARLY REAL TIME DATA WAREHOUSE DENGAN SERVICE ORIENTED ARCHITECTURE UNTUK MENUNJANG SISTEM INFORMASI RETAIL

2015 ◽  
Vol 14 (2) ◽  
pp. 11
Author(s):  
I Made Dwi Jendra Sulastra ◽  
Made Sudarma ◽  
I Nyoman Satya Kumara
Keyword(s):  
Information Systems ◽  
Web Service ◽  
Real Time ◽  
Data Warehouse ◽  
Service Oriented Architecture ◽  
Time Data ◽  
Real Time Data ◽  
Service Oriented ◽  
Design Integration ◽  
Source Table

Updates the data in the data warehouse is not traditionally done every transaction. Retail information systems require the latest data and can be accessed from anywhere for business analysis needs. Therefore, in this study will be made data warehouse model that is able to produce the information near real time, and can be accessed from anywhere by end users application. Modeling design integration of nearly real time data warehouse (NRTDWH) with a service oriented architecture (SOA) to support the retail information system is done in two stages. In the first stage will be designed modeling NRTDWH using Change Data Capture (CDC) based Transaction Log. In the second stage will be designed modeling NRTDWH integration with SOA-based web service. Tests conducted by a simulation test applications. Test applications used retail information systems, web-based web service client, desktop, and mobile. Results of this study were (1) ETL-based CDC captures changes to the source table and then store it in the database NRTDWH with the help of a scheduler; (2) Middleware web service makes 6 service based on data contained in the database NRTDWH, and each of these services accessible and implemented by the web service client.

Real-time data integration of an internet-of-things-based smart warehouse: a case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ammar Mohamed Aamer ◽  
Chelinka Rafiesta Sahara
Keyword(s):  
Internet Of Things ◽  
Data Integration ◽  
Real Time ◽  
Inventory Management ◽  
Radio Frequency Identification ◽  
Low Cost ◽  
Future Research ◽  
Time Data ◽  
Content Type ◽  
Real Time Data

Purpose Creating a real-time data integration when developing an internet-of-things (IoT)-based warehouse is still faced with challenges. It involves a diverse knowledge of novel technology and skills. This study aims to identify the critical components of the real-time data integration processes in IoT-based warehousing. Then, design and apply a data integration framework, adopting the IoT concept to enable real-time data transfer and sharing. Design/methodology/approach The study used a pilot experiment to verify the data integration system configuration. Radio-frequency identification (RFID) technology was selected to support the integration process in this study, as it is one of the most recognized products of IoT. Findings The experimentations’ results proved that data integration plays a significant role in structuring a combination of assorted data on the IoT-based warehouse from various locations in a real-time manner. This study concluded that real-time data integration processes in IoT-based warehousing could be generated into three significant components: configuration, databasing and transmission. Research limitations/implications While the framework in this research was carried out in one of the developing counties, this study’s findings could be used as a foundation for future research in a smart warehouse, IoT and related topics. The study provides guidelines for practitioners to design a low-cost IoT-based smart warehouse system to obtain more accurate and timely data to support the quick decision-making process. Originality/value The research at hand provides the groundwork for researchers to explore the proposed theoretical framework and develop it further to increase inventory management efficiency of warehouse operations. Besides, this study offers an economical alternate for an organization to implement the integration software reasonably.

scholarly journals Data integration by two-sensors in a LEAP-based Virtual Glove for human-system interaction

2021 ◽  
Author(s):  
Giuseppe Placidi ◽  
Danilo Avola ◽  
Luigi Cinque ◽  
Matteo Polsinelli ◽  
Eleni Theodoridou ◽  
...  
Keyword(s):  
Data Integration ◽  
Real Time ◽  
Vision System ◽  
Hand Tracking ◽  
Selection Strategy ◽  
Motion Sensors ◽  
Leap Motion ◽  
Time Data ◽  
Lower Velocity ◽  
Human System

AbstractVirtual Glove (VG) is a low-cost computer vision system that utilizes two orthogonal LEAP motion sensors to provide detailed 4D hand tracking in real–time. VG can find many applications in the field of human-system interaction, such as remote control of machines or tele-rehabilitation. An innovative and efficient data-integration strategy, based on the velocity calculation, for selecting data from one of the LEAPs at each time, is proposed for VG. The position of each joint of the hand model, when obscured to a LEAP, is guessed and tends to flicker. Since VG uses two LEAP sensors, two spatial representations are available each moment for each joint: the method consists of the selection of the one with the lower velocity at each time instant. Choosing the smoother trajectory leads to VG stabilization and precision optimization, reduces occlusions (parts of the hand or handling objects obscuring other hand parts) and/or, when both sensors are seeing the same joint, reduces the number of outliers produced by hardware instabilities. The strategy is experimentally evaluated, in terms of reduction of outliers with respect to a previously used data selection strategy on VG, and results are reported and discussed. In the future, an objective test set has to be imagined, designed, and realized, also with the help of an external precise positioning equipment, to allow also quantitative and objective evaluation of the gain in precision and, maybe, of the intrinsic limitations of the proposed strategy. Moreover, advanced Artificial Intelligence-based (AI-based) real-time data integration strategies, specific for VG, will be designed and tested on the resulting dataset.

scholarly journals Design of an IoT based Real Time Environment Monitoring System using Legacy Sensors

2018 ◽  
Vol 210 ◽  
pp. 03008
Author(s):  
Aparajita Das ◽  
Manash Pratim Sarma ◽  
Kandarpa Kumar Sarma ◽  
Nikos Mastorakis
Keyword(s):  
Air Pollution ◽  
Light Intensity ◽  
Real Time ◽  
Environmental Conditions ◽  
Low Cost ◽  
Environment Monitoring ◽  
Time Data ◽  
Graphical Information ◽  
Real Time Data ◽  
Sun Light

This paper describes the design of an operative prototype based on Internet of Things (IoT) concepts for real time monitoring of various environmental conditions using certain commonly available and low cost sensors. The various environmental conditions such as temperature, humidity, air pollution, sun light intensity and rain are continuously monitored, processed and controlled by an Arduino Uno microcontroller board with the help of several sensors. Captured data are broadcasted through internet with an ESP8266 Wi-Fi module. The projected system delivers sensors data to an API called ThingSpeak over an HTTP protocol and allows storing of data. The proposed system works well and it shows reliability. The prototype has been used to monitor and analyse real time data using graphical information of the environment.

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