scholarly journals Port Digitalization with Open Data: Challenges, Opportunities, and Integrations

2019 ◽  
Vol 5 (2) ◽  
pp. 30 ◽  
Author(s):  
Tommi Inkinen ◽  
Reima Helminen ◽  
Janne Saarikoski
Keyword(s):  
Real Time ◽  
Open Data ◽  
Traffic Monitoring ◽  
Transport Infrastructure ◽  
Digital Data ◽  
Time Data ◽  
Application Development ◽  
Technical Requirements ◽  
Starting Point ◽  
Study Results

Digitalization is frequently addressed in recent economic and social scientific literature. This paper applies a distinction to digital data (raw data) and digital technologies (including both software platforms and hardware solutions). The open data is defined as follows: it is publicly available and non-chargeable data (information content) that is machine readable. Open data enables software and application development for external partners and users. A common feature in open-data applications is location-based identification (e.g., real-time traffic monitoring). These include spatial map visualizations, and monitoring of traffic and modes of transport. This visualized information provides additional support for data-based decision-making and management as these study results indicate. This information is valuable particularly in the decisions concerning unconventional and sudden events. This research indicates that the most suitable data resources for opening include information related to port transport infrastructure. In terms of temporal monitoring, static road and rail data is currently the most potential alternative for open data in ports. The main reasons are that these data sources are already at least partly published. However, they are not always in open-data formats. Static data is also a grounded starting point because the technical requirements are much less demanding in comparison to real-time data-processing and management

scholarly journals Smarter Open Government Data for Society 5.0: Are Your Open Data Smart Enough?

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5204
Author(s):  
Anastasija Nikiforova
Keyword(s):  
Industry 4.0 ◽  
Economic Value ◽  
Open Data ◽  
Digital Data ◽  
Open Government ◽  
Data Sets ◽  
Time Data ◽  
Open Government Data ◽  
Information And Communication ◽  
Government Data

Nowadays, governments launch open government data (OGD) portals that provide data that can be accessed and used by everyone for their own needs. Although the potential economic value of open (government) data is assessed in millions and billions, not all open data are reused. Moreover, the open (government) data initiative as well as users’ intent for open (government) data are changing continuously and today, in line with IoT and smart city trends, real-time data and sensor-generated data have higher interest for users. These “smarter” open (government) data are also considered to be one of the crucial drivers for the sustainable economy, and might have an impact on information and communication technology (ICT) innovation and become a creativity bridge in developing a new ecosystem in Industry 4.0 and Society 5.0. The paper inspects OGD portals of 60 countries in order to understand the correspondence of their content to the Society 5.0 expectations. The paper provides a report on how much countries provide these data, focusing on some open (government) data success facilitating factors for both the portal in general and data sets of interest in particular. The presence of “smarter” data, their level of accessibility, availability, currency and timeliness, as well as support for users, are analyzed. The list of most competitive countries by data category are provided. This makes it possible to understand which OGD portals react to users’ needs, Industry 4.0 and Society 5.0 request the opening and updating of data for their further potential reuse, which is essential in the digital data-driven world.

Applications of Subseasonal-to-Seasonal Forecasts: Progress and Future Plans

2021 ◽  
Author(s):  
Christopher White ◽  
Joanne Robbins ◽  
Daniela Domeisen ◽  
Andrew Robertson
Keyword(s):  
Real Time ◽  
Disaster Preparedness ◽  
Best Practice ◽  
Focal Point ◽  
Global Network ◽  
Seasonal Forecasts ◽  
Time Data ◽  
Application Development ◽  
User Communities ◽  
New Generation

<p>Subseasonal-to-seasonal (S2S) forecasts are bridging the gap between weather forecasts and long-range predictions. Decisions in various sectors are made in this forecast timescale, therefore there is a strong demand for this new generation of predictions. While much of the focus in recent years has been on improving forecast skill, if S2S predictions are to be used effectively, it is important that along with scientific advances, we also learn how best to develop, communicate and apply these forecasts.</p><p>In this paper, we present recent progress in the applications of S2S forecasts, and provide an overview of ongoing and emerging activities and initiatives from across the wider weather and climate applications and user communities, as follows:</p><ul><li>To support an increased focus on applications, an additional science sub-project focused on S2S applications has been launched on the World Meteorological Organization WWRP-WCRP S2S Prediction Project: http://s2sprediction.net/. This sub-project will provide a focal point for research focused towards S2S applications by exploring the value of applications-relevant S2S forecasts and highlighting the opportunities and challenges facing their uptake.</li> <li>Also supported by the S2S Prediction Project, the ongoing Real-Time Pilot initiative http://s2sprediction.net/file/documents_reports/16Projects.pdf is making S2S forecasts available to 15 selected projects that are addressing user needs over a two year period (November 2019 through to November 2021). By making this real-time data available, the initiative is drawing on the collective experiences of the researcher and user communities from across the projects. The Real-Time Pilot will develop best practice guidelines for producing useful and useable, application-orientated forecasts and tools that can be used to guide future S2S application development. We will present an update on the initiative, including results from an initial set of questionnaires that focussed on engagement strategies and practices, supporting a review of how projects were designs, the roles and responsibilities of different project participants and the methods used to determine project success.</li> <li>To increase the uptake and use of S2S forecasts more widely across the research and user communities, we present a new initiative: a global network of researchers, modellers and practitioners focused on S2S applications, called S2Sapp.net – a community with a shared aim of exploring and promoting cross-sectoral services and applications of this new generation of predictions.</li> <li>Finally, we will provide an update on a recently-submitted applications community review paper, covering sectoral applications of S2S predictions, including public health, disaster preparedness, water management, energy and agriculture. Drawing from the experience of researchers and users working with S2S forecasts, we explore the value of applications-relevant S2S predictions through a series of sectoral cases where uptake is starting to occur.</li> </ul>

scholarly journals Semantic Traffic Sensor Data: The TRAFAIR Experience

2020 ◽  
Vol 10 (17) ◽  
pp. 5882
Author(s):  
Federico Desimoni ◽  
Sergio Ilarri ◽  
Laura Po ◽  
Federica Rollo ◽  
Raquel Trillo-Lado
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Smart Cities ◽  
Low Cost ◽  
Semantic Annotation ◽  
Open Data ◽  
Transportation Systems ◽  
Sensor Data ◽  
Time Data ◽  
Future Evolution

Modern cities face pressing problems with transportation systems including, but not limited to, traffic congestion, safety, health, and pollution. To tackle them, public administrations have implemented roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. In the case of traffic sensor data not only the real-time data are essential, but also historical values need to be preserved and published. When real-time and historical data of smart cities become available, everyone can join an evidence-based debate on the city’s future evolution. The TRAFAIR (Understanding Traffic Flows to Improve Air Quality) project seeks to understand how traffic affects urban air quality. The project develops a platform to provide real-time and predicted values on air quality in several cities in Europe, encompassing tasks such as the deployment of low-cost air quality sensors, data collection and integration, modeling and prediction, the publication of open data, and the development of applications for end-users and public administrations. This paper explicitly focuses on the modeling and semantic annotation of traffic data. We present the tools and techniques used in the project and validate our strategies for data modeling and its semantic enrichment over two cities: Modena (Italy) and Zaragoza (Spain). An experimental evaluation shows that our approach to publish Linked Data is effective.

SUPDUT: An Environment to Implement Logic Control Applications for Pipelines

2002 ◽  
Author(s):  
Luiz F. de J. Bernardo ◽  
Eliane A. Cid ◽  
Paulo de T. A. Correia ◽  
Ruy L. Milidiu´ ◽  
Frederico dos S. Liporace
Keyword(s):  
Real Time ◽  
Distributed Applications ◽  
Time Data ◽  
Application Development ◽  
Software Environment ◽  
Minimal Impact ◽  
Development Organization ◽  
Object Oriented Design ◽  
Wide Range ◽  
New Applications

The reliable operation of product transfers in pipelines is essential to the economic results of a pipeline company. This operation heavily depends on calculations performed over real time raw and historical data to assure the expected level of confidence in the operational results. This paper describes the development of a software environment, SUPDUT (abbreviation for the portuguese term Supervisor de Oleodutos, or Pipeline Supervisor), to be used in the development, organization, execution and maintenance of operational applications and to support their communication with other corporate and basic real time systems (SCADA). Application in this context means all kinds of operational or corporate calculations that require information from SCADA. The main advantage of the SUPDUT architecture is that it simplifies the application development and maintenance process, by providing a server that deals with all the complexity related to SCADA communication and application scheduling. The application developer therefore does not need to be concerned with those issues. It also makes the application development independent from the SCADA that collects real time data. The environment is designed to facilitate a simple and rapid implementation of new applications with a minimal impact on the system. Other important SUPDUT environment features are: complete object-oriented design, planned support for distributed applications and reliable application scheduling, support for a wide range of application scheduling options, support for multiple SCADA, support for multiple languages for application development (FORTRAN, C, C++ and Java) and robustness to the addition of new applications. The SUPDUT environment requirements definition and design are completed, and it is in its coding phase as this paper is being written. The first production version of the software is expected to be delivered by the end of 2002.

scholarly journals Landslide Geohazard Monitoring, Early Warning and Stabilization Control Methods

2014 ◽  
Vol 36 (1) ◽  
pp. 3-13 ◽  
Author(s):  
Zbigniew Bednarczyk
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Warning System ◽  
Landslide Monitoring ◽  
High Plasticity ◽  
Monitoring Methods ◽  
Time Data ◽  
Stabilization Control ◽  
Starting Point ◽  
On Line

Abstract This paper is a presentation of landslide monitoring, early warning and remediation methods recommended for the Polish Carpathians. Instrumentation included standard and automatic on-line measurements with the real-time transfer of data to an Internet web server. The research was funded through EU Innovative Economy Programme and also by the SOPO Landslide Counteraction Project. The landslides investigated were characterized by relatively low rates of the displacements. These ranged from a few millimetres to several centimetres per year. Colluviums of clayey flysch deposits were of a soil-rock type with a very high plasticity and moisture content. The instrumentation consisted of 23 standard inclinometers set to depths of 5-21 m. The starting point of monitoring measurements was in January 2006. These were performed every 1-2 months over the period of 8 years. The measurements taken detected displacements from several millimetres to 40 cm set at a depth of 1-17 m. The modern, on-line monitoring and early warning system was installed in May 2010. The system is the first of its kind in Poland and only one of several such real-time systems in the world. The installation was working with the Local Road Authority in Gorlice. It contained three automatic field stations for investigation of landslide parameters to depths of 12-16 m and weather station. In-place tilt transducers and innovative 3D continuous inclinometer systems with sensors located every 0.5 m were used. It has the possibility of measuring a much greater range of movements compared to standard systems. The conventional and real-time data obtained provided a better recognition of the triggering parameters and the control of geohazard stabilizations. The monitoring methods chosen supplemented by numerical modelling could lead to more reliable forecasting of such landslides and could thus provide better control and landslide remediation possibilities also to stabilization works which prevent landslides.

scholarly journals Analysis of fractional factor system for data transmission in SDN

2019 ◽  
Vol 4 (1) ◽  
pp. 191-196 ◽  
Author(s):  
Jianzhang Wu ◽  
Jiabin Yuan ◽  
Wei Gao
Keyword(s):  
Real Time ◽  
Data Transmission ◽  
Sufficient Conditions ◽  
Traffic Monitoring ◽  
Data Traffic ◽  
Time Data ◽  
Real Time Data ◽  
Fractional Factor ◽  
Factor System

AbstractIn software definition networks, we allow transmission paths to be selected based on real-time data traffic monitoring to avoid congested channels. Correspondingly, this motivates us to study the existence of fractional factors in different settings. In this paper, we present several extend sufficient conditions for a graph admits ID-Hamiltonian fractional (g, f )factor. These results improve the conclusions originally published in the study by Gong et al. [2].

scholarly journals A Smart Decision System for Digital Farming

Agronomy ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 216 ◽  
Author(s):  
Carlos Cambra Baseca ◽  
Sandra Sendra ◽  
Jaime Lloret ◽  
Jesus Tomas
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Information Exchange ◽  
New Technologies ◽  
Open Data ◽  
Weather Conditions ◽  
Added Value ◽  
Aerial Images ◽  
Sampled Data ◽  
Application Development

New technologies have the potential to transform agriculture and to reduce environmental impact through a green revolution. Internet of Things (IoT)-based application development platforms have the potential to run farm management tools capable of monitoring real-time events when integrated into interactive innovation models for fertirrigation. Their capabilities must extend to flexible reconfiguration of programmed actions. IoT platforms require complex smart decision-making systems based on data-analysis and data mining of big data sets. In this paper, the advantages are demonstrated of a powerful tool that applies real-time decisions from data such as variable rate irrigation, and selected parameters from field and weather conditions. The field parameters, the index vegetation (estimated using aerial images), and the irrigation events, such as flow level, pressure level, and wind speed, are periodically sampled. Data is processed in a decision-making system based on learning prediction rules in conjunction with the Drools rule engine. The multimedia platform can be remotely controlled, and offers a smart farming open data network with shared restriction levels for information exchange oriented to farmers, the fertilizer provider, and agricultural technicians that should provide the farmer with added value in the form of better decision making or more efficient exploitation operations and management.

scholarly journals A traffic model aware of real time data

2016 ◽  
Vol 26 (03) ◽  
pp. 445-467 ◽  
Author(s):  
Rinaldo M. Colombo ◽  
Francesca Marcellini
Keyword(s):  
Real Time ◽  
Traffic Monitoring ◽  
Traffic Model ◽  
Monitoring Systems ◽  
Well Posedness ◽  
Time Data ◽  
Numerical Integrations ◽  
Real Time Data ◽  
Ill Posed ◽  
Gps Devices

Nowadays, traffic monitoring systems have access to real time data, e.g. through GPS devices. We propose a new traffic model able to take into account these data and, hence, able to describe the effects of unpredictable accidents. The well-posedness of this model is proved and numerical integrations show qualitative features of the resulting solutions. As a further motivation for the use of real time data, we show that the inverse problem for the Lighthill–Whitham and Richards (LWR) model is ill-posed.

Realistic Database for Semiconductor Device Analysis

1998 ◽  
Author(s):  
C.G. Kim ◽  
B.S. Sun ◽  
J.H. Koo ◽  
G.J. Jang ◽  
S.Y. Lee
Keyword(s):  
Real Time ◽  
Failure Modes ◽  
Semiconductor Device ◽  
Operation Time ◽  
Digital Data ◽  
Physical Analysis ◽  
Data Types ◽  
Time Data ◽  
Database Structure ◽  
Inspection Data

Abstract When one department performs extensive analysis, the need for common data within a database structure may be required. A realistic paperless database was developed to solve department needs. This database is carried out with the combination of a Client Module, Operation Module and Management Module. The Client Module includes on-line request for analysis, intensive query, retrieval of the analysis result with digital image and image processing. The Operation Module provides real-time digital data acquisition from the analysis equipment, which have the data types of image, text or graph and real-time data transmission to a dedicated server Digital Alpha 4100. The Management Module includes approval of the request for analysis from the Client Module, creation of reports about analysis results and statistical service for the subjects like failure modes in a device, operation time of equipment and so on. These modules allow multi-users to access the database through the Web on the Intranet. Our database can be also linked to the in-line database and the failure analysis with DRT SEM and physical analysis can become more effective with the use of in-line inspection data. This paper presents the framework of the database along with a technical description of the database implementation.

Leveraging Polio GIS platforms in the African Region for mitigating Covid-19 contact tracing challenges (Preprint)

2020 ◽  
Author(s):  
Godwin Ubong Akpan ◽  
Isah Mohammed Bello ◽  
Kebba Touray ◽  
Reuben Ngofa ◽  
Daniel Oyaole ◽  
...  
Keyword(s):  
Data Collection ◽  
Real Time ◽  
Critical Role ◽  
Open Data ◽  
Contact Tracing ◽  
Quality Data ◽  
Time Data ◽  
Outbreak Response ◽  
African Region ◽  
Health Crisis

BACKGROUND The growth of the novel coronavirus 2019 (COVID-19) pandemic in Africa is an urgent public health crisis. Estimated models project over 150,000 deaths and 4,600,000 hospitalizations in the first year of disease in the absence of adequate interventions. Electronic contact tracing, therefore, offers a critical role in decreasing COVID-19 transmission; yet if not conducted properly can rapidly become a bottleneck for synchronized data collection, case detection, and case management. While the continent is currently reporting relatively low COVID-19 cases, digitized contact tracing mechanisms are necessary for standardizing real-time reporting of new chains of infection to quickly reverse growing trends and halt the pandemic. OBJECTIVE The aim of this study is describing an effective contact tracing smartphone app developed with expertise and experience gained from the numerous digital apps that the Polio programme has used to successfully support disease surveillance and immunization assessment in the African Region. A secondary objective is to describe how we leveraged Polio GIS resources to enhance existing contact tracing solutions to be more efficient through the connection to real-time data visualization platforms. METHODS We propose the use of a hybrid Open Data Kit (ODK) electronic COVID-19 contact registra- tion form that automates contacts and follow-ups. A proof-of-concept form on ODK has been developed that integrates collected contact tracing information from multiple platforms to generate an interactive regional dashboard to monitor the COVID-19 response. Analytics outputs extrapolate key outbreak response indi- cators such as timeliness, completeness and outcomes of contact tracing including new positive cases. This system allows multiple outbreak outputs to be monitored including sources of new infection for immediate response with minimal disruption to existing contact tracing tools. RESULTS Standardized electronic registration of COVID-19 contacts and follow-up using ODK has en- hanced monitoring of contact tracing. Countries and communities have increased their capacity to track COVID-19 cases and contacts in the general population quickly based on the onset of signs or symptoms. Registered contacts for contact tracing are matched to their respective cases more efficiently and for con- tacts that can engage in self-reporting, the anonymity of self-reporting. The country-specific results suggest that higher adoption rates of the tools may result in better quality data on the pandemic and elicited better decisions for a response. CONCLUSIONS Our proposed contact tracing solution which uses ODK based tools on smartphones and visualization bridge systems presents a scalable and easy to implement solution, that collects and aggregates good quality contact data with geographic information that can help make spatial based decisions and preserves privacy while demonstrating the potential to help make better decisions in response to an epidemic or pandemic outbreak. This application has been applied to the current COVID-19 pandemic and can also be used for other epidemics or pandemics in the future, to achieve quality data collection for better decision making.

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