scholarly journals Towards Scalable Distributed Framework for Urban Congestion Traffic Patterns Warehousing

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
A. Boulmakoul ◽  
L. Karim ◽  
M. Mandar ◽  
A. Idri ◽  
A. Daissaoui
Keyword(s):  
Real Time ◽  
Moving Objects ◽  
Transportation Network ◽  
Transportation Systems ◽  
Added Value ◽  
Traffic Patterns ◽  
Cloud Infrastructure ◽  
Real Time Control ◽  
Time Data ◽  
Urban Network

We put forward architecture of a framework for integration of data from moving objects related to urban transportation network. Most of this research refers to the GPS outdoor geolocation technology and uses distributed cloud infrastructure with big data NoSQL database. A network of intelligent mobile sensors, distributed on urban network, produces congestion traffic patterns. Congestion predictions are based on extended simulation model. This model provides traffic indicators calculations, which fuse with the GPS data for allowing estimation of traffic states across the whole network. The discovery process of congestion patterns uses semantic trajectories metamodel given in our previous works. The challenge of the proposed solution is to store patterns of traffic, which aims to ensure the surveillance and intelligent real-time control network to reduce congestion and avoid its consequences. The fusion of real-time data from GPS-enabled smartphones integrated with those provided by existing traffic systems improves traffic congestion knowledge, as well as generating new information for a soft operational control and providing intelligent added value for transportation systems deployment.

scholarly journals Vision based hardware-software real-time control system for autonomous landing of an UAV

2020 ◽  
Author(s):  
Krzysztof Blachut ◽  
Hubert Szolc ◽  
Mateusz Wasala ◽  
Tomasz Kryjak ◽  
Marek Gorgon
Keyword(s):  
Control System ◽  
Real Time ◽  
Heterogeneous Computing ◽  
Computing System ◽  
Video Stream ◽  
Real Time Control ◽  
Time Data ◽  
Autonomous Landing ◽  
Computing Platform ◽  
Time Control

In this paper we present a vision based hardware-software control system enabling autonomous landing of a mul-tirotor unmanned aerial vehicle (UAV). It allows the detection of a marked landing pad in real-time for a 1280 x 720 @ 60 fps video stream. In addition, a LiDAR sensor is used to measure the altitude above ground. A heterogeneous Zynq SoC device is used as the computing platform. The solution was tested on a number of sequences and the landing pad was detected with 96% accuracy. This research shows that a reprogrammable heterogeneous computing system is a good solution for UAVs because it enables real-time data stream processing with relatively low energy consumption.

Modelling real-time control of WWTP influent flow under data scarcity

2015 ◽  
Vol 73 (7) ◽  
pp. 1637-1643 ◽  
Author(s):  
Stefan Kroll ◽  
Geert Dirckx ◽  
Brecht M. R. Donckels ◽  
Mieke Van Dorpe ◽  
Marjoleine Weemaes ◽  
...  
Keyword(s):  
Real Time ◽  
Treatment Plant ◽  
Added Value ◽  
Minor Role ◽  
Real Time Control ◽  
Time Control ◽  
Spatial System ◽  
System Properties ◽  
Secondary Settling ◽  
A Minor

In order to comply with effluent standards, wastewater operators need to avoid hydraulic overloading of the wastewater treatment plant (WWTP), as this can result in the washout of activated sludge from secondary settling tanks. Hydraulic overloading can occur in a systematic way, for instance when sewer network connections are extended without increasing the WWTP's capacity accordingly. This study demonstrates the use of rule-based real-time control (RTC) to reduce the load to the WWTP while restricting the overall overflow volume of the sewer system to a minimum. Further, it shows the added value of RTC despite the limited availability of monitoring data and information on the catchment through a parsimonious simulation approach, using relocation of spatial system boundaries and creating required input data through reverse modelling. Focus was hereby on the accurate modelling of pump hydraulics and control. Finally, two different methods of global sensitivity analysis were employed to verify the influence of parameters of both the model and the implemented control algorithm. Both methods show the importance of good knowledge of the system properties, but that monitoring errors play a minor role.

scholarly journals A Comprehensive Comparative Analysis of the Basic Theory of the Short Term Bus Passenger Flow Prediction

Symmetry ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 369 ◽  
Author(s):  
Huawei Zhai ◽  
Licheng Cui ◽  
Yu Nie ◽  
Xiaowei Xu ◽  
Weishi Zhang
Keyword(s):  
Real Time ◽  
Public Transportation ◽  
Transportation Systems ◽  
Training Data ◽  
Time Data ◽  
Short Term ◽  
Passenger Flow ◽  
Modeling Process ◽  
Automatic Passenger Counters ◽  
Public Transportation Systems

In order to meet the real-time public travel demands, the bus operators need to adjust the timetables in time. Therefore, it is necessary to predict the variations of the short-term passenger flow. Under the help of the advanced public transportation systems, a large amount of real-time data about passenger flow is collected from the automatic passenger counters, automatic fare collection systems, etc. Using these data, different kinds of methods are proposed to predict future variations of the short-term bus passenger flow. Based on the properties and background knowledge, these methods are classified into three categories: linear, nonlinear and combined methods. Their performances are evaluated in detail in the major aspects of the prediction accuracy, the complexity of training data structure and modeling process. For comparison, some long-term prediction methods are also analyzed simply. At last, it points that, with the help of automatic technology, a large amount of data about passenger flow will be collected, and using the big data technology to speed up the data preprocessing and modeling process may be one of the directions worthy of study in the future.

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.

scholarly journals Adaptive Algorithm of a Tap-Changer Controller of the Power Transformer Supplying the Radial Network Reducing the Risk of Voltage Collapse

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5403
Author(s):  
Robert Małkowski ◽  
Michał Izdebski ◽  
Piotr Miller
Keyword(s):  
Real Time ◽  
Power Transformer ◽  
Wind Farms ◽  
Voltage Collapse ◽  
Real Time Control ◽  
Time Data ◽  
Medium Voltage ◽  
Time Control ◽  
University Of Technology ◽  
Technical Solutions

The development of renewable energy, including wind farms, photovoltaic farms as well as prosumer installations, and the development of electromobility pose new challenges for network operators. The results of these changes are, among others, the change of network load profiles and load flows determining greater volatility of voltages. Most of the proposed solutions do not assume a change of the transformer regulator algorithm. The possibilities of improving the quality of regulation, which can be found in the literature, most often include various methods of coordination of the operation of the transformer regulator with various devices operating in the Medium-Voltage (MV) network. This coordination can be decentralized or centralized. Unfortunately, the proposed solutions often require costly technical resources and/or large amounts of real-time data monitoring. The goal of the authors was to create an algorithm that extends the functionality of typical transformer control algorithms. The proposed solution allows for reducing the risk of voltage collapse. The performance of the proposed algorithm was validated using multivariate computer simulations and tests with the use of a physical model of the distribution network. The DIgSILENT PowerFactory environment was used to develop the simulation model of the proposed algorithm. Then, tests were conducted on real devices installed in the LINTEˆ2 Laboratory at the Gdańsk University of Technology, Poland. Selected test results are included in this paper. All results have shown that the proposed algorithm makes it possible to increase the reserve of the voltage stability of the node, in which it is applied, thus mitigating the risk of a voltage collapse occurring. The proposed algorithm does not require complex and costly technical solutions. Owing to its simplicity, it has a high potential for practical application, as confirmed by the real-time control experiment in the laboratory.

The Analysis of Accounting Information Activities Blending SOA

2011 ◽  
Vol 267 ◽  
pp. 35-38
Author(s):  
Yan Fang Niu
Keyword(s):  
Knowledge Management ◽  
Real Time ◽  
Value Chain ◽  
Process Integration ◽  
Accounting Information ◽  
Added Value ◽  
Accurate Information ◽  
Real Time Control ◽  
Financial Reports ◽  
Time Control

Accounting value chain can be considered as composed by the five accounting information activities: capturing economic events, accounting business process integration, real-time financial reports, accounting real-time control, accounting information knowledge management. How to fully reflect the added-value of these activities is the key to produce the real-time, accurate information. This paper illustrates these accounting information activities blending the emerging SOA.

scholarly journals Still normal? Contextualizing real-time data with long-term statistics to monitor anomalies and systematic changes in storm surge activity – Introduction of a prototype web tool storm surge monitor for the German coasts

2021 ◽  
Author(s):  
Xin Liu ◽  
Insa Meinke ◽  
Ralf Weisse
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Storm Surge ◽  
Storm Surges ◽  
Added Value ◽  
Time Data ◽  
Storm Activity ◽  
The Public ◽  
Real Time Data

Abstract. Storm surges represent a major threat to many low-lying coastal areas in the world. While most places can cope with or are more or less adapted to present-day risks, future risks may increase from factors such as sea level rise, subsidence, or changes in storm activity. This may require further or alternative adaptation and strategies. For most places, both forecasts and real-time observations are available. However, analyses of long-term changes or recent severe extremes that are important for decision-making are usually only available sporadically or with substantial delay. In this paper, we propose to contextualize real-time data with long-term statistics to make such information publicly available in near real-time. We implement and demonstrate the concept of a ”storm surge monitor” for tide gauges along the German North Sea and Baltic Sea coasts. It provides automated near real-time assessments of the course and severity of the ongoing storm surge season and its single events. The assessment is provided in terms of storm surge height, frequency, duration, and intensity. It is proposed that such near real-time assessments provide added value to the public and decision-making. It is further suggested that the concept is transferable to other coastal regions threatened by storm surges.

Design and Application of a Communication System Based on Codesys

2014 ◽  
Vol 1044-1045 ◽  
pp. 1113-1117 ◽  
Author(s):  
Jia Liu ◽  
Wei Ping Fu ◽  
Lei Zhou ◽  
Na Qie ◽  
Wen Yun Wang
Keyword(s):  
Real Time ◽  
Communication System ◽  
Data Exchange ◽  
Intelligent Robot ◽  
Real Time Control ◽  
Time Data ◽  
Time Control ◽  
Physical Channel ◽  
Soft Plc ◽  
Set Up

A model of wireless network data interchange was built to solve cross-platform exchange data in intelligent robot. In the framework of embedded Soft-PLC - Codesys real-time operating system, we apply Socket network programming technology based on TCP/IP communication protocol to set up a physical channel between VC++ platform and the Codesys platform. It realizes the real-time data exchange between host-computer and slave-computer uploaded embedded operation system of robot. A special multi-threaded processing class was developed to enhance the multi-tasking allocation ability of the system. Exchanged data was packaged and analyzed to ensure the accuracy of transmitted data. The experiment shows built communication system platform is justifiable, and data transmission speed is less than 10ms. It is able to meet the needs of real-time control in intelligent robot.

Sign in / Sign up

Export Citation Format

Share Document