An evaluation system based on the self-organizing system framework of smart cities: A case study of smart transportation systems in China

2020 ◽  
Vol 153 ◽  
pp. 119371 ◽  
Author(s):  
Jianghui Yan ◽  
Jinping Liu ◽  
Fang-Mei Tseng
Keyword(s):  
Evaluation System ◽  
Smart Cities ◽  
Transportation Systems ◽  
The Self ◽  
System Framework ◽  
Smart Transportation ◽  
Self Organizing

Comparing Machine Learning Models for the Predictions of Speed in Smart Transportation Systems

2022 ◽  
pp. 34-46
Author(s):  
Amtul Waheed ◽  
Jana Shafi ◽  
Saritha V.
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Smart Cities ◽  
Learning Algorithms ◽  
High Capacity ◽  
Transportation Systems ◽  
Machine Learning Algorithms ◽  
Smart Transportation ◽  
Data Propagation ◽  
Machine Learning Models

In today's world of advanced technologies in IoT and ITS in smart cities scenarios, there are many different projections such as improved data propagation in smart roads and cooperative transportation networks, autonomous and continuously connected vehicles, and low latency applications in high capacity environments and heterogeneous connectivity and speed. This chapter presents the performance of the speed of vehicles on roadways employing machine learning methods. Input variable for each learning algorithm is the density that is measured as vehicle per mile and volume that is measured as vehicle per hour. And the result shows that the output variable is the speed that is measured as miles per hour represent the performance of each algorithm. The performance of machine learning algorithms is calculated by comparing the result of predictions made by different machine learning algorithms with true speed using the histogram. A result recommends that speed is varying according to the histogram.

Fruitful Synergy Model of Artificial Intelligence and Internet of Thing for Smart Transportation System

2020 ◽  
Vol 4 (1) ◽  
pp. 43-57 ◽  
Author(s):  
Vikram Puri ◽  
Chung Van Le ◽  
Raghvendra Kumar ◽  
Sandeep Singh Jagdev
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Urban Transportation ◽  
Fall Detection ◽  
Transportation System ◽  
Transportation Systems ◽  
Support Vector ◽  
Smart Transportation ◽  
Artificial Neural Network Ann

In urban transportation systems, bicycle sharing systems are majorly deployed in major cities of both developed and developing countries. The recent boom of bicycle sharing system along with its upgraded technology have opened new opportunities towards urban transportation system. With the enlargement of intelligent transportation systems (ITS's), smart bicycle sharing schemes are more popular to smart cities as a green transportation mode. In this article, the Internet of Things (IoT) and artificial intelligence-based monitoring devices have been proposed for the bicycles. This system contains a harmful exhaust gas sensor, wireless module, and a GPS receiver and camera that are capable to send data with time and date stamping. In addition, sensor also integrated on the bicycle for the fall detection. An artificial neural network (ANN) and support vector machine (SVM) applied to the data collected at central server is designed to analyze the root mean square error (RMSE), and coefficient of correlation (R2). Result shows that ANN performance is better when compared to SVM.

Visualization of fish community distribution patterns using the self-organizing map: A case study of the Great Morava River system (Serbia)

2013 ◽  
Vol 248 ◽  
pp. 20-29 ◽  
Author(s):  
Milica Stojkovic ◽  
Vladica Simic ◽  
Djuradj Milosevic ◽  
Dejan Mancev ◽  
Tadeusz Penczak
Keyword(s):  
Fish Community ◽  
River System ◽  
Distribution Patterns ◽  
The Self ◽  
Self Organizing Map ◽  
Morava River ◽  
Self Organizing

scholarly journals MOBDA: Microservice-Oriented Big Data Architecture for Smart City Transport Systems

2020 ◽  
Vol 4 (3) ◽  
pp. 17 ◽  
Author(s):  
Suriya Priya R. Asaithambi ◽  
Ramanathan Venkatraman ◽  
Sitalakshmi Venkatraman
Keyword(s):  
Big Data ◽  
Intelligent Transportation Systems ◽  
Consumer Satisfaction ◽  
Smart Cities ◽  
Transportation Systems ◽  
Transport Systems ◽  
Hybrid Architecture ◽  
Smart Transportation ◽  
Transport Services ◽  
Data Architecture

Highly populated cities depend highly on intelligent transportation systems (ITSs) for reliable and efficient resource utilization and traffic management. Current transportation systems struggle to meet different stakeholder expectations while trying their best to optimize resources in providing various transport services. This paper proposes a Microservice-Oriented Big Data Architecture (MOBDA) incorporating data processing techniques, such as predictive modelling for achieving smart transportation and analytics microservices required towards smart cities of the future. We postulate key transportation metrics applied on various sources of transportation data to serve this objective. A novel hybrid architecture is proposed to combine stream processing and batch processing of big data for a smart computation of microservice-oriented transportation metrics that can serve the different needs of stakeholders. Development of such an architecture for smart transportation and analytics will improve the predictability of transport supply for transport providers and transport authority as well as enhance consumer satisfaction during peak periods.

scholarly journals Smart Cities and Data Analytics for Intelligent Transportation Systems: An Analytical Model for Scheduling Phases and Traffic Lights at Signalized Intersections

2021 ◽  
Vol 11 (15) ◽  
pp. 6816
Author(s):  
Fatih Gunes ◽  
Selim Bayrakli ◽  
Abdul Halim Zaim
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Transportation Systems ◽  
Signalized Intersections ◽  
Effective Control ◽  
Main Role ◽  
Smart Transportation ◽  
Traffic Lights ◽  
Service Rates

This paper is intended to improve the performance of signalized intersections, one of the most important systems of traffic control explained within the scope of smart transportation systems. These structures, which have the main role in ensuring the order and flow of traffic, are alternative systems depending on the different methods and techniques used. Determining the operation principles of these systems requires an extremely careful and planned study, considering their important role. Performance outputs obtained from the queue analyses made in previous studies formed the input of this study. The most important techniques are used in the effective control of intersections, such as signal timing: in particular, the use of effective green time and order of the transitions between phases. In this research, a traffic-sensitive signalized intersection control system was designed with the suggested methods against these two problems. The sample intersections were selected from three cities with the highest population density as the case study area. In the analysis of the performance of the connection arms of the selected intersections, flow intensity data were taken into consideration, as well as the arrival and service rates. Based on this, the outputs of the two proposed models regarding the use of phase transitions and effective green durations were compared with two other adaptive control systems and their positive results were shared. The results showed that signalized intersections, operating with a well-planned and correctly chosen technique, better regulate density and queuing.

scholarly journals Exploratory Analysis of Public Transportation Data in Curitiba

2020 ◽  
Author(s):  
Nádia P. Kozievitch ◽  
Tatiana M. C. Gadda ◽  
Keiko V. O. Fonseca ◽  
Marcelo O. Rosa ◽  
Luiz C. Gomes Jr. ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Public Transportation ◽  
Exploratory Data Analysis ◽  
User Behavior ◽  
Transportation Systems ◽  
Urban Mobility ◽  
Smart Transportation ◽  
Exploratory Data ◽  
Over Time

Smart transportation systems have been providing more data over time (such as bus routes, users, smartphones, etc.). Such data provides a number of opportunities to identify various facets of user behavior and traffic trends. In this paper we address some of the urban mobility challenges (already discussed by the Brazilian Computer Society), from a number of different perspectives, including (i) pattern discovery, (ii) statistical analysis, (iii) data integration, and (iv) open and connected data. In particular, we present an exploratory data analysis with GIS for public transportation toward a case study in Curitiba, Brazil.

Developing our own organisations

2021 ◽  
pp. 99-110
Author(s):  
Peter Beresford
Keyword(s):  
Identity Politics ◽  
The Self ◽  
Self Organization ◽  
Disabled People ◽  
Shared Experience ◽  
Working Together ◽  
The Difference ◽  
Self Organizing

This chapter develops the discussion about working together by exploring how to have a real say — how we can develop our own organisations, as a basis for self-organization, rather than merely serving other people's causes. It looks beyond identity politics and the limitations associated with them, to focus on organising on the basis of shared experience, particularly of discrimination and exclusion. The chapter provides a basis for self-organizing around common understandings and strongly internalised goals arising from the desire to challenge oppression. It then returns to the self-organizing of disabled people, which has highlighted the difference between traditional processes where non-disabled people controlled the agenda and one where disabled people seek to speak and act on their own behalf, setting up and controlling their own organisations. Ultimately, the chapter mentions the case study of a 'user-led organisation', Shaping Our Lives, in which the author has been actively involved. Like other self-run organisations, it has done things differently to achieve different objectives, offering helpful insights for advancing participatory ideology in practice.

scholarly journals Using Self-Organizing Maps for Rural Territorial Typology

2011 ◽  
pp. 107-126 ◽  
Author(s):  
Marcos Santos da Silva ◽  
Edmar Ramos de Siqueira ◽  
Olívio Teixeira ◽  
Maria Manos ◽  
Antônio Monteiro
Keyword(s):  
Neural Network ◽  
Temporal Analysis ◽  
The Self ◽  
Self Organizing Map ◽  
Clustering Methods ◽  
Self Organizing Maps ◽  
Policy Makers ◽  
Spatial Temporal Analysis ◽  
Self Organizing

This work assessed the capacity of the self-organizing map, an unsupervised artificial neural network, to aid the process of territorial design through visualization and clustering methods applied to a multivariate geospatial temporal dataset. The method was applied in the case study of Sergipe‘s institutional regional partition (Territories of Identity). Results have shown that the proposed method can improve the exploratory spatial-temporal analysis capacity of policy makers that are interested in territorial typology. A new partition for rural planning was elaborated and confirmed the coherence of the Territories of Identity.

scholarly journals Transport Inequalities and the Adoption of Intelligent Transportation Systems in Africa: A Research Landscape

2021 ◽  
Vol 13 (22) ◽  
pp. 12891
Author(s):  
Olasupo O. Ajayi ◽  
Antoine B. Bagula ◽  
Hloniphani C. Maluleke ◽  
Isaac A. Odun-Ayo
Keyword(s):  
Systematic Review ◽  
Information And Communication Technologies ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Western World ◽  
Smart Transportation ◽  
African Cities ◽  
The Impact

Intelligent Transportation Systems (ITS), also known as Smart Transportation, is an infusion of information and communication technologies into transportation. ITS are a key component of smart cities, which have seen rapid global development in the last few decades. This has in turn translated to an increase in the deployment and adoption of ITS, particularly in countries in the Western world. Unfortunately, this is not the case with the developing countries of Africa and Asia, where dilapidated road infrastructure, poorly maintained public/mass transit vehicles and poverty are major concerns. However, the impact of Westernization and “imported technologies” cannot be overlooked; thus, despite the aforementioned challenges, ITS have found their way into African cities. In this paper, a systematic review was performed to determine the state of the art of ITS in Africa. The output of this systematic review was then fed into a hybrid multi-criteria model to analyse the research landscape, identify connections between published works and reveal research gaps and inequalities in African ITS. African peculiarities inhibiting the widespread implementation of ITS were then discussed, followed by the development of a conceptual architecture for an integrated ITS for African cities.

Optimal Planning of Distributed Generation Using Self-Organizing Optimization Algorithm

2014 ◽  
Vol 852 ◽  
pp. 720-724
Author(s):  
Wen Song ◽  
Qi Qiang Li
Keyword(s):  
Distributed Generation ◽  
Optimization Algorithm ◽  
Distribution System ◽  
Optimal Location ◽  
The Self ◽  
Energy Losses ◽  
Optimal Planning ◽  
Optimization Methodology ◽  
Self Organizing

Recently, distributed generation (DG) has gained lots of attention due to a variety of benefits it can bring to the traditional power produce and distribution system. Identify the optimal location and size of DG in the distribution network is one of the crucial problems of DG integration, because a non-optimal planning might cause some adverse effects. In this paper, an optimization model with the consideration of minimizing energy losses is formulated first, and then an optimization methodology based on the Self-organizing Optimization Algorithm (SOA) is proposed. Finally, a case study is carried out to demonstrate the effectiveness of the proposed procedure.

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