scholarly journals The Shared Bicycle and Its Network—Internet of Shared Bicycle (IoSB): A Review and Survey

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2581 ◽  
Author(s):  
Shu Shen ◽  
Zhao-Qing Wei ◽  
Li-Juan Sun ◽  
Yang-Qing Su ◽  
Ru-Chuan Wang ◽  
...  
Keyword(s):  
Public Transportation ◽  
Technology Development ◽  
Smart Cities ◽  
Transport Systems ◽  
Intelligent Transport Systems ◽  
Transportation Mode ◽  
Technical Problems ◽  
Intelligent Transport ◽  
Shared Bicycle ◽  
First Time

With the expansion of Intelligent Transport Systems (ITS) in smart cities, the shared bicycle has developed quickly as a new green public transportation mode, and is changing the travel habits of citizens heavily across the world, especially in China. The purpose of the current paper is to provide an inclusive review and survey on shared bicycle besides its benefits, history, brands and comparisons. In addition, it proposes the concept of the Internet of Shared Bicycle (IoSB) for the first time, as far as we know, to find a feasible solution for those technical problems of the shared bicycle. The possible architecture of IoSB in our opinion is presented, as well as most of key IoT technologies, and their capabilities to merge into and apply to the different parts of IoSB are introduced. Meanwhile, some challenges and barriers to IoSB’s implementation are expressed thoroughly too. As far as the advice for overcoming those barriers be concerned, the IoSB’s potential aspects and applications in smart city with respect to technology development in the future provide another valuable further discussion in this paper.

scholarly journals Short-Term IoT Data Forecast of Urban Public Bicycle Based on the DBSCAN-TCN Model for Social Governance

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Dazhou Li ◽  
Chuan Lin ◽  
Wei Gao ◽  
Guangbao Yu ◽  
Jian Gao ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Public Transportation ◽  
Clustering Algorithm ◽  
Smart Cities ◽  
Dropout Rate ◽  
Urban Transport ◽  
Transport Systems ◽  
Social Governance ◽  
Shared Bicycle

Internet of Things will play a vital role in the public transport systems to achieve the concepts of smart cities, urban brains, etc., by mining continuously generated data from sensors deployed in public transportation. In this sense, smart cities applied artificial intelligence techniques to offload data for social governance. Bicycle sharing is the last mile of urban transport. The number of the bike in the sharing stations, to be rented in future periods, is predicted to get the vehicles ready for deployment. It is an important tool for the implementation of smart cities using artificial intelligence technologies. We propose a DBSCAN-TCN model for predicting the number of rentals at shared bicycle stations. The proposed model first clusters all shared bicycle stations using the DBSCAN clustering algorithm. Based on the results of the clustering, the data on the number of shared bicycle rentals are fed into a TCN neural network. The TCN neural network structure is optimized. The effects of convolution kernel size and Dropout rate on the model performance are discussed. Finally, the proposed DBSCAN-TCN model is compared with the LSTM model, Kalman filtering model, and autoregressive moving average model. Through experimental validation, the proposed DBSCAN-TCN model outperforms the traditional three models in terms of two metrics, root mean squared logarithmic error, and error rate, in terms of prediction performance.

scholarly journals Security in Intelligent Transport Systems for Smart Cities: From Theory to Practice

Sensors ◽  
2016 ◽  
Vol 16 (6) ◽  
pp. 879 ◽  
Author(s):  
Muhammad Javed ◽  
Elyes Ben Hamida ◽  
Wassim Znaidi
Keyword(s):  
Smart Cities ◽  
Transport Systems ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Theory To Practice

scholarly journals INTELLIGENT TRANSPORT SYSTEMS EXPLOITING SMART WIRELESS SENSING NODES

2020 ◽  
Author(s):  
Filippo Giammaria Praticò ◽  
Rosario Fedele ◽  
Sara Pizzi ◽  
Giuseppe Araniti
Keyword(s):  
Data Exchange ◽  
Smart Cities ◽  
Transport Systems ◽  
Wireless Sensing ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Related Data ◽  
5G Network ◽  
Wireless Sensing System ◽  
Control Traffic

Future smart cities that will exploit the forthcoming fifth-generation (5G) network will strongly contribute to the development of intelligent transport systems, which will be able to effectively manage changing infrastructural conditions, and to timely exchange crucial information with different stakeholders to improve sustainability and safety. To this end, smart wireless sensing nodes can be effectively exploited. Consequently, the objectives of this study are: 1) to describe the setup and the main potentialities of a wireless sensing system designed for monitoring the environmental and structural conditions on road pavements; 2) to provide an overview about the capability of the 5G network to enable the data exchange required by the designed system. Each sensing node includes different sensors, and is able to send the data gathered from the resource-constrained sensors to a web server used for data processing. Vibrational-, acoustical-, and environmental-related data are used to control traffic pollution, road availability and structural status. The paper describes the in-lab tests carried out on asphalt concrete samples to: i) calibrate the sensors; ii) define structural and environmental thresholds. Results show that the tested node is able to provide reliable data that can be used for the above-described purposes.

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