MDPI - Publisher of Open Access Journals

14 pages, 3845 KB

Open AccessArticle

Hierarchical Agglomerative Clustering of Bicycle Sharing Stations Based on Ultra-Light Edge Computing

by Juan José Vinagre Díaz, Rubén Fernández Pozo, Ana Belén Rodríguez González, Mark R. Wilby and Carmen Sánchez Ávila

Sensors 2020, 20(12), 3550; https://doi.org/10.3390/s20123550 - 23 Jun 2020

Cited by 8 | Viewed by 3983

Abstract

Bicycle sharing systems (BSSs) have established a new shared-economy mobility model. After a rapid growth they are evolving into a fully-functional mobile sensor platform for cities. The viability of BSSs is floored by their operational costs, mainly due to rebalancing operations. Rebalancing implies transporting bicycles to and from docking stations in order to guarantee the service. Rebalancing performs clustering to group docking stations by behaviour and proximity. In this paper we propose a Hierarchical Agglomerative Clustering based on an Ultra-Light Edge Computing Algorithm (HAC-ULECA). We eliminate the proximity and let Hierarchical Agglomerative Clustering (HAC) focus on behaviour. Behaviour is represented by ULECA as an activity profile based on the net flow of arrivals and departures in a docking station. This drastically reduces the computing requirements which allows ULECA to run as an edge computing functionality embedded into the physical layer of the Internet of Shared Bikes (IoSB) architecture. We have applied HAC-ULECA to real data from BiciMAD, the public BSS in Madrid (Spain). Our results, presented as dendograms, graphs, geographical maps, and colour maps, show that HAC-ULECA is capable of separating behaviour profiles related to business and residential areas and extracting meaningful spatio-temporal information about the BSS and the city’s mobility. Full article

(This article belongs to the Special Issue Trends on Edge Computing and Artificial Intelligence for Next Generation Sensor Networks)

► Show Figures

Figure 1

24 pages, 4544 KB

Open AccessReview

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

by Shu Shen, Zhao-Qing Wei, Li-Juan Sun, Yang-Qing Su, Ru-Chuan Wang and Han-Ming Jiang

Sensors 2018, 18(8), 2581; https://doi.org/10.3390/s18082581 - 7 Aug 2018

Cited by 41 | Viewed by 13703

Abstract

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. Full article

(This article belongs to the Special Issue Crowd-Sensing and Remote Sensing Technologies for Smart Cities)

► Show Figures

Figure 1

Search Results (2)

Further Information

Guidelines

MDPI Initiatives

Follow MDPI

Saved Queries

Search Filter Reset All

Years

Feature Papers

Subjects

Journals

Article Types

Countries / Regions

Search Results (2)

Further Information

Guidelines

MDPI Initiatives

Follow MDPI