Benedict Shajulin
Indian Institute of Information Technology Kottayam, Kottayam, Kerala India.
New Gener Comput. 2022;40(4):1009-1027. doi: 10.1007/s00354-021-00147-x. Epub 2022 Jan 29.
Suggesting tourists/residents about the pollution-free locations and controlling the number of passengers in a shareable vehicle have become crucial tasks to smart city officials as they plummet health issues such as asthma or COVID-19. Recently, city authorities, transport logistic designers, and policymakers have tasked researchers/entrepreneurs to innovate in shared mobility systems. This paper proposes a Blockchain-Enabled Shared Mobility (BESM) architecture that allocates seats to residents/tourists in a shareable vehicle based on air quality and COVID-19 information of traveling locations. BESM involves smart city authorities, vehicle owners, hospital authorities, and residents using permissioned-blockchains to collaboratively decide on allocating travel seats. Experiments were carried out at the IoT Cloud research laboratory to manifest the allocation of seats. For instance, BESM excluded in allocating seats to asthma patients and limited the number of travelers in the cities where COVID-19 cases or pollution levels were higher in numbers using BESM. The pollution levels of cities were monitored using air quality monitoring sensors or predicted using a few prediction algorithms such as Random Forests (RF), Linear Regression (LR), Quantile Regression (QR), Ridge Regression (RR), Lasso Regression (LaR), ElasticNet Regression (ER), Support Vector Machine (SVM), and Recursive Partitioning (RP). In succinct, the article unfolded the primordial importance of the proposed BESM architecture for promoting efficient shared mobility aspects in smart cities.
向游客/居民推荐无污染地点并控制共享车辆中的乘客数量,已成为智慧城市官员的关键任务,因为这些问题会导致哮喘或新冠肺炎等健康问题激增。最近,城市当局、交通物流设计师和政策制定者要求研究人员/企业家在共享出行系统方面进行创新。本文提出了一种基于区块链的共享出行(BESM)架构,该架构根据出行地点的空气质量和新冠肺炎信息,在共享车辆中为居民/游客分配座位。BESM涉及智慧城市当局、车主、医院当局以及使用许可区块链的居民,以共同决定出行座位的分配。在物联网云研究实验室进行了实验,以展示座位分配情况。例如,BESM在为哮喘患者分配座位时将其排除在外,并在新冠肺炎病例或污染水平较高的城市中,使用BESM限制旅行者数量。城市的污染水平通过空气质量监测传感器进行监测,或使用一些预测算法进行预测,如随机森林(RF)、线性回归(LR)、分位数回归(QR)、岭回归(RR)、套索回归(LaR)、弹性网络回归(ER)、支持向量机(SVM)和递归分区(RP)。简而言之,本文阐述了所提出的BESM架构对于促进智慧城市中高效共享出行方面的首要重要性。