For this part you have to read the following articles (scientific/ blog articles):

Topic 1: Big Data in Transport

  • Article 1.1 :"Big Data for transportation and mobility: recent advances, trends and challenges". You can find the article here.

Abstract: Big Data is an emerging paradigm and has currently become a strong attractor of global interest, specially within the transportation industry. The combination of disruptive technologies and new concepts such as the Smart City upgrades the transport data life cycle. In this context, Big Data is considered as a new pledge for the transportation industry to effectively manage all data this sector required for providing safer, cleaner and more efficient transport means, as well as for users to personalize their transport experience. However, Big Data comes along with its own set of technological challenges, stemming from the multiple and heterogeneous transportation/mobility application scenarios. In this survey we analyze the latest research efforts revolving on Big Data for the transportation and mobility industry, its applications, baselines scenarios, fields and use case such as routing, planning, infrastructure monitoring, network design, among others. This analysis will be done strictly from the Big Data perspective, focusing on those contributions gravitating on techniques, tools and methods for modeling, processing, analyzing and visualizing transport and mobility Big Data. From the literature review a set of trends and challenges is extracted so as to provide researchers with an insightful outlook on the field of transport and mobility.

Topic 2: Big Data in Shipping

  • Article 2.1: "Big Data in Shipping: Insights For Operational Optimisation". You can find the article here

Abstract: The use of big data in the maritime industry is widely regarded as the next revolutionary breakthrough. By definition, big data refers to expansive and diverse datasets that expand at an accelerated pace. Currently, big data has already made significant advancements across multiple sectors, ranging from banking and finance to healthcare. As the demand for improved operational efficiency and cost-effectiveness in shipping operations continues to escalate, big data stands poised to wield its influence within the maritime industry.

Indeed, in today’s digital age, competition is stiff in various industries, including the maritime sector, and companies are constantly looking to invest in solutions that can help them boost productivity while lowering overall expenses. Consequently, the demand for more advanced and innovative solutions like marine data analysis is rising at an impressive rate among various end users, such as commercial shippers. To gain a comprehensive understanding of the relevance of big data analytics in the shipping industry, this article explores the potential applications of big data in optimising maritime operations. 

Topic 3: Big Data in Logistics

  • Article 3.1: "Big Data in Logistics: 10 Successful Examples". You can find the article here 

Abstract: Big Data is an emerging paradigm and has currently become a strong attractor of global interest, specially within the transportation industry. The combination of disruptive technologies and new concepts such as the Smart City upgrades the transport data life cycle. In this context, Big Data is considered as a new pledge for the transportation industry to effectively manage all data this sector required for providing safer, cleaner and more efficient transport means, as well as for users to personalize their transport experience. However, Big Data comes along with its own set of technological challenges, stemming from the multiple and heterogeneous transportation/mobility application scenarios. In this survey we analyze the latest research efforts revolving on Big Data for the transportation and mobility industry, its applications, baselines scenarios, fields and use case such as routing, planning, infrastructure monitoring, network design, among others. This analysis will be done strictly from the Big Data perspective, focusing on those contributions gravitating on techniques, tools and methods for modeling, processing, analyzing and visualizing transport and mobility Big Data. From the literature review a set of trends and challenges is extracted so as to provide researchers with an insightful outlook on the field of transport and mobility.

 

Last modified: Saturday, 29 June 2024, 12:39 PM