Applications of AI, IoT, and Cloud Computing in Smart Transportation: A Review

Smart transportation systems have emerged as a promising solution for improving the efficiency, safety, and sustainability of transportation. The integration of emerging technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and Cloud Computing has enabled the development of intelligent transportation systems that can optimize traffic flow, enhance driver safety, and reduce transportation costs. In this study, we conducted a systematic review of the literature to explore the applications of AI, IoT, and Cloud Computing in smart transportation systems. Our findings indicate that AI can be used for autonomous vehicles, traffic management, predictive maintenance, driver assistance, and demand forecasting. IoT can enable connected vehicles, real-time fleet management, smart parking, traffic monitoring, and remote diagnostics. Cloud Computing can facilitate vehicle-to-cloud communication, scalable infrastructure, data analytics, mobility-as-a-service, and predictive maintenance. The integration of these technologies can result in a comprehensive smart transportation system that can improve the overall efficiency of transportation systems. Our study provides insights for researchers, practitioners, and policymakers on the potential applications of AI, IoT, and Cloud Computing in smart transportation systems

Potential applications of advanced aircraft in developing countries

Air transportation concepts for movement of cargo in developing countries are reviewed using aicraft which may appear in the future. For certain industrial applications, including mining and forestry, the relative costs of doing the job using different types of aircraft are compared with surface transportation systems. Two developing countries, Brazil and Indonesia, were taken as examples to determine what impact they might have on the aircraft markets of the future. Economic and demographic data on developing countries in general, and Brazil and Indonesia in particular, are reviewed. The concept of an industrial city in a remote area developed around an airport is discussed. It is noted that developing areas generally lack extensive surface transportation systems and that an air transportation system can be implemented in a relatively short time. A developing nation interested in rapid expansion may thus find the role of air cargo far more important than has been true in developed nations. Technological developments which may dramatically increase the performance of agricultural aircraft are also reviewed

Applications of Expert Systems in Transport

BACKGROUND Experienced judgement and specialist knowledge are essential to the proper specification, understanding and interpretation of data and computer analyses. The human expert has traditionally supplied this knowledge and judgement with the computer doing the necessary number-crunching. However, artificial intelligence (AI) research provides ways of embodying this knowledge and judgement within computer programs. Despite an early lead in the field, UK research and developmnent into AI techniques was held back in the 1970s when the then Science Research Council took the view that the 'combinatorial explosion' of possibilities would be an insurmountable obstacle to AI developent. But in America and Japan research continued, and the surge of interest in the 1980s has been a consequence of the 'Fifth Generation Computer' research programme initiated by Japan (Feigenbaum and McCorduck; 1984). This led in Europe to the ESPRIT programme of advanced technology research, and in the UK to the Alvey programme (Department of Industry, 1982). As a result, all sectors of industry have been encouraged to consider how such advanced technology can be applied, and the transport industry is no exception. This paper sets out to explain some of the relevant techniques in simple terms, and to describe a number of situations in which transport planning and operations might be helped through their use, illustrating this by reference to the pioneering work going on in transport applications in the USA, Britain and Australia

AI-enabled Integration in the Supply Chain - A Solution in the Digitalization Era

Artificial Intelligence (AI) is getting increased attention from various manufacturing industries, including fashion and textiles, due to its ability to work effectively, similar to human intelligence. This Systematic Literature Review (SLR) paper proposes potential future research directions that emphasize the impacts of AI on supply chain integration (SCI) efforts through information sharing (IS). A structured literature review of articles in the 2010-2021 period, addressing geographic location, journals, publishers, authors, research designs, and applied theories, has been used to prepare this paper. The additional discussion of AI incorporates information from the structured review to conclude the findings and suggest future research directions. The authors have used the Scopus database and prestigious peer-reviewed journals to search for relevant papers using suitable keywords. This paper concluded that the Asian region has the highest concentration of publications and that AI adoption positively affects the IS-SCI relationship. Empirical quantitative research design and resource-based view theory are prominent among the reviewed publications. This SLR paper is limited by not having the impacts of AI discussed at the subset level

Advanced Manned Launch System (AMLS) study

To assure national leadership in space operations and exploration in the future, NASA must be able to provide cost effective and operationally efficient space transportation. Several NASA studies and the joint NASA/DoD Space Transportation Architecture Studies (STAS) have shown the need for a multi-vehicle space transportation system with designs driven by enhanced operations and low costs. NASA is currently studying an advanced manned launch system (AMLS) approach to transport crew and cargo to the Space Station Freedom. Several single and multiple stage systems from air-breathing to all-rocket concepts are being examined in a series of studies potential replacements for the Space Shuttle launch system in the 2000-2010 time frame. Rockwell International Corporation, under contract to the NASA Langley Research Center, has analyzed a two-stage all-rocket concept to determine whether this class of vehicles is appropriate for the AMLS function. The results of the pre-phase A study are discussed

The SIMPSONS project: An integrated Mars transportation system

In response to the Request for Proposal (RFP) for an integrated transportation system network for an advanced Martian base, Frontier Transportation Systems (FTS) presents the results of the SIMPSONS project (Systems Integration for Mars Planetary Surface Operations Networks). The following topics are included: the project background, vehicle design, future work, conclusions, management status, and cost breakdown. The project focuses solely on the surface-to-surface transportation at an advanced Martian base

Introduction to ‘Artificial intelligence in failure analysis of transportation infrastructure and materials'

Transportation infrastructures, including roads, bridges, tunnels, stations, airports and subways, play fundamental roles in modern society. Engineering failures of transportation infrastructures may result in significant damage to the public. The traditional methods are to monitor, store and analyse the information during the infrastructure and material design, testing, construction, numerical simulations, evaluation, operation, maintenance and preservation, using mechanistic-based, material-based and statistics-based approaches. In recent decades, artificial intelligence (AI) has drawn the attention of many researchers and has been used as a powerful tool to understand and analyse the engineering failures in transportation infrastructure and materials. AI has the advantages of conveniently characterizing infrastructure materials in multi-scale, extracting failure information from images and cloud points, evaluating performance from the signals of sensors, predicting the long-term performance of infrastructure based on big data and optimizing infrastructure maintenance strategies, etc. In the future, AI techniques will be more effective and promising for data collection, transmission, fusion, mining and analysis, which will help engineers quickly detect, analyse and finally prevent the engineering failures of transportation infrastructure and materials. This theme issue presents the latest developments of AI in failure analysis of transportation infrastructure and materials

Advanced chemical propulsion at NASA Lewis: Metallized and high energy density propellants

Two of the programs at the NASA Lewis Research Center investigating advanced systems for future space missions are the Metallized Propellant Program and the Advanced Concepts Program. Each program includes both experimental and theoretical studies of future propellants and the associated vehicle impacts and significant payload benefits for many types of space transportation. These programs are described