1,625 research outputs found
Performance evaluation of shuttle-based storage and retrieval systems using discrete-time queueing network models
Shuttle-based storage and retrieval systems (SBS/RSs) are an important part of today‘s warehouses. In this work, a new approach is developed that can be applied to model different configurations of SBS/RSs. The approach is based on the modeling of SBS/RSs as discrete-time open queueing networks and yields the complete probability distributions of the performance measures
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
DATASET2050 D5.1 - Mobility assessment
This document provides documentation on the mobility assessment metrics and methods for use within DATASET2050. On the one hand it describes what the key performance areas, attributes, indicators and metrics such as seamlessness, cost, duration, punctuality, comfort, resilience, etc. incorporated into the model are. On the other, it gives details about mobility metric computation, modelling methodology, visualisations used etc
eXplainable data processing
Seminario realizado en U & P U Patel Department of Computer Engineering, Chandubhai S. Patel Institute of Technology, Charotar University of Science And Technology (CHARUSAT), Changa-388421, Gujarat, India 2021[EN]Deep Learning y has created many new opportunities, it has unfortunately also become a means for achieving ill-intentioned goals. Fake news, disinformation campaigns, and manipulated images and videos
have plagued the internet which has had serious consequences on our society. The myriad of information available online means that it may be difficult to distinguish between true and fake news, leading many users to unknowingly share fake news, contributing to the spread of misinformation. The use of Deep Learning to create fake images and videos has become known as deepfake. This means that there are ever more effective and realistic forms of deception on the internet, making it more difficult for internet users to distinguish reality from fictio
Deployment of DeepTech AI Models in Engineering Solutions
Ponencia presentada en ICRAMAE-2k21, International Conference on Recent Advances in Mechanical and Automation Engineering, Vivekananda Global University, Jaipur, India, 29-30th November 2021[EN]Industrial Engineering is a branch of engineering that focuses on the design and operation of industrial processes. It involves the application of science to the construction of production systems. This field has undergone significant advancements over the last decades. In the last centuries, the emergence of
different technologies has led to breakthroughs in engineering, making it possible to automate processes in industries. Steam, electricity, the internet, and now Artificial Intelligence technologies have all brought with them greater levels of automation to machinery, gradually decreasing human involvement in processes such as procurement, raw material handling, manufacturing and quality control
The implementation and operation of the VTS in the Turkish straits and Sea of Marmara
Turkish Maritime Shipping and Traffic in the Turkish Straits and the Sea of Marmara has been effected due to lack of dissemination of navigational information, traffic monitoring and management during the past. There has always been a need for ships to navigate accurately and safely. This problem has created a number of ship collisions, accidents, fires, deaths and major pollution spills, loss of vessels and cargoes. This lack of proper traffic management has been led to the blockage of Straits by some casualties. These results directly cause harm to both the Turkish economy and environment and also effect other countries which have to use these sea ways. The paper examines the current traffic situation in the Turkish Straits and the Sea of Marmara and investigates current developments in vessel traffic management systems around the world. An attempt is made to determine how best the new technology can be applied to improve safety and effectiveness in the Straits. A number of recommendations on how a suitable and practicable VTS system may be successfully implemented in the Straits to fulfil the requirements of this sensitive area are made. To assist the development of a proposed VTS, technical specifications, operational plans, procedures and regulations, as well as training requirements for VTS operators, are recommended. The paper concludes with some views on the status of the Turkish Straits bearing in mind apparent conflicts between International Legislation
Book of abstracts of the 24th Euro Working Group on Transportation Meeting
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