CORTEXA
← Browse
crossrefApplied Sciences2025-02-07Cited by 7

Investigating the Effects of Ground-Transmitted Vibrations from Vehicles on Buildings and Their Occupants, with an Idea for Applying Machine Learning

Marta Mikielewicz, Anna Jakubczyk-Gałczyńska, Robert Jankowski

Vibrations observed as a result of moving vehicles can potentially affect both buildings and the people inside them. The impacts of these vibrations are complex, affected by a number of parameters, like amplitude, frequency, and duration, as well as by the properties of the soil beneath. These factors together lead to various effects, from slight disruptions to significant structural damage. Occupants inside affected buildings may experience discomfort, disrupted sleep patterns, and increased stress levels due to the pervasive nature of vibrations. Low-frequency vibrations, typically ranging from 5 to 25 Hz, are of particular concern since they can exacerbate these effects by resonating with internal human organs. To effectively mitigate these issues, a comprehensive approach is required, starting with some interventions at the source. This may involve strategic choices in road construction materials and advancements in vehicle design to reduce the transmission of vibrations through the ground to the surrounding environment. Understanding the complexities of vibration dynamics is essential in urban planning, serving as a fundamental consideration in the development of modern infrastructure that prioritizes the well-being and safety of its inhabitants. Therefore, the aim of the present study is to consider artificial neural networks to assess the potential impact of traffic-induced vibrations on a building’s residents. The results of the study indicate that the proposed method of utilizing machine learning can be effectively applied for such purposes.

View free PDFSource page

Related papers

crossrefApplied Sciences2025-02-08Cited by 5

Applying Machine Learning to Preselective Weighing of Moving Vehicles

Paweł Kowaleczko, Tomasz Kamiński, Mariusz Rychlicki, Zbigniew Kasprzyk, Marek Stawowy, Jacek Trzeszkowski

The paper presents the general characteristics of weighing systems for vehicles in motion. A number of problems and constraints that accompany these systems to ensure adequate accuracy in the operation of these systems are pointed out. The efficient operation of WIM systems is al…

View free PDFSource page
crossrefApplied Sciences2024-04-24Cited by 3

Vehicle-to-Cyclist Collision Prediction Models by Applying Machine Learning Techniques to Virtual Reality Bicycle Simulator Data

Ángel Losada, Francisco Javier Páez, Francisco Luque, Luca Piovano, Nuria Sánchez, Miguel Hidalgo

The study of vulnerable road users (VRUs) behavior is key to designing and optimizing driving assistance systems, such as the autonomous emergency braking (AEB) system. These kinds of devices could help lower the VRU accident rate, which is of particular interest to cyclists, who…

View free PDFSource page
crossrefApplied Sciences2024-12-06Cited by 8

Charging Strategies for Electric Vehicles Using a Machine Learning Load Forecasting Approach for Residential Buildings in Canada

Ahmad Mohsenimanesh, Evgueniy Entchev

The global electric vehicle (EV) market is experiencing exponential growth, driven by technological advancements, environmental awareness, and government incentives. As EV adoption accelerates, it introduces opportunities and challenges for power systems worldwide due to the larg…

View free PDFSource page
crossrefApplied Sciences2022-11-16Cited by 9

CAVeCTIR: Matching Cyber Threat Intelligence Reports on Connected and Autonomous Vehicles Using Machine Learning

George E. Raptis, Christina Katsini, Christos Alexakos, Athanasios Kalogeras, Dimitrios Serpanos

Connected and automated vehicles (CAVs) are getting a lot of attention these days as their technology becomes more mature and they benefit from the Internet-of-Vehicles (IoV) ecosystem. CAVs attract malicious activities that jeopardize security and safety dimensions. The cybersec…

View free PDFSource page
crossrefApplied Sciences2021-11-25Cited by 7

Applying Machine Learning Models to First Responder Collisions Beside Roads: Insights from “Two Vehicles Hit a Parked Motor Vehicle” Data

Mohammadali Tofighi, Ali Asgary, Ghassem Tofighi, Brady Podloski, Felippe Cronemberger, Abir Mukherjee, et al.

First responders including firefighters, paramedics, and police officers are among the first to respond to vehicle collisions on roads and highways. Police officers conduct regular roadside Please check if the country name is correct traffic controls and checks on urban and rural…

View free PDFSource page
crossrefApplied Sciences2024-07-17Cited by 9

Advancing Crayfish Disease Detection: A Comparative Study of Deep Learning and Canonical Machine Learning Techniques

Yasin Atilkan, Berk Kirik, Koray Acici, Recep Benzer, Fatih Ekinci, Mehmet Serdar Guzel, et al.

This study evaluates the effectiveness of deep learning and canonical machine learning models for detecting diseases in crayfish from an imbalanced dataset. In this study, measurements such as weight, size, and gender of healthy and diseased crayfish individuals were taken, and a…

View free PDFSource page