This research pioneers the application of a diverse set of advanced machine learning and optimization methods, to predict the erodibility of lateritic soil treated with cement and nanostructured quarry fines, providing a groundbreaking, data-driven approach that enhances traditional erosion analysis techniques. Traditional experimental methods for erosion analysis are often complex and resource-intensive; therefore, this research focuses on developing predictive models using Python. To build the machine learning and optimization models, 121 data points were collected from existing literature. The dataset includes erodibility measurements of unsaturated lateritic soil treated with local cemen... More >

Pilgrimage tourism in India is a cultural and deeply spiritual journey, especially for elderly individuals who view it as a cherished life milestone. However, their mobility and accessibility needs are often under-addressed in policy and planning. This study examines inclusive mobility challenges faced by elderly pilgrims in Haridwar through qualitative and quantitative data from 225 participants, including interviews, group discussions, and field observations. Findings reveal physical, sensory, and cognitive barriers that restrict freedom, dignity, and spiritual fulfilment. Existing infrastructure and services, such as signage and pathways, are frequently inadequate. The research highlights... More >

There has been recorded differences between a train spulled by a locomotive and a train unit with all the bogies moving simultaneously. This study aims at the slip of wheel on a railway track under these different movements using finite element simulation on a ballasted railway track. The railway track was subjected to a loaded wheel moving at different speeds using two modes: translation-controlled (wagons pulled by locomotive) and rotation-controlled (simultaneously moving bogies) motion. The results were obtained in the form of track vibrations and wheel slip under moving loads at changing speeds and wheel-rail friction. It was concluded that the force transferred to the substructure does... More >

In this research paper, advanced artificial intelligence (AI) techniques have been applied in predicting the mechanical properties of black cotton soil (BCS) treated by the method of partial displacement of the soil. The materials of the displacement operation were fly ash (FA) and quarry dust (QD), which are both solid wastes derived from coal combustion in power plants and quarrying of stones for the production of aggregates. Previous activities show that BCS has never been treated by displacement of the soil sample but by the addition of these cementitious materials as wt % of the dry soil. The advanced AI techniques were the ANN, GP and the EPR, which executed forty data entries collecte... More >

Pavement maintenance is a critical aspect of transportation and infrastructure management, as it directly impacts traffic flow, vehicle maintenance, safety and accident rate. Effective prediction and prevention of pavement deterioration are essential for optimizing pavement maintenance strategies, reducing cost, and ensuring the lifespan or longevity of transportation. This study presents the development of Adaptive Neuro-Fuzzy inference system (ANFIS) for predicting pavement deterioration. The data used for this analysis is a historical data and field investigation data from the Cross River State pavement Maintenance Agency, Calabar, Nigeria. The ANFIS model was trained using a dataset with... More >

The use of personal protective equipment (PPE) has gained universal acceptance as a critical measure for safeguarding individuals against hazardous environments, including exposure to infectious agents and harmful substances. The increased use of PPE across various industries has resulted in a significant rise in its consumption. Primarily, the steady surge in global COVID cases has caused a sudden rise in demand for PPE. However, the indiscreet and irrational disposal method can potentially augment the impending climate change problem. In the prevailing situation, there is a need to assess their current mode of disposal in terms of carbon emissions. The present study aims to perform carbon... More >

This study evaluated the potential of readily available Indian soils, red soil (Bengaluru) and black cotton soil (Belgaum), as sustainable and cost-effective alternatives to synthetic landfill liners for heavy metal containment. Utilizing Scanning Electron Microscopy (SEM) and Energy-Dispersive Spectroscopy (EDS), we characterized the soil's microstructural properties and elemental composition to assess their adsorption capabilities. To enhance metal capture, soils were amended with lime, cement, and fly ash. Batch leaching experiments, simulating landfill conditions with copper and chromium contamination, quantified adsorption efficiency. Microscopic analysis of leached samples using SEM an... More >

This study employs Response Surface Methodology (RSM) to model and optimize earthquake-induced ground movements in gravelly geohazard-prone environments. RSM efficiently evaluates the interactions of seismic parameters, including soil type, fault distance, and peak ground acceleration (PGA), reducing computational and experimental efforts. A dataset of 234 entries encompassing 11 seismic and soil stress variables was curated and analyzed, yielding a high-precision predictive model with an R² of 0.9997. The resulting closed-form equation facilitates accurate risk assessment, structural safety optimization, and seismic resilience planning. By identifying critical thresholds and nonlinear rela... More >

The inaugural editorial of Sustainable Intelligent Infrastructure introduces the journal's mission to address global challenges such as urbanization, climate change, and resource depletion by integrating sustainability principles with advanced technologies. It aims to provide a multidisciplinary platform for high-quality research that explores the synergy between smart technologies, artificial intelligence, machine learning, and data analytics in sustainable infrastructure. The journal aspires to become a leading voice in global discourse, bridging the gap between traditional infrastructure and intelligent systems while driving innovation to meet the United Nations' Sustainable Development G... More >