Department of Civil Engineering

Permanent URI for this collectionhttp://localhost:4000/handle/123456789/1927

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Author: search.filters.author.Gupta, RajivSubject: search.filters.subject.Civil Engineering

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Now showing 1 - 10 of 82
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    Inception SN: An Inception based Convolutional Neural Network for Hyperspectral Image Classification
    (IEEE, 2021-10) Gupta, Rajiv
    Hyperspectral satellite imagery provides a wealth of spatial and spectral information about a given scene of interest. Therefore it is widely used in several applications like pixel-wise classification, vegetation mapping, ocean color monitoring and so on. Many pixel-wise classification algorithms like support vector machine, random forest, parallelopiped classifier, and neural networks are used for this purpose. The advent of convolutional neural networks (CNN) has brought about great development in this field, owing to their unique property of automatic feature extraction. Plain CNN architectures perform only one of pooling/convolution at each stage for feature extraction. This paper describes a new CNN architecture, the Inception SN, which makes use of both pooling and convolution at each stage to effectively extract features. It also makes use of spatial and spectral information in order to carry out classification. The outcome of this is a robust algorithm which performs well even with lower training data.
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    Stability Analysis of Directional Tunnel in Sandy Soil
    (IOP, 2021-06) Gupta, Rajiv
    In recent times, water storage is becoming a confronting task because of the depletion of water resources worldwide. Domestic rainwater harvesting and human-made structures for water procurement achieved significance because of the increase in intermittent water accessibility. In turn, functional water infrastructures fetch prominence in the wake of constructive coordination among the communities in a locality. Low water security and losses through evaporation observed by practising different rainwater harvesting methods create a research gap to construct water infrastructure in rural areas to procure water productively. The current research work represents the model of a water storage structure, named directional tunnel (DT), which is placed below the ground level in a declination, as it reduces evaporation and temperature, thus storing rainwater for longer days. DT stores runoff and rainwater collected from the rooftop of multiple houses in a selected locality. The detailed working of the DT is discussed using Building Information Modelling (BIM) concept. Combined with the engineering geological characteristics, the DT's stability during water storage comes into the picture as the whole structure interacts with the soil. The current study also focuses on the behaviour of DT with respect to sandy soil using PLAXIS 3D software, and the results are interpreted for practical viability.
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    Automated Bacteria Colony Counting on Agar Plates Using Machine Learning
    (ASCE, 2021-10) Gupta, Rajiv
    The identification of E. coli bacteria is critical for the prevention of health risks. According to EPA-approved gold standard methods, 24–48 h are required to count viable cells in water. Manual counting of viable bacteria colonies on agar plates is time-consuming and can be prone to human error. The method requires experts to identify and count colonies on agar plates using a microscope. Hence, the bacterial counting procedure must be automated in order to decrease error. The main objective of this study was to develop an automatic system for bacteria colony counting. A total of 1,301 groundwater samples were collected from eight districts in Rajasthan, India, for a field investigation. The results were validated using artificial intelligence (AI) methods on this experimental data set. We automated the process of E. coli bacteria identification using a convolutional neural network (CNN). We developed a smartphone application for the rapid detection of E. coli bacteria on agar plates using CNN. We also automated the process of bacteria colony counting using faster region-based convolutional neural network (R-CNN) to overcome manual cell counting process limitations. A graphical user interface (GUI) application was created to rapidly count bacteria colony–forming units on agar plates using faster R-CNN. The developed faster R-CNN model achieved an overall accuracy of 97% and an error (loss) of 0.10. The performance of the CNN and faster R-CNN models was validated using F-score, precision, sensitivity, and accuracy statistical measures. The comparative analysis showed that the faster R-CNN model is reliable and effective in E. coli cell counting. The study developed a system for identifying and counting viable cells of E. coli bacteria in water that can be used to forecast hotspots of water contamination.
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    State of the Art for Integrating Modern Technologies to Develop a Sustainable Water Management Model
    (AnKa Publisher, 2022) Gupta, Rajiv
    Numerous fast-developing techniques such as Building Information Modelling (BIM) and Geographical Information System (GIS) are implemented in the construction industry to meet sustainability goals. BIM is a single platform that integrates different tools and practices to create the digital representation of the multiple stages of the project. BIM technology was utilized for various projects related to smart water management and smart city development, integrating GIS and remote sensing technology like Light Detection and Ranging (LiDAR). Integrated technology makes it possible to cover the entire field, incorporating geospatial information and real site situations. Water management in urban areas is critical due to the absence of management and water infrastructure. The main objective of this study is to elaborate on the existing water management practices and tools through the literature study. The bibliometric analysis gives the author’s relationship and technological growth in integrating BIM, GIS, LiDAR, and countless applications. This review proposes a framework model by uniting various methodologies and techniques to create a sustainable water management system. The suggested framework model would help to achieve the long-term sustainability goals for the water management system
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    Application of BIM framework on rural infrastructure
    (Springer, 2022-02) Gupta, Rajiv
    Rural infrastructure (RI) projects face multiple obstacles, such as unavailability of materials and machinery, poor estimation, failure in documentation, cost overrun during their operations. The current study identifies a method to surpass the encountered challenges. Building information modelling (BIM), a construction management process, has been adopted in various fields for acquiring efficient construction deliverables in a project lifecycle. Previous researchers have focused on enhancing and applying the BIM framework for infrastructure projects in urban areas such as airports, bridges, highways, and tunnels. However, the application of BIM in a rural scenario is minimal, and its execution for overcoming the hurdles faced in RI projects remains a gap. The current research work modifies BIM in a rural viewpoint, as rural BIM (R-BIM) framework, by incorporating essential attributes based on previously performed rural studies to get over the uncertainties. The R-BIM framework explores various dimensions emphasising a rural water management (RWM) project and highlights the operation of the BIM cloud with the engagement of concerned stakeholders.
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    Assessment of sustainability index for rural water management using ANN
    (IWA, 2022) Gupta, Rajiv; Kumar, Gaurav
    The current study proposes a sustainability index (SI) measure based on artificial neural networks (ANN) and globally accepted parameters. Some of the available methods for SI measurement are multi-criteria analysis, external costs, energy analysis, and ecological footprint methods. However, validity remains a concern due to a system's needs, criteria, and requirements. Generally, sustainability is assessed in economic, environmental, and social issues, which varies across regions and countries. Most of the studies accept sub-indices but to a limited extent. Therefore, the proposed study develops an SI evaluation method based on the idea of multi-sustainability incorporating operations, institutions, risks, and climate factors besides economic, environmental, and social issues. All these issues might not be applicable to a single project but may help to develop a complete index when applied. The present study considered different scenarios in building a method to calculate SI using ANN. The results obtained by the ANN model for various input parameters helped to identify the best water conservation strategy. Sensitivity analysis was also performed to determine the uncertainty contribution/significance of the input variables for the water scarcity in the study region. The developed model in the study is tested on a rural water management system.
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    A Sustainable Integrated Rural Water Management with emphasis on Network Prioritization, Household Water Treatment and Real-Time Feedback
    (IEEE, 2022) Gupta, Rajiv; Kumar, Dhanesh
    Rural water infrastructure management, an essential aspect of sustainable living in rural areas, is an ignored subject compared to urban areas. For instance, multiple urban studies, such as integrated urban water management (IUWM) and water sensitive urban design (WSUD), discuss the structured management of water, land, and resources for acquiring the most lucrative and societal benefits. However, many rural water infrastructures lack proper planning, coordination, and monitoring. Besides, minimal applied decision making at lower levels misleads to the inefficiency of rural water sources. Research gaps exist in long term water quality testing and continuous monitoring of stored water in rural areas. The current study aims to develop a decentralized system, termed Sustainable Integrated Rural Water Management (SIRWM), for overcoming the challenges plaguing rural areas by utilizing rainwater harvesting (RWH) as the primary source in a study area in Rajasthan, India. The overall setup of the SIRWM targets to diminish over-reliance on groundwater sources in areas facing drought. The study comprises five segments, in the sequential order of survey and data collection, network prioritization, implementation of RWH system using Building Information Modelling (BIM) tools, installation of water filters at households, and collection of real-time feedback through interactive voice response system (IVRS) (an android application) in a selected community of the study area. The integration of all these components results in achieving a robust rural water management.
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    Methodologies of Scenario Development for Water Resource Management
    (CRC Press, 2022) Gupta, Rajiv; Kumar, Gaurav
    Efficient management of the resources requires applying scenario development, which helps manage future needs and available resources with lesser difficulties. In this chapter, one of the most vital sources for life, water resources, has been reviewed for the various methodologies and modelling approaches adopted in its scenario development. Scenarios have been planned considering different possibilities incorporating various water balance models, climate models, prediction, and simulation methods. All the methods encountered are either predictive or derivative for the predicted values. Predictions are carried out either by hybridizing the methods or in isolation, but ultimately require derivative models to generate the results. Encountered methods are found complex having rigorous prediction processes. Further directions are suggested (1) to make more straightforward and more uncomplicated prediction methods with the principle to make science for all; and (2) empowering Geographic Information System for predicting future besides presentation and analysis
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    A Strategic Design Approach for Implementing Rainwater Management System Using an Integration of GIS and BIM Tool
    (CIC, 2023-02) Gupta, Rajiv
    An increase in urbanization and uncontrolled development has resulted in a water stress situation, which necessitates the exploration of alternate water sources. Rainwater has proven to be a prominent alternate water source after being efficiently harvested. On-ground implementation of the Rainwater Harvesting System (RWHs) at a community level in urban areas has always been challenging and requires technological advancement. To facilitate the implementation of RWHs, the proposed study provides a comprehensive methodology by integrating the Geographical Information System (GIS) and the Building Information Modeling (BIM) tools. Initially, the hydro-spatial analysis was performed with a GIS tool to obtain an optimized rainstorm collection network and to aid in establishing the geometrical properties of RWHs. Further, an outcome from the analysis was utilized to develop a visualization model using the BIM tool. The proposed methodology is implemented as a case study in the municipality of Jaipur (India). The developed multidimensional BIM contributes to the sustainability of the project in terms of resources, economy, and efficiency over the life cycle. As an outcome, the proposed study provides a comprehensive methodology for effectively utilizing rainwater to cope with the growing water demand and contribute to flood mitigation in urban regions.
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    A systematic basin-wide approach for locating and assessing volumetric potential of rainwater harvesting sites in the urban area
    (Springer, 2022-09) Gupta, Rajiv
    Rainwater harvesting (RWH) has proven to be an efficient method of curtailing water scarcity by substituting it as an alternative water supply which also helps to mitigate the risk of flooding caused due to heavy rainfall. While overcoming the water-related issues, implementation and identifying potential harvesting sites in urban areas on a large scale has always been challenging, necessitating additional research and constraint considerations. The proposed study implements a basin-wide approach and creates a tool using the geographical information system (GIS) to pinpoint site locations to collect rainstorm water. For determining the feasible number of RWH sites, the scenarios were created by considering the minimum basin area. In addition, the volumetric potential of the identified RWH sites was evaluated using the SCS-CN (Soil Conservation Services Curve Number) method by estimating rainfall runoff volume. The proposed methodology is implemented as a case study on the extended area of Jaipur in India, and the analysis shows that all identified locations lie on the outskirts of the study area, ensuring land availability for developing rainwater harvesting structures. As an outcome, the proposed methodology helps to establish the relationship between the basin area, the number of identified RWH sites, and their volumetric potential, creating a benchmark for further conducting similar studies on other areas.