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Recent Advances in Applied Sciences

Engineering and Technology Innovations

Editors: Ritesh Bhat, Nithesh Naik, Ketan Kotecha, Antony V. Samrot, Sachi Nandan Mohanty, Bhaskar Somani

Publisher: Springer Nature Switzerland

Book Series : Sustainable Civil Infrastructures

Part of: Springer Professional "Business + Economics & Engineering + Technology" , Springer Professional "Engineering + Technology"

Table of Contents

About this book

This book commences with an editorial overview, providing a comprehensive introduction to the current landscape and future prospects in engineering and technology. Volume 1 of the International Conference on Innovative Discoveries and Emerging Advancements in Applied Sciences (iDEAAS) 2024 proceedings is a groundbreaking compilation that encapsulates the forefront of engineering and technological innovations. This meticulously curated book serves as a cornerstone for professionals, academics, and students who are navigating the ever-evolving realms of engineering and technology. This sets the tone for a deep dive into a series of specialized topics.

In the aerospace and marine technologies section, the book presents pioneering research and studies. It offers insights into the latest advancements in aerospace engineering, delving into the complexities and innovations in aircraft and spacecraft design. Simultaneously, it explores the strides made in marine technologies, highlighting the synergies and technological crossovers between these two critical fields. The infrastructure and environment section addresses one of the most pressing concerns of the 21st century—sustainable development. This section is particularly insightful for its focus on the environmental impact of infrastructure development and the challenges of maintaining ecological balance.

Mechatronics and automation is another highlight of this volume, where the fusion of mechanical engineering, electronics, and computing leads to fascinating innovations in automation and system design. This section underscores the importance of interdisciplinary approaches in solving complex engineering problems and enhancing operational efficiency in various industries. In the realm of computing and information technology, the book explores the transformative impact of digital technologies on engineering.

The book culminates with a comprehensive summary that not only synthesizes the key themes discussed but also looks ahead at the future of engineering and technology. It offers a visionary perspective on the emerging trends and potential advancements that are poised to redefine the engineering landscape.

Frontmatter

Sustainable Urban Infrastructure

Frontmatter

Chapter 1. Innovative Approaches and Advancements in Sustainable Materials and Technologies for Enhanced Longevity and Efficiency for Urban Infrastructure

Abstract

The escalating demand for urban infrastructure necessitates innovative sustainability approaches. This chapter explores the latest advancements in sustainable materials and technologies designed to enhance the longevity, efficiency, and environmental impact of the urban infrastructure. By examining cutting- edge research and real-world applications, we aimed to provide a comprehensive overview of how sustainable materials are transforming urban landscapes. Key topics include high-performance concrete, recycled materials, bio-based materials, and smart technologies that are integrated into construction practices. The potential for these materials to reduce the carbon footprint, improve resource efficiency, and promote resilient urban environments is critically assessed.

Koushik Chakraborty, Nazeer Shaik, Ali Ihsan Alanssari, Ali Naji Saeed, Ammar H. Shnawa

Chapter 2. Sustainable Materials for Infrastructure Development to Revolutionize Civil Engineering

Abstract

This study explored the pivotal role of sustainable materials in revolutionizing civil engineering practices, particularly in the realm of infrastructure development. With the looming challenges of climate change and dwindling natural resources, the adoption of innovative materials and techniques is imperative to ensure the longevity and environmental responsibility of the built environment. The key innovations discussed included green concrete, bamboo reinforcement, recycled plastics, and timber engineering. These materials offer viable alternatives to traditional construction materials, significantly reducing carbon emissions, minimizing resource depletion, and mitigating waste generation. By embracing sustainable materials, civil engineers can spearhead a transformative shift towards more resilient, eco-friendly infrastructure systems that meet the needs of present and future generations.

Harish Dutt Sharma, Archana Sandhu, Yazan Basil Hassan Al-Rubaie, Abbas Nuaithal Nema, Rouaida Kadhim A. Al-Hussein

Chapter 3. Harnessing Renewable Energy for Energy Security towards Sustainable Urban Development

Abstract

Urban areas are facing significant challenges related to energy consumption, environmental sustainability, and climate change. Harnessing renewable energy sources is a promising solution to address these challenges and promote sustainable urban development. This study explores various renewable energy technologies suitable for urban environments, including solar power, wind energy, and geothermal energy. It examines the potential benefits, challenges, and integration strategies of urban landscapes. Additionally, this paper discusses policy frameworks, financial incentives, and community engagement strategies to facilitate the adoption of renewable energy in urban areas. By leveraging renewable energy resources, cities can reduce greenhouse gas emissions, enhance energy security, and foster resilient communities, thereby contributing to a more sustainable future.

Deepti Thakral, Neha Batra, Zainab Failhal-lami, Aya Ali Salim, Adil Abbas Alwan

Chapter 4. Building Climate Resilience in Urban Infrastructure with Machine Learning Techniques

Abstract

The global issue of urban heat island (UHI) formation affects both developed and developing nations. Climate change, agricultural productivity, and water and air quality are only a few of the environmental factors that are profoundly impacted by its expansion and development. The impact of urban heat islands (UHI) is exacerbated by changes in land topog- raphy, which are mostly caused by industry and urbanization. The effects of urban heat islands (UHI) are especially noticeable in dry climates or places where cities are expanding rapidly without adequate planning. However, consistent surface monitoring of the Earth is required for a complete understanding, which is required for UHI detection and reduction. Nevertheless, a great deal of effort, time, and materials are needed for this task. To address this issue, many computational and numerical methods have been developed to identify the emergence and propagation of UHI. Urban Canopy Model (UCM), Building Energy Model (BEM), and Urban Heat Island Intensity (UHII) are three prominent examples of such approaches. For this pur- pose, remote sensing photography has a lot of potential as a tool for investigating and forecast- ing UHI mechanisms. Utilizing Remote Sensing data acquired in Chennai, India, this study examines Land Surface Temperature (LST) and plant health with the purpose of evaluating UHI. Analyzing changes in land use and land cover (LULC) using classifiers such as Support Vector Machine (SVM), Random Forest (RF), and Maximum Likelihood Classification (MLC) evaluates plant health. Classifiers like this make it simpler to sort land into various buckets by showing how land cover has changed over time. The link between land cover change and UHI formation may be better understood with the use of classifiers, which organize pixels into clas- ses based on their similarity.

N. Bhuvaneswary, N. Mohanapriya, A. Thamaraiselvi, S. Sinduja, K. Sivapriya, G. Vinuja

Chapter 5. Wind Turbine Reliability Through AI-Driven Predictive Maintenance and IIoT Integration

Abstract

Predominantly running to failure maintenance is practiced in the wind energy industry. This type of breakdown reaction is an expensive proposition for operators. Because wind turbines are dispersed throughout and remotely in accessible locations, they are difficult to access during the operation and maintenance of wind farms. Hence, consistent predictive monitoring of the system and its subassemblies is required to reduce the huge downtime maintenance costs and prevent catastrophic failure. The Industrial Internet of Things, together with artificial intelligence, supports the continuous monitoring of machines in real time to detect the wear conditions early and to schedule the repairs in advance, thereby reducing the down, decreasing the cost of maintenance, and increasing productivity. A system of condition monitoring is a deployable early warning system that relies on sensor data to predict the failure and remaining useful life of the system, assemblies, and their components.

Deepak Dudeja, Nikhil Ranjan, Zainab Failhal Lami, Aya Ali Salim, Doaa Saadi Kareem

Smart Infrastructure and Urban Development

Frontmatter

Chapter 6. Towards Smarter Cities: Integration of Technology and Infrastructure

Abstract

Congestion, pollution, inefficient use of resources, and threats to public safety are just a few of the many issues that cities throughout the world are facing as urbanization speeds up. There is an increasing need to create smarter cities by combining modern technology with more conventional infrastructure in order to solve these problems. An examination of “smart cities” is presented in this article, with an emphasis on how infrastructure and technology work hand in hand. There is great potential for urban environments to be optimized through the combination of infrastructure and technology. While smart energy networks improve sustainability by optimizing energy use and distribution, intelligent transportation systems can reduce traffic congestion through real-time data analysis and dynamic routing. Deploying sensor networks also allows for improved water saving and garbage collection, among other resource management improvements. This paper showcases successful deployments of smart city technologies by reviewing current initiatives and case studies from around the world. Additionally, it delves into important factors that lawmakers, urban planners, and tech developers should keep in mind while working to encourage innovation and build communities that are more liveable, sustainable, and resilient. Finally, a revolutionary chance to solve urban problems and increase quality of life is presented by the convergence of infrastructure and technology. The full potential of smart solutions may be realized by cities by embracing innovation and collaboration, leading to more connected, efficient, and inclusive urban settings.

K. R. N. Aswini, C. Aarthi, S. Radha, C. Aparna, M. Sivaraja, Abhijeet Das

Chapter 7. Integrating Technology and Civil Infrastructure for Smart Urban Development

Abstract

Rapid urbanization in the twenty-first century presents numerous challenges and opportunities for city planners and civil engineers. The concept of resilient cities has emerged as a critical framework for addressing urban vulnerability and ensuring sustainable development. This chapter explores the integration of advanced technologies and civil infrastructure to create smart and resilient urban environments. By leveraging Geographic Information Systems (GIS), Internet of Things (IoT) devices, and sustainable design principles, cities can enhance their infrastructure resilience, improve residents’ quality of life, and achieve long-term sustainability goals. This comprehensive analysis includes case studies, theoretical models, and practical applications, illustrating how technology and civil infrastructure can be harmonized to develop smart urban spaces that are adaptable to environmental, social, and economic changes.

Neeraj Kumar Verma, B. Kannadasan, Zahraa Al-Barmani, Zamen Latef Naser, Yazan Basil Hassan Al-rubaie, Israa Abed Jawad

Chapter 8. Smart Infrastructure Management: Leveraging Artificial Intelligence for Precision Crack Detection and Maintenance

Abstract

The effective management and maintenance of civil infrastructure, particularly in buildings, are vital for ensuring structural integrity and safety. This paper investigates the application of Artificial Intelligence (AI) in enhancing precision crack detection and maintenance of building infrastructure. Traditional methods of crack detection often rely on manual inspections, which can be time-consuming, labor-intensive, and prone to human error. AI technologies, particularly machine learning and computer vision, offer significant advancements in automating and improving the accuracy of crack detection. By employing AI-driven systems, real-time data from various sensors and imaging devices can be analyzed to identify and classify cracks with high precision. These systems can detect minute cracks that might be overlooked by human inspectors, thus preventing minor issues from escalating into major structural problems. The integration of AI with other modern tools such as drones and robotic inspection devices further enhances the reach and effectiveness of monitoring efforts. Moreover, AI can assist in predictive maintenance by analyzing patterns and trends from historical and real-time data, enabling proactive maintenance strategies. This approach not only enhances the safety and durability of buildings but also reduces maintenance costs and downtime. The paper also discusses the challenges of implementing AI in crack detection, including the need for large datasets for training algorithms, the complexity of integrating AI with existing infrastructure, and addressing data privacy concerns. In conclusion, leveraging AI for crack detection and maintenance in building infrastructure represents a significant step forward in ensuring structural safety and operational efficiency. This paper provides insights into the current state of AI applications in this field and offers recommendations for future research and development.

Malige Gangappa, N. Subhash Chandra, Ponugoti Kalpana, Sarangam Kodati, M. Dhasaratham

Chapter 9. Integrating Geographic Information Systems (GIS) and Remote Sensing (RS) for Smart Urban Planning

Abstract

Geographic Information Systems (GIS) and Remote Sensing (RS) play integral roles in modern urban planning by providing comprehensive spatial data and analytical tools. This study examined the application of GIS and RS in urban planning, focusing on their capabilities in data acquisition, analysis, visualization, and decision-making. The integration of GIS and RS technology enables planners to assess urban environments, monitor changes, and formulate sustainable development strategies. Case studies have highlighted the effectiveness of GIS and RS in addressing various urban planning challenges, such as land use management, infrastructure planning, environmental conservation, and disaster mitigation. Additionally, this study discusses emerging trends and future directions for utilizing GIS and RS to enhance urban planning processes and outcomes.

Shivendra Kumar Singh, Anshu Tiwari, Aya Ali Salim, Karim M. Aty, Ali Hasan Dheidan

Chapter 10. Assessment of Urban Heat Island Effects for Building Climate Resilience Through Remote Sensing and Machine Learning Techniques

Abstract

The creation of urban heat islands (UHI) is a major problem for industrialized and developing countries worldwide. Its growth and development have far-reaching effects on many environmental variables, including global warming, crop yield, and water and air quality. Changes in the topography of the land brought about mainly by urbanization and industrialization have increased the severity of urban heat islands (UHI). In areas where there is rapid urbanization without proper town planning or in dry regions, the impacts of UHI are more pronounced. Nevertheless, to detect and reduce the UHI effect, a thorough comprehension is necessary, which can be attained through regular surface monitoring of the Earth. However, this method requires considerable time, energy, and resources. Several computational and numerical approaches have been devised to detect the appearance and spread of UHI to address this problem. Among these methodologies, the Urban Canopy Model (UCM), Building Energy Model (BEM), and Urban Heat Island Intensity (UHII) are prominent. Remote sensing photography shows great promise as a method for studying and predicting UHI. To evaluate the UHI effect, this research examines Land Surface Temperature (LST) and plant health using Remote Sensing data collected in Chennai, India. Using classifiers such as Random Forest (RF), Maximum Likelihood Classification (MLC), Support Vector Machine (SVM), and Land Use Land Cover (LULC), change analysis assesses the health of the vegetation. By visualizing changes in land cover, these classifiers make it easier to classify the land into different categories. Classifiers provide insight into the dynamics of land cover change and its relationship with UHI generation by computing pixel similarity and effectively grouping each pixel into its own class.

Shikha Verma, Rashi Tanwar, Aya Ali Salim, Ameer Kaissar Ibrahim, Jenan Ali Hammoode

Advanced Civil Engineering Techniques

Frontmatter

Chapter 11. Design and Analysis of Solar-Powered Water Desalination Tank Using Parabolic Trough Collector

Abstract

This paper presents solar thermal desalination of seawater by constructing a solar trough collector, condensation chamber, and charcoal filter for desalination of seawater, and filtration of obtained water samples with a simple low-cost technique. Solar trough collector consists of an aluminium sheet polished on one side with a solar reflective film which is fixed in a parabolic shape using a wooden frame and then the trough is fixed on a frame made of PVC pipes. A copper pipe coated with black paint on the outer surface of the copper pipe and is fixed at the focal point of the parabolic collector, the copper pipe is enclosed using a glass plate which is fixed to the parabolic collector, and a plastic water jar is used as saline water storage tank which is coated with black paint on outer surface. In this paper design and analysis of solar-powered water desalination tank using parabolic trough collector is experimented. The saline water uses solar energy after passing through desalination tank have Total Dissolved Solid, electrical conductivity and Alkanity of the water reduced a lot and becomes normal drinking water.

Ipsita Bose Roy Choudhury, Arla Anusha, Kadanthailiu Kame, Kathula Raghunath Reddy

Chapter 12. An Experimental Investigation on Properties of Sawdust Concrete

Abstract

Sawdust substituted fine aggregate in concrete to the extent that the concrete's compressive strength and density at days 7, 14, 21, and 28 were within the range of plain concrete's typical strengths. In daily life, concrete is most frequently utilized as a building material and is readily available everywhere these days. When strength, durability, ductility, tensile strength, and absorption resistance are needed, concrete is the ideal material to use. Everyday items like sawdust, rice husk, egg shells, and coir are used to reduce construction material costs and to make use of natural resources. One waste product that is widely available and can be utilized in place of fine aggregate is sawdust. Research on the use of waste products in concrete has been conducted by the building sector throughout the past ten years. The characteristics of both fresh and hardened concrete are impacted differently by each waste product. Any development must include a discussion of natural resources and an environmental presentation. Continuous technological and industrial progress has led to a problem with waste material disposal. By using waste materials appropriate for concrete production, construction costs can be reduced while still achieving safe waste material disposal. Concrete made with waste materials is not only more affordable, but it also addresses some of the disposal problems.

P. Parameswara Rao, K. Yogi, M. Kiran, M. Adarsh

Chapter 13. An Experimental Investigation on Replacement of Natural Sand by Foundry Sand in Paver Blocks

Abstract

This study examines the potential of using waste foundry sand (WFS) as a substitute for natural sand in making concrete paver blocks. Foundry sand is a by-product of metal casting industries, and its disposal is an environmental challenge. By incorporating WFS in various proportions (0, 5, 10, 20, and 30%), we evaluated its effects on the physical and mechanical properties of the paver blocks, such as compressive strength, tensile strength, and water absorption. Our findings indicate that WFS is finer and chemically different from natural river sand. The water absorption of the paver blocks with WFS was found to be between 4.3 and 4.6% by mass. Compressive strength tests revealed values between 50.2 and 55.2 MPa, while tensile strength ranged from 3.50 to 3.78 MPa. Although the control mix (100% natural sand) showed the highest strengths, optimal results were achieved with 5 and 10% WFS replacement. In conclusion, incorporating WFS up to 10% can produce paver blocks with comparable strength to those made with natural sand, offering a sustainable and effective use of industrial waste in construction. This approach not only mitigates environmental issues related to WFS disposal but also provides a cost-effective alternative for producing high-quality concrete products.

P. Parameswara Rao, H. Chennabasappa, C. Vinay, C. Shravan Reddy

Chapter 14. An Experimental Investigation on Partial Replacement of Fine Aggregate with Crumb Rubber in Concrete

Abstract

In recent years, the utilization of waste products has increased, as a small step in the usage of waste like rubber tires is thrown out for construction purposes. The rubber tires are made into required aggregate sizes called crumb rubber and replaced in place of aggregate works. This will be very easy to use, economical, and easy-to-use crumb rubber. The objective of this study is to examine the impact of partially replacing the fine aggregate in concrete with crumb rubber, specifically in sizes ranging from 4.75 mm to less than 0.075 mm. The replacement percentages tested were 5, 10, and 15%. The mechanical properties of M25 grade concrete were evaluated by testing two specific properties of rubberized concrete: compressive strength, flexural strength, and split tensile strength. We recorded and analyzed the results of these tests. We conducted a comparative analysis of the compressive strength, split tensile strength, and flexural strength of concrete mixes containing 5, 10, and 15% of a certain ingredient, and found that the 5% mix performed better than the other variations. The findings indicated that the compressive strength of concrete made from waste tire rubber was significantly lower than that of regular concrete. However, concrete incorporating waste tire rubber exhibited ductile and plastic behavior.

M. C. Venkatasubbaiah, S. Venkata Sai, T. Venu, S. Sricharan

Chapter 15. Comprehensive Analysis and Mitigation of Traffic Accidents on NH-40: A Civil Highways Infrastructure Perspective

Abstract

Due to urbanization, population growth, and the proliferation of vehicles (motorized and non-motorized), the complexity of traffic accident situations has increased. The purpose of this research is to examine NH-40 highway traffic accidents using a multi-method approach. Using the Quantum of Accident approach and the Accident-Prone Index approach, the study identifies high-risk sites, collects accident data, analyzes preliminary data, and selects highway segments. Corrective actions are suggested to lessen the likelihood of accidents after site inspections. To forecast the likelihood of accidents given certain traffic and road variables, sophisticated modeling approaches including Poisson Regression, Multiple Linear Regression, and Simple Linear Regression are used. On top of that, we poll people to find out how they feel about road safety and what they do while driving. A prototype accident-avoidance system that makes use of current technology like sensors and microcontrollers is also investigated in the research. The results high-light the significance of combining accurate data gathering, advanced modeling, and technology advancements to improve road safety and decrease accident rates.

V. Balamurugan, M. Vasanthakumar, A. Saranya, Karpaga Priya, R. Vani, V. Saravanan

Smart Healthcare Infrastructure

Frontmatter

Chapter 16. Intelligent Solutions for Urban Mobility and Smart Healthcare Infrastructure: Transforming Transportation for Sustainable Cities

Abstract

Urban areas are facing significant challenges in transportation and healthcare infrastructure due to population growth, rapid urbanization, and environmental concerns. This chapter explores the integration of intelligent solutions to address these challenges and transform urban mobility for sustainable cities. By leveraging technologies such as artificial intelligence, Internet of Things (IoT), and data analytics, cities can optimize transportation systems, improve traffic flow, reduce congestion, and enhance public transportation accessibility. Additionally, the chapter discusses the importance of incorporating smart healthcare infrastructure within urban mobility frameworks to ensure efficient emergency response, medical accessibility, and healthcare delivery. Through innovative strategies and collaborative efforts between government, private sector, and communities, cities can create more liveable, resilient, and sustainable environments for their residents.

Sasikumar, Sudheer, Ponmurugan, Vidya Sagar Reddy, Chandrasekar, Abhijeet Das

Chapter 17. Renewable Energy and Smart Healthcare Infrastructure for Sustainable Urban Development

Abstract

This paper explores the integration of renewable energy and smart healthcare infrastructure as pivotal components for sustainable urban development. By leveraging renewable energy sources such as solar, wind, and bioenergy, cities can reduce their carbon footprint and foster environmental sustainability. Concurrently, smart healthcare infrastructure, enabled by advanced technologies like IoT, AI, and big data analytics, promises to enhance the efficiency, accessibility, and quality of urban health services. This study reviews existing literature, identifies key trends and challenges, and proposes a comprehensive framework for the implementation of these technologies. Through case studies and empirical analysis, the paper demonstrates the potential benefits and outlines a roadmap for future research and practical applications.

Winson Medidhi, Kandula Srikanth, Ponmurugan Panneer Selvam, Anand Anbalagan, K. G. Parthiban, Abhijeet Das

Chapter 18. IoT-Driven Transformation in Smart Healthcare Infrastructure: Enhancing Patient Care Through Connected Devices, Sensors, and Networks

Abstract

The role of IoT in revolutionizing smart healthcare infrastructure is profound, harnessing the power of connected devices, sensors, and networks to enhance patient care and clinical outcomes. By integrating IoT technology, healthcare systems can achieve unprecedented levels of efficiency, accuracy, and personalization. Connected devices and sensors provide real-time data, enabling continuous monitoring and proactive management of patient health. Smart healthcare infrastructure leverages IoT to address challenges such as rising costs, aging populations, and disparities in access to care. The deployment of wearable devices, telemedicine platforms, big data analytics, and artificial intelligence within this infrastructure enhances the capability to deliver personalized treatment plans and ensure timely interventions. Furthermore, IoT-enabled systems facilitate seamless communication between healthcare providers and patients, promoting better health outcomes and improving the overall patient experience. It also introduces a new algorithm designed to optimize the functionality of IoT-based healthcare solutions, ensuring more efficient resource allocation, accurate predictions of patient needs, and enhanced treatment personalization. Through this comprehensive examination, the chapter highlights the crucial role of IoT in shaping the future of healthcare delivery and advancing community health.

B. Jothi, S. Madhubalan, J. Jeyasudha, Ponmurugan Panneer Selvam, P. Gomathi, S. Prabu

Chapter 19. Enhancing Healthcare Infrastructure Through Smart Solutions

Abstract

Congestion, pollution, inefficient use of resources, and threats to public safety are just a few of th Malicious nodes in S-Health networks may use the Sybil attacks covered in this chapter to compromise privacy and security. The proposed system, known as SybilWatch Enhanced Privacy-Aware Smart Health (E-PASH), primarily consists of three parts: initialization, secure communication, and Sybil node detection. At startup, the Lightweight Encryption Algorithm (LEA) encrypts Smart Health Records (SHRs) utilizing prime order grouping. During the secure communication phase, encrypted SHRs are transferred to prevent unauthorized access. The cluster head is implementing the new BlueTits Detection (BTD) algorithm while simultaneously monitoring for any suspicious user behavior. By analyzing characteristics such as Master key and Last One-Time Authentication, the cluster head is able to identify Sybil nodes. As soon as the Sybil attack is detected, a fresh revocation list is promptly shared with active users to minimize the impact on privacy and system integrity.

P. S. Arthy, C. Visali, E. Thangadurai, T. Manikandan, A. Sahaya Anselin Nisha, T. Bernatin

Technological Innovations in Urban Planning and Management

Frontmatter

Chapter 20. Geographic Information Systems (GIS) and Remote Sensing (RIS) in Urban Planning

Abstract

Geographic Information Systems (GIS) and Remote Sensing (RS) play integral roles in modern urban planning by providing comprehensive spatial data and analytical tools. This paper examines the application of GIS and RS in urban planning, focusing on their capabilities in data acquisition, analysis, visualization, and decision-making. The integration of GIS and RS technologies enables planners to assess urban environments, monitor changes, and formulate sustainable development strategies. Case studies highlight the effectiveness of GIS and RS in addressing various urban planning challenges, such as land use management, infrastructure planning, environmental conservation, and disaster mitigation. Additionally, the paper discusses emerging trends and future directions in utilizing GIS and RS for enhancing urban planning processes and outcomes. This study explores the application of Geographic Information Systems (GIS) and Remote Sensing (RS) in urban planning, highlighting their significance in enhancing decision-making processes. Using a case study approach, the research examines how these technologies contribute to efficient land use planning, infrastructure development, and environmental management. Key findings demonstrate that GIS and RS can significantly improve the accuracy of urban sprawl detection, with a 15% increase in predictive accuracy over traditional methods. Additionally, the integration of these technologies led to a 20% reduction in the time required for environmental impact assessments. The study concludes that GIS and RS are invaluable tools for modern urban planners, providing detailed spatial data that supports sustainable urban development.

K. P. Rama Prabha, M. Thangamani, V. Annapoorani, Abhijeet Das, K. Govarthanambikai, G. Vinuja

Chapter 21. Utilizing Machine Learning Methods to Forecast Passenger Safety in Smart Urban Transportation Systems

Abstract

For passengers traveling on roadways, airways, and waterways, survival chances must be predicted to prevent the loss of human life and property damage, including buses, airplanes, and ships. In this paper, a dataset that contains passenger information has been taken. Many algorithms are applied to predict the passenger survival chances (Logistic regression model, SVM model, KNN model, Gaussian Naive Bayes model, decision tree model). The results show that the Naive Bayes model is getting the maximum accuracy score in predicting the survival chances of passengers. Several machine learning models were used to measure the accuracy of predicting passenger safety using the proposed methodology. Some of the models that have been studied include K-nearest neighbours (KNN), Decision Trees, Naive Bayes, Logistic Regression, and Support Vector Machines (SVM). The most effective methods were logistic regression (75.74%), decision trees (74.25%), KNN (66.04%), and SVM (63.8%), in that order, following the Naive Bayes algorithm, which achieved the highest degree of success with an accuracy score of 76.86%.

P. M. S. S. Chandu, S. Vaithyasubramanian, R. Sundararajan, P. Vaidhyanathan, V. Thamarai Selvi

Chapter 22. Performance Evaluation of Stored Image Data Sets Retrieval Using Image Attribute Average Technique in Smart Home Environment

Abstract

Knowledge extraction can be done either through content-based or picture-based retrieval. With today’s Increasing popularity of image-based content, most searches are done through image-based queries, which will bring more accurate and relevant material based on the input. Picture-type queries differ from text-based queries in that the user requires domain knowledge. Before creating the image data sets, input or stored images must be trained. The user must make a designated similarity measure for the input set. It will help the researchers find relevant content more quickly and accurately. It will save searching and processing time. This paper employs several techniques, including using a colour histogram for the image, which aids in quantizing the image and calculating the colour of each pixel, which is saved for future processing. Using this histogram, the user creates different colour bins, which helps produce the desired outputs. The results of the trial validate this method. These techniques can be particularly beneficial in the context of Smart Home applications.

D. Saravanan, K. V. S. S. N. Murty, Maruthy Subarahmaniyam, P. Vaidhyanathan, V. Thamarai Selvi, S. Vaithyasubramanian

Chapter 23. Multi-Tier Parking Management System for Commercial and Residential Places Using Timed Colored Petri Nets (TCPN) with Inhibitor Arcs

Abstract

A Petri Net model has been established to park cars that arrive at the arena within the allotted time. If there are k floors and m x n parking slots per level, each car is assigned a quadruple (i, j, k, tm) if one is available. All vehicles must be removed after the ‘tm’ hours of parking. When a car arrives and is numbered, the clock starts. Each car that arrives will receive a quadruple until the parking lot is filled. It will be displayed if the arena does not have parking or cars. If a car leaves before the ‘tm’ hours, the slot is reserved for the next car. This concept was developed utilizing a timed, colored Petri net with an inhibitor arc. Time will be important because each car may only use the slot for a limited time. Consumers from three complexes, including parking users, were interviewed to assess the proposed parking system. According to the report, most people prefer to have no time constraints and to choose their parking locations.

M. I. Mary Metilda, S. Vaithyasubramanian, P. Vaidhyanathan, V. Thamarai Selvi

Chapter 24. Innovative Water Management and Smart Healthcare Infrastructure: Building Resilient Cities for the Future

Abstract

In an era marked by rapid urbanization and environmental challenges, the concept of resilient cities has emerged as a crucial paradigm for sustainable development. This paper delves into the innovative integration of water management and healthcare infrastructure to fortify urban resilience. Through the adoption of smart technologies like IoT sensors, big data analytics, and AI algorithms, cities can revolutionize their approach to water resource management and healthcare delivery. By examining case studies and best practices, this paper illustrates how the synergy between water management and healthcare infrastructure not only enhances the adaptability of cities to climate change but also fosters healthier and more livable urban environments. With a focus on building sustainable and resilient cities for the future, this paper offers insights into the transformative potential of converging water management and healthcare infrastructure.

Polaki Sujatha, Sravanam Sreeja, M. Malini Gayathri, Ajay Sheoran, Sarojarani Polamarasetti, Abhijeet Das

Innovative Applications of IoT and Machine Learning

Frontmatter

Chapter 25. Design and Implementation of an IoT-Based Real-Time Monitoring System for Ground Vibration in Opencast Mines in Civil Infrastructure

Abstract

Extensive studies on smart wireless technologies have been conducted in both open-cast and underground mines in the last several years. In particular, the nearby community has annoyance concerns due to the unclear ground tremor caused by blasting practices. The aforementioned systematic literature has shown the current systems that can record the PPV in opencast mines, which are standard seismographs, and the qualities that these systems have, including their benefits and limits. The wireless technology is used to record the levels of ground vibration in this study. Using Internet of Things (IoT) technology, this project aims to build an indigenous wireless system that can accurately measure blast vibrations and transmit that data in real-time from the source node to the end user. To do this, a system was developed and deployed in an opencast mine. It comprises a microcontroller unit, a GPRS/GSM radio communication device, and a MEMS sensor. The created model is trustworthy, cheap, adaptable, and simple to use.

S. Kannan, V. Sujay, P. Siva Satya Sreedhar, Tedla Balaji, Maduri V. N. S. S. R. K. Sai Somayajulu, Sarojarani Polamarasetti

Chapter 26. Improving Decision-Making and Managing Civil Infrastructure in Buildings

Abstract

BIM offers a comprehensive platform for planning, designing, constructing, and managing buildings by providing detailed digital representations of physical and functional characteristics. IoT devices contribute by collecting real-time data on various building parameters, such as energy consumption, structural health, and environmental conditions. AI algorithms analyze this data to predict maintenance needs, optimize energy use, and enhance overall building performance. This integration facilitates a proactive approach to infrastructure management, shifting from reactive maintenance to predictive and preventive strategies. It enables stakeholders to make informed decisions based on accurate, up-to-date information, reducing operational costs, minimizing downtime, and extending the lifespan of building components. Additionally, the paper discusses the benefits of these technologies in enhancing sustainability by improving energy efficiency and reducing the carbon footprint of buildings. The paper also addresses the challenges associated with implementing these technologies, including the need for skilled personnel, the high initial costs, and concerns about data security and privacy. Solutions and recommendations for overcoming these challenges are provided to guide policymakers, engineers, and facility managers in adopting these advanced tools effectively. In conclusion, the paper underscores the importance of leveraging BIM, IoT, and AI to enhance decision-making and management of civil infrastructure in buildings, ultimately contributing to safer, more efficient, and sustainable built environments.

Ponugoti Kalpana, Shaik Abdul Nabi, Potu Narayana, K. Keerthi, K. Naresh

Chapter 27. Biomimetic Smart Materials and Responsive Structure for Sustainable Building Environment: A Comprehensive Analysis

Abstract

This review elaborates the incorporation and implementation of biomimetic smart materials in responsive building structures, focusing on the development of environmental sustainable and efficient energy consumption in the construction sector. By mimicking responsive mechanisms of natural living organisms like plant movements and animal functions, biomimetic phenomenon provides an innovative solution for active environmental responsiveness in the development of building envelopes. By means of an extensive literature study on recent case studies, explores the potential utilization of biomimetic smart materials with specific characteristics such as improved thermal regulation, energy conservation, and reduction in environmental impact. Through comparison, it has been demonstrated that biomimetic materials exhibit greater strength, durability and adaptability, as well as being more environmentally friendly than traditional materials. For example, spider-silk-inspired fibers achieve tensile strengths of up to 1.5 GPa, exceeding the strength of steel, while maintaining light weight, making them ideal for high-performance structural applications. Nacre-effect compounds improve impact resistance by 50% and toughness by 60% compared to conventional compounds. In addition, the gecko-inspired adhesives offer a reversible 10 N/cm² adhesion strength, providing durable yet easy-to-remove bonding solutions. Ultimately, this review demonstrates that biomimetic smart materials can be utilized to enhance the efficiency and sustainability of infrastructure applications by employing nature's design principles to achieve more sustainable construction practices.

Nidhya Rathinavel, Arun Murugesan, Abdul Aleem Mohamed Ismail

Chapter 28. Path Planning Using Defuzzification Approach for Autonomous Vehicles

Abstract

Path planning is one of the most crucial elements of autonomous driving (AD). Due to its capacity to directly make judgments based on observation and learn from the environment, learning-based path planning techniques are of interest to many academics. The standard reinforcement learning approach of the deep Q-network has made major strides in AD since the agent normally learns driving tactics simply by the intended reward function, which is difficult to adapt to the driving scenarios of urban roadways. However, such methodologies rarely use the global path data to address the problem of directional planning, like turning around at an intersection. In addition, the link between different motion instructions like these might easily lead to an erroneous prediction of the route orders due to the fact that the steering and the accelerator are independently governed in a real-world driving system. This research proposes and implements a Provisional Cross-layered Deep Q-Network (PC-DQN) for path planning in end-to-end autonomous vehicles, where the universal path is employed to direct the vehicles from the starting point to ending point. We employ the concept of Improved Harmony Search optimized fuzzy control (HIS-FC) and propose a defuzzification approach to increase the stability of anticipating the values of various path instructions in order to manage the reliance of distinct path instructions in Q-networks. We carry out extensive tests in the CARLA simulator and contrast our approach with cutting-edge approaches. The suggested strategy outperforms existing methods in terms of learning efficiency and driving reliability, according to experimental findings.

L. Sharmila, M. Misba, K. Udayakumar

Title: Recent Advances in Applied Sciences
Editors: Ritesh Bhat
Nithesh Naik
Ketan Kotecha
Antony V. Samrot
Sachi Nandan Mohanty
Bhaskar Somani
Publisher: Springer Nature Switzerland
Electronic ISBN: 978-3-031-84335-8
Print ISBN: 978-3-031-84334-1
DOI: https://doi.org/10.1007/978-3-031-84335-8