In intelligent transportation system, traffic surveillance is an important topic. One challenging problem for complex urban traffic surveillance system is robust vehicle detection and tracking. Therefore, in this paper, we develop a two-stage approach for moving vehicle detection system. The proposed system mainly consists of two stages such as hypothesis generation (HG) and hypothesis verification (HV). In the first step, we generate the hypotheses using shadows under vehicles is darker than road region concept. In the second step, we verify hypotheses generated in the first step whether correct or not using optimal feedforward neural network (OFFNN). Here, to extract vehicle features, we utilize two types of histogram orientation gradients descriptors (HOG). In training stage, the histogram orientation gradients features are given to the OFFNN classifier. The weights corresponding FFNN is optimally select using improved grasshopper optimization algorithm (IGOA). The experimental results show that the proposed moving vehicle detection system performs better accuracy compare to other methods.

Within the era of Industry 5.0, agencies are experiencing extensive changes pushed by way of statistics-pushed choices, new technologies, and connectivity. This looks at and explores how the complexity of Industry 5.0 is typically driven by Business Intelligence (BI) and large records analytics. We live in a generation packed with large amounts of dynamic and diverse statistics because of the convergence of cyber-bodily systems, smart devices, and the Internet of Things (IoT). For organizations to efficaciously leverage those large quantities of information, commercial Business Intelligence (BI) and statistics analytics are essential technologies. Business intelligence normally entails the collection, evaluation, and presentation of corporation information, forming the premise for knowledgeable selection-making. Business Intelligence (BI) in Industry 5.0 consists of real-time analytics and predictive insights that move beyond widespread reporting.

As society transitions into the digital era, the anticipated requirements and expectations placed on various sectors undergo profound transformations. This proposed study explores the shifting landscape, identifying key demands and expectations across various domains and highlighting the requirement for adaptability and innovation. The digital era has directed transformative changes, redefining the landscape of libraries into dynamic digital repositories. Anticipating the future requirements and expectations in this evolving domain is imperative for effectively catering to user needs. The term ‘digital library,' often referred to as a ‘digital repository,' is crucial in contemporary information. The process of transforming a digital repository into an institutional repository (IR) is of dominant importance. The variations observed in institutional repositories are designed to align with users' demands and expectations for digital information and services.

The advent of blockchain technology offers revolutionary possibilities for various industries, including the library sector. This chapter delves into the application of blockchain in establishing collaborative library networks, with a particular focus on its advantages for knowledge sharing and resource pooling. Blockchain's decentralized, secure, and transparent ledger system provides an innovative solution to many challenges faced by libraries today. In collaborative library networks, blockchain can ensure the maintenance of a unified, tamper-proof catalog of resources. This decentralized cataloging system guarantees that all participating libraries have access to consistent and current information, reducing redundancy and discrepancies. Moreover, blockchain facilitates efficient tracking and management of interlibrary loans through smart contracts, which automate the processes of loan requests, approvals, and returns. Additionally, blockchain technology can significantly improve the management of intellectual property and digital rights within library networks.

In the digital era, preserving the authenticity and integrity of digital archives is increasingly challenging due to risks such as data corruption, unauthorized modifications, and technological obsolescence. Traditional preservation methods are often insufficient to address these issues, which jeopardizes the long-term reliability and accessibility of digital records. Blockchain technology offers a transformative solution with its decentralized and immutable ledger system. By recording transactions in a way that prevents retroactive alterations, blockchain ensures the integrity and authenticity of digital records, providing a robust, tamper-proof method for digital preservation. Successful implementations (Jackson, 2024), such as the UK National Archives and the Archangel Project, highlight blockchain's effectiveness in creating secure, verifiable digital archives(Rajkumar, Viji, et al., 2024). The integration of blockchain technology into digital preservation strategies has demonstrated significant potential for addressing persistent challenges.

Blockchain technology has the potential to revolutionize academic libraries by enhancing research and collaboration. By providing a decentralized and transparent platform, blockchain can facilitate the secure and efficient sharing of research data and resources among academics globally. This fosters greater collaboration, as researchers can easily verify the authenticity of data and build upon each other's work without concerns about data tampering. Blockchain's immutable ledger ensures that all contributions are recorded transparently, thus promoting trust and integrity in academic research. Traditional publishing often involves lengthy and opaque processes, but blockchain can streamline these by providing a transparent and efficient system for manuscript submission, peer review, and publication. Smart contracts can automate and enforce peer review protocols, ensuring timely and unbiased reviews.

Drone Technology is being used by an increasing number via the development area to improve some of the elements of its operations. Drones have unique competencies that can grow construction projects effectiveness, protection, and affordability. This study examines how drones are presently being used inside the construction zone and the way they could affect construction site online surveying, project control, development monitoring, and safety inspections. The study additionally addresses the difficulties and capacity benefits of incorporating the drone era into production methods. The drone era has a variety of capabilities to change traditional techniques inside the production industry and decorate challenge outcomes. Drone-era software creation has become a recreation-changing trend with many benefits, from more suitable productivity to safer and greater sustainable operations. Drones are being used for some purposes, which include environmental tracking, site online surveying, inspections, and development tracking. This study examines the several uses of drones within the construction sector and talks about how this technology may affect the sector going forward

Implementing blockchain in libraries involves several key steps to ensure successful integration and optimal functionality. Firstly, libraries need to identify specific use cases where blockchain technology can add value, such as in cataloging, digital rights management, and user authentication. Following this, it's essential to conduct a feasibility study and pilot projects to evaluate the effectiveness of blockchain applications in a library setting. This should be complemented by training staff on blockchain fundamentals and its benefits. Building partnerships with blockchain experts and technology providers can also facilitate a smoother implementation process. Technical considerations include ensuring robust cybersecurity measures, choosing the appropriate blockchain platform (public, private, or consortium), and integrating blockchain with existing library management systems. Infrastructure requirements involve upgrading or investing in new hardware and software that support blockchain operations, as well as ensuring a reliable and scalable network infrastructure.

Blockchain technology deals a transformative approach to enhancing access to information by leveraging its dispersed and apparent nature. Traditional information access systems often face challenges such as restricted access, censorship, and inequalities in information dissemination. Blockchain decentralizes control, enabling a more resilient structure for accessing and sharing information, which is particularly beneficial in regions with restricted access. This technology democratizes data control, ensuring that no single entity can restrict the flow of information, thereby promoting inclusivity and diversity in knowledge sharing. In the realm of scholarly publishing, blockchain facilitates open access models, reducing costs and increasing the accessibility of research. Authors can retain control over their work while sharing it globally, accelerating the dissemination of knowledge and fostering greater collaboration and innovation. This can help underserved communities gain access to essential information and services, promoting a more inclusive and equitable digital world.

As the mixture of artificial intelligence (AI) continues to permeate several sectors, ethical considerations have ended up a focus in ensuring responsible and sustainable AI deployment. This virtual library explores the multifaceted moral dimensions related to AI implementation. The gathering of scholarly articles and studies papers delves into key moral problems, spanning troubles which includes bias and fairness, transparency, responsibility, privacy, and societal impact. The number one section of the virtual library addresses the undertaking of algorithmic bias and fairness, reading how biases in AI systems can perpetuate societal inequalities. Various methods to mitigating bias and selling fairness in AI algorithms are explored, providing insights into the improvement of more equitable AI programs. Transparency and duty are the focal factors of the second one segment, emphasizing the need for clean conversation of AI decision-making techniques and mechanisms for holding AI systems answerable for their movements.

Effective presentation slides are crucial for conveying information efficiently, yet existing tools lack content analysis capabilities. This paper introduces a content-based PowerPoint presentation generator, aiming to address this gap. By leveraging automated techniques, slides are generated from text documents, ensuring original concepts are effectively communicated. Unstructured data poses challenges for organizations, impacting productivity and profitability. While traditional methods fall short, AI-based approaches offer promise. This systematic literature review (SLR) explores AI methods for extracting data from unstructured details. Findings reveal limitations in existing methods, particularly in handling complex document layouts. Moreover, publicly available datasets are task-specific and of low quality, highlighting the need for comprehensive datasets reflecting real-world scenarios. The SLR underscores the potential of Artificial-based approaches for information extraction but emphasizes the challenges in processing diverse document layouts. The proposed is a framework for constructing high-quality datasets and advocating for closer collaboration between businesses and researchers to address unstructured data challenges effectively

In the dynamic landscape of contemporary education, the integration of educational technology (EdTech) and the evolving role of libraries stand as pivotal forces in shaping and supporting online learning experiences. This chapter delves into the intricate synergy between educational technology and libraries, exploring their collaborative potential in fostering enhanced online learning environments. The introduction sets the stage by elucidating the background and context, emphasizing the paramount importance of EdTech in the digital age, and outlining the critical role libraries play in facilitating online learning. The subsequent sections dissect the multifaceted dimensions of educational technology in online learning, elucidating the diverse array of technological tools, their integration into teaching and learning processes, and their profound impact on student engagement and academic outcomes. As the narrative unfolds, attention shifts to the metamorphosis of libraries into supportive hubs for online learning, tracing the evolution of their role in the digital era. In the dynamic landscape of contemporary education, the integration of educational technology (EdTech) and the evolving role of libraries stand as pivotal forces in shaping and supporting online learning experiences. This chapter delves into the intricate synergy between educational technology and libraries, exploring their collaborative potential in fostering enhanced online learning environments. The introduction sets the stage by elucidating the background and context, emphasizing the paramount importance of EdTech in the digital age, and outlining the critical role libraries play in facilitating online learning. The subsequent sections dissect the multifaceted dimensions of educational technology in online learning, elucidating the diverse array of technological tools, their integration into teaching and learning processes, and their profound impact on student engagement and academic outcomes. As the narrative unfolds, attention shifts to the metamorphosis of libraries into supportive hubs for online learning, tracing the evolution of their role in the digital era.

The Blockchain era has rapidly gained recognition for its capability to revolutionize various industries, which include libraries. This abstract delves deeper into the important components of blockchain programs in libraries. It explores how blockchain can facilitate transparent and relaxed transactions within interlibrary loan structures, foster virtual rights management for content material acquisition, and decorate the authenticity of digital records. Additionally, the abstract explores the potential of blockchain in permitting libraries to create immutable facts of provenance for rare materials and organizing decentralized structures for useful resource sharing among libraries worldwide. Utilizing blockchain technology, libraries can't handily ensure the trustworthiness of records but also foster innovation in virtual protection and access offerings. This aims to offer a complete assessment of the possibilities and implications of integrating blockchain into library operations, paving the way for a more green and obvious data environment.

The biggest challenge in the global market is Counterfeiting, it has undesirably affected consumer perception and damaged the brand reputation of the product. Recently few techniques used in the identification of counterfeit products include block chaining, RFID tags, and unique code techniques among others but they do not entirely control the existence of counterfeits in the market as well as losing their dependability and scalability. Consequently, these techniques are expensive and technologically advanced. This research presents a new approach based on reliable product authentication using QR code technology powered by mathematical computational algorithms. Employing implementing this system; however, customers can recognize fake goods and sustain the brand’s integrity. The proposed approach entails creating Unique QR codes for every product whose coded data contains the encrypted product information. These include product numbers, manufacturing dates as well as batch numbers of the products which are hashed and then encrypted with sophisticated computational algorithms; these two algorithms secure the product, one generating QR codes for a product containing information thereof and the other that confirms if the consumer is holding a genuine item using a mobile application. Through experimental results, it was evident that the system is highly accurate, reliable, and speedy since verification times averaged below 1 second. This research also outlines some of the strengths of the proposed system including enhanced product originality as well as potential limitations such as internet connectivity and initial set-up costs. In future work, we will optimize our encryption algorithm and expand to other products within the system’s coverage area.

As numerous manufacturing enterprises are progressing towards Industry 4.0, advanced predictive models are required to optimize contemporary construction practices. The precise prediction of the compressive strength of cement is crucial, as it is an integral material for any constructional unit. This research paper explores numerous advanced machine learning and ensemble learning techniques for effective concrete strength prediction, enabling proactive quality control measures in an Industry 4.0 based environment. The research utilizes an open-source dataset and employs advanced machine learning techniques to interpret and learn intricate relationships among input features, such as cement quantity, blast furnace slag content, fly ash ratios, water weight, superplasticizer usage, and coarse and fine aggregate proportions, as well as curing age for predictive modeling. Experimental results validate the Histogram-Based Gradient Boosting model as an optimal technique for effectivey forecasting the compressive strength of cement in Newtons per square millimeter (MPa), with a cross-validation R2 Score of 0.922. The findings of this research work contributes to the increasing demand for accurate and scalable predictive models within the quality control unit of an Industry 4.0 based manufacturing firm.

Age estimation is of prime significance in forensic science and clinical dentistry. Age estimation based on teeth improvement is one solid approach. Numerous radiographic strategies are proposed on the southern populace for evaluating Dental Age (DA), and a comparative appraisal was observed to be insufficient in Indian populace. Henceforth, this investigation goes for detailing a classification model for DA estimation in Indian kid’s populace utilizing Demirjian’s technique. In this exploration, a Fuzzy Neural Network with Teaching Learning - Based Optimization (FNN-TLBO) is proposed for classification of DA. At first, the OPG input image is preprocessed for diminishing noise and smoothing the image by utilizing Anisotropic Diffusion Filter (ADF). Thusly, the whole teeth from teeth picture are portioned utilizing Active Contour Model (ACM) with Analytic Hierarchy Process (AHP) optimization and after that morphological post handling has been connected on the sectioned outcome to advance the order precision. Next, specific highlights are removed, for example, GLCM, Haralick features, Haufsdroff distance, crown and root, tooth density, size, Geometric features such as roughness, concavity, convexity, area and perimeter to upgrade the expectation exactness. Finally, the age has been classified with FNN-TLBO. In this FNN, TLBO is utilized to take care of the system training issue. Recreation results shows that the expected FNN-TLBO procures better execution with deference than accuracy rate of 89%, specificity rate of 89.12%, precision rate of 64.152%, recall rate of 92% and F-measure rate of 71.12% compared than exist algorithms like Modified Extreme Learning Machine with Sparse Representation Classification (MELM-SRC), Radial Basis Function Network (RBFN), Demirjian and Adaptive Neuro Fuzzy Inference System (ANFIS) schemes.

In smart cities and urban environment, monitoring of water quality is very essential for environmental sustainability, resource optimization, cost management and streamlining the treatment process. In this research, an extensive dataset containing various contaminants such as aluminum, ammonia, arsenic, and others is utilized to effectively classify the safety level of water. Different machine learning and ensemble learning classifiers including LightGBM, XGBoost, CatBoost, Bagging, Gradient Boosting, Random Forest, Decision Tree, AdaBoost, MLP, and Extra Trees were implemented to conduct an empirical experimentation. Various performance metrics like Accuracy, Precision, Recall, F-1 Score, F-2 Score, Sensitivity, Specificity and AUC-ROC were used to evaluate the machine learning techniques utilized in this research. Experimental results indicate that the LightGBM ensemble technique outperformed other models with the accuracy of 97.13% and AUC-ROC of 98.99%, due to its optimized gradient boosting and effective processing of categorical features. This research contributes to the algorithmic approach for developing decision support tools for improving sustainable smart city water management techniques.

User Authentication and Privacy explores the application of blockchain technology in enhancing user authentication and protecting user privacy within library systems. The decentralized and immutable nature of blockchain provides a robust alternative to traditional centralized authentication methods, which are often vulnerable to breaches and unauthorized access. By utilizing blockchain, libraries can implement a secure and transparent system for verifying user identities, significantly reducing the risk of data tampering and unauthorized access. This study delves into the specifics of how blockchain can safeguard user data, ensuring confidentiality and integrity. Additionally, the use of blockchain for identity management in libraries is examined, demonstrating its potential to offer a streamlined, tamper-proof, and trustless environment for identity verification. Blockchain's ability to enhance data security and protect user privacy makes it an ideal solution for modernizing library management systems.

Digital libraries, as dynamic repositories of diverse and expansive information, encounter significant privacy and security concerns that necessitate careful attention. The intersection of vast datasets, user interactions, and the imperative to maintain information accessibility amplifies the complexity of safeguarding privacy and ensuring robust security measures. Privacy concerns within digital libraries revolve around the collection and handling of user data. As users engage with the digital library, their personal information, search patterns, and preferences become integral components of the library's dataset. Striking a balance between utilizing this data for personalized services and respecting user privacy requires a delicate approach. Users rightfully demand transparency regarding data practices, the purpose of data collection, and assurance that their information is handled responsibly.

This paper explores the transformative fusion of Quantum computing, Artificial Intelligence (AI), the Internet of Things (IoT), and advanced optical systems within smart city development. A significant innovation within this study is the concept of “optical IoT,” wherein IoT relies on advanced optical technologies, including high-resolution cameras, LiDAR scanners, meters, sensors, and wearables, strategically distributed throughout urban environments for real-time image data acquisition. Traditional smart city models may rely on conventional data acquisition methods that are not real-time or high-resolution, leading to delayed and less accurate urban management decisions. Existing models might use disparate systems for monitoring and management, which can result in inefficient resource allocation and coordination, especially in critical situations like emergency response. In this research Advanced Smart City Architecture (ASCA) this integration empowers the system to excel in tasks such as semantic segmentation, enabling precise identification and categorization of urban elements. Quantum optical systems are employed in quantum-enhanced sensors, such as quantum-enhanced interferometers and atomic clocks. These sensors offer improved precision for measurements like distance, time, and acceleration. The ASCA approach equips city planners, administrators, and emergency responders with real-time urban monitoring and management capabilities. This dynamic system yields numerous advantages, including optimized resource allocation, enhanced traffic management, improved environmental quality, and swift emergency response capabilities. This research underscores the immense potential of ASCA in reshaping urban development and sustainability within smart cities. By harmonizing AI, IoT, and advanced optical systems, this paradigm shift enables smart cities to evolve into more efficient and resilient urban environments. These cities become finely attuned to the ever-evolving needs of their residents, ultimately fostering innovation and progress at an unprecedented scale. Proposed ASCA achieves an impressive 91.98% enhancement in sustainable smart city development when compared to these existing techniques.