Volume 11 | Issue 10 | October-2023

 Abstract

Automatic Vehicle Number Plate Recognition (ANPR) systems are widely used in intelligent transportation, traffic surveillance, toll automation, and security monitoring. This research presents the design and implementation of a Raspberry Pi-based Vehicle Number Plate Recognition Detection System using image processing and machine learning techniques. The proposed system utilizes a Raspberry Pi 4 integrated with a camera module to capture real-time vehicle images. OpenCV is employed for image preprocessing, edge detection, and contour extraction to localize the number plate region. Character segmentation is performed using morphological operations, and Optical Character Recognition (OCR) techniques are applied for alphanumeric character recognition. The system is developed using Python and optimized to run efficiently on a low-cost embedded platform. Experimental results demonstrate satisfactory detection and recognition accuracy under varying lighting and environmental conditions. The proposed model provides a cost-effective, portable, and real-time solution suitable for smart parking systems, toll plazas, institutional entry management, and traffic law enforcement. The integration of embedded computing with computer vision enhances automation while reducing human intervention, making the system a practical approach for intelligent transportation infrastructure development.

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 Keywords

Automatic Number Plate Recognition (ANPR), Vehicle Number Plate Detection, Raspberry Pi, Embedded System, OpenCV, Image Processing, Optical Character Recognition (OCR), Deep Learning, Intelligent Transportation System, Real-Time Monitoring.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Climate change is a significant driver of hydrological variability. Changes in rainfall intensity, distribution, and temperature can affect the relationship between precipitation and runoff. The sensitive nature of the Indian monsoon makes future water resource planning in India increasingly complex. The objective of this study is to evaluate the impact of climate change on water availability in river basins. Historical streamflow data from the selected basins, along with observed rainfall and temperature records from the India Meteorological Department (IMD), were analyzed to identify long-term trends. Correlation and regression analyses were used to quantify the relationships between rainfall, temperature, and streamflow. The Soil and Water Assessment Tool (SWAT) was applied to model baseline and projected scenarios. The results show a positive trend in both temperature and rainfall. The analysis revealed a strong dependence of streamflow on seasonal precipitation. Future simulations indicate that the timing and magnitude of rainfall and dry-season flow may change significantly by the 2050s. Alterations in the pattern and scale of water availability could pose challenges for irrigation scheduling and water management. The findings highlight the importance of incorporating climate projections into regional water-resource management strategies to enhance the adaptive capacity of river-basin systems.

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 Keywords

Climate change; rainfall-runoff relationship; river basin hydrology; CMIP6; IMD data; SWAT model; water availability; climate projection; SSP2-4.5; SSP5-8.5; India

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A large amount of material, labour, equipment and energy is lost as waste throughout the life cycle of construction projects. Material waste can reach double-digit percentages for key products such as concrete, masonry units, timber and finishing materials, while process waste can cause unnecessary labour, waiting time and avoidable transportation. These inefficiencies drive cost overruns, schedule delays and environmental impacts, yet they are often treated as side effects rather than symptoms of sub-optimal resource management. Resource optimisation and waste reduction can be addressed through a unified management framework. This paper builds on concepts from lean construction, highlighting lean production control and digital tools as key enablers. To make these concepts actionable for practitioners, the paper introduces stage-wise tables of strategies, a conceptual figure linking resource decisions to waste streams, and key performance indicators for monitoring materials, labour, equipment and schedule performance. Implementation challenges related to organisational fragmentation, information gaps, capacity constraints and technology integration are discussed, and recommendations are provided for embedding resource optimisation into everyday project practice.

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 Keywords

Construction waste, resource optimization, lean construction, waste minimization, materials management, just-in-time delivery, site logistics planning, building information modelling (BIM), resource-constrained scheduling, performance indicators.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Language is a medium of expression. People use language to exchange their thoughts and feelings with each other. Words are the root of any language which further makes sentences, which hepls in the exchange of thoughts. This implies that words determine the pace of a language and also the future of the language . The fixes it's position according to the period and space. The word which is explosively in use at present time may be obsolete in the near future as the language dwells in the society and it is constantly changing. Society changes from time to time. Hence, words also changes its forms with the changes occurring in the society. The form of words that are accepted and used by the changing society are considered to be "the Chalti" form of words. It indicates the form of an active vocabulary.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Language, Word, Chalti, Assamese.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Dry Eye Syndrome, Public Awareness, Dietary Management, Omega-3 Fatty Acids, Nutritional Education, Ocular Health, Community Intervention, India

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Calcium ion, Ion-selective electrode, Simplified strategies, Electrochemical sensor, Analytical applications, Membrane fabrication

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study examines the rapidly growing payroll outsourcing industry through the lens of SWAS Pay, a new market entrant adopting a Software-as-a-Service model. The global payroll outsourcing market, valued at $9.9-$12.01 billion (2021-2024), is projected to reach $15.5-$24.36 billion by 2033, driven by a 5.04%-7.45% CAGR, as organizations prioritize cost efficiency, compliance automation, and scalable HR solutions. SWAS Pay's hybrid approach combines full-managed payroll services with AI-driven SaaS technology, targeting small-to-medium enterprises (SMEs) in BFSI, healthcare, and IT sectors that seek to mitigate risks associated with multi-state operations and complex labor regulations. The paper analyzes three critical success factors: (1) Operational efficiency through automated tax compliance and error reduction, (2) Cost optimization by eliminating in-house payroll infrastructure and training costs, and (3) Strategic HR reallocation, enabling clients to focus on core business functions. SWAS Pay's competitive differentiation lies in its integrated compliance dashboard, real-time analytics, and dedicated account management SwaS feature that bridge the gap between software automation and personalized service. Implementation challenges include data security concerns inherent to third-party payroll management and the high customer acquisition costs in a market dominated by established players like ADP and Paychex. This abstract synthesizes market data, operational strategies, and competitive positioning specific to SWAS Pay's context, while adhering to the structural requirements of academic abstracts.

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 Keywords

Strategic Outsourcing for Operational Efficiency: A Case Study of Payroll Transformation at SWAS Pay

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 Abstract

The outbreak of COVID-19 led to profound shifts in societal behviours, including a notable uptick in pet adoption as individuals sought companionship during periods of lockdown. This research investigates the consequent expansion of the pet care industry in urban India, with a particular focus on its anticipated market growth and underlying consumer trends. Projections suggest that by 2025, the Indian pet care market could burgeon to a valuation of $2.8 billion, propelled chiefly by heightened pet ownership rates, especially in major metropolitan hubs like Bengaluru. This study employs a mixed-methods approach, combining quantitative data analysis with qualitative insights garnered from interviews, surveys, and industry experts. By examining the perspectives of both pet owners and service providers, it aims to provide a comprehensive understanding of the evolving pet care landscape in urban India post-lockdown. The research elucidates the concerns of pet owners transitioning back to work routines, necessitating reliable and tailored pet care solutions to balance their professional commitments with the needs of their pets. Key findings underscore a burgeoning demand for convenient and personalized pet care services encompassing pet sitting, grooming, veterinary care, and behavioural training.

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The Evolution of Pet Care Services: Meeting the Demands of Modern Pet Owners

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 Abstract

Cybersecurity risks have promulgated the researcher's argument for efficient and effective models for managing incidents. Most traditional methods of executing tasks entail using human resources, which results in slow performance and costly errors. Understanding the new role of AI and ML applications in RPA for optimizing the progressive execution of automated incident management in contextualizations of cybersecurity is crucial for this paper. With the integration of AI and ML, the RPA can analyze large volumes of data and find inconsistent patterns and probable threats quickly; hence, better responses can be made. This paper also reviews different AI and ML approaches that might be applied to ensure efficient threat identification, pattern recognition, and incident resolution. Only practical examples are presented to illustrate the algorithms' effectiveness. Further, the paper presents primary issues and alternatives that cover technical issues and ethical concerns regarding the employment of AI-activated automation. As highlighted in the study, adopting RPA by incorporating AI and ML enhances service delivery and minimizes the time and resources needed to manage the incidents. Therefore, it is a rich source of knowledge enhancement for modern cybersecurity mechanisms.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

RPA, Cyber threat, IBM security, Cyber security

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Green banking is an emerging trend in the global banking industry, with the aim of integrating environmental sustainability into financial practices. This research paper delves into the concept of green banking, explores its significance, and assesses its implementation across various financial institutions. By analysing secondary data from industry reports, scholarly articles, and case studies, this paper provides insights into how green banking contributes to environmental conservation, supports sustainable development, and encourages eco-friendly practices within the banking sector.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Green banking, Sustainable finance, Environmental sustainability, Eco-friendly banking, Green investments, Financial services

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Creative Commons Attribution 4.0 and The Open Definition