The explosive growth of Internet of Things (IoT) devices has generated considerable data in diverse networks. This poses serious challenges in collecting timely information and managing frequency resources optimally. In particular, unauthorized access, measurement constraints, and variable channel conditions cause interference, performance degradation, and security compromise, especially in distributed IoT systems. This research presents a comprehensive system for improving data collection in heterogeneous IoT networks. Using complex mathematical models and machine learning algorithms, the system aims to increase the efficiency of frequency resource utilization and reduce interference in network access. A Q-based reinforcement learning method is designed along with an intelligent MAC protocol. Simulation results show that this method increases channel utilization efficiency by 25%, reduces interference probability by 30% compared to traditional methods such as ALOHA, and provides a flexible and scalable solution for frequency resource management. The performance of the proposed system is significantly better than traditional methods, increasing channel utilization efficiency by 25% and reducing the probability of interference by 30%. The system's self-learning capability enables effective frequency resource management even in complex and dense environments. This research presents an innovative method for data collection in IoT networks that combines machine learning and mathematical modeling, providing a secure and scalable solution for the next generation of heterogeneous networks. This system paves the way for designing more stable and efficient networks in various fields, including smart cities and industries.

In the current era of data-intensive applications, including OTT services, IoT, and autonomous systems, efficient image compression is indispensable in order to minimize bandwidth consumption while preserving visual quality. Conventional compression techniques frequently fail to satisfactorily balance compression ratios and the preservation of critical image details. This work introduces a novel adaptive image compression method that is area-aware and utilizes a dual-background classification system to improve data preservation. The method classified areas into major and minor backgrounds by aggregating image regions based on visual characteristics. It applied aggressive quantization to less salient regions and refined compression techniques for critical details. A saliency map, reflecting human visual perception, guides this process, ensuring the preservation of the most visually significant information. By customizing quantification to the visual priorities of a particular region, the proposed methodology enhances the quality of images and the efficacy of compression. Extensive testing demonstrates that the area- aware approach outperforms traditional compression algorithms, enhancing the visual experience and significantly reducing data traffic. This research work mainly focuses on the reducing of data size and simultaneously preserving the image quality at required regions by using of adaptive compression techniques. This is particularly relevant for applications that necessitate high-quality image transmission in a data-driven world.

This study presents a year-long vibration-based structural health monitoring (SHM) of the Swarnamukhi River Bridge and Bhakta Kannappa Sethu Bridge using a MEMS accelerometer integrated with a lowcost microcontroller system. The monthly dynamic response parameters of acceleration, displacement, frequency, and velocity were monitored from June 2024 to May 2025 under four traffic loads (Low to Peak). Advanced diagnostic indices including Normalized Dynamic Index (NDI), Dynamic Performance Ratio (DPR), Stiffness Degradation Index (SDI), and Health Stability Index (HSI) were computed to assess real-time structural integrity. Results revealed Bhakta Kannappa exhibited higher dynamic variability, with peak displacement and velocity reaching 1.418 mm and 0.03742 m/s. In contrast, Swarnamukhi exhibited higher stiffness and frequency stability, with peak values of 0.02931 m/s and 1.088 mm, respectively. Swarnamukhi's greater stability up to 358.00 was supported by HSI values, but Bhakta Kannappa's lower HSI (< 50) indicated wider reaction variations. Seasonal diagnostic trends have documented the effects of heat and stress accumulation caused by traffic. In situations where resources are limited, the combination of inexpensive MEMS (Micro-Electro-Mehanical Systems) sensors and diagnostic indices offers a potent foundation for continuous SHM, facilitating predictive maintenance and enhancing bridge resilience.

This study aimed to evaluate the impact of participatory urban planning on community well-being and quality of life. Urban planning is done to transform urban areas into sustainable cities with adequate open spaces and many features of smart cities. To achieve successful urban planning, active and involved participation of the stakeholders is necessary. Many aspects, like the social and cultural identities of the nation, its technological competencies, adequate knowledge and expertise in urban planning and sustainable development, are required. A survey of 150 Saudi professionals with expertise or interest in urban development and community well-being showed that the above results have only been partially achieved. These results were only partially and sometimes indirectly supported by the literature. Community participation in urban planning may be improved by using social media platforms and information and communication technologies. These methods will be useful to connect urban planning officials/local governments with concerned stakeholders. Although the specific social and cultural identities of Saudi Arabia need consideration in ensuring community participation, this should not be at the exclusion of non-Saudi communities.

Urban architecture's role is vital in creating an inclusive environment for visually impaired people and affording them easy accessibility in navigating through the built environment. This paper debates the essential principles of urban design, which focus on tactile, auditory, and sensory elements to accommodate visually impaired people. It underlines best practices in architectural practice, including the integration of textured paths, audible signals, high contrasts, and wayfinding systems that enhance spatial awareness and mobility. The paper further explores the psychological and social impacts of accessible urban spaces and highlights the importance of inclusive design for independence and social participation. It provides recommendations for taking innovative approaches to user-centred design that will set a path for architects, urban planners, and policy-makers in creating an environment that serves all members of society with equity. This present research exemplified the transformation potential within urban architecture in the pursuit of building truly inclusive cities for visually impaired people's empowerment.

This research delves into the intricate relationship between environmental characteristics and livestock distribution in Al-Manathira district, Iraq. The study evaluates the influence of natural factors such as land topography, soil fertility, water resource availability, and climatic conditions on the spatial patterns of livestock species, including cattle, sheep, goats, and buffalo. Employing a mixed-methods approach, it combines field surveys, soil analysis, and spatial data mapping to reveal how environmental zones shape the densities and productivity of various livestock. Results highlight significant correlations between fertile soils, proximity to water resources, and livestock density, particularly in riverine lowlands. This analysis provides actionable insights for optimizing livestock management practices, promoting sustainable agricultural development, and addressing the challenges posed by environmental constraints in semi-arid regions like Al-Manathira.

In nature, the bucking behavior of the web of I section reduces the member's strength considerably. Hence, in common practice, people use the intermediate and end stiffeners to improve the strength of the beam. The stiffeners are connected to the web using the welded connections. In this paper, the experimental study on steel beams with and without stiffeners is reported. The weld length of the stiffeners has been varied and the study has been carried out. Three specimens were tested. One without stiffeners, one with full weld, and one with half weld. The strength will be enhanced due to the presence of stiffeners. The increase is about 53%. It is interesting to note that the strength of the half weld and full-weld specimens is not very different. All the other parameters such as ductility, stiffness, and energy dissipation are reported in the paper.