In recent years, blockchain technology has emerged as a promising solution for securing electronic health records (EHRs) while preserving patient privacy. Traditional e-health systems facilitate EHR sharing among healthcare providers but also introduce significant privacy risks, such as unauthorized access and data breaches. Blockchain, when integrated with privacy-preserving techniques, enhances transparency, integrity, and availability in EHR management. Smart contracts further strengthen security by enabling automated authentication and access control. This paper provides a comprehensive survey of blockchain-based access control frameworks in healthcare, categorizing them into permissioned and permissionless approaches. It also explores cryptographic privacy-preserving techniques designed to mitigate privacy risks. Additionally, blockchain platforms and consensus protocols commonly used in these frameworks are analyzed. The methodology follows a structured paper selection process, leading to the final inclusion of 45 research papers focusing on blockchain-based privacy preservation and access control in healthcare. Furthermore, it presents real-world case studies that illustrate the practical implementation of blockchain-based access control in healthcare settings, highlighting their strengths and challenges. Finally, it identifies privacy-related challenges, open research issues, and future directions to guide further research in this evolving domain.

Sustainability in software engineering encompasses environmental, human, social, and economic dimensions, each essential for ensuring software’s positive and lasting impact. This paper presents an innovative Internet of Things (IoT)-based Smart Waste Management (SWM) system. The proposed system addresses key limitations in existing solutions, including lack of real-time responsiveness, inefficient routing, inadequate emergency detection, and limited user-centric design. While prior studies have investigated IoT applications in SWM, challenges remain in achieving dynamic, integrated, and scalable systems for sustainable urban development. The proposed solution introduces a holistic architecture that enables real-time monitoring of waste bin levels and fire incidents through Waste Bin Level Monitoring Units (BLMUs) equipped with ultrasonic and flame sensors. Data is transmitted via Wi-Fi to a centralized City Command and Control Center (4C), allowing for automated alerts and dynamic route optimization. A dual-platform software suite supports both administrative and operational workflows: a desktop web application and a role-based Android mobile app developed in Flutter, and integrated with Google Cloud Firestore, enabling centralized data management and efficient resource allocation. We validated the system through a working prototype, demonstrating notable contributions including enhanced emergency responsiveness, optimized waste collection routes, and improved stakeholder engagement. This research contributes to the advancement of sustainable urban infrastructure by offering a scalable, data-driven SWM framework grounded in software engineering principles and aligned with smart city objectives. This paper presents an innovative IoT-based Smart Waste Management (SWM) system that addresses key limitations in existing solutions, including insufficient real-time responsiveness, inefficient routing, inadequate emergency detection, and limited user-centric design.

This work conducts a comprehensive examination of the impact of rotational motion on the transmission of thermomechanical waves in microelongated thermoelastic materials. The analysis is conducted within the framework of fractional‐order heat conduction by incorporating the β ‐fractional derivative into three established thermoelastic models: the Lord–Shulman (L–S) theory, the dual‐phase‐lag (DPL) model, and the refined dual‐phase‐lag (RDPL) model. The essential mathematical frameworks governing heat transfer, elastic deformation, and microelongation are methodically derived to precisely characterize the combined thermal and mechanical interactions. These equations explicitly incorporate limited thermal wave velocities, rotating influences, and the inherent microstructural elongation properties of the medium. To simplify the resulting mathematical formulation and facilitate analytical tractability, an appropriate nondimensionalization process is employed in conjunction with a suitable transform method. This methodology lowers the original set of highly coupled partial differential equations (PDEs) to a more manageable form, from which precise analytical formulas for the displacement components, microelongation field, temperature distribution, and stress tensors are derived. The derived solutions provide a comprehensive description of the spreading behavior of thermoelastic waves in microelongated materials subjected to rotational motion. To validate and illustrate the theoretical findings, numerical computations are carried out, allowing a detailed comparison of the responses predicted by the L–S, DPL, and RDPL models. These comparisons are performed for two distinct scenarios: one incorporating fractional‐order effects and the other based on the classical nonfractional formulation. The findings of this work highlight the interaction of rotational motion, β ‐fractional heat conduction, and phase‐lag effects in determining the dynamic thermoelastic response of microelongated materials. The proposed framework offers a more broad and physically accurate description of wave propagation events in such media, which could be useful for advanced material modeling and engineering applications.