Journal of Advanced Engineering & Applied Sciences
The Journal of Advanced Engineering & Applied Sciences (JAEAS) is a peer-reviewed, open-access scholarly publication dedicated to advancing research and innovation in engineering, technology, and applied sciences. JAEAS provides a platform for academics, researchers, and industry professionals to disseminate high-quality original research, review articles, and technical studies that contribute to scientific knowledge and practical applications in engineering and allied disciplines.
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Effect of Antenna Design Optimization and Signal Processing Techniques on Signal Strength
The nature of wireless communication systems which are rapidly evolving has raised the need to have an efficient transmission and reception of signals. Optimization of the antenna design and signal processing methods are important in boosting signal strength and the overall communication performance. The paper explains how the antenna design optimization and improved signal processing technique can be employed to complement each other to improve the signal strength within the modern day communication system. It is a quantitative study and is interested in the combination of design parameters such as the geometry of the antenna, frequency tuning and material selection with digital signal processing such as filtering, modulation and elimination of noise. Findings of the literature available indicate that a combination of efficient signal processing approach along with optimized antenna geometry towards its design, improves the signal quality, alongside interference mitigation and data system reliability by magnitudes. The work is a contribution to the field since it offers a holistic perception of the interaction between the two domains to affect signal strength and any engineer and researcher in the field of telecommunications and wireless network design can use it.
Copyright (c) 2026 Hassan Ahmad, Hina Rashid (Author) https://creativecommons.org/licenses/by/4.0
Impact of Hybrid Renewable Systems and Energy Management Systems on Power Supply Stability
The growing demand on the world to have a reliable and sustainable energy has heightened studies on hybrid renewable energy systems and energy management systems to guarantee constant supply of power. Hybrid renewable systems that combine several renewable resources, including solar, wind, and storage technologies, are a promising way to overcome the challenge of intermittency and variability of single-source energy systems. Energy management systems are essential in ensuring that energy generation, storage and distribution are optimized to be stable and efficient in the power supply networks. In this paper, we will discuss the synergies between hybrid renewable systems and energy management systems in terms of the stability of power supply based on the results of the recent literature. According to the results, hybrid integration will increase the reliability of the system and intelligent energy management will increase the load balancing, decrease the fluctuations of power and increase the overall stability of the grid. The research adds to the knowledge on how organized integration of renewables and progressive control measures can enhance sustainable and robust power infrastructure in contemporary electricity networks.
Copyright (c) 2026 Azhar Hussain, Fatima Saleem (Author) https://creativecommons.org/licenses/by/4.0
Impact of Sustainable Materials and Material Composition on Structural Strength
Changing to sustainable construction materials is one of the most far reaching changes in the practice of civil and structural engineering in the last twenty years which was motivated by the environmental requirements, resource limitations and changing performance demands. This paper explored how sustainable materials and material composition affect structural strength among the civil engineers, construction professionals, and material specialists in the infrastructure and construction industries in Pakistan. The quantitative approach was used. The respondents sampled were 200 chosen using purposive sampling criteria on the basis of engagement in material selection and structural design. The perceptions of sustainable material properties, material composition optimization practices, and structural strength results were measured in a structured questionnaire with a 5-point Likert scale with additional technical performance indicators. Descriptive statistics were used to summarize profiles of respondents. Cronbachs alpha, Composite Reliability (CR), and Average Variance Extracted (AVE) were used to evaluate reliability and validity. Inter-variable correlations were studied using correlation analysis. The hypothesized relationships were tested using Structural Equation Modeling with SmartPLS 4.0. Sustainable materials showed a high level of positive direct impact on the structural strength (beta = 0.46, p <.001), and material composition shows the same high level of positive direct impact (beta = 0.43, p <.001). The structural model was found to explain 59.4% of the variance in structural strength (R-squared = 0.594). These results demonstrate that sustainable material use and optimization of material composition systematically are complementary and reinforcing directions towards structural strength realization, and have significant implications to sustainable construction practice in Pakistan.
Copyright (c) 2026 Ahmed Salman (Author) https://creativecommons.org/licenses/by/4.0
Effect of Power Electronics Control Techniques and Switching Optimization on Energy Efficiency
The increased need of power efficient power systems in industrial, commercial as well as renewable energy systems has brought power electronics control methods and switching optimization to a strategic level in engineering. This paper measured the impact of energy saving in the professionals of the power generation and distribution market in Pakistan by power electronics control methods and switching optimization. A quantitative research design that is engineering-oriented was adopted. A purposive survey sample of 200 electrical engineers, designers of power systems and industry experts were surveyed using a structured survey instrument comprising of perceptual scales, and technical assessment indicators, which was chosen via purposive sampling based on pertinent experience in the field. Descriptive statistics were used to summarize the profile of respondents and variables. Measures of reliability and validity were measured using Cronbach alpha, Composite Reliability (CR) and Average Variance Extracted (AVE). Inter-variable relationships were analyzed using correlation analysis. The measurement model and structural relationships were tested with Structural Equation Modeling (SEM) with SmartPLS 4.0. These power electronics control techniques showed a strong positive impact on energy efficiency (beta = 0.51, p < .001), and switching optimization also had a strong positive direct impact (beta = 0.44, p < .001). This model was able to explain 62.3 percent of the variation in energy efficiency (R-squared = 0.623). These results demonstrate that both the intentional use of high-level techniques of control and organized optimization of switching parameters are key levers in the attainment of real energy efficiency gains in the power systems in Pakistan.
Copyright (c) 2026 Anas Aamir Memon (Author) https://creativecommons.org/licenses/by/4.0
Effect of Mechatronic Systems on Precision Engineering: Mediating Role of Control Algorithms
The combined use of mechanical, electrical, electronic and computational subsystems, known as mechatronic systems, have emerged as essential facilitators of precision engineering in contemporary manufacturing and robotics applications. This paper has examined how mechatronic systems influence the results of precision engineering using control algorithms as a mediator variable. A quantitative type of research design was adopted. A structured questionnaire with technical evaluation criteria was used to gather data on 200 mechatronics engineers, automation specialists, and manufacturing professionals in the manufacturing and robotics sectors in Pakistan using purposive sampling as a selection criterion based on relevant professional expertise. Respondent descriptions were summarized by descriptive statistics. Cronbach alpha, Composite Reliability (CR) and Average Variance Extracted (AVE) were used to measure reliability and validity. Inter-variable relationships were analysed using correlation analysis. The analysis of the direct effects and the mediating effect by control algorithms was tested by the Structural Equation Modeling with SmartPLS 4.0. There was a strong positive direct impact of mechatronic systems on precision engineering (beta = 0.34, p < .001) and a strong positive impact on control algorithms (beta = 0.56, p < .001). Control algorithms were a significant predictor of precision engineering ( beta = 0.48, p < .001). Mechanistic mediation analysis established the significant indirect impact of mechatronic systems on precision engineering using control algorithms (indirect beta = 0.269, 95% CI [0.188, 0.354]) meaning that it is partially mediated. The complete model was a 64.7-percent predictor of precision engineering (R-squared = 0.647). These results confirm that the main process by which the capabilities of the mechatronic systems can be converted into the precision engineering results is the sophistication of control algorithms.
Copyright (c) 2026 Akhtar Mahmood (Author) https://creativecommons.org/licenses/by/4.0
Ethical and Social Implications of Big Data Analytics in Decision Making Processes
The Big Data analytics has transformed how decisions are arrived at in most industries by facilitating the capabilities to process large quantity of data within a limited period of time and obtain insights, predictions and arrive at decisions. Though all of these innovations are yielding positive outcomes in increasing efficiency, evidence-based policymaking, and innovation, there exist severe ethical and social consequences as well. The most notable ones are the atmosphere of privacy erosion, algorithm bias, absence of transparency and lack of accountability, the surveillance threat, and the heightened social disparities. Through the frames of public policy, business strategies, the health care and the police, with regard to the ethical and social perspective, this paper critically reviews the ethical and social challenges of the decision-making perspective of the responsible data usage through review of structures and governance mechanisms of the responsible data usage. The interdisciplinary synthesis of scholarship in the research results in the identification of the requirements/recommendations to the ethical guidelines, regulatory supervision and inclusive practice required to provide fairness, accountability and respect to the individual rights in the age of big data.
Copyright (c) 2025 Asia Khan (Author) https://creativecommons.org/licenses/by/4.0
Fourier analysis is one of the pillars of modern signal processing methods, making it possible to transform complex signals into basic sinusoidal signals. This mathematical framework makes it easy to analyze, synthesize and transform signals in both the time and frequency domains. The applications of Fourier analysis are in a variety of fields such as telecommunications, audio processing, image processing, biomedical engineering, and radar systems. This research is based on the theoretical basis of Fourier series and Fourier transform, the practical realization of Fourier series and Fourier transform in digital signal processing (DSP), and its performance in noise reduction, filtering and spectrum analysis. The study also addresses the progress made in the field of fast Fourier transform (FFT) algorithms and its effect with the computational efficiency. By combining advances in Fourier analysis with new digital signal processing methods, engineers can achieve the following: Clear up signals Optimal data transmission and performance improvements. The results indicate the critical importance of Fourier methods in the design, implementation, and optimization of analog and digital signal processing information systems. Furthermore, the research highlights that computational techniques have continued to evolve and there are newer and newer applications of Fourier analysis in large signal processing situations and in real-time signal processing situations.
Copyright (c) 2025 Muhammad Amir, Muhammad Talal Aslam (Author) https://creativecommons.org/licenses/by/4.0
Digital Transformation in Public Administration: Challenges and Opportunities
Digital transformation is now one of the top significant reforming agendas in the public administration domain with various governments worldwide catering to the increasing demands of efficiency, transparency, accountability, and services to the citizen issue. The whole digital technologies (e-government platforms, big data analytics, artificial intelligence and the cloud) has profoundly altered the way the public establishments start planning the policies, resources and communication with its citizens. The authors of this research paper provide the overview of the phenomenon of digital transformation in public administration studying critically the opportunities and challenges of public administration as the consequence of the literature review of scholarly articles and governance practices. The paper demonstrates the positive effects of digital transformation in the efficiency of the administration, and effects on both the quality of the service and citizen and evidence-based policy making. At the same time it realizes that it has to cope with the continuous pressure of digital divide, cyber security, organizational resolute, skills deficiency and regulatory and ethical issues. The combination of theoretical approach to the subject and empirical data enable this article to contribute to the insights into the topic of digital governance and can benefit the policymakers and administrators of the states that intend to implement the strategies of digital transformation as well as their sustainability and inclusiveness.
Copyright (c) 2025 Sikandar Ali Bhatti (Author) https://creativecommons.org/licenses/by/4.0
Applied Statistical Modeling for Productivity and Efficiency Analysis in Pakistan's Industrial Firms
In the industrial companies and more so in the developing economies like in Pakistan, the competitiveness and sustainable growth heavily depend on productivity and efficiency. Over the past few years, applied statistical modeling has become an effective method of analyzing the level of productivity, efficiency differentials, and performance drivers at the firm level. This paper will discuss how statistical models, such as regression analysis, stochastic frontier analysis and panel data techniques, have been used to analyze productivity and efficiency in the industrial sector in Pakistan. On the basis of firm level and sectorial evidence, the study evaluates how statistical modeling can facilitate informed decision-making, benchmarking performance, and policy formulation. The results indicate that statistical applications have a strong capability of offering perspectives about the efficiencies gaps, resource exploitation, and structural limitations on the productivity of industry in Pakistan. The research shows the significant role of analytical methods in order to enhance the performance and competitiveness of industry in the developing economies through the use of data.
Copyright (c) 2025 Muhammad Haris Aslam (Author) https://creativecommons.org/licenses/by/4.0
Social Media Influencers and Behavioral Changes: Technological and Psychological Perspectives
The social media influencers have become the figure of change in online societies due to their changing lifestyles, societal values, and consumer decision-making. Through technologies, algorithms, and inter-active platforms, influencers may be able to impact an enormous effect on the attitude, lifestyle habits, and psychological state of the followers. In this study paper, the technological processes and psychological processes on how social media influencers can lead to behavioral changes in demographic groups will be discussed. Based on the interdisciplinary writing, the paper has identified the importance of credibility, parasocial relationship, content personalization and pattern of digital engagement, which are all instrumental and result in the effect of the influencer. It also addresses the concerns of the related question, including the algorithms biases, the moral aspect of the question, and the impact it has on the psychological health. The findings are educative to researchers, practitioners and policy makers that might be keen to understand the functionality of the role of influencers in a digital mediated society.
Copyright (c) 2025 Sara Syed (Author) https://creativecommons.org/licenses/by/4.0
Mathematical Modeling of Epidemic and Population Dynamics Systems
Epidemiics and population dynamics mathematical modeling is an important instrument of comprehending the dissemination of dreadful diseases, anticipating population changes, and assessing intervention plans. The SIR (Susceptible-Infectious-Recovered), SEIR (Susceptible-Exposed-Infectious-Recovered), and Lotka-Volterra are examples of models used to study the relationship between groups of people and the disease. These models apply the concept of differential equations to the rates of change in populations and disease compartments over time to allow the researcher and the policy makers to predict the peak of an epidemic, assess vaccination policies, and the stability of the population in most cases. Complex dynamics (nonlinearity, stochasticity, and time-dependent intervention) can be studied using mathematical models with the help of computational simulations. This paper provides an overview of the major mathematical models in epidemic and population dynamics modeling, and particularly their uses in the planning of the health of the populace, ecological research and resource management.
Copyright (c) 2025 Iram Zafar (Author) https://creativecommons.org/licenses/by/4.0
Fixed Point Theory and Its Applications in Engineering Problems
The Fixed Point Theory is one of the essential areas of mathematics, which offers solutions to equations, according to which a given function causes a point to be itself. The theory has wide applications in engineering, especially in solving nonlinear equations, optimization, and algorithms that are iterative. To provide solutions with guaranteed existence and uniqueness, fixed point theorems, including the Banach Contraction Principle and the Schauder Fixed Point Theorem provide such assurances, and are usable in the engineering model, where stability and accuracy are needed. Control systems, fluid dynamics, signal processing, structural analysis and electrical circuits are also used in engineering. This paper gives a summary of Fixed Point Theory and explains why it is significant in the solutions of any practical engineering problem based on theoretical and computers techniques.
Copyright (c) 2025 Muhammad Sulman (Author) https://creativecommons.org/licenses/by/4.0
Smart Grids: Optimization and Stability Challenges
The shift from conventional energy structures to clever grids is a primary soar ahead withinside the cutting-edge international of electricity. Smart grids contain the incorporation of robust communique, automatic methods and clever manipulate structures which might be geared toward enhancing efficiency, availability and sustainability. However, the emergence of extra renewable electricity sources, allotted generation, electric powered automobiles and bidirectional electricity waft has offered complicated optimization and balance demanding situations. These demanding situations are created via way of means of the intermittency of renewables, non-linear machine dynamics, cyber-bodily interactions and real-time operational constraint considerations. This studies article opinions the important thing optimization and balance demanding situations encountered through clever grids, critiques the optimization strategies which can be presently in place, and analyzes balance problems concerning the voltages, frequency, and device dynamics. The examine describes an prepared manner of methodology, discusses outcomes primarily based totally on machine modeling and overall performance evaluation, and identifies destiny studies instructions for resilient and strong operation of clever grids.
Copyright (c) 2025 Daniyal Zaheer (Author) https://creativecommons.org/licenses/by/4.0
High-Energy Particle Physics and Accelerator Studies
High Energy particle physics is the study of the building blocks of matter and their interactions on the smallest scales, whilst accelerator studies is the study of the development and optimisation of the machines in which these sociabilities can be explored. In this article the theory of particle physics is reviewed and the most important highlights of the development of this field are presented along with the technology of accelerators from radio frequency (RF) cavities to plasma wake field accelerators. We provide a method that is used for design of experiments and accelerators, discuss representative data and performance metrics, discuss some of the scientific and technological issues, and make some concrete recommendations about future research and facility development. The work involves synthesis of the theory, instrumentation, data analysis and computation techniques that are pertinent to modern high energy physics programs.
Copyright (c) 2025 Muhammad Ahmad (Author) https://creativecommons.org/licenses/by/4.0
Sustainable Manufacturing Practices and Green Engineering Solutions
Green engineering and sustainable manufacturing combine the environmental stewardship to production and design processes to minimize the amount of resources, waste, and emissions without economic and quality product expectations. The article is a review of theoretical backgrounds, approaches and empirical research on best practices and engineering innovations that facilitate manufacturing sustainability. The main issues are material substitution, energy efficiency, life cycle assessment, waste reduction, pollution prevention, and circular economy plans. A mixed methodology is a synthesis of literature, case studies, and quantitative studies. Data tables are used to summarize comparative performance indicators and results of sustainable interventions. The case study identifies the role of built-in methods and technology in enhancing the environment and competitiveness. The article ends with policy and managerial suggestions on the way forward in the area of sustainable manufacturing and green engineering.
Copyright (c) 2025 Iffat Tariq (Author) https://creativecommons.org/licenses/by/4.0
Statistical Process Control in Industrial Engineering
Statistical Process Control (SPC) stands as a pillar of quality operations and the optimization of the processes in the field of industrial engineering. SPC is a set of statistical techniques used to monitor, control, and implement improvements on the production process through the identification of variability, reduction of defects, and improvement of the working process. The research studies the SPC methods including control charts, process capability study and Six Sigma strategies with emphasis on their use in manufacturing systems, service systems and production systems. The paper combines the theoretical background and applied implementation policies with a focus on real-time monitoring and early detection of deviations, as well as continuous improvement. Results have shown that effective utilization of SPC can greatly result in stability of a process, lower expenditure, and quality of the product. The most important difficulties, such as human issues, accuracy of data collection, and compatibility with Industry 4.0 technologies, are also addressed. The study adds value to the overall idea of the importance of SPC in industrial engineering and offers practical recommendations to those practitioners and researchers interested in the field of optimizing production systems.
Copyright (c) 2025 Razia Asghar (Author) https://creativecommons.org/licenses/by/4.0
Optimization Techniques in Civil, Mechanical, and Electrical Engineering
Optimization techniques are central to the field of engineering, and can help engineer and engineering disciplines in their efficient design, analysis and operation of systems that are constrained and have performance goals. In civil, mechanical and electrical engineering, optimization techniques can be used for better performance of structures, lesser material requirements, optimized energy efficiency, and intelligent control approaches. This article gives a review of classical and modern optimization methods, such as linear optimization, nonlinear optimization, integer optimization, metaheuristic optimization, multi-objective optimization, and optimization applications in fields of engineering technology. A methodical methodology that combines theoretical foundations, algorithmic selection and implementation strategies. Comparative analysis based on case data describing how optimization creates performance enhancement and cost reduction. The synthesis offers insights into potential best practice and future research directions of engineering optimization.
Copyright (c) 2025 Naqvi syed Ali Jafar (Author) https://creativecommons.org/licenses/by/4.0
Numerical Methods for Partial Differential Equations
Partial Differential Equations (PDEs) are the mathematical engine of many models that have applications in the physical, biologic and engineering sciences. Numerical methods are essential to get approximate solutions if analytical solutions are not available. This article gives a full treatment of numerical methods for PDEs in the style of a research article with each section to address the theory, algorithmic choices, implementation approaches, and empirical comparisons. Finite difference, finite element, finite volume, spectral and discontinuous Galerkin methods are presented along with focuses on consistency, stability, convergence, adaptivity and solver performance. Part of the evaluation includes the use of representative model problems to assess accuracy, computational cost and robustness of models for several elliptic, parabolic and hyperbolic problems. The work ends with a set of practical recommendations, as well as a list of selected suggestions for genuine references for further study.
Copyright (c) 2025 Shah Fahad (Author) https://creativecommons.org/licenses/by/4.0
Water Resource Management Using Engineering Innovations
Water aid control is important a good way to meet developing worldwide needs and in mitigating water shortage to make certain the sustainability of the environment. Innovations in engineering this can be in layout of infrastructure, real-time tracking and remedy technologies, that are key in optimizing availability, excellent and certainly distribution of water. This article presents a detailed review on engineering methods in water harvesting, storage, distribution, treatment and reuse. It has been proven that through the individual case studies and the provisional data that incorporated solutions work effectively in resolving the multi-faceted issues regarding water. The results of this study combine the theoretical foundations, methodological frameworks and the outcomes on performance to inform policy makers, engineers and other stakeholders about initiatives promoting water resilience.
Game Theory Applications in Economics and Social Sciences
Game theory: game theory offers a formal and mathematical language in which we can model strategic interaction among agents in a situation that their payoffs are depending on the choices of other agents. Originating in economics, it has now spread to political science, sociology, psychology, law and computer science. This article sees over static and dynamic games, cooperative and non-cooperative games, complete and incomplete information games, some major results (empirical and experimental), as well as demonstrating methods employed to apply game theory to the problems of market design, public goods, voting and political bargaining behavior, social norms, and networked behavior. A mixed qualitative-analytical methodology is used, including the use of canonical models, laboratory and field experiments and their use of applied case studies. Data analysis is a means of synthesizing the empirical regularities across domains and drawing attention to where the theory has worked and where refinements of behavioral analysis must be made. The paper ends with policy relevant recommendations and directions for research.
Copyright (c) 2025 Muhammad Muzammil Asghar (Author) https://creativecommons.org/licenses/by/4.0
Data Science Techniques for Cybersecurity Threat Detection
Due to the explosive development of digital technologies and the Internet of Things (IoT), there has been an enormous influx of data, and the number of advanced cyber threats has also increased. Conventional cybersecurity controls are mostly not able to identify sophisticated and dynamic attacks as they happen. This essay will discuss how data science methods, such as, but not limited to, machine learning (ML), deep learning (DL), natural language processing (NLP), and big data analytics, are being used to detect, classify, and prevent cybersecurity threats. The study, based on the review conducted through analytical research, illustrates the beneficial impact of data-driven models on the intrusion detection, malware classification, phishing detection, and anomaly analysis. The combination of predictive analytics and cybersecurity systems can ensure the ability to monitor threats and assess risks in real time and respond automatically. Other issues that are considered in the paper include data imbalance, adversarial attacks, and model explainability. The results indicate that data science can increase the resilience of cybersecurity through the provision of proactive defense measures, which, in the end, will contribute to more secure and smarter digital ecosystems.
Copyright (c) 2025 Furqan Naseer (Author) https://creativecommons.org/licenses/by/4.0
Simulation Studies on 5G Network Performance
Within a short period of time, wireless communications technologies have developed to the fifth-generation (5G) network, which is offered with ultra-high data rates, great connections among devices, and low latency. Simulation-based research is crucial towards the study and optimization of the 5G performance under diverse deployment conditions to achieve such ambitious goals. The present paper reviews some of the important simulation studies which analyze the performance of 5G networks in terms of throughput, latency, spectrum allocation, and energy consumption. Different simulation models like NS-3, MATLAB and OMNeT++ are considered in terms of their capacity to model the dynamics of physical layer, mobility patterns and strategies of resource allocation. The results have shown that the use of simulation settings can successfully forecast the actual performance and optimize the network prior to the implementation at a large scale. Nevertheless, there are still challenges of computational complexity, model channel precision, and heterogeneous networks integration. The paper finds that simulation studies are essential to create an efficient 5G architecture, test new protocols, and guarantee that future networks can be used to address the needs of new systems like autonomous, IoT, and immersive communication technology.
Copyright (c) 2025 Syed Sarim Ali (Author) https://creativecommons.org/licenses/by/4.0
AI-Powered Industrial Automation: Trends and Challenges
The introduction of Artificial Intelligence (AI) has greatly changed the nature of automation in industries making manufacturing processes smarter, efficient, and adapting. Industrial automation using AI makes use of machine learning (ML), deep learning (DL), computer vision and predictive analytics to streamline the production process, cut down on operational expenses, increase safety and quality. In this paper, we are going to take a look at the modern trends and uses and issues which are related to the integration of AI into industrial automation systems. Among the most important tendencies, there are autonomous robotics, predictive maintenance, AI-based quality control, and real-time process optimization. Another issue that the study recognizes potentially impacting the successful implementation of AI technologies is the issue of data security, system interoperability, workforce adaptation, and algorithm transparency. The results indicate that, although AI adoption can be highly beneficial in terms of productivity, efficiency, and decision-making, one should pay extra attention to the issue of data governance, human-machine cooperation, and the regulatory framework to implement AI sustainably.
Copyright (c) 2025 Muhammad Amir (Author) https://creativecommons.org/licenses/by/4.0
Smart Healthcare Systems Using Wearable Devices: A Review
Wearable technology is changing the way healthcare is provided because it promotes real-time and constant monitoring of physiological parameters beyond the hospital. Remote patient monitoring, chronic disease management, preventive care and personalized wellness Smart healthcare systems based on wearables and Internet of Things (IoT) connectivity, cloud analytics and artificial intelligence (AI), are increasingly popular. This review analyzes the existing environment of wearable device-based smart healthcare systems, presents the device architecture, data collection and analytics algorithms, clinical environment, advantages and disadvantages. The main opportunities are better patient outcomes, lower healthcare expenses and increased patient engagement whereas the main challenges remain associated with the sensor accuracy, data privacy, interoperability, power independence and clinical validation. The recent research is condensed to find out the next trends, including federated learning of wearable data, energy-independent sensors and wearable assimilation into the larger medical ecosystems. The results are expected to inform researchers, clinicians and system designers to design and implement wearable based smart healthcare solutions.
Wearables and Internet of Things (IoT) connectivity
Copyright (c) 2025 Dur-E- Adan (Author) https://creativecommons.org/licenses/by/4.0
3D Printing of Biodegradable Polymers for Biomedical Application
With the development of additive manufacturing and 3D printing in particular, biomedical industry has been transformed to produce personalized, multi-dimensional, and patient-specific parts. Biodegradable polymers among other materials have come in to play as a solution to medical devices, tissue engineering, and drug delivery systems as a sustainable and biocompatable alternative to other materials. This paper discusses the 3D printing technique in the production of bio-based biomedical items in using polymers (polylactic acid, PLA, polycaprolactone, PCL and polyglycolic acid, PGA). It talks about how the polymers can facilitate controlled degradation, mechanical stability and biological compatibility which makes them suitable in the application of bone scaffolds, implants, and wound healing systems. The paper also explores the existing issues such as optimization of the processes, mechanical strength, and sterilization issue, and future opportunities of smart biodegradable materials combined with nanotechnology. The results indicate that the 3D printing of biodegradable polymers cannot only increase the level of precision and sustainability but also is an essential step towards the personalized medicine and regenerative healthcare solutions.