Journal of Engineering Education and Practice
Journal of Engineering Education and Practice (JEEP) is a peer-reviewed academic journal published by SYNAPSE EDUCATIONAL RESEARCH INSTITUTE (SMC-PRIVATE) LIMITED. The journal provides a platform for researchers, academics, and professionals to publish high-quality research related to engineering education, innovation, and practical engineering applications. The journal is published semiannually and welcomes contributions from scholars around the world. Scope The journal covers a broad range of topics in engineering and engineering education, including but not limited to: Engineering Education and Teaching Methods Mechanical Engineering Electrical and Electronic Engineering Civil and Structural Engineering Computer and Software Engineering Industrial and Manufacturing Engineering Chemical Engineering Environmental Engineering Artificial Intelligence in Engineering Robotics and Automation Sustainable and Green Engineering Engineering Management and Technology Innovation More opportunities to publish your research: Submit Your Manuscript
SYNAPSE EDUCATIONAL RESEARCH INSTITUTE (SMC-PRIVATE) LIMITED
SECURING U.S. CRITICAL INFRASTRUCTURE WITH AUTONOMOUS LANGUAGE AGENTS: A TRUSTWORTHY, POLICY-ALIGNED FRAMEWORK FOR HIGH-RISK ENTERPRISE REASONING
The rapid deployment of autonomous language agents across enterprise systems presents unprecedented security challenges for U.S. critical infrastructure sectors including energy, water, transportation, healthcare, and financial systems. This paper addresses the fundamental tension between the operational benefits of AI-driven decision-making and the security risks inherent in deploying autonomous reasoning systems within high-stakes environments. Through comprehensive analysis of existing literature, threat modeling, and policy frameworks, we identify critical gaps in current approaches to securing AI agents in critical infrastructure contexts. We propose a novel trustworthy AI framework comprising five integrated layers: Policy Alignment, Reasoning Verification, Human Oversight, Secure Execution, and Audit Governance. Our methodology synthesizes insights from NIST AI Risk Management Framework, cybersecurity best practices, and enterprise governance requirements to create a policy-aligned architecture specifically designed for high-risk reasoning scenarios. The framework addresses key threats including prompt injection, model hallucinations, decision manipulation, adversarial reasoning, insider misuse, and system drift through a comprehensive defense-in-depth approach. Evaluation demonstrates that the proposed architecture significantly enhances trustworthiness metrics compared to existing solutions while maintaining operational efficiency. This research contributes to the emerging field of AI governance by providing a practical, implementable framework that bridges the gap between theoretical AI safety principles and operational critical infrastructure protection requirements
Copyright (c) 2024 I K M SAAMEEN YASSAR (Author) https://creativecommons.org/licenses/by/4.0
SMART GRID TECHNOLOGIES AND THEIR ROLE IN REDUCING ENERGY CONSUMPTION: A STUDY ON THE FUTURE OF RENEWABLE ENERGY INTEGRATION
Smart grid technologies represent a fundamental transformation of traditional electrical infrastructure, enabling bidirectional energy flows, real-time monitoring, and intelligent demand response to optimize energy consumption and integrate renewable energy sources. This study provides a comprehensive analysis of smart grid implementations across 45 pilot projects in North America, Europe, and Asia from 2015-2023, examining technological efficacy, energy savings, and integration challenges. Results demonstrate that advanced metering infrastructure (AMI) reduces residential energy consumption by 5-15% through behavioral feedback, while dynamic pricing strategies achieve 10-25% peak demand reduction. Grid modernization incorporating phasor measurement units (PMUs) and distribution automation reduces system losses from 6.8% to 3.2% on average, while improving renewable integration capacity from 20% to 45% of total generation. Machine learning algorithms for load forecasting achieve 92.3% accuracy, enabling better generation planning and reducing reserve requirements by 15-30%. Energy storage integration, particularly lithium-ion batteries at grid scale, enhances renewable utilization by 22-40% through time-shifting of solar and wind generation. However, cybersecurity vulnerabilities present significant risks, with penetration testing revealing successful attacks on 18% of smart meter networks and 12% of SCADA systems. Economic analysis indicates that smart grid investments yield benefit-cost ratios of 2.8-4.2 over 20 years, with payback periods of 6-12 years depending on regional factors. Consumer acceptance varies substantially, with 65% of residential users embracing time-of-use pricing but only 35% accepting direct load control of appliances. This research concludes that smart grids are essential for achieving renewable energy targets and reducing overall consumption, but require robust cybersecurity frameworks, standardized interoperability protocols, and equitable policy designs to ensure widespread adoption and maximize environmental benefits while maintaining grid reliability and security.
Copyright (c) 2025 Syed Muhammad Shakir Bukhari (Author) https://creativecommons.org/licenses/by/4.0
EXPLORING THE USE OF ROBOTICS IN HEALTHCARE: INNOVATIONS IN SURGICAL ASSISTANCE AND REHABILITATION TECHNOLOGIES
The integration of robotics into healthcare represents a paradigm shift in medical practice, enhancing precision, consistency, and accessibility. This study investigates the dual domains of robotic surgical assistance and robotic rehabilitation technologies, evaluating their clinical efficacy, economic impact, and patient outcomes. In surgical robotics, systems like the da Vinci Surgical System have transitioned from novelty to standard of care for numerous procedures, offering minimally invasive options with improved dexterity and visualization. Concurrently, in rehabilitation, robotic exoskeletons and assistive devices are revolutionizing physical therapy for stroke, spinal cord injury, and neurological disorders, providing high-dose, repetitive, and data-driven therapy. Through a mixed-methods analysis incorporating clinical trial data, cost-benefit models, and user acceptance surveys, this research assesses the tangible benefits and limitations of these technologies. Findings indicate that robotic-assisted surgery significantly reduces patient hospital stays, blood loss, and complication rates in procedures like prostatectomy and hysterectomy, though high capital costs remain a barrier. In rehabilitation, robotic devices demonstrate superior motor recovery outcomes compared to conventional therapy alone, due to personalized assistance and objective progress metrics. However, challenges persist, including technology affordability, clinician training requirements, and the need for more robust, long-term outcome data. The study concludes that robotics in healthcare is moving beyond augmentation towards essential transformation, but its sustainable integration necessitates focused policy on reimbursement models, interdisciplinary training, and continued innovation to improve cost-effectiveness and accessibility for diverse healthcare systems globally.
Copyright (c) 2025 Kamran Iqbal, Arslan Nadeem (Author) https://creativecommons.org/licenses/by/4.0
ADVANCES IN SUSTAINABLE TRANSPORTATION: A COMPARATIVE STUDY OF ELECTRIC, HYDROGEN, AND HYBRID VEHICLES
The global transportation sector is undergoing a fundamental transformation to mitigate its environmental impact, which contributes significantly to greenhouse gas emissions and urban air pollution. This comparative study quantitatively evaluates the sustainability performance of three pivotal vehicle technologies: Battery Electric Vehicles (BEVs), Hydrogen Fuel Cell Vehicles (FCEVs), and Plug-in Hybrid Electric Vehicles (PHEVs). The analysis adopts a life-cycle assessment (LCA) framework, integrating parameters for total cost of ownership (TCO), well-to-wheel (WTW) emissions, energy efficiency, and infrastructure requirements. Using a mixed-methods, problem-based methodology, the research models real-world performance across a 10-year lifespan under current and projected energy grid scenarios. The results indicate that BEVs currently offer the highest WTW energy efficiency and the lowest operational emissions in regions with a decarbonized electricity grid, with an average efficiency of 77-86% compared to 30-40% for FCEVs. However, FCEVs demonstrate superior range and refueling times, presenting a compelling case for long-haul freight. PHEVs serve as a transitional technology, reducing emissions by 40-60% over conventional vehicles but remain reliant on fossil fuels. Infrastructure analysis reveals that BEV charging networks are expanding rapidly but face grid load challenges, while hydrogen infrastructure remains nascent and capital-intensive. The study concludes that a diversified strategy is essential; BEVs are optimal for urban and short-haul applications, FCEVs for heavy-duty and long-distance transport, and PHEVs for bridging the gap during infrastructure development. Policymakers must prioritize grid decarbonization and targeted infrastructure investments to realize the full sustainability potential of each technology.
Copyright (c) 2025 Aiman Shabbir, Nida Hafeez (Author) https://creativecommons.org/licenses/by/4.0
THE ROLE OF BLOCKCHAIN IN ENHANCING CYBERSECURITY: A STUDY ON THE APPLICATIONS OF DISTRIBUTED LEDGER TECHNOLOGY IN PROTECTING CRITICAL INFRASTRUCTURE
The escalating sophistication and frequency of cyberattacks targeting critical infrastructure necessitate innovative approaches to cybersecurity that transcend traditional perimeter-based defenses. This study provides a comprehensive analysis of blockchain technology applications in enhancing cybersecurity for critical infrastructure sectors including energy, finance, healthcare, and transportation through a mixed-methods investigation of 120 implementations across 35 countries from 2017-2023. Results demonstrate that blockchain-based solutions reduce successful cyberattacks by 45-65% through decentralized authentication, immutable logging, and consensus-based validation mechanisms. Identity and access management systems leveraging blockchain achieve 99.7% authentication accuracy while eliminating single points of failure, reducing credential theft incidents by 72-88% compared to traditional centralized systems. Supply chain security applications increase provenance verification accuracy from 68% to 96% while reducing verification time from 5.3 days to 2.1 hours. However, significant challenges persist: quantum computing threatens current cryptographic foundations, with projections indicating vulnerability within 8-15 years; scalability limitations constrain transaction throughput to 20-30% of traditional database systems; and interoperability with existing infrastructure remains problematic for 65% of implementations. Energy consumption analysis reveals proof-of-work consensus mechanisms increase electricity usage by 300-500% compared to centralized alternatives, though proof-of-stake and other consensus algorithms reduce this to 10-25% overhead. Regulatory frameworks lag behind technological development, with only 18 countries establishing blockchain-specific cybersecurity regulations. This research concludes that blockchain represents a paradigm-shifting approach to cybersecurity, but realizing its full potential requires addressing scalability-energy trade-offs, developing quantum-resistant cryptography, establishing standardized interoperability protocols, and creating adaptive regulatory frameworks through coordinated international collaboration and public-private partnerships.
Copyright (c) 2025 Ume Habiba, Junaid Hassan (Author) https://creativecommons.org/licenses/by/4.0
THE DEVELOPMENT OF AUTONOMOUS DRONES FOR DISASTER RELIEF OPERATIONS: TECHNOLOGICAL INNOVATIONS AND CHALLENGES
The increasing frequency and severity of natural disasters worldwide necessitate advanced technological solutions for effective emergency response. This study provides a comprehensive analysis of autonomous drone technologies specifically developed for disaster relief operations, examining their capabilities, deployment effectiveness, and persistent challenges through a mixed-methods investigation of 75 disaster events across 30 countries from 2015-2023. Results demonstrate that autonomous drones reduce search and rescue response times by 65-85% compared to traditional methods, increase survivor detection accuracy by 40-60%, and deliver emergency supplies with 92-97% success rates in complex environments. Artificial intelligence integration enables real-time damage assessment with 88-94% accuracy in identifying structural vulnerabilities, while swarm coordination allows simultaneous coverage of disaster zones up to 100 square kilometers with centimeter-level mapping precision. Communication relay drones establish temporary networks within 15-45 minutes, restoring connectivity to 85-95% of isolated populations. However, regulatory restrictions limit operations in 60% of international deployments, battery limitations constrain mission durations to 25-45 minutes for most platforms, and adverse weather conditions degrade sensor performance by 30-50%. Economic analysis reveals that drone deployment reduces traditional disaster response costs by 20-35% while decreasing responder risk exposure by 45-70%. This research concludes that autonomous drones represent a transformative technology for disaster management, but realizing their full potential requires addressing regulatory harmonization, technological limitations, ethical considerations regarding privacy and autonomy, and integration with existing emergency response frameworks through international cooperation and standardized protocols.
Copyright (c) 2025 Arslan Nadeem, Muzammil Ali (Author) https://creativecommons.org/licenses/by/4.0
DESIGN AND IMPLEMENTATION OF A SMART GRID SYSTEM FOR EFFICIENT RENEWABLE ENERGY INTEGRATION AND LOAD BALANCING
This study presents the design and implementation of a smart grid system aimed at enhancing the integration of renewable energy sources, specifically solar and wind power, while optimizing load balancing and improving grid efficiency. The proposed system incorporates advanced forecasting algorithms, real-time data processing, energy storage technologies, and demand response mechanisms to address the challenges associated with the variability of renewable energy. Results indicate a 10% increase in renewable energy utilization, a 15% reduction in energy losses, and a 7% reduction in operational costs, demonstrating significant improvements in overall system efficiency. The predictive model reached 97% accuracy using a 2.2% margin of error. Energy storage systems achieved 94% efficiency by dispersing surplus renewable power produced during peak times into power reduction periods for stabilizing the power infrastructure. The demand response program managed to reduce peak demands by 12.9 percent by moving customer power usage into times with low demand which benefited power grid reliability. The smart grid accomplished all its objectives including load balancing with renewable integration together with operational expense reduction. The outcome evidence shows smart grids eliminate renewable energy reliability issues through their sustainable and affordable solutions which help design modern power system networks. Research investment into upgraded power systems represents the primary scientific challenge because it needs to handle rising energy needs coupled with growing renewable energy penetration.
Copyright (c) 2025 Moaz Israr (Author) https://creativecommons.org/licenses/by/4.0
DESIGN AND INTEGRATION OF DIODE-BASED POWER CONVERSION CIRCUITS FOR EFFICIENT MECHANICAL BATTERY SYSTEMS
This study investigates the design and integration of diode-based power conversion circuits within mechanical battery systems to improve energy efficiency, system reliability, and performance. The research addresses the challenges associated with energy losses, thermal management, and the integration of advanced control algorithms in mechanical energy storage systems, particularly flywheel-based systems. The results demonstrate a significant enhancement in energy conversion efficiency by reducing both conduction and switching losses, compared to conventional power conversion circuits.Power loss reduction throughout the charging and discharging cycles primarily depended on using advanced switching controls together with efficient diodes. System stability and operating efficiency received additional support when dynamic control algorithms were incorporated for better energy flow regulation. The research demonstrates through its findings that diode-based circuits offer stable performance over time because they excel at mechanical load regulation alongside temperature management. Mechanical battery systems would benefit from diode-based power conversion circuits since they offer sustainable and efficient operation with better dependability. The innovative research approach introduces new storage technology possibilities for broad utilization at scale which strengthens renewable energy system storage capabilities.
Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0
COMPUTATIONAL APPROACHES TO ENHANCING THE THERMAL MANAGEMENT OF WIRING SYSTEMS IN HIGH-POWER ELECTRONICS
This study investigates the thermal management of wiring systems in high-power electronics, focusing on the impact of material selection, cooling methods, and wiring configurations on system performance. A comprehensive computational analysis was conducted to assess thermal resistance, temperature rise, and failure rates under various conditions. Our results indicate that copper provides the best thermal conductivity among the materials tested, offering a significant advantage in heat dissipation compared to aluminum, silver, and nickel. The study also explores different cooling strategies, with liquid cooling and phase change materials showing the highest efficiency in reducing temperature rise, achieving reductions of up to 40%. The hybrid cooling systems that use heat sinks together with liquid cooling delivered the highest potential for improvement while enhancing thermal performance and extending system life expectancy. An investigation into the influence of wire gauge exposed that reducing wire thickness reduces overall system temperature but generates larger temperature variations. A failure test confirmed that dependable system operation depends heavily on cooling technologies because proper cooling techniques result in fewer failures and longer operational timeframes. Synthesized data advocates for selecting appropriate wires alongside cooling solutions in high-power wiring systems to enhance their operation performance. The proposed research presents potential avenues to explore hybrid cooling solutions while studying materials with high thermal conductivity levels for better high-power electronics thermal management.
DEVELOPMENT OF HYBRID ENERGY STORAGE SYSTEMS: INTEGRATING MECHANICAL BATTERIES WITH DIODE RECTIFIERS FOR OPTIMIZED POWER MANAGEMENT
This study investigates the development of a hybrid energy storage system (HESS) that integrates mechanical batteries, specifically flywheel energy storage systems (FESS), with diode rectifiers to optimize power management. The aim of this research is to improve the efficiency, power flow control, and overall system stability under varying operational conditions, including high-power bursts and continuous low-power demands. A MATLAB/Simulink simulation model was developed to analyze the hybrid system's performance, which was then validated through real-world prototype testing. The results demonstrate a significant increase in energy efficiency, with the hybrid system achieving up to 95% efficiency in high-power demand scenarios, compared to 85% without diode rectifiers. During high power spikes the flywheel operated mainly while the lithium-ion battery maintained continuous low output for effective energy storage distribution. Effective SOC control by both components enabled maximum system durability and protected against both overcharging and deep discharge incidents. The hybrid system showed excellent promise as an energy storage solution because it successfully adapted to various energy profiles that appear during renewable energy integration and electric vehicle operations. The stability results from simulation and prototype examinations converged on a similar conclusion as past studies did indicate minimal energy dissipation (10%). Experimental studies have validated using mechanical batteries with diode rectifiers as a practical solution to improve power management technology in modern energy storage applications including electric vehicles and renewable energy systems and grid stabilization.
MODELING AND SIMULATION OF ADVANCED WIRING SYSTEMS FOR EFFICIENT POWER DISTRIBUTION IN MULTI-STORY BUILDINGS
This study investigates the optimization of power distribution systems in multi-story buildings through advanced wiring configurations, integration of renewable energy sources, and machine learning-based optimization. Using detailed modeling and simulation techniques, we evaluated the performance of various building configurations to assess key indicators such as power loss, voltage stability, energy efficiency, and system reliability. The results demonstrated that advanced wiring systems significantly reduced power loss by up to 15% compared to conventional designs. The system design upgrade led to significant enhancements in voltage stability which displayed values between 3% compared to the conventional wire standard that provided variations between 8%. Solar and wind together with other renewable energy sources boosted system efficiency which simultaneously reduced carbon emissions by 10% and enhanced energy efficiency by 20%. System dependability improved by 6% while machine learning for optimisation forecasting lowered energy consumption by 12% during power distribution and maintenance need predictions. Research reveals that initial costs of modern systems exceed traditional systems but these modern systems generate long-term financial advantages that create a 18% greater return on investment (ROI) during ten years. Studies confirm that novel wiring techniques and sustainable power management strategies should be used in order to enhance the sustainability and efficiency characteristics of multi-story buildings. Modern urban infrastructure designers and electrical engineers can obtain valuable knowledge by studying this research which aims to build durable energy-efficient systems.
NEXT-GENERATION SMART WIRING TECHNIQUES FOR REAL-TIME DATA TRANSMISSION AND POWER MANAGEMENT IN INTEGRATED BUILDING SYSTEMS
This study investigates the development and performance evaluation of next-generation smart wiring techniques designed to optimize real-time data transmission and power management in integrated building systems (IBS). The proposed system integrates adaptive power management protocols with dynamic data routing, aimed at addressing the limitations of traditional wiring solutions in terms of bandwidth, energy efficiency, and scalability. Comparative analysis with existing technologies such as conventional wiring, Power over Ethernet (PoE), and hybrid systems reveals that the proposed smart wiring system significantly outperforms these alternatives. The results demonstrate a substantial increase in data transmission speeds, with the proposed system achieving 500 Mbps, compared to 250 Mbps for conventional systems. Additionally, power consumption is reduced by up to 30%, with the proposed system consuming only 85 watts, compared to 120 watts for traditional systems. The scalability analysis validates that the proposed solution delivers stable performance in extensive smart building operations while linking more devices thus maintaining peak functional standards. Reliability and fault tolerance testing helps enhance the proposed system by producing quick recoveries along with minimal data loss. The user satisfaction survey reports high approval because the suggested system received 4.9 out of 5 in ratings for performance, ease of use, and satisfaction which surpassed ratings of conventional systems. These results demonstrate the effectiveness of advanced smart wiring solutions for modern smart buildings because they support better energy management and integration and operational efficiency.
CURRENT TRENDS AND FUTURE DIRECTIONS IN THE DESIGN, DEVELOPMENT, AND SIMULATION OF NEXT-GENERATION UAV NAVIGATION SYSTEMS: ADVANCING AUTONOMY, PRECISION, AND RELIABILITY
The automatic navigation system represents an essential factor in drone technology while continuously growing important within modern technological applications. Modern navigation systems requiring independent operation have become critical due to the rising importance of drones in multiple industries. The cutting-edge technologies expand drone usages across agricultural, logistics, military along with environmental surveillance sectors and strengthen their combat prowess. The understanding of drone automated navigation development together with current technology status in this dynamic industry serves as key elements for predicting industry directions and driving innovation. This essay presents a comprehensive analysis of drone autonomous navigation progress while treating different industrial applications in detail. The analysis evaluates existing systems to present their current benefits and flaws and recommends ways to improve future versions of these technologies. The paper predicts and investigates future advancements in drone navigation systems as it works to develop and spread their wider utilization. This research serves as a resourceful document for developers and practitioners of drone automated navigation technology while they investigate potential new application fields.
ADVANCING THERMAL MANAGEMENT IN ELECTRIC VEHICLE BATTERIES THROUGH THE INTEGRATION OF PHASE CHANGE MATERIALS: ENHANCING EFFICIENCY AND LONGEVITY
EV technology popularity demands us to control Li-ion battery temperature performance to protect their reliability and safety. The batteries generate significant heat during charging and discharging cycles that leads to thermal runaway and reduces battery life efficiency. This research tests phase change materials' suitability for use inside Li-ion battery thermal management systems for EV applications. PCMs maintain stable battery temperatures during cooling because heat capture and release phases are their established properties. Research used both computer models and physical tests to check the cooling performance between PCM systems and regular liquid or air-cooling methods. Scientists investigated various PCMs including organic and inorganic types plus composite materials before adding graphene-enhanced composites to enhance heat removal. Our experiments show that the PCM system controls temperature spikes during quick charging sessions while improving battery pack temperatures and keeping the battery components stable to extend battery life. Using PCM coolers produces significant energy savings which raises total energy efficiency levels beyond what active cooling systems can achieve. Results show PCM thermal management systems as an eco-friendly cost-effective energy-efficient solution for electric car battery temperature control problems. The combination of PCM and BTMS supports new electric vehicles as better battery cooling technology than traditional systems. This research demonstrate Phase Change Materials (PCMs) have major benefits for temperature control of lithium-ion batteries in electric vehicles (EVs). The battery pack stays at even temperatures better because PCMs use their passive cooling method to absorb and release thermal energy as they change phases. By testing PCMs against usual active cooling procedures data prove this technology can reduce temperature rise more effectively while stabilizing overall battery pack temperatures. Our temperature control system works better because it protects the battery against thermal runaway incidents and also makes the battery last longer. The examination showed that PCM-based cooling performs better than active devices with fans since it operates without external power for temperature control. EV battery technology developers should use PCM-cooled systems as their optimal choice because PCM's self-cooling method saves energy effectively. When graphene and carbon nanotubes strengthen composite PCM heat transfer improves significantly to enhance overall cooling performance.
Battery Thermal Management Systems (BTMS)
UTILIZING ARTIFICIAL INTELLIGENCE FOR PREDICTIVE MAINTENANCE IN AIRCRAFT: ENHANCING EFFICIENCY, SAFETY, AND OPERATIONAL RELIABILITY
Artificial intelligence (AI) based predictive maintenance in the aviation is revolutionizing the aircraft maintenance and operation. AI systems can even predict potential faults before they occur by reading data from an array of aircraft sensors, and therefore initiate timely and effective repair initiatives. By applying a proactive rather than reactive strategy, the maintenance expenses decrease, safety increases and unscheduled downtime decreases. Predictive maintenance uses artificial intelligence (AI) by using technologies like machine learning, data analytics, and internet of things (IoT) to keep monitoring and checking the rest state of a aircraft parts continuously. This review lays out in tremendous detail the advantages of AI-based predictive maintenance, its impact on the aviation industry and how it works. Thus, anyone could understand the sense of and great possibilities of the AI predictive maintenance. Predictive maintenance provides a great chance for airlines to save expenses, boost operational effectiveness and safety. The difficulties to put these ideas into practice are far outweighed by their possible advantages. As technology advances, predictive maintenance will become an important facet in modern aviation, allowing airlines to run more efficiently as well as give customers more service. By utilizing cutting edge sensors and data analytics, as well as machine learning, airlines can flip from reactive to proactive maintenance and ensure that at all times their fleet is in top shape. Beyond that, this method makes air travel safer and more reliable which means saving money as well.
WATER RESOURCES ENGINEERING: INNOVATIVE TECHNIQUES FOR SUSTAINABLE WATER SUPPLY AND WASTEWATER TREATMENT IN URBAN AREAS
It becomes exceedingly difficult for urban settlements to survive without the components of sustainable water supply and wastewater treatment. Number one, there are many rapid processes that make urban settlements deadly: rapid urbanization, climate change, and increased pressure upon water resources. This research attempts to explore new techniques for the sustainable management of water, mainly highlighting different advanced procedures employed to corrupt the claims of reliable water supply and wastewater treatment in an urban setting. The infrastructure itself is an old rivalry: In general, aging water systems, environment degradation, enroute to energy consumption, constitute worthy opponents against productive water management. Advanced membrane technologies, biological treatment systems, and integrated water reuse systems might provide such solutions. The establishment of green infrastructure with constructs like rain gardens, permeable pavements, and constructed wetlands allows the management of stormwater while aiding in groundwater recharge. This includes recovery of effluent resources and energy through advanced oxidation processes (AOP), electrochemical treatment modes, and biofuel production from wastewater. On the other hand, smart water management systems integrated with real-time monitoring, data analytics, and AI-based predictions can optimally and adaptively utilize water resources. The programs will optimize water use, efficiently detect leaks, and predict future maintenance needs to improve operational efficiency. The study also shed light on the others within the community of interest and a solid policy framework inducing sustainable water practices. Campaigns to educate the masses about water-saving technologies, among other incentives, are an essential hallmark for the successful implementation of sustainable water management strategies with planning done collaboratively with stakeholders on the ground. The fusion of these innovative concepts assists not only in guaranteeing water supply but also in environmental, climate resilience, and fiscal savings. The research concludes that resilience-based, integrated, and innovative approaches must be considered in evolving viable and sustainable urban water systems facing future challenges. Sustainable water management remains the sustenance for any enduring environmental sustainability, public health, and socio-economic development in any fast-urbanizing scenario.
LEVERAGING ARTIFICIAL INTELLIGENCE MODELS FOR EARLY DETECTION AND DIAGNOSIS OF NEUROLOGICAL DISORDERS: A COMPARATIVE ANALYSIS OF TECHNIQUES AND APPLICATIONS
Detection of Alzheimer's disease (AD) must happen before the onset of neurodegenerative symptoms. The purpose of this research was to improve AD prediction and early diagnosis through machine learning by analyzing artificial intelligence models (convolutional neural networks, CNN) alongside support vector machines (SVM) and random forests (RF) for neuroimaging data (MRI, PET) assessment. Researchers conducted a study about the diagnostic power of AI models optimized by combining DNA sequencing results with brain scan and medical history information. The researchers associated with feature significance analysis to determine which model prediction variables created the most impact by deploying SHAP values alongside other methods. The study evaluated practical model applications by conducting separate training sessions with AI models on clinical data representing different patient environments. The validation of each model occurred through statistical measurement consisting of accuracy, precision, recall, F1 score and area under the curve (AUC). The research showed CNN as the superior model because it achieved highest accuracy at 92% as well as highest precision at 93% and recall at 91% and area under the curve at 0.95. The study established that CNN serves as an effective technique for detecting Alzheimer's disease at its early stage through the identification of minor imaging deviations. The accuracy score obtained from CNN was superior to the results found in SVM and RF. The model displayed important validity through cross-validation tests critical for clinical application. The application of artificial intelligence models especially CNN has the potential to advance both Alzheimer's disease treatment and diagnosis through prompt identification and improved treatment results.
Copyright (c) 2024 Ranya Mohammed Elmagzoub, Muhammad Danial Ahmad Qureshi (Author) https://creativecommons.org/licenses/by/4.0
DEVELOPMENT OF LOW-COST, HIGH-PRECISION SENSORS FOR ENVIRONMENTAL MONITORING IN REMOTE AREAS
This study presents the development and evaluation of low-cost, high-precision environmental sensors designed for deployment in remote areas. These sensors, fabricated using innovative materials such as graphene and conductive polymers, were evaluated across multiple parameters, including particulate matter, CO₂ levels, soil moisture, and temperature. The sensors demonstrated exceptional accuracy, with a precision rate exceeding 98% for most environmental measurements, which is comparable to existing commercial solutions. Notably, the sensors maintained high performance even under challenging environmental conditions, such as extreme humidity and temperature fluctuations. Energy efficiency served as the main design objective because these affordable sensors worked with solar power effectively using about 80% less energy than typical systems used under normal circumstances. The whole system cost assessment demonstrated outstanding cost reductions due to an over 75% reduction. This sensor system provides value to resource-limited locations where nontechnical users can operate it easily thanks to its basic deployment requirements and minimal maintenance needs. These affordable sensors have demonstrated their potential to convert distant environmental observation through their reasonable price point according to this study. The established tools give local populations direct control over preservation projects which enables them to take ownership of environmental management responsibilities. These sensor developments enable global environmental safeguarding alongside renewable resource management because they provide workable solutions for monitoring environmental conditions in areas with limited resources.
Copyright (c) 2025 Kirubanandan Shanmugam (Author) https://creativecommons.org/licenses/by/4.0
INNOVATIVE APPROACHES TO EARTHQUAKE-RESISTANT BUILDING DESIGN: ANALYZING THE EFFECTIVENESS OF NEW SEISMIC MATERIALS
This study investigates the effectiveness of innovative seismic materials in enhancing earthquake-resistant building designs. The materials analysed include carbon fiber reinforced polymers (CFRP), glass fiber reinforced polymers (GFRP), shape-memory alloys (SMAs), Bamboo, and Hempcrete. A comprehensive evaluation was conducted based on key parameters such as tensile strength, energy dissipation, durability, cost, environmental impact, and seismic resilience. The results indicate that CFRP and SMAs perform exceptionally well across all metrics, particularly in tensile strength and energy dissipation, making them highly suitable for applications in high-seismic regions. However, their high cost limits their widespread adoption. In contrast, Bamboo and Hempcrete, while cost-effective and environmentally sustainable, exhibited lower seismic performance, with reduced tensile strength and energy dissipation capabilities. Despite their eco-friendly properties, these materials are not recommended for use in earthquake-prone areas without additional reinforcement. This study demonstrates how decisions about material selection must balance both performance quality and cost expenditure while promoting sustainable methods to produce resilient low-cost options. The analysis demonstrates that using high-performance materials combined with sustainable choices provides a satisfactory solution for earthquake-resistant construction. The study brings important research to earthquake engineering by offering design guidelines that address material selection during building construction projects. Future research should develop tactics to expand affordability and accessibility of high-performance seismic materials which will enable their wider application for earthquake-resistant infrastructure.
Copyright (c) 2025 Nida Hafeez (Author) https://creativecommons.org/licenses/by/4.0
ARTIFICIAL INTELLIGENCE ALGORITHMS FOR REAL-TIME TRAFFIC MANAGEMENT AND OPTIMIZATION IN AUTONOMOUS VEHICLES
This study explores the application of artificial intelligence (AI) algorithms for real-time traffic management and optimization in autonomous vehicles (AVs), focusing on their impact on traffic flow, safety, and energy efficiency. AI-driven systems, incorporating machine learning and reinforcement learning, were deployed in various traffic scenarios, including peak hour traffic, accident conditions, and road closures. The results demonstrated a significant reduction in congestion, with an average decrease of 32.5% during peak hours, along with a 60% reduction in accidents across all scenarios. Additionally, the implementation of AI algorithms led to a 7.5% reduction in energy consumption, highlighting the potential of these systems to contribute to environmental sustainability. Real-time traffic data analysis ability of AI enables smarter decisions during decision-making processes while improving coordination between autonomous vehicles and vehicles with human operators. The promising results of the study encountered obstacles in data privacy, cybersecurity and integrating systems with existing infrastructure. AI-based traffic management systems deliver significant benefits to efficiency and safety but proper solution of encountered issues remains essential for general adoption. The research demonstrates how artificial intelligence brings revolutionary possibilities to urban traffic management which enables next-generation transportation solutions.
Copyright (c) 2025 Olumhense Benedict Adoghe (Author) https://creativecommons.org/licenses/by/4.0
INVESTIGATION OF ADVANCED COMPOSITE MATERIALS FOR LIGHTWEIGHT STRUCTURAL COMPONENTS IN AEROSPACE APPLICATIONS
The aerospace industry’s pursuit of lightweight, high-performance materials has led to increased interest in advanced composite materials, particularly carbon fiber-reinforced polymers (CFRPs) and hybrid composites. This study investigates the mechanical properties, environmental durability, and cost-effectiveness of CFRPs, glass fiber-reinforced polymers (GFRPs), and hybrid composites for use in lightweight aerospace structural components. Comprehensive testing was conducted to assess tensile strength, flexural strength, impact resistance, environmental degradation, and non-destructive internal integrity. The results revealed CFRPs surpassed GFRPs and hybrid composites in aerospace applications because they delivered higher tensile strength at 1800 MPa as well as better impact resistance at 300 J/m². Hybrid composites reached a tensile strength level of 1500 MPa and impact resistance of 400 J/m² resulting in equivalent performance to each other yet GFRPs did not show suitable outcomes in mechanical tests or environmental durability assessments. Aging durability tests showed that CFRP and hybrid composites maintained their tensile strength within 5% and 7% but GFRP experienced a 20% weakness. Non-destructive testing of CFRP components showed better reliability because it detected lower numbers of internal defects. The initial expense of GFRPs proves reasonable because these materials deliver superior performance throughout an extended lifespan although they are priced competitively regarding raw materials together with production expenses. Research shows that hybrid composites offer a suitable substitution for high-performance aircraft components next to CFRPs with superior cost-performance values. A valuable material assessment system for aerospace applications becomes essential due to this research which reveals the need for balancing performance durability and cost-effectiveness in selection processes.
Copyright (c) 2025 Aiman Shabbir (Author) https://creativecommons.org/licenses/by/4.0
THERMAL MANAGEMENT IN HIGH-PERFORMANCE ELECTRONICS: INNOVATIVE HEAT DISSIPATION SOLUTIONS FOR COOLING SYSTEMS
The effective management of thermal issues, particularly high-performance electronic systems where increasing power densities and compact designs only exacerbate the problems of heat dissipation, is critically important. Increasingly enhanced processing abilities for electronic devices, among others, coupled with decreasing dimensions, only serve to complicate any maintenance of good thermal conditions. This study looks into a wide range of novel cooling techniques designed to enhance heat dissipation efficiency and operational stability of the advanced electronic devices. Among others examined in detail were liquid cooling systems, heat pipes, and phase-change materials (PCMs) to avert thermal challenges while allowing the devices to be performing well and have long-life spans. Liquid cooling systems manage thermal conduction and can remove high quantities of heat flow; hence, they have been widely used for modern processors and graphic units. Heat pipes and vapor chambers utilize phase-change processes to transfer heat away from and toward the components, contributing to the leveling of temperature distributions. In wasting heat, PCMs, on the other hand, absorb and release latent heat, thus giving a passive solution for thermal regulation during peak operation period.The study then emphasized the integration of novel materials and nanotechnology-based approaches such as graphene-enhanced thermal interfaces and nanofluids which promise to enhance thermal conductivity and cooling performance. Now, this allows the reduction of thermal resistance and improvement in cooling system efficiency. Moreover, design strategies such as microchannel heat sinks and advanced thermal interface materials (TIMs) are discussed so as to improve heat-transfer rates and reduce thermal bottlenecks. This highlights a need for a multifaceted combining advanced materials, design innovations, and efficient thermal management systems to address the growing extent of thermal issues in high-performance electronics. This work enhances the ongoing discussion on sustainable and effective thermal solutions, giving recommendations for future scalable and adaptable cooling systems that will suit different electronic architectures.
Copyright (c) 2023 Ume Habiba, Muzammil Ali (Author) https://creativecommons.org/licenses/by/4.0
LOW-POWER HARDWARE DESIGN FOR INTERNET OF THINGS (IOT): ENERGY-EFFICIENT CIRCUITRY FOR BATTERY-POWERED DEVICES
Today, the Internet of Things (IoT) has propelled a very high need for energy-efficient hardware designs, especially for battery-operated devices that are usually in remote or inaccessible regions. The following research looks into low-power hardware design principles and advances concentrated on energy-efficient circuitry as a core element of application towards IoT. It also researches the techniques and technologies that facilitate great performance without any energy loss and thus prolonging the life of battery-operated devices in IoT.Solutions on low-power VLSI seem to be very critical in balancing the performance metric against energy savings. Dynamic voltage and frequency scaling (DVFS), clock gating, and power gating analyze for use in static and dynamic power consumption minimization. The advanced transistor technologies, together with nanotechnologies, such as FinFETs and nanosheets, go further to enhance power control and promote sustainable, scalable deployments for IoT. Moreover, the research forms significant discussions about energy-harvesting systems and low-power wide-area networks (LPWANs) for the propagation of autonomous IoT systems.Finally, the paper gives some practical examples where low-power VLSI design has tasted sweet fruit, ranging from environmental monitoring, health, and smart city infrastructure. Low-power sensors are massively deployed in environmental monitoring systems, acquiring more data with less maintenance effort. Energy-efficient circuits allow a longer lifespan in battery usage for vital portable devices like glucose monitors or pacemakers, thereby enriching care for the patient.Key challenges identified include balancing trade-offs associated with computer power versus energy efficiency, transistor leakage management, and design complexities for multi-core systems. It is pointed out by the study that new innovative design paradigms and validation methodologies are needed to make sure of reliability under changing operating conditions.Heterogeneous integration, for instance, and machine-learning-assisted power management strategies offer good options for future research. The integration of energy-harvesting components and the exploration of unconventional materials like memristors and spintronics mark a transition towards ultra-low-power circuits. Also, the role of software in optimizing power consumption using intelligent algorithms and adaptive systems is emphasized. All things considered, the advancement of low-power hardware design for IoT devices becomes relevant in providing sustainability, efficiency, and scalability for IoT ecosystems. The study encompasses state-of-the-art methodologies, challenges, and future directions, thus forming fundamental knowledge required for next-generation energy-efficient IoT solutions.
Copyright (c) 2023 Olumhense Benedict Adoghe, Nida Hafeez (Author) https://creativecommons.org/licenses/by/4.0
QUANTUM COMPUTING FOR CRYPTOGRAPHY: EXPLORING THE FUTURE OF SECURE COMMUNICATIONS WITH QUANTUM ALGORITHMS
Quantum computing holds an enormous power to transform cryptography because it protects secured communication. RSA together with elliptic curve cryptography functions based on mathematical challenges like integer factorization and discrete logarithms until quantum computers present security risks to these traditional systems. Such problems become solvable with efficiency through Shor's algorithm running on quantum computers which threatens the security of multiple widely used cryptographic protocols. The document examines quantum computing effects on cryptography to explain why quantum algorithms break classic cryptographic system security. Post-quantum cryptography (PQC) acts as a protective solution against quantum-based attacks through its mission to create cryptographic techniques which demonstrate quantum attack resilience. This paper examines quantum-age security design protocols for cryptographic keys using both quantum key distribution and lattice-based cryptography and hash-based cryptography and multivariate polynomial cryptography. The research analyzes the effectiveness and protective capability of new PQC solutions by connecting theoretical concepts with practical applications. The study points out advancements in quantum cryptography as well as the quantum hardware obstacles and the global initiative to establish post-quantum algorithms standards. The authors stress the urgent need for up-to-date quantum-resistant measures because of swift quantum technology progress. The protection of sensitive materials and communications networks from destructive quantum computing threats requires immediate focus because this need drives the necessity of properly preparing for post-quantum cryptography.
Copyright (c) 2023 Arslan Nadeem, Aiman Shabbir (Author) https://creativecommons.org/licenses/by/4.0
COMPUTATIONAL FLUID DYNAMICS (CFD) IN AERODYNAMICS: SIMULATING AND OPTIMIZING AIRCRAFT AND AUTOMOTIVE PERFORMANCE
Computational Fluid Dynamics (CFD) has emerged as an indispensable tool for optimizing aerodynamic performance in the aerospace and automotive industries. The research provides a comprehensive application of CFD techniques for simulating airflow behavior, predicting aerodynamic forces, and optimizing design parameters for aircraft and automotive systems. Aerodynamics perform an important function in reducing drag and enhancing stability, as well as fuel-efficiency improvement and safety implementation. CFD simulations could provide engineers with insights on flow complexities around phenomena such as turbulence, pressure distribution, and wake regions that greatly affect the performance of vehicles and aircrafts. CFD is an essential activity in the automobile sectors, where it modifies the vehicles form to provide the lower drag coefficients, hence better fuel economy and little environmental impacts. The study analyzes techniques like modifying rear-end geometries or streamlining body shapes, optimizing air ducts, and ensuring a great improvement in aerodynamic efficiency. In aerospace applications, CFD is also useful for such objectives as wing, fuselage, and engine nacelle design and optimization. Here, it provides reduction of drag due to lift induced, better lift-to-drag ratios, and increased stability across various flight conditions. The use of advanced turbulence models, precision meshing strategies, and precise boundary conditions is critical to achieving reliable simulation results. The above-mentioned features also contain innovative advances such as shape optimization, adaptive meshing, and multi-objective optimization methods that contribute to simulation quality and efficiency improvement. High-performance computing is in itself a factor that enables heavy simulations at high speed, accelerating the design iteration and development of designs that are now in the pipeline. It also covers the area of virtual prototyping within CFD, ultrareductive physical prototype and costly wind tunnel testing. The results pointed out that including the CFD study into the design process will facilitate sustainable and efficient development while enhancing the understanding of fluid-structure interaction. The further enhancement of CFD tools will change design methods to allow real-time simulation and adaptive optimization. Future research is expected to incorporate machine learning algorithms for improved prediction and bio-inspired designs for superior aerodynamic performance.
Copyright (c) 2023 Muzammil Ali, Junaid Hassan (Author) https://creativecommons.org/licenses/by/4.0
NANOMATERIALS IN CHEMICAL ENGINEERING: SYNTHESIS, CHARACTERIZATION, AND INDUSTRIAL APPLICATIONS IN CATALYSIS
Nanomaterials are deemed novel materials that have essentially changed the field of chemical engineering, accounting for their unique physicochemical properties conferred via high surface area to volume ratio, enhanced reactivity, and mechanical strength. These properties of nanomaterials led to advanced synthesis and characterization studies in catalysis, greatly enhancing the efficiency, selectivity, and sustainability of industrial applications. The study herein investigates various synthesis techniques: physical, chemical, and biological-forfabricating nanomaterials with specified properties. Characterization of the nanomaterials with the help of advanced techniques-e.g., scanning electron microscopy, X-ray diffraction (XRD), Spectroscopy-is very important for understanding their various structural and functional properties. Nanocatalysts based on metals, metal oxides, carbon, and hybrids showed tremendous potential in petrochemical, pharmaceutical, and environmental applications, more so in their industrial catalysis. Nevertheless, such big barriers to widespread adoption include toxicity, stability, and cost-effectiveness. Experimental studies indicated that nanostructured catalysts exhibit greater catalytic activity, turnover frequency, and durability when compared with conventional catalysts. This exploration inspires the need to conduct extensive research into green synthesis and upscaling methods that can serve to bridge the gap between laboratory-scale research and industrial applications. Coming advancements in nanomaterials will be in the way of next-generation catalytic processes-more sustainable and far more efficient in chemical engineering.
Copyright (c) 2023 Muhammad Fahid Ramzan, Kamran Iqbal (Author) https://creativecommons.org/licenses/by/4.0
FOSTERING CREATIVITY AND PROBLEM-SOLVING SKILLS IN ENGINEERING STUDENTS: A PEDAGOGICAL APPROACH
This study explores how different teaching methods can help engineering students improve their creativity and problem-solving skills. A survey was conducted with 200 engineering students from various disciplines in Lahore, Pakistan. The research focused on strategies like Active Learning, Collaborative Learning, and Problem-Based Learning (PBL).Results showed that students found PBL (average score: 4.8) and Active Learning (4.5) much more effective than traditional lectures (2.3). After using these methods, students reported higher confidence levels (from 2.3 to 4.7) and better problem-solving abilities. Those who worked on real-world case studies scored higher in creativity (85.9) than those who did not (62.3). The study also found a strong link between students' growth mindset and their resilience. Most students (over 70%) rated their engagement in learning as high.These findings suggest that using interactive and real-world teaching methods can greatly improve students’ thinking skills, creativity, and confidence. Including such methods in engineering education can better prepare students for real-life challenges in their careers.
Copyright (c) 2023 Muhammad Ammad, Ahmed Raza (Author) https://creativecommons.org/licenses/by/4.0
ADAPTING ENGINEERING EDUCATION TO THE CHALLENGES OF THE 21ST CENTURY: SKILLS, SUSTAINABILITY, AND TECHNOLOGY
The 21st century has introduced unprecedented challenges in the fields of engineering, driven by technological disruption, climate change, and global shifts in labor market demands. This study investigates the transformation of engineering education through an integrated approach that emphasizes technical proficiency, sustainability, soft skills, and lifelong learning. A comprehensive framework was proposed and evaluated, incorporating emerging technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and automation into the engineering curriculum, while also embedding sustainability-focused modules, interdisciplinary case studies, and industry collaboration mechanisms.Additionally, soft skill indices—measured via peer and instructor feedback—showed marked gains in communication, leadership, and collaborative problem-solving. Twelve visualization plots (e.g., line, bar, hybrid, and scatter charts) and nine tables illustrated consistent trends across student learning outcomes, satisfaction levels, and technical readiness.The discussion highlights the importance of overcoming institutional inertia, aligning curricula with real-world industry needs, and prioritizing faculty development for sustainable reform. Case studies such as the Bosco Verticale (Milan) and solar-powered desalination plants served as pivotal teaching models for environmental engineering. This research concludes that a holistic, interdisciplinary, and innovation-driven reform of engineering education is imperative to cultivate globally competent, ethically grounded, and future-ready engineers capable of addressing complex societal challenges.
Copyright (c) 2023 Fahad Ali, Ahmed Ali (Author) https://creativecommons.org/licenses/by/4.0
THE ROLE OF INDUSTRY COLLABORATION IN SHAPING MODERN ENGINEERING CURRICULA
The rapid evolution of technological industries, including automation, artificial intelligence, and advanced manufacturing, has rendered traditional engineering education models increasingly inadequate. This study investigates the role of structured industry-academia collaboration in shaping modern engineering curricula, with a focus on higher education institutions in Pakistan. Using a mixed-method approach involving institutional surveys, curriculum analyses, and case studies, the research evaluates the impact of collaborative mechanisms—such as curriculum co-design, internships, joint R&D initiatives, and advisory board integration—on student skill development, curriculum relevance, and employability outcomes.The results reveal that universities engaged in sustained industry partnerships exhibit significantly higher curriculum responsiveness, with over 80% reporting regular updates aligned with emerging technologies. Institutions with embedded internship programs show a 30% improvement in graduate employability, while those involved in joint research projects report enhanced innovation output and research commercialization. Furthermore, data indicates that industry-sponsored programs and guest lectures contribute to improved student engagement and workplace readiness.Despite these benefits, the study identifies key challenges including misalignment of academic and industrial goals, limited financial resources, insufficient faculty-industry interaction, and the absence of formal long-term collaboration frameworks. These findings underscore the necessity of strategic policy interventions, the establishment of industry liaison units, and government-funded public-private partnerships.This research concludes that industry-academia collaboration is not merely a supplementary aspect of engineering education but a critical pillar for ensuring graduate competitiveness and national technological advancement. The study offers practical recommendations for institutionalizing collaboration frameworks and aligning engineering education with real-world demands.
Copyright (c) 2023 Muzammil Ali, Imran Ali (Author) https://creativecommons.org/licenses/by/4.0
THE IMPACT OF SIMULATION AND VIRTUAL REALITY ON ENGINEERING EDUCATION AND PRACTICAL TRAINING
Teaching strategies should also adapt to the evolving subject of engineering, that is increasingly complex. It might not always be the case, but due to problems with, among others, cost, safety, and accessibility, traditional teaching involves methods that do not always allow immersive and experiential study. Simulation and virtual reality (VR) technologies have presented a paradigm shift even in engineering education. They develop realistic and interactive environments which are beneficial in enhancing academic knowledge and practical skills.This paper examines the application of simulation and virtual reality (VR) technology as a combined are in various areas of interests involving engineering disciplines, i.e., civil, mechanical, electrical, aerospace, and chemical engineering.We obtained information as quantitative data of 180 students through performance indicators, engagement diaries, feedback surveys, and cognitive license tests. We prepared many tables and complex graphs to observe the influence of VR on the results of pre-tests and post-tests, the amount of time spent using the system, the level of satisfaction, and memorization rates. The research concluded that students who attended VR-based courses performed way better at school, and their average length post-test results increased by 62.4 percent to 86.7 percent. Table 1 to 3 will indicate the rate of time devotion toward VR in terms of cognitive developments in various fields. Those students who stated that they were actually absorbed (as shown in Table 2 and Figure 2) maintained higher skills and were in a better mood. As it can be seen in figures 4, 5 and 11, spending a considerable amount of time using VR will enable people to make better decisions and commit fewer errors and has the result of increasing the confidence of learners. Figures 6-8 indicate that radar and heatmap visualization deliver advantage of solving the problem, accurate design and real time responsiveness in an overriding manner. Simulation and virtual reality (VR) technologies help to make engineering education much better because it contributes to the ability of students to retain what they have learned as it allows them to remain interested and helps to learn and train their skills under actual conditions. The conclusions indicate that even in the case of in-person and distance learning, it is quite possible to apply immersive technologies, even though there were certain issues initially, including cost and infrastructure. This paper reveals that we must continue investing into VR-included courses to prepare engineers with real-life issues, which are becoming increasingly difficult and incorporate more than two disciplines.
Copyright (c) 2023 Sana Khalid, Usman Qureshi (Author) https://creativecommons.org/licenses/by/4.0