International Journal of Innovations in Science & Technology
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Site Suitability Analysis of Smog Cutting Towers in District Lahore, Pakistan
Get PDFIntroduction/Importance of Study:
Lahore, one of Pakistan’s most populous cities, is home to a diverse demographic comprising residents from various ethnic, linguistic, and cultural backgrounds. Recently, the city has been grappling with severe smog-related challenges, primarily due to vehicular emissions, industrial activities, and the burning of crop residues in neighboring agricultural regions. These factors have exacerbated numerous environmental and health issues, making the situation increasingly dire.
Novelty Statement:
Lahore’s 24 major hospitals, while indicative of a robust healthcare infrastructure, also underscore the vulnerability of a significant number of patients to the adverse effects of smog. The Normalized Difference Moisture Index (NDMI) reveals limited water availability in Lahore, which hinders natural cleansing mechanisms like rainfall that typically help remove pollutants from the atmosphere.
Material and Methods:
This research relies on secondary data sources, including Sentinel 2 imagery, to analyze urban expansion and moisture levels in the city. Traffic control data has been used to pinpoint areas with high traffic congestion, while elevated air pollution levels have been overlaid with hospital locations, marked using Google Earth data. This comprehensive approach aims to mitigate smog\u27s impact in Lahore by identifying areas most in need of smog-cutting towers.
Results and Discussion:
The research methodology focused on key parameters such as urban expansion, traffic choke points, vulnerable populations in hospitals, and the overall moisture index, which highlights the city’s capacity to retain moisture. The analysis identified major congestion areas, including Garhi Shahu, McLeod Road, Mughalpura, and Shahdara, as significant sources of pollution. The NDMI further confirmed limited water availability, exacerbating smog retention. To address these challenges, the strategic placement of four smog-cutting towers within a 5 km range in Lower Mall Road, Thokar Niaz Baig, Mughalpura, and Model Town has been recommended. These locations, characterized by high traffic congestion, elevated air pollution levels, and significant urban development, present a targeted approach to reducing smog in Lahore.
Concluding Remarks:
The identified locations in Lahore—Lower Mall Road, Thokar Niaz Baig, Mughalpura, and Model Town—are crucial for the effective mitigation of smog. The strategic placement of at least four smog-cutting towers within these areas will significantly influence the rate of smog production, retention, and impact, given the high traffic congestion, elevated pollution levels, and substantial urban development in these regions
Revolutionary Hologram Systems: Pioneering a New Frontier in Visual Technology
Get PDFNew technologies are enabling the development of consolidated, portable holographic displays that can be utilized in a variety of settings, making holographic content more accessible and shareable. Holographic displays represent objects in three dimensions, providing a more pragmatic and immersive viewing experience. This is particularly important in sectors such as architecture, design, and medical imaging, where the representation of depth can aid in comprehension and decision-making. This study presents a revolutionary and efficient method for converting 2D images into immersive 3D holograms using Blender software and a holographic FP. The process begins with Blender, an open-source 3D creative software that transforms 2D photographs into dynamic 3D models to add depth and realism. These transformed images are then uploaded to a user-friendly mobile app, which acts as an intermediary for seamless transfer to a holographic display. The smartphone app offers an intuitive interface for image customization and management. This study contributes to the understanding and practical application of 3D holographic displays by addressing key challenges and outlining the development process, resulting in a versatile tool. These recent breakthroughs in holography are expanding its potential applications and enhancing user experiences, making holographic technology increasingly significant in industries such as healthcare, education, entertainment, and data visualization
Austempering Time and Its Influence on the Mechanical Performance of Inverse Bainite: Insights from Hardness, Toughness, and Strength Testing
Get PDFThis study examines the impact of austempering time on the mechanical properties of 0.8C experimental steel with inverse bainitic microstructures. Samples were austenitized at 900 °C and austempered at 420 °C for 30, 60, 90, and 120 minutes. The effects on hardness, impact toughness, and (UTS) were analyzed. Microstructural evaluations by optical microscope, scanning electron microscope, and energy dispersive spectroscopy confirmed the formation of inverse bainite. Mechanical testing showed that increasing austempering time leads to higher hardness due to cementite lath growth and reduced ferrite content, but also results in lower Charpy impact energy, indicating reduced toughness. While UTS initially decreases, it increases sharply after 120 minutes, accompanied by brittle fracture. This study suggests that prolonged austempering enhances hardness and strength but increases brittleness, making these structures less suitable for applications involving sudden forces
Prediction of Brain Stroke Using Federated Learning
Get PDFStroke often arises from an abrupt blockage in the blood vessels supplying the brain and heart. Detecting early warning signs of stroke can significantly reduce its impact. In this study, we propose an early prediction method for stroke using various Machine Learning (ML) techniques, considering factors such as hypertension, body mass index, heart disease, average glucose levels, smoking habits, prior stroke history, and age. These attributes, rich in information, were utilized to train three distinct classifiers: Logistic Regression, Decision Tree, and K-nearest neighbors for stroke prediction. In this study, Federated Learning (FL) has been applied to combine the ML models (Logistic Regression (LR), Decision Tree (DT), and K-Nearest Neighbors (KNN)) from distributed medical data sources while preserving patient privacy. By aggregating locally trained models from multiple hospitals or devices, FL ensures the robustness of the weighted voting classifier without requiring direct data sharing, thereby enhancing stroke prediction accuracy across diverse datasets. Subsequently, the results from these base classifiers were combined using a weighted voting approach to achieve the highest accuracy. Our study demonstrated an impressive accuracy rate of 97%, with the weighted voting classifier outperforming the individual base classifiers. This model proved to be the more accurate in predicting strokes. Additionally, the Area Under the Curve (AUC) value for the weighted voting classifier was notably high, and it exhibited the lowest false positive and false negative rates compared to other classifiers. Consequently, the weighted voting classifier emerged as an almost ideal tool for predicting strokes, offering valuable support to both physicians and patients in identifying and preventing potential stroke incidents
AI-Driven Control and Processing System for Smart Homes with Solar Energy
Get PDFIn recent years, the utilization of solar energy has grabbed attention in the industrial and domestic zones. The existing systems to use the services of solar cells are conventional. These systems require parameters (irradiance and temperature) for desirable results that are unknown to the end user. These parameters change with regions and human to human. Therefore, an Artificially Intelligent, Control and Processing System is designed to get more accurate results with the unique feature of empowering the end user, which uses the parameters assembled on different regions. The proposed system has an improved PV model based on (ANN) that resembles experimental results with a few readily available, reprogrammable input parameters from the PV module datasheet. The developed system uses regional irradiation data which exhibits minimal fluctuations. In the model presented here; to avoid overburdening problems, loads were divided into manageable chunks MK. In this case load chunks (needed) were moved from solar to utility more stably and economically. Briefly stated the suggested solution provides a complete package for integrating solar energy systems with the grid in an automated and resilient way
Geospatial Analysis of Land Fragmentation and Its Impact on Land Use of District Peshawar, Pakistan
Get PDFThe study analyzes how land fragmentation affects the use of the land in sample villages of Peshawar district. Globally, land is a primary source of productivity, yet the population is expanding at an alarming rate. This population growth has an effect on how land is acquired and used, which frequently results in the problem of land fragmentation. To meet the study\u27s goals, data were gathered from both primary and secondary sources including an intensive field survey using a questionnaire as well as land revenue department and population census organization. Out of a total of 279 villages two sample villages, namely village Ghalji Kander Khel and village Mathra were selected by random means for detailed and intensive study. During 1990-91 to 2020-21, fragmented land in sample villages increased. In village Ghalji Kander Khel fragmented land increased from 5.6% in 1990-91 to 23.9% in 2020-21 while in village Mathra fragmented land increased from 6.9% in 1990-91 to 27.1% in 2020-21 indicating an overall four-time increase during past two decades. The main cause of land fragmentation in sample villages is the Law of Inheritance, followed by population growth, market prices, financial difficulties, social issues, and government infrastructure. In sample villages, both area under cultivation and cultivable waste decreased out of which in village Ghalji Kander Khel cultivated land shrunk from 3478 kanal (1 kanal =506 m2) to 2194.1kanals and cultivable waste reduced from 31.1 to 25.4 kanal from 1990-91 to 2020-21. In village Mathra, cultivated land contracted from 5473.2 kanal in 1990-91 to 3443.94 kanal in 2020-21, and cultivable waste diminished from 117.81 kanal to 32.4 kanal. The built-up area enlarged from 802.4 kanal to 1298.1 kanal in Ghalji Kander Khel and from 1392.3 kanal to 1991.6 kanal in Mathra. Finally, it was revealed that most of the area under cultivation is transformed into other land uses. The conversion of cultivable waste to cultivable land took place on a very small scale
Addressing Illicit Tobacco Growth in Pakistan: Leveraging AI and Satellite Technology for Precise Monitoring and Effective Solutions
Get PDFThe market share of illicit tobacco products in Pakistan has seen a significant surge in recent years. In 2022, it reached a staggering 42.5%. Since January 2023, there has been a sharp 32.5% increase in volumes of Duty Not Paid (DNP) products and a remarkable 67% surge in the quantities of smuggled cigarettes. This rise can be attributed to the unregistered and unlicensed tobacco cultivation in Pakistan. This sector has largely relied on conventional methods for data collection in the field, primarily managed by the country\u27s crop statistical departments. The utilization of cutting-edge artificial intelligence techniques and satellite imagery for generating crop statistics has the potential to address this issue effectively. We established a synergy by combining images from two remote sensing satellites and collected field data to detect tobacco crops using Recurrent Neural Networks (RNN). The results affirm the effectiveness of these techniques in detecting and estimating the acreage of tobacco crops in the observed areas, particularly in a union council of the Swabi region. We conducted surveys to collect training and validation data through our proprietary smartphone application, GeoSurvey. The collected data was subsequently refined, preprocessed, and organized to prepare it for use with our deep learning algorithm. The model we developed for the detection and acreage estimation of tobacco crops is called Convolutional Long Short-Term Memory (ConvLSTM). We created two datasets from the acquired satellite images for comparison. Our experimentation results demonstrated that the use of ConvLSTM for the synergy of Sentinel-2 and Planet-Scope imagery yields higher training and validation accuracy, reaching 98.09% and 96.22%, respectively. In comparison, the use of time series Sentinel-2 images alone achieved training and testing accuracy of 97.78% and 95.56%
Global Climate Change Adaptation: Mitigating Flooding Impacts in Pakistan
Get PDFClimate change is indeed a wide-reaching problem with noteworthy consequences. The climate in Pakistan has been experiencing a quick-changing pattern, accompanied by an increase in the intensity and frequency of extreme events due to global warming. The capacity of people to adapt to climate change is crucial in reducing its impacts. Over the past decade, the irregular incidents of weather events such as floods, droughts, heat waves, and cyclones have had a significant impact on the economic growth of the country. The main goal of this study is to assess how well the local community is able to adapt to the challenges posed by climate change. The study was specifically conducted in Mianwali district, Punjab province, Pakistan focusing on this specific location allows for a more in-depth analysis of the adaptive capacity of its local community to climate change. A thorough survey of the district was conducted, and the responses of the people were recorded through questionnaires and interviews. People were asked about their views on climate change and the adaptive strategies they are implementing to tackle its effects. The findings unfolded the fact that the limitations of being unaware of environmental issues are not only the lack of education but also the financial constraints are there. The study also explained that the residents of Mianwali who are aware of climate change and flood trends are more concerned about growing and using a variety of crops as a resilience tactic. Although there is a greater number of people who are not even aware of climate change and the association of floods with it, the public also claimed that the local authorities are not providing them with any information in time. So, the results suggest a clear insight for the stakeholders and policymakers to manage flooding and climate change by providing the people with crucial information beforehand and managing the situation by suggesting and implementing multiple adaptive measures
Numerical Analysis of Flow Past Over Square Rods Using Control Rod at Distinct Gap Spacing
Get PDFThe influence of Reynolds number and gap spacing on flow via two detachable square rods with a small control rod in between is examined using two-dimensional numerical simulations. The range of gap spacing is determined by taking Re = 80–200 and g = 0.50–6.0. First, the impact of the computational domain and the accuracy of the grid points are analyzed. Among these are crucial flow modes, fully formed two rows of vortex shedding flows, fully developed regular and irregular vortex shedding flows, consistent flow, and shear layer reattachment. For every combination of (Re, g), the Cdmean of the C1 rod is higher than the Cdmean of the C2 rod. Additionally, push causes Cdmean2 values to be negative between g = 0.50 and 2.0. The value of Cdmean that is larger is 1.3907 (Re, g) = (150, 3.0). Furthermore, for (Re, g) = (200, 3.0) and (200, 1.50), respectively, for C1 and C2, the greatest percentage decrease in Cdmean is 19.3% and 120.3%, respectively
Development of A Web based GIS Solution for Flood Inundation Mapping and Assessment in Lahore, Pakistan
Get PDFIntroduction
Geographic information system (GIS) is a strong tool in flood hazard mapping, mitigation, and management. GIS-based approaches provide the wayforward to measure the flood inundation. Integration of web technologies with GIS (Web-GIS) is quite significant to accomplish the aim.
Methodology
In this research, HEC-RAS 1D was used to map the flooded areas around River Ravi at Lahore. The output of HEC-RAS with Web-GIS stack were used to build the interactive flood measuring tool. The Web-GIS stack used for this study was based on Geo Server, PHP, HTML, CSS, and JavaScript. Geo Server provides the OGC implemented standards with vendor specific capabilities like WMS Animator to animate the flood inundation on the User-Interface (UI) and extent animation to make visual interpretations. CQL filter is vendor specific capability in Geo Server used to measure the flood inundation.
Results
The outcomes of HEC-RAS are handy enough to measure, map and present the damages not only to analyst but also to the layman. The working and animated layers are shown in result section of this research.
Conclusion
This web-based flood inundation is robust, user-friendly, and expandable for more features, scenarios, and conditions. This research concludes that visual and web-based data is handy to understand for common person/intellectuals