ALBERT

Description: 〈p〉〈em〉〈span〉This study delves into the management of electronic waste (e-waste) stemming from the disposal of personal electronic items and mobile phones, primarily in response to the remarkable surge in the utilization of these devices within the Hassan city populace in recent years. The principal objectives revolved around investigating the existing disposal methods for electronic devices including mobile phones and collecting fundamental data concerning their disposal practices within the geographical confines of Hassan city of Karnataka State. Additionally, an endeavor was undertaken to gauge the level of awareness among respondents regarding the potential hazards posed by e-waste. It was observed that a significant proportion of the Hassan population typically retains especially electronic devices is cell phones, once these devices become outdated and obsolete. Among the prevalent disposal methods, the most widespread approach involves selling these gadgets to scrap dealers or junk shops, whereas recycling practices remain relatively underutilized. Notably, a mere minority of individuals engage in recycling activities. An intriguing revelation emerged, with 65% of respondents expressing concern about the adverse repercussions of improper e-waste disposal on human health and the environment. Astonishingly, all respondents admitted to having no knowledge of the fate of their discarded electronic devices. Based on the findings gleaned from this survey, it is strongly recommended that a comprehensive review be conducted on the overarching management of e-waste stemming from this electronic waste including mobile phones, gadgets in the Hassan city of Karnataka State. The purpose of these surveys and data collection endeavors is to approximate the volume of e-waste generated through the disposal of these devices. This information is envisioned to assist stakeholders and government agencies in formulating effective and efficient legislation and policies for the proficient management of e-waste〈/span〉〈/em〉〈/p〉

Description: 〈p〉〈em〉Indian Railroads is one of the largest railroad systems in the World. The Indian railway system has grown significantly over the years, as seen by the massive construction of its railroads; nonetheless, some accidents are caused by fractures in the railway track. Splits may occur because of the track's expansion or contraction brought on by seasonal variations. This study proposes a crack monitoring vehicle that employs an ultrasonic sensor to detect fractures on railway tracks and uses an Arduino Uno to facilitate the GSM and GPS module to send an SMS to the testing station, thereby mitigating the problems caused by these cracks. This intelligent system works like a remote monitoring system which gives an alert to stop the passage of trains in that path. The proposed model involves the use of Arduino, ultrasonic sensor, buzzer, GSM module, and GPS module.〈/em〉〈/p〉

Description: 〈p〉〈em〉Road safety is a critical concern in the modern world, where advancements in technology have made our lives easier but have also given rise to increased traffic hazards and road accidents. The "Car Accident Detector and Informer" project is an innovative system aimed at enhancing road safety by accurately detecting and informing about car accidents in real-time. This project integrates advanced sensors, microcontroller technology, and communication protocols to create an efficient accident detection and notification system. Utilizing GPS and GSM technology for precise location tracking and instant notifications, this system has the potential to reduce emergency response times, save lives, and minimize property damage. This research paper presents a detailed overview of the project, including its objectives, working principles, components, advantages, disadvantages, and prospects.〈/em〉〈/p〉

Description: 〈p〉〈em〉Spatiotemporal data analytics is a dynamic field that seeks to extract valuable information from data that integrates both spatial and temporal dimensions. This article explores the importance of this emerging field and its applications in a variety of fields, including environmental science, public health, and urban planning. Spatiotemporal data analysis addresses important research questions, such as determining event probabilities, understanding change patterns, identifying associations between events, and predicting events Future. However, this comes with many challenges, including managing large datasets, ensuring data quality, dealing with spatial and temporal autocorrelation, and more. To address these challenges, proposed solutions include data reduction and sampling, dimensionality reduction, data compression, use of spatial and temporal indexes, parallel and distributed processing, data filtering and pre- processing. Furthermore, strategies to handle spatial and temporal autocorrelation include exploratory data analysis, using spatial weight matrices, including spatially lagged variables, and regression models. spatial attribution, cluster analysis, etc for spatial autocorrelation and for temporal autocorrelation, solutions include time series analysis, differencing, ARIMA models, lagged variables, time series decomposition, exponential smoothing, state space modelling, machine learning, cross-validation, and regularization techniques. These approaches provide valuable insights to address the complexity of spatio-temporal data analysis and unlock its potential in various fields.〈/em〉〈/p〉

Description: 〈p〉〈em〉Diamond drilling, a core drilling technique employing diamond-encrusted drill bits, has emerged as a critical method for extracting cylindrical rock samples from diverse geological formations. This article provides an extensive overview of diamond drilling, encompassing its equipment, applications, challenges, and its pivotal role in geological exploration, mining, and construction projects. The versatility of diamond drilling is evident in its adaptability to various rock types, spanning the gamut from soft sedimentary strata to formidable crystalline structures. In mining, it serves as an indispensable tool for assessing the quality, depth, and size of mineral deposits. Likewise, in construction and civil engineering, diamond drilling aids in ascertaining geological conditions for safe and stable foundation design. Environmental considerations are paramount in contemporary drilling practices, with containment measures for drilling fluids to mitigate ecological impacts. Safety precautions are rigorously adhered to, ensuring the well-being of workers and the integrity of drilling operations. Furthermore, core samples extracted through diamond drilling are instrumental in geological investigations. These samples, meticulously analyzed, yield insights into rock composition, mineral content, and geological structures. They inform decisions in resource exploration, mine planning, and construction project management. This review underscores the invaluable contributions of diamond drilling to our understanding of the Earth's subsurface, emphasizing its adaptability, environmental consciousness, and safety. By examining the critical aspects of this technique, this article illuminates the profound impact of diamond drilling on various industries and the scientific community, positioning it as an indispensable tool for unlocking the secrets hidden beneath the Earth's surface.〈/em〉〈/p〉

Description: 〈p〉〈em〉The COVID-19 pandemic has underscored the necessity for digital infrastructure and accessibility, particularly in the education sector. This paper investigates the benefits and effectiveness of utilizing Green Cloud Computing (GCC) techniques for the dissemination of educational library data in remote regions of India during this critical period. The GCC model, known for its energy efficiency and reduced environmental impact, is proposed as a robust, scalable, and eco-friendly solution for providing remote educational access. The research utilizes a mixed-methods approach, incorporating both quantitative assessments of data reach and usage, and qualitative surveys to understand user experiences. The study reveals that GCC techniques can significantly improve educational resource distribution, thereby mitigating the educational disparities further exacerbated by the pandemic. These findings reinforce the potential of GCC techniques as a sustainable and inclusive technology in reshaping the educational landscape in remote regions.〈/em〉〈/p〉

Description: 〈p〉〈em〉One of the most crucial global issues of our era is climate change, whose consequences are presently being felt all over the world. As climate change keeps on forgoing, it's important that governments, organizations, and businesses take visionary actions for adapting and protecting themselves from calamities.〈/em〉〈em〉 This paper summarizes the application of Remote Sensing (RS) and 〈/em〉〈em〉Geographic Information System (〈/em〉〈em〉GIS) in observing impact of climate change on drought, soil moisture, land degradation, food security, EHIs’ characterization and blue carbon science and review of AI based climate solutions. The〈/em〉〈em〉 〈/em〉〈em〉integration of advanced machine learning algorithms,〈/em〉〈em〉 〈/em〉〈em〉real-time data analysis, and other cutting-edge technologies could lead to even more effective climate change〈/em〉〈em〉 〈/em〉〈em〉adaptation strategies. AI-activated climate change adaptation strategies have the prospective to significantly〈/em〉〈em〉 〈/em〉〈em〉improve the resilience of infrastructure communities, and businesses to the changing climate.〈/em〉〈strong〉〈/strong〉〈/p〉

Description: 〈p〉〈em〉Urban transportation systems face significant challenges due to rapid population growth and development. This study delves into the enhancement of road safety in Navi Mumbai by employing Geographic Information System (GIS) and Remote Sensing (RS) techniques. The escalating rate of vehicular accidents in Navi Mumbai presents a pressing concern. This research investigates accident data and traffic patterns, identifying vulnerable areas prone to accidents and congestion. By conducting spatial analysis using GIS and RS, the study aims to uncover accident hotspots and traffic congestion zones, offering insights into underlying road safety issues. The research methodology involves a multi-stage process. Initial data collection from various sources, including police reports, live traffic data, and satellite imagery, forms the foundation. Geographic coordinates extracted and processed through GIS applications aid in plotting accident locations and creating density maps. Additionally, on-site investigations at strategically chosen locations provide invaluable insights into local conditions, traffic patterns, and contributing factors to congestion and accidents. The findings are presenting tailored solutions for each area, ranging from optimized traffic signal timings to infrastructural improvements. The findings of this study present actionable insights aimed at improving road safety and traffic management in Navi Mumbai. Recommendations encompassing signal optimizations, infrastructure enhancements, and community engagement strategies offer a holistic approach to mitigate traffic congestion and reduce accidents. The collaborative effort with relevant authorities, as highlighted in the study, serves as a crucial step towards implementing these recommendations for meaningful change. This research not only identifies critical areas for intervention but also serves as a model for leveraging GIS and RS techniques to enhance the road safety in urban areas, paving the way for safer and efficient transportation networks in the future.〈/em〉〈/p〉

Description: 〈p〉〈em〉The urgency to transition to renewable energy sources is underscored by the environmental crises stemming from our reliance on non-renewable fuels. This study focuses on assessing wind energy potential in Odisha, India, utilizing satellite data and Geographic Information System (GIS) technologies. The research addresses the critical need for strategic planning and site selection before investing in renewable energy infrastructure. By employing a model that integrates various free satellite datasets and leverages fundamental physical principles, the study calculates wind power density (WPD) at a height of 90 meters above the surface for both onshore and offshore locations. The methodology involves acquiring and processing datasets such as temperature, wind speed, digital elevation model (DEM), pressure, air density, and land use/land cover (LULC) classifications. The model applies equations derived from physical laws to determine key parameters necessary for calculating WPD. Specifically, temperature and pressure data are used to estimate air density, while surface roughness is assigned based on LULC classes with windspeed at 10m to extrapolate wind speed at 90 meters above ground level. The method can be used at any hub height. Results reveal significant wind energy potential in Odisha, particularly along the coastal regions. Jagatsinghpur and Puri emerge as areas with high WPD onshore, while the offshore exclusive economic zone (EEZ) of Odisha exhibits substantial wind energy resources. The model outputs provide valuable insights for various studies related to renewable energy and facilitate informed decision-making in site selection analyses. Furthermore, the study emphasizes the simplicity and effectiveness of the developed model,〈/em〉〈br〉〈em〉making it a practical tool for assessing wind energy potential in other regions as well. Overall, this research contributes to the global effort towards transitioning to sustainable energy sources and combating climate change. By highlighting the renewable energy potential of Odisha, it underscores the importance of harnessing wind energy as a viable pathway towards a cleaner, greener future.〈/em〉〈/p〉

Description: 〈p〉The research strives to enhance digital surveying methodologies for precise and detailed land mapping, utilizing advanced instruments like terrestrial scanners, SLAM scanners, total stations, DGPS, and drones. The survey conducted at Ratnagiri Hill in Udaipur aims to scrutinize and compare the merits and drawbacks of each surveying method. The study outlines a systematic process encompassing data collection, processing, output generation, and validation of survey techniques. It highlights the adaptability of these methods across various〈br〉domains, such as building conservation, restoration, and mapping of typically inaccessible areas, emphasizing their potential for time and resource savings. The research underscores the effectiveness of a one-time data collection process for subsequent work, laying the groundwork for the advancement of digital surveying technologies. When integrated with the Total station and DGPS survey, the combination of terrestrial scanners, drones, and SLAM scanners achieves a vertical accuracy of around 32 mm.〈/p〉