Search Results (2,422)

Accurate indoor positioning is essential for many applications. However, current methods often fall short in complex environments due to signal fluctuations. We propose a new indoor positioning approach, that is, improved sequential deep learning (ISDL), to address this issue. First, we apply sequential classification algorithms to progressively narrow the search space, reducing potential location regions into smaller neighborhoods. Next, we combine a deep neural network (DNN) with Weighted K-Nearest Neighbors (WKNN) to refine the final location prediction. Then, we validate our method using the publicly available $UJIndoorLoc$ dataset, demonstrating superior accuracy compared to existing methods. Specifically, we achieved 95% floor prediction accuracy and reduced the average positioning error to just 7.82 m. By combining sequential classification and the DNN-WKNN hybrid model, we achieve better localization in complex indoor environments. This system offers practical improvements for real-time location-based services and other applications requiring precise indoor positioning. Full article

In recent years, shared e-scooters have become increasingly popular as a mode of transportation in urban areas. Shared e-scooters have emerged as a convenient and sustainable transportation option in urban areas, providing users with a flexible and efficient way to travel short distances within a city. Many service providers and local municipalities are interested in implementing shared e-scooter operational models. However, determining which operating model to prefer and what the service areas will be is a significant problem. We aimed to solve the implementation of three different operational models, the site selection problem of station locations, and service areas for Erzurum, the metropolitan city in this study. As shared e-scooter is quite a new transportation mode; information collected to assess the operational models’ sustainability performance may be indeterminate and vague. In this study, the Geographic Information System (GIS)-based hybrid multi-criteria decision-making (MCDM) method is proposed for the solution of implementation, site selection, and service areas problems of three different shared e-scooter operational models. To this end, a four-step scientific and strategic solution approach is developed: (i) the identification and detailed explanation of 5 main and 24 sub-criteria, (ii) the weighting of criteria through the Analytical Hierarchical Process (AHP), Multi-Influencing Factor (MIF), and Best–Worst Method (BWM) in order to increase the sensitivity and robustness of the study, (iii) obtaining a suitability map for the solution of implementation, site selection, and service areas problems of operational models, and (iv) assigning shared e-scooter stations and analyzing their performance levels with COmplex PRoportional ASsessment (COPRAS). The results show that, in Erzurum, the central three districts are the most suitable for service areas. The paper’s solution methodology can help service providers and policymakers invest in sustainable shared e-scooter operational models, even in situations of high uncertainty. Full article

Today, facility location planning primarily pertains to the long-term strategic and operational decision-making of large public and private organizations, and the significant costs associated with facility location, construction, and operation have turned location research into long-term decision-making. Presenting a hub location model for the green supply chain can address the current status of facilities and significantly improve demand coverage at an acceptable cost. Therefore, in this study, a network of facilities for hub location in the service site domain, considering existing and potential facilities under probable scenarios, has been proposed. After presenting the mathematical model, validation was performed on a small scale, followed by sensitivity analysis of the main parameters of the model. Furthermore, a metaheuristic algorithm was employed to analyze the NP-Hardness of the model. Additionally, two metaheuristic algorithms, NSGAII and MOPSO, were developed to demonstrate the efficiency of the model. Based on the conducted analysis, it can be observed that the computational time increases exponentially with the size of sample problems, indicating the NP-Hardness of the problem. However, the NSGAII algorithm performs better in terms of computational time for medium-sized problems compared to the MOPSO algorithm. These algorithms were chosen due to their proven efficiency in handling NP-hard optimization problems and their ability to balance exploration and exploitation in search spaces. Full article

The study area is a densely populated residential zone located in central Mexico, characterized by a semi-arid climate and diverse land uses, including domestic, commercial, and services. In the study area, water demand is assessed based on land use requirements set by national and local regulations, and an urban configuration pinpoints spaces suitable for rainwater harvesting for self-consumption. This research proposes indicators based on urban, demographic, and hydrological parameters to assess the effectiveness of low-impact development (LID) techniques, such as rooftop rainwater harvesting, aimed at reducing water scarcity in a residential area vulnerable to water shortages in a semi-arid city in the Global South. Additionally, hydrological design conditions are defined to estimate the potential volumes of recoverable water. Indicators for infiltrated water, available water for consumption, runoff water, and sufficient water are established. This framework enables the development of strategies to mitigate water scarcity and improve water management in the area. Full article

The LBS2ITS project, titled “Curricula Enrichment Delivered through the Application of Location-Based Services to Intelligent Transport Systems”, is a collaborative initiative funded by the Erasmus+ program of the European Union. The primary objectives of the project were twofold: to develop new curricula and modernize existing programs at four universities in Sri Lanka. This effort was driven by the need to align educational offerings with the rapidly evolving fields of Location-Based Services (LBSs) and Intelligent Transport Systems (ITSs). A key feature of the LBS2ITS project is its interdisciplinary approach, which draws on expertise from a range of academic disciplines. The project has successfully developed curricula that integrate diverse fields such as geomatics, cartography, transport engineering, urban planning, environmental engineering, and computer science. By blending these perspectives, the curricula provide students with a holistic understanding of LBSs and ITSs, preparing them to address complex, real-world challenges that span multiple sectors. In this paper, the curriculum development and modernization process is detailed, with a particular focus on the two key phases: teacher training and curriculum development. The teacher training phase was crucial in equipping educators with the skills and knowledge necessary to deliver the new and updated courses. This phase also provided an opportunity for teachers to familiarize themselves with the latest trends and technologies in LBSs and ITSs, ensuring that they could effectively convey this information to students. The development phase focused on the creation of the curriculum itself, ensuring that it met both academic standards and industry needs. The curriculum was designed to be flexible and responsive to emerging technologies and methodologies, allowing for continuous improvement and adaptation. Additionally, the paper delves into the theoretical frameworks underpinning the methodologies employed in the project. These include Problem-Based Learning (PBL) and Problem-Based e-Learning (PBeL), both of which encourage active student engagement and foster critical thinking by having students tackle real-world problems. The emphasis on PBL ensures that students not only acquire theoretical knowledge but also develop practical problem-solving skills applicable to their future careers in LBSs and ITSs. Furthermore, the project incorporated rigorous quality assurance (QA) mechanisms to ensure that the teaching methods and curriculum content met high standards. This included regular feedback loops, stakeholder involvement, and iterative refinement of course materials based on evaluations from both students and industry experts. These QA measures are essential for maintaining the relevance, effectiveness, and sustainability of the curricula over time. In summary, the LBS2ITS project represents a significant effort to enrich and modernize university curricula in Sri Lanka by integrating cutting-edge technologies and interdisciplinary approaches. Through a combination of innovative teaching methodologies, comprehensive teacher training, and robust quality assurance practices, the project aims to equip students with the skills and knowledge needed to excel in the fields of LBSs and ITSs. Full article

Urbanization growth and climate change have increased the frequency and severity of floods in urban areas. One of the effective methods for reducing stormwater volume and managing urban floods is the low-impact development best management practice (LID-BMP). This study aims to mitigate flood volume and peak discharge caused by land use changes in the Darabad basin located in Tehran, Iran, using LID-BMPs. For this purpose, land use maps were extracted for a period of 23 years from 2000 to 2022 using Landsat satellite images. Then, by using a combination of geographic information system-based multi-criteria decision analysis (GIS-MCDA) method and spatial criteria, four types of LID-BMPs, including bioretention basin, green roof, grass swale, and porous pavement, were located in the study area. Next, rainfall–runoff modeling was applied to calculate the changes in the mentioned criteria due to land use changes and the application of LID-BMPs in the area using soil conservation service curve number (SCS-CN) method. The simulation results showed that the rise in built-up land use from 43.49 to 56.51 percent between the period has increased the flood volume and peak discharge of 25-year return period by approximately 60 percent. The simulation results also indicated that the combined use of the four selected types of LID-BMPs will lead to a greater decrease in stormwater volume and peak discharge. According to the results, LID-BMPs perform better in shorter return periods in a way that the average percentage of flood volume and peak discharge reduction in a 2-year return period were 36.75 and 34.96 percent, while they were 31.37 and 26.5 percent in a 100-year return period. Full article

This study analyzes the clean energy infrastructure resilience on Santa Cruz Island, located in the Galapagos archipelago, facing identified multi-natural hazard scenarios such as earthquakes, tsunamis, volcanic eruptions, and extreme weather events. Although Santa Cruz Island has a relatively modern energy infrastructure, its geographic location and lack of clear emergency management actions would significantly affect its performance. Risk assessment components, such as exposure and vulnerability, are also analyzed, highlighting the need for strategic interventions to ensure the continuity of energy supply and other essential services. Proved methodologies are used to propose action plans, including structural and non-structural solutions and simulations based on disaster scenarios. As a result, a series of strategies are revealed to strengthen the response and adaptation capacity of both critical infrastructure and the local community. These strategies hold the potential to ensure the island’s long-term energy security and sustainability, reducing its carbon footprint and instilling hope for a resilient future. Full article

The rapid detection of landslide phenomena that may be triggered by extreme rainfall events is a critical point concerning timely response and the implementation of mitigation measures. The main goal of the present study is to identify susceptible areas by estimating changes in the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Bare Soil Index (BSI), and Synthetic Aperture Radar (SAR) amplitude ratio before and after extreme rainfall events. The developed methodology was utilized in a case study of Storm Daniel, which struck central Greece in September 2023, with a focus on the Mount Pelion region on the Pelion Peninsula. Using Google Earth Engine, we processed satellite imagery to calculate these indices, enabling the assessment of vegetation health, soil moisture, and exposed soil areas, which are key indicators of landslide activity. The methodology integrates these indices with a Weight of Evidence (WofE) model, previously developed to identify regions of high and very high landslide susceptibility based on morphological parameters like slope, aspect, plan and profile curvature, and stream power index. Pre- and post-event imagery was analyzed to detect changes in the indices, and the results were then masked to focus only on high and very high susceptibility areas characterized by the WofE model. The outcomes of the study indicate significant changes in NDVI, NDMI, BSI values, and SAR amplitude ratio within the masked areas, suggesting locations where landslides were likely to have occurred due to the extreme rainfall event. This rapid detection technique provides essential data for emergency services and disaster management teams, enabling them to prioritize areas for immediate response and recovery efforts. Full article

The increasing use of unmanned aerial vehicles (UAVs) in the commercial and recreational sectors has led to a heightened demand for effective recovery solutions after a crash, particularly for lightweight drones. This paper presents the development of a long-range and low-cost emergency radio beacon designed specifically for small UAVs. Unlike traditional emergency locator transmitters (ELTs), our proposed beacon addresses the unique needs of UAVs by reducing size, weight, and cost, while maximizing range and power efficiency. The device utilizes a global system for mobile (GSM)-based communication module to transmit location data via short message service (SMS), eliminating the need for specialized receivers and expanding the operational range even in obstacle-rich environments. Additionally, a built-in global navigation satellite system (GNSS) receiver provides precise coordinates, activated only upon impact detection through an accelerometer, thereby saving power during normal operations. Experimental tests confirm the extended range, high precision, and compatibility of the prototype with common mobile networks. Cost-effective and easy to use, this beacon improves UAV recovery efforts by providing reliable localization data to users in real time, thus safeguarding the UAV investment. Full article

Constructing an ecological security pattern in ecologically fragile areas is crucial for maintaining regional ecological stability. This study focuses on the Kunlun Mountain region, identifying ecological sources based on habitat suitability assessments and ecosystem services. An ecological resistance evaluation index system is constructed, considering topography, land use, and habitat quality. The minimum cumulative resistance model is then applied to identify ecological corridors, with areas exhibiting higher ecological currents designated as ecological nodes. By integrating the spatial characteristics of ecosystem services, an ecological security pattern is established. The results are as follows: (1) The ecological source area covers approximately 11.30% of the study area. (2) The cumulative length of ecological corridors is 21,111 km, mainly distributed along valleys, gentle slopes, and oasis areas. (3) The areas of ecological nodes and ecological barriers are 126.75 km² and 46.75 km², respectively. Ecological nodes are mainly distributed on both sides of the Kunlun Mountains, while ecological barriers are primarily located in the central mountainous area of the Kunlun Mountains. (4) The findings recommend establishing an ecological security pattern consisting of “2 horizontal and 4 vertical corridors and 5 zones” to ensure the ecological security of the Kunlun Mountains. The integration of ecological corridors and ecosystem services in constructing a regional ecological security pattern provides valuable decision-making tools for protecting ecosystems and species in fragile areas. Full article

The field of real estate valuations is multivariate in nature. Each property has different intrinsic attributes that have a bearing on its final value: location, use, purpose, access, the services available to it, etc. The appraiser analyzes all these factors and the current status of other similar properties on the market (comparable assets or units of comparison) subjectively, with no applicable rules or metrics, to obtain the value of the property in question. To model this context of subjectivity, this paper proposes the use of a fuzzy system. The inputs to the fuzzy system designed are the variables considered by the appraiser, and the output is the adjustment coefficient to be applied to the price of each comparable asset to obtain the price of the property to be appraised. To design this model, data have been extracted from actual appraisals conducted by three professional appraisers in the urban center of Santa Cruz de Tenerife (Canary Islands, Spain). The fuzzy system is a decision-helping tool in the real estate sector: appraisers can use it to select the most suitable comparables and to automatically obtain the adjustment coefficients, freeing them from the arduous task of calculating them manually based on the multiple parameters to consider. Finally, an evaluation is presented that demonstrates its applicability. Full article

Urbanization exerts significant stress on urban river ecosystems, leading to their degradation and the loss of environmental functions. Several studies have focused on restoring these urban rivers to enhance environmental quality and contribute to overall city well-being. However, such restoration efforts encounter economic, environmental, and social challenges. This study proposes a methodological framework to aid public managers in prioritizing areas for urban river restoration. The approach integrates the concept of environmental services with urban development opportunities to address these dual demands. Central to this framework is the introduction of the criticality index for watershed restoration (CIWR), which categorizes watershed areas based on environmental quality indicators, using river restoration as a guiding principle. Additionally, legally protected environmental areas were considered as opportunity layers. This study used geographic information systems (GIS) to manage and overlay datasets for a case study in the João Mendes Watershed in Niterói, southeast Brazil, which illustrated the use of the CIWR. By intersecting this framework with the opportunity layers, priority locations were identified for potential river restoration management practices. The results indicated that the overall criticality condition of this watershed for river restoration is low. The study further discusses potential measures for river restoration in the identified priority areas, underscoring the importance of strategic planning in urban environmental management. The CIWR proved to be an easily applicable and replicable management decision tool for comparing watersheds and assessing deficient environmental services, with both numerical and spatial results. Its use, combined with the “opportunity” layer, enables public managers to define priority areas for river restoration practices based on clear and objective criteria. Full article

New healthcare management strategies aim to reduce in-person visits and patient hospitalization while ensuring patient safety. These strategies optimize resources, alleviate pressure on healthcare services, and decrease travel and mobility within healthcare environments. This research analyzes the environmental impact and sustainability associated with transportation and mobility in traditional hospital-based healthcare services, which have been relocated to bring healthcare closer to patients. This retrospective study utilizes data from two hospital centers spanning the years 2021 to 2023. The objective is to highlight the environmental benefits and sustainability of providing healthcare in the patient’s environment. The methodology employs life cycle analysis to compare three scenarios: traditional healthcare in hospitals, healthcare provided at the patient’s location through home hospitalization and medical consultations at nearby health centers, and healthcare professionals’ travel using electric vehicles. The results demonstrate that healthcare professionals traveling to the patient’s home or nearby health centers reduce environmental impact across all analyzed impact categories. Promoting home hospitalization, specialized consultations at local health centers, and primary care can effectively reduce unnecessary patient travel and minimize environmental impact, enhancing sustainability. Health policies should prioritize actions to reduce hospital visits, emphasizing prevention over disease treatment. Such practices would not only benefit patients but further promote sustainability and environmental protection. Full article

Background/Objectives: Many social and environmental factors contribute to the disproportionate burden of COVID-19 mortality. Access to healthcare services has not been thoroughly examined as a factor contributing to COVID-19 mortality. This study examines distance to ERs and ICUs, uninsurance rates, and county-level COVID-19 mortality rates. Methods: Using data from the American Hospital Association survey, we identified hospitals providing emergency and intensive care services. Hospital locations were geocoded, and straight-line distance was calculated from the population-weighted county centroid. The county proportion of uninsured residents came from the American Community Survey. Generalized linear regression models with a log-link were used to examine study factors and county COVID-19 mortality rates. Results: A total of 2640 (84.0%) U.S. counties or county-equivalents were included in this analysis. The median COVID-19 mortality rate was 240 deaths per 100,000. In adjusted models, increasing distance to ERs (IRR: 0.95; 95% CI: 0.92, 0.98) or ICUs (IRR: 0.61; 95% CI: 0.57, 0.65) was not significantly associated with increased COVID-19 mortality. The proportion of residents (IRR: 3.81; CI: 2.58, 5.62) uninsured was significantly associated with increased COVID-19 mortality rates. Conclusions: Being in close proximity to hospital-based healthcare services may not provide any significant benefit for COVID-19 mortality outcomes, considering that hospitals are largely located in more densely populated areas conducive to COVID-19 spread. Financial barriers may largely contribute to persons avoiding necessary COVID-19 care. To continue to combat COVID-19 and future pandemics, greater attention should be focused on eliminating financial barriers to receiving medically necessary care. Full article

Flash floods are a concerning social issue that affect urban areas all over the world. Flash floods can disrupt vital services, damage infrastructure, have socio-economic impacts on the earth’s surface, and significantly impact the community near the water body. Household and commercial damage, physical health issues from contaminated floodwater, mental health issues including post-traumatic stress disorder, and even fatalities are some of these common effects. Additionally, it is anticipated that climate change, continuous population growth, and urbanisation will increase flood events and flood risk exposure. Nature-based solutions (NbS) for flood management that lower flood risks include sustainable, economical methods that improve biodiversity, ecosystem resilience, and community well-being. This in-depth study analyses research and literature that previous researchers conducted related to flood management around ASEAN countries, as all these countries are closely located and share similarities in climate and temperature. This survey focuses on identifying the most suitable and effective NbS to overcome the problem and appropriate non-structural measures to support it in solving the flood problem in Malaysia. NbS provide a multi-benefit approach by improving ecosystem resilience, cutting costs, and offering co-benefits, including biodiversity conservation and better water quality, in contrast to conventional methods that put infrastructure before environmental sustainability. This survey also looks at the weaknesses in the existing flood management system and provides recommendations to overcome these problems. Additionally, this survey offers practical policy suggestions to help incorporate NbS into regional and national flood control frameworks, guaranteeing that the solutions are not only socially just but also ecologically sound. Full article