Search Results (374)

Rural regions face significant barriers to adopting IoT technologies, due to limited connectivity, energy constraints, and poor technical infrastructure. While urban environments benefit from advanced digital systems and cloud services, rural areas often lack the necessary conditions to deploy and evaluate secure and autonomous IoT solutions. To help overcome this gap, this paper presents the Smart Rural IoT Lab, a modular and reproducible testbed designed to replicate the deployment conditions in rural areas using open-source tools and affordable hardware. The laboratory integrates long-range and short-range communication technologies in six experimental scenarios, implementing protocols such as MQTT, HTTP, UDP, and CoAP. These scenarios simulate realistic rural use cases, including environmental monitoring, livestock tracking, infrastructure access control, and heritage site protection. Local data processing is achieved through containerized services like Node-RED, InfluxDB, MongoDB, and Grafana, ensuring complete autonomy, without dependence on cloud services. A key contribution of the laboratory is the generation of structured datasets from real network traffic captured with Tcpdump and preprocessed using Zeek. Unlike simulated datasets, the collected data reflect communication patterns generated from real devices. Although the current dataset only includes benign traffic, the platform is prepared for future incorporation of adversarial scenarios (spoofing, DoS) to support AI-based cybersecurity research. While experiments were conducted in an indoor controlled environment, the testbed architecture is portable and suitable for future outdoor deployment. The Smart Rural IoT Lab addresses a critical gap in current research infrastructure, providing a realistic and flexible foundation for developing secure, cloud-independent IoT solutions, contributing to the digital transformation of rural regions. Full article

Semantic change detection technology based on remote sensing data holds significant importance for urban and rural planning decisions and the monitoring of ground objects. However, simple convolutional networks are limited by the receptive field, cannot fully capture detailed semantic information, and cannot effectively perceive subtle changes and constrain edge information. Therefore, a dynamic graph reasoning network with layer-by-layer semantic decomposition for semantic change detection in remote sensing data is developed in response to these limitations. This network aims to understand and perceive subtle changes in the semantic content of remote sensing data from the image pixel level. On the one hand, low-level semantic information and cross-scale spatial local feature details are obtained by dividing subspaces and decomposing convolutional layers with significant kernel expansion. Semantic selection aggregation is used to enhance the characterization of global and contextual semantics. Meanwhile, the initial multi-scale local spatial semantics are screened and re-aggregated to improve the characterization of significant features. On the other hand, at the encoding stage, the weight-sharing approach is employed to align the positions of ground objects in the change area and generate more comprehensive encoding information. Meanwhile, the dynamic graph reasoning module is used to decode the encoded semantics layer by layer to investigate the hidden associations between pixels in the neighborhood. In addition, the edge constraint module is used to constrain boundary pixels and reduce semantic ambiguity. The weighted loss function supervises and optimizes each module separately to enable the network to acquire the optimal feature representation. Finally, experimental results on three open-source datasets, such as SECOND, HIUSD, and Landsat-SCD, show that the proposed method achieves good performance, with an SCD score reaching 35.65%, 98.33%, and 67.29%, respectively. Full article

Accurate estimation of available rooftop areas for PV power generation at the city scale is critical for sustainable energy planning and policy development. In this study, using publicly available high-resolution satellite imagery, rooftop solar energy potential in urban, rural, and industrial areas is estimated using deep learning models. In order to identify roof areas, high-resolution open-source images were manually labeled, and the training dataset was trained with DeepLabv3+ architecture. The developed model performed roof area detection with high accuracy. Model outputs are integrated with a user-friendly interface for economic analysis such as cost, profitability, and amortization period. This interface automatically detects roof regions in the bird’s-eye -view images uploaded by users, calculates the total roof area, and classifies according to the potential of the area. The system, which is applied in 81 provinces of Turkey, provides sustainable energy projections such as PV installed capacity, installation cost, annual energy production, energy sales revenue, and amortization period depending on the panel type and region selection. This integrated system consists of a deep learning model that can extract the rooftop area with high accuracy and a user interface that automatically calculates all parameters related to PV installation for energy users. The results show that the DeepLabv3+ architecture and the Adam optimization algorithm provide superior performance in roof area estimation with accuracy between 67.21% and 99.27% and loss rates between 0.6% and 0.025%. Tests on 100 different regions yielded a maximum roof estimation accuracy IoU of 84.84% and an average of 77.11%. In the economic analysis, the amortization period reaches the lowest value of 4.5 years in high-density roof regions where polycrystalline panels are used, while this period increases up to 7.8 years for thin-film panels. In conclusion, this study presents an interactive user interface integrated with a deep learning model capable of high-accuracy rooftop area detection, enabling the assessment of sustainable PV energy potential at the city scale and easy economic analysis. This approach is a valuable tool for planning and decision support systems in the integration of renewable energy sources. Full article

The Sustainable Development Goals seek to achieve universal, adequate, and equitable access to drinking water and sanitation by the year 2030. Yet, significant and persistent disparities in water and sanitation access exist, with rural and low-income households in Sub-Saharan Africa exhibiting some of the lowest levels. This paper uses household surveys from rural villages in Zambia’s Western Province to identify, highlight, and examine spatial barriers to improved water and sanitation. Most households included in the study area drink unimproved water, including surface water, and either use unimproved sanitation facilities or practice open defecation. Access to improved water sources and improved sanitation in the study area lags behind the rest of rural Zambia. Beyond the distance to urban areas that makes piped water and sanitation expensive, the location of these villages in the Barotse Floodplain necessitates seasonal migration, which creates barriers to universal access to improved water and sanitation. Full article

The European Union’s developing rural development plan places digital and precision agriculture at the centre of agricultural modernisation and economic development. This article examines how agricultural practices in rural EU regions are being influenced by smart technology, such as drones, IoT sensors, satellite-based research, and AI-driven platforms, through an analysis of recent data from sources across the European Union. This study applies a mixed-methods approach, combining quantitative analysis of strategic policy documents and EU databases, to evaluate the ways in which precision agriculture reduces input consumption, increases productivity, reduces labour shortages and rural area depopulation, and improves sustainability. By investing in infrastructure, developing communities for data exchange, and organising training for farmers, European policies such as the Strategic Plans of the Common Agricultural Policy (CAP), the SmartAgriHubs initiative, and the AgData program actively encourage the transition to digital agriculture. Cyprus is analysed as a case study to show how targeted investments and initiatives supported by the EU can help smaller countries, with limited natural resources, to realise the benefits of digital transformation in agriculture. A special focus is placed on how solutions adapted to agro-climatic and socioeconomic conditions can contribute to strengthening the competitiveness of the agricultural sector, attracting young people to get involved in this field and opening up new economic opportunities. The results of previous research indicate that digital agriculture not only improves productivity but also proves to be a strategic mechanism for attracting and retaining young people in rural areas. Thus, this work additionally contributes to the broader goal of the European Union—the development of smart, inclusive, and sustainable rural areas, in which digital technologies are not only seen as tools for efficiency but also as key means for integrated and long-term rural development. Full article

The timeshare is gradually becoming an essential global tourism operation model, especially in rural areas of China, where the leisure industry is developing rapidly. Meanwhile, the environmental issues of the rapidly growing timeshare-related building production have received widespread attention. The existing research on zero-carbon buildings considers carbon emissions as a constant value and cannot adapt to the impact of user changes during the operation phase. Constructing a low-carbon design applicable to timeshare is significant for controlling carbon emissions in the construction industry and responding to the environmental crisis. The practical carbon emissions of touristic apartments depend on the requirement changes in different customer clusters. The timeshare theory reflects the requirement change in different customer clusters based on the timeshare property ownership change. This paper focuses on a dynamic design strategy for zero-carbon building openings to reduce practical carbon emissions. Firstly, this research clarifies the primary customer clusters and conducts a touristic apartment unit model by timeshare property ownership. Then, this research clarifies the changes in customer requirements to analyze the spatial function changes in the operating phase. Finally, the study identifies six dynamic carbon emission indicators, such as the window-to-wall ratio, ventilation rate, and effective daylight area, and through passive design methods, provides 13 variable devices applied in the operating phase to control dynamic carbon emission indicators by customers. This paper also offers a flexible method to effectively decrease and accurately control carbon emissions by reducing the possible device utility. Full article

Rural landscapes play a key role in preserving ecological processes, cultural identity, and socio-economic well-being, yet these areas often face challenges such as land degradation, water scarcity, and an inadequate road network. A sustainable approach to rural landscape and tourism planning is essential for enhancing both environmental resilience and socio-economic vitality in areas facing degradation and global change. This study aims to develop and validate an integrated methodological workflow that combines Landscape Character Assessment (LCA), ECOVAST guidelines, SWOT analysis, and open-source GIS techniques, complemented by a bottom-up approach of spontaneous fruition mapped through Wikiloc heatmaps. The framework was applied to a case study in Paternò, Eastern Sicily, Italy—a territory distinguished by its key local values such as Calanchi formations, proximity to Mount Etna, and cultural heritage. Through this application, eight distinct Landscape Units (LUs) were delineated, and key strengths, weaknesses, opportunities, and threats for sustainable development were identified. Using open-access data and a survey-free protocol, this approach facilitates detailed landscape assessment without extensive fieldwork. The methodology is readily transferable to other rural Italian and Mediterranean contexts, providing practical guidance for researchers, planners, and stakeholders engaged in sustainable tourism development and landscape management. Full article

Rural road programs are essential for enhancing connectivity in remote areas, yet they frequently encounter schedule delays and budget overruns. This study explores the extent to which specific project characteristics influence these deviations in Colombian rural road contracts. A dataset comprising 229 projects was extracted from the national SECOP open-procurement platform and processed using the CRISP-DM protocol. Following the cleaning and coding of 14 project-level variables, statistical analyses were conducted using Spearman correlations, Kruskal–Wallis tests, and post-hoc Wilcoxon comparisons to identify significant bivariate relations I confirm I confirm I confirm hips. A Random Forest model was subsequently applied to determine the most influential multivariate predictors of cost and time deviations. In parallel, a directed content analysis of contract addenda reclassified 22 recorded deviation descriptors into ten internationally recognized categories of causality, enabling an integrated interpretation of both statistical and documentary evidence. The findings indicate that contract value, geographical region, and contractor configuration are significant determinants of cost and time performance. Additionally, project intensity and discrepancies between awarded and bid values emerged as key contributors to cost escalation. Scope changes and adverse weather conditions together accounted for 76% of all documented deviation triggers, underscoring the relevance of robust front-end planning and climate-risk considerations in rural infrastructure delivery. The findings provide information for stakeholders, policymakers, and professionals who aim to manage the risk of schedule and budget deviations in public infrastructure projects. Full article

To promote Chinese-style modernization, we must unremittingly promote the all-round revitalization of the countryside. Industry and agriculture are inseparable. The light industry is a traditionally dominant industry in China and is closely linked to the revitalization of rural areas. The coordination and resonance between the high-quality development of the light industry and rural revitalization is a significant area of research. This study developed models for coupling coordination degree and fuzzy set qualitative comparative analysis. It utilized data from 2012 to 2022 to empirically analyze the relationship between the high-quality development of China’s light industry and rural revitalization. Both of the systems had reached a condition of moderate coupling and showed dynamic interactive coupling. The degree of coupling coordination is affected by multiple variables, like economic development and scientific and technological innovation. There are two ways to promote the two to achieve a highly coupled and coordinated state. Therefore, this study opens up a novel methodological perspective and innovative path for research in related fields. Full article

Human migration has driven transformative shifts in agricultural systems by reshaping how communities relate biologically and culturally to the land. Migration demands the reconfiguration of preexisting human–environment relationships, a process central to agricultural history. Understanding adaptation strategies is essential for land studies as it highlights the impact of cultural persistence on agricultural practices and the potential challenges in integrating migrant rural knowledge with local ecological systems. In the late 19th century, a significant migration wave occurred from the Veneto region in northeastern Italy to southern Brazil, significantly impacting Brazilian agri-food production. This study investigates the biocultural adaptation strategies employed by the first Veneto communities in their new Brazilian environment. Data for this research were derived from the letters sent by Veneto migrants from Brazil in the initial wave of Italian migration (1877–1894). Utilising Critical Discourse Analysis and Sentiment Analysis of migrants’ letters, we explored the Veneto settlers’ perceptions of the Brazilian landscape, agri-food production practices, and culinary traditions. Our findings show that the Brazilian environment was perceived as predominantly negative, particularly in the wilderness areas. The initial Venetian migrant settlement exhibited no genuine biocultural adaptation strategies. Instead, they deliberately resisted Brazilian influences, striving to reproduce Veneto’s agricultural model verbatim in their new surroundings. The study also opens a new trajectory in historical ethnobiology, thus suggesting new potential applications of the analysis of migrants’ letters. Full article

Background/Objectives: The INTegRated InterveNtion of pSychogerIatric Care (INTRINSIC) network introduces an innovative model of psychogeriatric care, combining tertiary mental healthcare with primary care for older adults in low-resource settings in Greece via telemedicine. This study explores viewpoints of healthcare professionals on care delivery within the frames of old-age mental telehealth services in low-resource settings. Methods: All healthcare professionals, including 13 medical and 11 non-medical professionals from diverse healthcare units in urban, rural, and insular areas, participated in a semi-structured survey. Thematic analysis identified key insights. Results: Most participants (N = 19) highlighted the high usability of the INTRINSIC services and their high satisfaction for being members of the network (N = 17) was attributed to the collaborative delivery of integrated, specialized healthcare services in primary healthcare (N = 17). Further identified advantages of the services included the positive impact on timely care delivery (N = 6), cost effectiveness, and alleviation of hospital strain. Healthcare professionals valued the holistic approach of the INTRINSIC services to psychogeriatric care (N = 8) and their role in the improvement of it in communities in low-resource settings (N = 13). However, challenges were also reported, including the low openness and reluctance of service users (N = 7), difficulties in using the INTRINSIC digital platform (N = 5), and increased workload (N = 5). Conclusions: Despite these issues, the INTRINSIC services embody an innovative telehealth model for delivering high-quality, tertiary, mental, and cognitive healthcare services to older adults in underserved areas. Full article

Background/Objectives: The COVID-19 pandemic exposed critical vulnerabilities in healthcare systems, especially in ensuring continuity of care for patients with chronic diseases. Rehabilitation services, essential for recovery following SARS-CoV-2 infection, were among the most disrupted. This exploratory study aimed to assess Romanian patients’ perceptions of the accessibility and quality of post-COVID-19 rehabilitation services, focusing on individuals with chronic conditions. Methods: This exploratory cross-sectional study was conducted over a 12-month period in 2024. Data were collected from 76 adult patients diagnosed with at least one chronic condition (hypertension, diabetes mellitus, ischemic heart disease, cancer, or chronic obstructive pulmonary disease) and with confirmed prior SARS-CoV-2 infection. Most participants were recruited during outpatient specialty consultations, with a smaller number included from hospital settings, all located in Bucharest. A structured questionnaire was administered by the principal investigator after obtaining informed consent. Quantitative data were analyzed using non-parametric methods following confirmation of non-normal distribution via the Shapiro–Wilk test (p < 0.05). Satisfaction scores were reported as medians with interquartile ranges (IQR), and group comparisons were performed using the Mann–Whitney U test. A mixed-methods approach was employed, including thematic analysis of open-ended responses. Results: Patient satisfaction with rehabilitation services was consistently low. The median satisfaction scores [IQR] were accessibility 1.0 [0.0–2.0], quality of services 0.0 [0.0–4.0], staff empathy 0.0 [0.0–5.0], and perceived effectiveness 0.0 [0.0–5.0]. The median score for perceived difficulties in access was 1.0 [1.0–2.0], indicating widespread barriers. No statistically significant differences were observed between urban and rural participants or across chronic disease categories. Thematic analysis (n = 65) revealed key concerns including lack of publicly funded services, cost barriers, limited physician referral, service scarcity in rural areas, and demand for home-based rehabilitation options. Conclusions: Romanian patients with chronic illnesses and previous SARS-CoV-2 infection continue to face substantial barriers in accessing post-COVID-19 rehabilitation services. These findings highlight the need for more equitable and integrated recovery programs, especially for vulnerable populations in underserved settings. Full article

Rural plans incorporating regional identity are vital for fostering regional revitalization and offering viable policy alternatives. The need for a systematic approach that recognizes both the diversity and shared characteristics of rural areas has become increasingly clear. Although numerous studies have explored rural classification, research examining specific regional characteristics remains limited. Hence, this study aimed to establish a comprehensive standard for developing effective rural plans. To this end, a study was conducted to classify the characteristics of rural areas using topic modeling, which is a text-mining algorithm. An analysis of publications on rural revitalization projects in Korea over the past decade revealed five common factors of success themes across each region. The five success factors, “local cultural experience”, “environment and landscape utilization”, “community activation”, “regional infrastructure development”, and “local economic activation”, should be considered in rural areas with different characteristics when establishing rural plans and policies. This classification of success factors serves as the foundation for establishing rural plans and policies. By applying different weights to the five success factors according to the unique characteristics and conditions of each region, it would open a great number of possibilities to establish more precise and effective customized plans. Future research is required to provide more empirical and broadly applicable results based on the classification framework proposed in this study. Full article

The sustainable preservation of archeological heritage located in rural and coastal regions requires more than technical interventions; it necessitates the awareness and active participation of local communities. However, community involvement in heritage management in such areas remains limited. This study aims to analyze the levels of cultural heritage awareness, conservation tendencies, and tourism-related expectations among local residents and visitors in the Magarsus Archeological Area, located in the Karataş district on the eastern Mediterranean coast of Turkey. The study was conducted in three phases: a literature review, field observations, and a structured survey conducted between June and August 2022 with 510 participants (280 local residents and 230 domestic visitors from surrounding provinces). The data were analyzed using SPSS 25.0 through descriptive statistical methods, complemented by cross-tabulation and chi-square analysis to identify patterns across demographic variables. The survey results not only reflect general perceptions about heritage and tourism but also offer critical insights into how the rural and coastal character of the site shapes conservation attitudes and tourism behavior. The findings reveal nuanced perceptions, including strong symbolic appreciation for heritage and general openness to tourism, alongside concerns about cultural and environmental risks. While the local community prioritizes the potential for economic benefit, many participants also emphasized the importance of safeguarding local traditions, crafts, and culinary heritage. Nevertheless, concerns were expressed regarding the risks posed by uncontrolled tourism, including environmental degradation, erosion of cultural identity, and the commodification of heritage values. Based on these insights, the study introduces a governance approach built upon three interlinked pillars: community-based participation, environmental sustainability, and tourism practices aligned with cultural values. The proposed approach aims to support the inclusive and sustainable management of Magarsus and other rural and coastal archeological landscapes with similar characteristics. Full article

The Farmworker Family Health Program (FWFHP) annually supports 600 farmworkers in connectivity-challenged rural areas. Traditional paper-based data collection poses validity concerns, prompting a pilot of direct data entry using tablets and satellite internet to enhance efficiency. The purpose of this article is to describe, using the TIDier checklist, a real-time, live data-entry EMR intervention made possible by satellite internet. Utilizing a customized REDCap database, direct data entry occurred through tablets and satellite internet. Patients received a unique medical record number (MRN) at the mobile health clinic, with an interprofessional team providing care. Medication data, captured in REDCap before the mobile pharmacy visit, exhibited minimal defects at 6.9% of 319 prescriptions. To enhance data collection efficiency, strategies such as limiting free text variables and pre-selecting options were employed. Adequate infrastructure, including tablets with keyboards and barcode scanners, ensured seamless data capture. Wi-Fi extenders improved connectivity in open areas, while backup paper forms were crucial during connectivity disruptions. These practices contributed to enhanced data accuracy. Real-time data entry in connectivity-limited settings is viable. Replacing paper-based methods streamlines healthcare provision, allowing timely collection of occupational and environmental health metrics. The initiative stands as a scalable model for healthcare accessibility, addressing unique challenges in vulnerable communities. Full article