Search Results (568)

In light of urbanization, climate change, and the escalation of extreme weather events, flood management is becoming more and more important. Improving community resilience and reducing flood risks require prompt decision-making and effective communication. This study investigates how flood management systems can incorporate Large Language Models (LLMs), especially those that use Retrieval-Augmented Generation (RAG) architectures. We suggest a multimodal framework that uses a Flood Knowledge Graph to aggregate data from various sources, such as social media, hydrological, and meteorological inputs. Although LLMs have the potential to be transformative, we also address important drawbacks like governance issues, hallucination risks, and a lack of physical modeling capabilities. When compared to text-only LLMs, the RAG system significantly improves the reliability of flood-related decision support by reducing factual inconsistency rates by more than 75%. Our suggested architecture includes expert validation and security layers to guarantee dependable, useful results, like flood-constrained evacuation route planning. In areas that are vulnerable to flooding, this strategy seeks to strengthen warning systems, enhance information sharing, and build resilient communities. Full article

Forest fires have become increasingly frequent and severe due to climate change and intensified human activities, posing critical challenges to ecological security and emergency management. Despite the availability of abundant environmental, spatial, and operational data, these resources remain fragmented and heterogeneous, limiting the efficiency and accuracy of fire prediction and response. To address this challenge, this study proposes a Semantic Digital Twin-Driven Framework for integrating multi-source data and supporting forest fire prediction and response. The framework constructs a multi-ontology network that combines the Semantic Sensor Network (SSN) and Sensor, Observation, Sample, and Actuator (SOSA) ontologies for sensor and observation data, the GeoSPARQL ontology for geospatial representation, and two domain-specific ontologies for fire prevention and emergency response. Through systematic data mapping, instantiation, and rule-based reasoning, heterogeneous information is transformed into an interconnected knowledge graph. The framework supports both semantic querying (SPARQL) and rule-based reasoning (SWRL) to enable early risk alerts, resource allocation suggestions, and knowledge-based decision support. A case study in Sichuan Province demonstrates the framework’s effectiveness in integrating historical and live data streams, achieving consistent reasoning outcomes aligned with expert assessments, and improving decision timeliness by enhancing data interoperability and inference efficiency. This research contributes a foundational step toward building intelligent, interoperable, and reasoning-enabled digital forest systems for sustainable fire management and ecological resilience. Full article

Nigeria’s aquaculture sector, which has been dominated by the production of African catfish (Clarias gariepinus), has held considerable potential to improve national food security, support livelihoods, and contribute to economic growth. Although Nigeria has been ranked among the world’s leading producers of farmed catfish, a persistent fish supply deficit that exceeds 2.5 million metric tons annually has been reported. This gap has been sustained by factors such as low productivity, genetic decline, inadequate hatchery systems, and limited export competitiveness. A comprehensive perspective is presented in this review, in which findings from recent researches, field surveys, and stakeholder consultations have been synthesized. The dominance of hybrid species such as Heteroclarias, which has been driven by consumer demand due to fast growth and large body size, is highlighted. Additionally, ecological and genetic concerns resulting from unregulated breeding are emphasized. Major systemic constraints, which include poor broodstock management, weak hatchery infrastructure, low technical capacity, and poor supply chain governance, have also been identified. A strategic approach involves modernizing fish breeding programs by developing a robust and active Fish Breeding Community of Practice (FCoP), enhancing physical infrastructure, improving data collection and management, standardizing germplasm exchange procedures, and increasing the number and capacity of fish breeders and technicians in breeding programs. Identifying traits preferred by farmers and end-users ensures that fish breeding is demand-driven and inclusive. Building capacity in genomic resources to implement an accurate predictive platform for performance assessment will significantly shorten the breeding cycle and increase the rate of genetic progress. This will be complemented by the adoption of modern aquaculture technologies, such as recirculating aquaculture systems, and the development of institutional frameworks for production, certification, and traceability schemes. Capacity development, which should be promoted through collaboration among academic institutions, industry actors, and government agencies, has been recommended. The alignment of aquaculture expansion with environmental sustainability, improved biosecurity, and habitat protection has been considered critical. By outlining strategies for innovation, investment, and policy reform, this review provides a roadmap through which Nigeria’s catfish industry can be transformed into a globally competitive and sustainable sector. Full article

With the rapid deployment of intelligent transportation systems (ITS), the Internet of Vehicles (IoV) has become an increasingly vital component in the development of smart cities. However, the openness of IoV also gives rise to critical issues such as message security and identity privacy. Consequently, addressing message authentication in the IoV environment is a fundamental requirement for ensuring its sustainable and stable evolution. Firstly, this paper proposes an adaptive traffic authentication strategy (ATAS) By integrating traffic flow dynamics evaluation, traffic status scoring, time sensitivity assessment, and comprehensive strategy decision-making, the scheme achieves an effective balance between authentication efficiency and security in IoV scenarios. Secondly, to tackle the high overhead and security issues caused by multiple message transmissions in large-scale IoV application scenarios, this paper proposes a secure message transmission and authentication method based on the cloud-edge-client collaborative architecture. Leveraging aggregate message authentication code (AMAC) technology, this method validates both the authenticity and integrity of messages, effectively reducing communication overhead while maintaining reliable authenticated transmission. Finally, this paper builds an IoV co-simulation experimental environment using the SUMO 1.19.0, OMNeT++ 6.0.3, and Veins 5.0.0 software platforms. It simulates the interactive authentication process among vehicles, Road Side Units (RSUs), and the cloud platform, as well as the effects of traffic response strategies under different scenarios. The results demonstrate the potential of IoV authentication technology in improving traffic management efficiency, optimizing road resource utilization, and enhancing traffic safety, providing strong support for the secure communication and efficient management of IoV. Full article

The escalating challenges of climate change, soil degradation, and the need to ensure global food security are driving the transition towards more sustainable agricultural practices. Biostimulants, a diverse category of substances and microorganisms, have emerged as promising tools to enhance crop resilience, improve nutrient use efficiency (NUE), and support sustainable intensification. However, their widespread adoption is hampered by significant variability in efficacy and a lack of consensus on their optimal use. This comprehensive review synthesizes current scientific knowledge to critically evaluate the performance of biostimulants within sustainable agricultural systems. It aims to move beyond isolated case studies to provide a holistic analysis of their modes of action, efficacy under stress, and interactions with the environment. The analysis confirms that biostimulant efficacy is inherently context-dependent, governed by a complex interplay of biological, environmental, and management factors. Performance variability is explained by four core principles: the Limiting Factor Principle, the Biological Competition Axiom, the Stress Gradient Hypothesis, and the Formulation and Viability Imperative. A significant disconnect exists between promising controlled-environment studies and variable field results, highlighting the danger of extrapolating data without accounting for real-world agroecosystem complexity. Biostimulants are not universal solutions but are sophisticated tools whose value is realized through context-specific application. Their successful integration requires a precision-based approach aligned with specific agronomic challenges. We recommend that growers adopt diagnostic tools and on-farm trials, while producers must provide transparent multi-location field data and invest in advanced formulations. Future research must prioritize field validation, mechanistic studies using omics tools, and the development of crop-specific protocols and industry-wide standards to fully unlock the potential of biostimulants for building resilient and productive agricultural systems. Full article

U-Space, the European Union’s legal framework for enabling drone traffic in low altitude, has implications extending beyond airspace management, particularly on the sustainable development of urban areas. This article presents a case study involving regional and local level representatives, examining anticipated concerns and strategic interests, as well as managing requirements in urban U-Space planning. Following a three-stage capacity building process conducted in the German federal state of Hamburg, the results specify ambitions for enhancing economic attractiveness coupled with locally embedded visions for improved public service provision. Instruments that have shown apposite in the given setting to address concerns surrounding public order and security, as well as the impairment of area functions, are presented. The challenges of implementing U-Space in alignment with societal expectations are outlined. Based on the discussion of these findings, recommendations for local-level capacity-building policy and the multi-level governance of U-Space are derived. Full article

The Yangtze River fishing ban policy is a central measure in China’s watershed governance, and the adaptability of its policy tools and collaborative mechanisms directly influences the sustainability and effectiveness of basin management. This study systematically examines the evolution of policy themes, the characteristics of policy tool combinations, and their alignment with intergovernmental collaborative governance needs, drawing on 120 central government policy texts issued between 2002 and 2024. Using frequency analysis and policy tool coding, the findings reveal that (1) policy themes have shifted from fishery resource control to comprehensive ecological protection and, more recently, to integrated watershed management, thereby driving progressively higher demands for intergovernmental collaboration. (2) The policy tool structure has long been dominated by environmental tools, supplemented by supply-side tools, while demand-side tools remain underdeveloped. Imbalances persist, such as excessive emphasis on resource inputs over capacity building in supply-side tools, rigid constraints with limited flexibility in environmental tools, and a reliance on publicity while underutilizing market incentives in demand-side tools. (3) Tool combinations have adapted to changing collaboration needs, evolving from rigid constraints and fiscal subsidies to institutional frameworks and cross-regional cooperation, ultimately forming a governance model characterized by systemic guarantees and diversified collaboration. Based on these findings, this study recommends strengthening long-term governance mechanisms, improving cross-regional collaborative structures, authorizing local governments to design context-specific implementation details, enhancing fishermen’s livelihood security and social development, expanding public participation and oversight, and exploring market mechanisms for realizing ecological product value. These measures aim to advance collaborative governance in the Yangtze River Basin and foster a balanced integration of ecological protection and social development. Full article

Amid growing economic uncertainty and rising corporate default risks, effective legal reforms are essential for financial stability and sustainable business practices. This study examines the impact of China’s security interest system reform on corporate credit risk, highlighting its implications for corporate social responsibility (CSR) and sustainable development. Using a Difference-in-Differences approach and data from Chinese listed firms, the results show that the reform significantly reduces credit risk, particularly for asset-light, risk-averse, and growth-stage enterprises. Lower credit risk alleviates financing constraints, enabling firms to allocate more resources to Environmental, Social, and Governance (ESG) activities and long-term sustainability initiatives. The findings reveal that legal reforms in secured transactions not only serve as risk management tools but also function as institutional mechanisms that foster CSR engagement and contribute to building a sustainable economic cycle. This research fills a gap in linking legal system reform, credit risk mitigation, and CSR, offering practical insights for future policy design in sustainable finance and green innovation. Full article

In the context of the deep restructuring of the global industrial chain and the concurrent pursuit of green and sustainable development, enterprises need to secure long-term, reliable supply chain competitiveness. The burgeoning wave of digitalization is simultaneously reshaping industry landscapes. Based on a sample of the Chinese manufacturing sector, this study explores how supply chain digital transformation enhances commercial credit financing performance by improving corporate adjustment capability. The research finds that supply chain digital transformation strengthens a firm’s commercial credit financing capacity through a dual-core mediating mechanism of corporate adjustment capability: (1) enhancing the adjustment capability of operational management, which mitigates the negative impact of cost stickiness on financing; (2) enhancing the adjustment capability of organizational management, which amplifies the positive effect of organizational resilience on financing. The study further reveals key moderating effects: (1) External Governance: Strong ESG performance strengthens the financing effect of digitalization by building reputational capital. High industry competition strengthens the financing effect by prompting firms to optimize operational efficiency. (2) Internal Endowments: Environmental risk aversion stemming from a firm’s polluting nature significantly weakens the credit supply effect of digitalization. The market-oriented foundation underpinning private ownership effectively activates the credit supply effect of digitalization. This study constructs an integrated pathway model of “Digital Transformation–Corporate Adjustment Capability–Supply Chain Credit Access.” It provides a research perspective for understanding how digitalization reshapes the logic of supply chain finance and offers empirical evidence for pathways empowering enterprises through digital transformation. Full article

As smart campus construction continues to advance, traditional safety monitoring and environmental sensing systems are increasingly showing limitations in sensitivity, anti-interference capability, and deployment flexibility. Optical fiber sensing (OFS) technology, with its advantages of high sensitivity, passive operation, immunity to electromagnetic interference, and long-distance distributed sensing, provides a novel solution for real-time monitoring and early warning of critical campus infrastructure. This review systematically examines representative applications of OFS technology in smart campus scenarios, including structural health monitoring of academic buildings, laboratory environmental sensing, and intelligent campus security. By analyzing the technical characteristics of various types of optical fiber sensors, the paper explores emerging developments and future potential of OFS in supporting intelligent campus construction. Finally, the feasibility of building data acquisition, transmission, and visualization platforms based on OFS systems is discussed, highlighting their promising roles in campus safety operations, the integration of teaching and research, and intelligent equipment management. Full article

Generative Artificial Intelligence (GAI) is gaining increasing attention as a catalyst for advancing sustainability within project management for buildings and infrastructure. This paper systematically reviews 173 peer-reviewed publications, including 142 journal and conference papers, to examine the current research landscape. Bibliometric mapping and thematic synthesis reveal expanding applications of GAI in project planning, design optimization, risk management, and sustainability assessment, but adoption remains fragmented across regions and domains. This review identifies persistent challenges that constrain large-scale implementation, including data variability and interoperability gaps, high computational demand, limited regulatory alignment, and ethical and governance concerns, coupled with the absence of standardized evaluation metrics. In response, this paper outlines future research prospects through a structured agenda that emphasizes scalable and generalizable AI models, real-time integration with IoT and digital twins, explainable and secure AI systems, and policy-aligned governance frameworks. These priorities aim to strengthen environmental, social, and economic sustainability outcomes in the built environment. By clarifying current progress and knowledge gaps, this review supports both scholars and practitioners in strengthening the role of GAI in the built environment. Full article

In response to the changing international landscape and the risks associated with China’s supply chain security, conducting policy simulations on semiconductor supply chain security helps clarify the industry’s policies and governance strategies for semiconductor supply chain security in China. It also enables a better understanding of the current state and focus areas of China’s semiconductor supply chain security, which is of great significance for improving the security levels of semiconductor supply chains across provinces and cities and for constructing a secure, efficient, and autonomous semiconductor supply chain system. Firstly, this paper reviews the current research on semiconductor supply chains, supply chain security, and industrial policies. Secondly, based on the industrial policies for semiconductor supply chain security, an evolutionary game model is constructed, involving government departments, chain owner enterprises, and upstream and downstream small and medium-sized enterprises (SMEs) within the supply chain. Finally, the MATLAB R2016b system simulation method is employed to conduct a policy simulation analysis of China’s semiconductor supply chain security and further analyze the industrial policies related to semiconductor supply chain security. The results show that: (1) Supply chain security depends on multi-agent collaborative governance, with government leadership, and chain owner enterprises driving innovation in SMEs, improving digitalization levels, and ensuring supply chain autonomy and control. (2) Increasing government management revenue, raising the responsibility costs for chain owner enterprises, and reducing the innovation costs for SMEs can accelerate the achievement of the ideal governance state. Lastly, policy recommendations are proposed to build an autonomous and controllable supply chain system. Full article

Improving energy efficiency in buildings is critical for supporting sustainable growth in the construction sector. In this context, the implementation of passive solar solutions in the building envelope plays an important role. Trombe wall is a passive solar system that presents great potential for passive solar heating purposes. However, its performance can be enhanced when the Internet of Things is applied. This study employs a multi-domain smart system based on Matter-enabled IoT technology for maximizing Trombe wall functionality using appropriate 3D-printed ventilation grids. The system includes ESP32-C6 microcontrollers with temperature sensors and ventilation grids controlled by actuated servo motors. The system is automated with a Raspberry Pi 5 running Home Assistant OS with Matter Server. The integration of the Matter protocol provides end-to-end interoperability and secure communication, avoiding traditional systems based on MQTT. This work demonstrates the technical feasibility of implementing smart ventilation control for Trombe walls using a Matter-enabled infrastructure. The system proves to be capable of executing real-time vent management based on predefined temperature thresholds. This setup lays the foundation for scalable and interoperable thermal automation in passive solar systems, paving the way for future optimizations and addicional implementations, namely in order to improve indoor thermal comfort in smart and more efficient buildings. Full article

Purpose: The construction industry is now experiencing a thorough transformation through digital technologies, especially with building information modeling (BIM). Despite significant BIM advantages, most construction projects suffer from low BIM performance due to the fragmented BIM use mode. To facilitate lifecycle-integrated BIM implementation, this study demonstrates that introducing BIM lifecycle service providers (BLSPs) is feasible and offers significant improvements in terms of BIM benefits. Hence, this study proposes a customized framework to select BLSPs. Approach: This study utilized both qualitative and quantitative methods. It first adopted semi-structured interviews as part of the qualitative method to deduce the initial criteria for BLSPs’ selection. 30 interviews were conducted iteratively with managers proficient and experienced in selecting BLSPs, through which 25 initial criteria were identified. Then, as the basis of the applied quantitative method, a questionnaire survey was used to evaluate these criteria by determining the critical ones, identifying the latent factor groupings, and assigning criteria weights. Subsequently, an assessment framework was established. Finally, the study was in favor of eight construction projects, highlighting the practicality and validity of the framework. Findings: The results depicted that project BIM service capability is a primary factor for BLSPs’ selection. Within this factor, several specialized criteria need to be considered, such as “boundary spanning competence of the BIM manager” and “BIM service plans with lifecycle cognition.” Meanwhile, “past innovative BIM service practices” and “BIM research and development (R&D)” that originate in corporate innovation capacity were emphasized when selecting BLSPs. Furthermore, for holistic assessment and recognizing the peculiarities of digital BIM service, the study found that criteria like “Privacy and security” and “Backup system” are required, which demonstrate BIM service reliability. Originality/value: This study expands on the conventional partner selection frameworks in the construction sector and thus defines and validates a tailored one for BLSPs’ selection. Moreover, drawing such a reference solution from the framework, the study enables the selection of appropriate BLSPs for clients. Full article

The rapid expansion of the Internet of Things (IoT) demands scalable, efficient, and user-friendly gateway solutions that seamlessly connect resource-constrained edge devices to cloud services. Low-cost, widely available microcontrollers, such as the ESP32 and its ecosystem peers, offer integrated Wi-Fi/Bluetooth connectivity, low power consumption, and a mature developer toolchain at a bill of materials cost of only a few dollars. For smart-home deployments where budgets, energy consumption, and maintainability are critical, these characteristics make MCU-class gateways a pragmatic alternative to single-board computers, enabling always-on local control with minimal overhead. This paper presents the design and implementation of an embedded IoT gateway powered by the ESP32 microcontroller. By using lightweight communication protocols such as Message Queuing Telemetry Transport (MQTT) and REST APIs, the proposed architecture supports local control, distributed intelligence, and secure on-site data storage, all while minimizing dependence on cloud infrastructure. A real-world deployment in an educational building demonstrates the gateway’s capability to monitor energy consumption, execute control commands, and provide an intuitive web-based dashboard with minimal resource overhead. Experimental results confirm that the solution offers strong performance, with RAM usage ranging between 3.6% and 6.8% of available memory (approximately 8.92 KB to 16.9 KB). The initial loading of the single-page application (SPA) results in a temporary RAM spike to 52.4%, which later stabilizes at 50.8%. These findings highlight the ESP32’s ability to serve as a functional IoT gateway with minimal resource demands. Areas for future optimization include improved device discovery mechanisms and enhanced resource management to prolong device longevity. Overall, the gateway represents a cost-effective and vendor-agnostic platform for building resilient and scalable IoT ecosystems. Full article