Search Results (889)

Device-free localization and tracking (DFLT) has emerged as a promising technique for location-aware Internet-of-Things (IoT) applications. However, most existing DFLT systems based on narrowband sensing networks suffer from reduced accuracy in indoor environments due to the susceptibility of received signal strength (RSS) measurements to multipath interference. In this paper, we propose a real-time DFLT system leveraging ultra-wideband (UWB) sensors. The system estimates target-induced shadowing using two UWB RSS measurements, which are shown to be more resilient to multipath effects compared to their narrowband counterparts. To enable real-time tracking, we further design an efficient measurement protocol tailored for UWB networks. Field experiments conducted in both indoor and outdoor environments demonstrate that our UWB-based system significantly outperforms its traditional narrowband DFLT solutions in terms of accuracy and robustness. Full article

The accurate detection of tea buds in outdoor environments is crucial for the intelligent management of modern tea plantations. However, this task remains challenging due to the small size of tea buds and the limited computational capabilities of the edge devices commonly used in the field. Existing object detection models are typically burdened by high computational costs and parameter loads while often delivering suboptimal accuracy, thus limiting their practical deployment. To address these challenges, we propose TeaBudNet, a lightweight and robust detection framework tailored for small tea bud identification under outdoor conditions. Central to our approach is the introduction of Weight-FPN, an enhanced variant of the BiFPN designed to preserve fine-grained spatial information, thereby improving detection sensitivity to small targets. Additionally, we incorporate a novel P2 detection layer that integrates high-resolution shallow features, enhancing the network’s ability to capture detailed contour information critical for precise localization. To further optimize efficiency, we present a Group–Taylor pruning strategy, which leverages Taylor expansion to perform structured, non-global pruning. This strategy ensures a consistent layerwise evaluation while significantly reducing computational overhead. Extensive experiments on a self-built multi-category tea dataset demonstrate that TeaBudNet surpasses state-of-the-art models, achieving +5.0% gains in AP@50 while reducing parameters and computational cost by 50% and 3%, respectively. The framework has been successfully deployed on Huawei Atlas 200I DKA2 developer kits in real-world tea plantation settings, underscoring its practical value and scalability for accurate outdoor tea bud detection. Full article

Global warming, anthropogenic pressure, and urban expansion at the expense of green spaces are leading to an increase in the incidence of urban heat islands, creating discomfort and health issue for citizens. This present research aimed at quantifying the impact of nature-based solutions to support decision-making processes in sustainable energy action plans. A simple method is provided, linking applied thermodynamics to physics-informed modeling of urban built-up and green areas, high-resolution climate models at urban scale, greenery modeling, spatial georeferencing techniques for energy, and entropy exchanges evaluation in urban built-up areas, with and without vegetation. This allows the outdoor climate conditions and thermo-hygrometric well-being to improve, reducing the workload of cooling plant-systems in buildings and entropy flux to the environment. The finalization and post-processing of obtained results allows the definition of entropy footprints. The main findings show a decrease in greenery’s contribution for different scenarios, referring to a different climatological dataset, but an increase in entropy that becomes higher for the scenario with higher emissions. The comparison between the entropy footprint values for different urban zones can be a useful support to public administrations, stakeholders, and local governments for planning proactive resilient cities and anthropogenic impact reduction and climate change mitigation. Full article

This study develops a comprehensive evaluation framework for urban street alfresco spaces by integrating the Analytic Hierarchy Process (AHP) and Entropy Weight Method. Daxue Road in Shanghai is selected as a representative case to analyze key factors influencing urban street alfresco spaces, which refer to commercially utilized outdoor extensions of building facades along streets, typically in the form of semi-open, publicly accessible areas used for dining, vending, seating, or temporary retail activities. These spaces are typically operated by adjacent businesses or regulated by local policies, and they integrate pedestrian circulation, commercial vibrancy, and spatial adaptability. They serve as critical urban interfaces that foster street-level vibrancy, social interaction, and public life. The evaluation system covers five dimensions: Cognizability, Accessibility, Participation, Emotional Design, and Spatial Diversity. The methodological innovation lies in integrating subjective weights derived from AHP with objective weights obtained through entropy calculations, which enhances the scientific rigor and neutrality of the evaluation. The results show that traffic safety (weight = 0.0644) and locational attributes of streets (weight = 0.0574) are the most influential factors affecting user perception. Compared to previous studies that often prioritize visual aesthetics or commercial density, this study underscores the significance of traffic-related factors, indicating a shift in user preferences in high-density urban environments. The findings provide practical guidance for urban design and policy to improve the quality, safety, and vitality of street-level public spaces in high-density cities. This research contributes to the theoretical foundation for sustainable and human-oriented street regeneration. Full article

Temporary architecture, as an expression of the concept of impermanence, offers adaptable and time-sensitive spatial interventions that promote community engagement and encourage experimentation within the urban environment. Beyond its physical and functional qualities, this architectural approach acts as a social mediator, fostering dialogue, networking, and the exchange of ideas between local communities and professionals, while contributing to the development of a socio-cultural common ground. This paper explores the Greenfeel Architecture wooden pavilion as a case study of small-scale architecture embedded within a landscape dedicated to urban agriculture and community-driven activities. The design process was guided by the need to balance functional requirements—providing shelter from the sun and rain and facilitating social interactions—with the protection of the existing vegetation and the enhancement of local biodiversity, with particular emphasis on supporting bee populations. In line with sustainable construction principles, the pavilion was built through the reuse of recovered materials, including used bricks for pavement, wooden slabs for the facade and roof, and several structural components sourced from previous building projects. Since its completion, the pavilion has acted as an urban acupuncture point within the surrounding area and has become a host for various outdoor activities and educational workshops aimed at diverse groups, including children, adults, professionals, and laypersons alike. The duality between the scale of the pavilion and the scale of its social, cultural, or ecological influence highlights the potential of temporary architecture to become a tool for both physical and socio-cultural sustainability in an urban environment. Full article

Fire detection primarily relies on sensors such as smoke detectors, heat detectors, and flame detectors. However, due to cost constraints, it is impractical to deploy such a large number of sensors for fire detection in outdoor gardens and landscapes. To address this challenge and aiming to enhance fire detection accuracy in gardens while achieving lightweight design, this paper proposes an improved symmetry SSS-YOLOv8 model for lightweight fire detection in garden video surveillance. Firstly, the SPDConv layer from ShuffleNetV2 is used to preserve flame or smoke information, combined with the Conv_Maxpool layer to reduce computational complexity. Subsequently, the SE module is introduced into the backbone feature extraction network to enhance features specific to fire and smoke. ShuffleNetV2 and the SE module are configured into a symmetric local network structure to enhance the extraction of flame or smoke features. Finally, WIoU is introduced as the bounding box regression loss function to further ensure the detection performance of the symmetry SSS-YOLOv8 model. Experimental results demonstrate that the improved symmetry SSS-YOLOv8 model achieves precision and recall rates for garden flame and smoke detection both exceeding 0.70. Compared to the YOLOv8n model, it exhibits a 2.1 percentage point increase in mAP, while its parameter is only 1.99 M, reduced to 65.7% of the original model. The proposed model demonstrates superior detection accuracy for garden fires compared to other YOLO series models of the same type, as well as different types of SSD and Faster R-CNN models. Full article

Three-dimensional environment reconstruction refers to the creation of mathematical models of three-dimensional objects suitable for computer representation and processing. This paper proposes a novel 3D environment reconstruction approach that addresses the field-of-view limitations commonly faced by LiDAR-based systems. A rotary-driven LiDAR mechanism is designed to enable uniform and seamless full-field-of-view scanning, thereby overcoming blind spots in traditional setups. To complement the hardware, a multi-sensor fusion framework—LV-SLAM (LiDAR-Visual Simultaneous Localization and Mapping)—is introduced. The framework consists of two key modules: multi-threaded feature registration and a two-phase loop closure detection mechanism, both designed to enhance the system’s accuracy and robustness. Extensive experiments on the KITTI benchmark demonstrate that LV-SLAM outperforms state-of-the-art methods including LOAM, LeGO-LOAM, and FAST-LIO2. Our method reduces the average absolute trajectory error (ATE) from 6.90 m (LOAM) to 2.48 m, and achieves lower relative pose error (RPE), indicating improved global consistency and reduced drift. We further validate the system in real-world indoor and outdoor environments. Compared with fixed-angle scans, the rotary LiDAR mechanism produces more complete reconstructions with fewer occlusions. Geometric accuracy evaluation shows that the root mean square error between reconstructed and actual building dimensions remains below 5 cm. The proposed system offers a robust and accurate solution for high-fidelity 3D reconstruction, particularly suitable for GNSS-denied and structurally complex environments. Full article

Most research on domestic dog (Canis familiaris) behavior has focused on pets with restricted movement. However, free-ranging dogs exist in diverse cultural contexts globally, and their interactions with humans are less understood. Tourists can facilitate unrestricted dog movement into wilderness areas, where they may negatively impact wildlife. This study investigated which stimuli—namely, voice, touch, or food—along with inherent factors (age, sex, sociability) motivate free-ranging dogs to follow a human stranger. We measured the distance (up to 600 m) of 129 free-ranging owned and stray dogs from three villages in southern Chile as they followed an experimenter who presented them one of the above stimuli or none (control). To evaluate the effect of dog sociability (i.e., positive versus stress-related or passive behaviors), we performed a 30 s socialization test (standing near the dog without interacting) before presenting a 10 s stimulus twice. We also tracked whether the dog was in the company of other dogs. Each focus dog was video-recorded and tested up to three times over five days. Generalized linear mixed-effects models revealed that the food stimulus significantly influenced dogs’ motivation to follow a stranger, as well as a high proportion of sociable behaviors directed towards humans and the company of other dogs present during the experiment. Juveniles tended to follow a stranger more than adults or seniors, but no effects were found for the dog’s sex, whether an owner was present, the repetition of trials, the location where the study was performed, or for individuals as a random variable. This research highlights that sociability as an inherent factor shapes dog–stranger interactions in free-ranging dogs when food is given. In the context of wildlife conservation, we recommend that managers promote awareness among local communities and tourists to avoid feeding dogs, especially in the context of outdoor activities close to wilderness. Full article

This study investigated the nuanced influence of urban morphology on the thermal performance of nine mass housing blocks (21–26, 28–30) in New Belgrade’s Central Zone. These blocks, showcasing diverse structures, provided a robust basis for evaluating the design parameters. ENVI-met simulations were used to assess two scenarios: an “asphalt-only” environment, isolating the urban structure’s impact, and a “real-world” scenario, including green infrastructure (GI). Overall, the findings emphasize that while GI offers mitigation, the inherent urban built structure fundamentally determines thermal outcomes. An urban block’s thermal performance, it turns out, is a complex interplay between morphological factors and local climate. Crucially, simple metrics like Green Area Percentage (GAP) and Building Coverage Ratio (BCR) proved unreliable predictors of thermal performance. This highlights the critical need for urban planning regulations to evolve beyond basic surface indicators and embrace sophisticated, context-sensitive design principles for effective heat mitigation. Optimal performance arises from morphologies that actively manage heat accumulation and facilitate its dissipation, a characteristic exemplified by Block 22’s integrated design. However, even the best-performing Block 22 remains warmer compared to denser central areas, suggesting that urban densification can be a strategy for heat mitigation. Given New Belgrade’s blocks are protected heritage, targeted GI reinforcements remain the only viable approach for improving the outdoor thermal comfort. Full article

This study investigates the effectiveness of passive design in low-rise residential buildings located in arid desert climates, using the Dubai Solar Decathlon Middle East (SDME) competition as a case study. This full-scale experiment offers a unique opportunity to evaluate design solutions under controlled, realistic conditions; prescriptive, modeled performance; and monitored performance assessments. The prescriptive assessment reviews geometry, orientation, envelope thermal properties, and shading. Most houses adopt compact forms, with envelope-to-volume and envelope-to-floor area ratios averaging 1 and 3.7, respectively, and window-to-wall ratios of approximately 17%, favoring north-facing openings to optimize daylight while reducing heat gain. Shading is strategically applied, horizontal on south façades and vertical on east and west. The thermal properties significantly exceed the local code requirements, with wall performance up to 80% better than that mandated. The modeled assessment uses Building Energy Models (BEMs) to simulate the impact of prescriptive measures on energy performance. Three variations are applied: assigning minimum local code requirements to all the houses to isolate the geometry (baseline); removing shading; and applying actual envelope properties. Geometry alone accounts for up to 60% of the variation in cooling intensity; shading reduces loads by 6.5%, and enhanced envelopes lower demand by 14%. The monitored assessment uses contest-period data. Indoor temperatures remain stable (22–25 °C) despite outdoor fluctuations. Energy use confirms that houses with good designs and airtightness have lower cooling loads. Airtightness varies widely (avg. 14.5 m³/h/m²), with some well-designed houses underperforming due to construction flaws. These findings highlight the critical role of passive design as the first layer for improving the energy performance of the built environment and advancing toward net-zero targets, specifically in arid desert climates. Full article

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

The intensifying global demand for sustainable and nutrient-dense food sources necessitates the exploration of underutilized local resources. Arthrospira platensis var. toliarensis, a cyanobacterium endemic to Madagascar, was evaluated for its nutritional, functional, and environmental potential under small-scale, low-input outdoor cultivation. The study assessed growth kinetics, physicochemical parameters, and composition during two contrasting seasons. Biomass increased 7.5-fold in 10 days, reaching a productivity of 7.8 ± 0.58 g/m²/day and a protein yield of 4.68 ± 0.35 g/m²/day. The hot-season harvest showed significantly higher protein content (65.1% vs. 44.6%), enriched in essential amino acids. On a dry matter basis, mineral profiling revealed high levels of sodium (2140 ± 35.4 mg/100 g), potassium (1530 ± 21.8 mg/100 g), calcium (968 ± 15.1 mg/100 g), phosphorus (815 ± 13.2 mg/100 g), magnesium (389.28 ± 6.4 mg/100 g), and iron (235 ± 9.1 mg/100 g), underscoring its value as a micronutrient-rich supplement. The hydroethanolic extract had the highest polyphenol content (4.67 g GAE/100 g of dry extract), while the hexanic extract exhibited the strongest antioxidant capacity (IC₅₀ = 101.03 ± 1.37 µg/mL), indicating fat-soluble antioxidants. Aflatoxin levels (B1, B2, G1, and G2) remained below EU safety thresholds. Compared to soy and beef, this strain showed superior protein productivity and water-use efficiency. These findings confirm A. platensis var. toliarensis as a promising, ecologically sound alternative for improving food and nutrition security, and its local production can offer substantial benefits to smallholder livelihoods. Full article

Urban residential design influences local microclimates and human thermal comfort. This study combines empirical microclimate data with remotely sensed data on tree canopy cover, housing lot size, surface permeability, and roof colour to examine thermal differences between three newly built and three established residential suburbs in Western Sydney, Australia. Established areas featured larger housing lots and mature street trees, while newly developed suburbs had smaller lots and limited vegetation cover. Microclimate data were collected during summer 2021 under both heatwave and non-heatwave conditions in full sun, measuring air temperature, relative humidity, wind speed, and wet-bulb globe temperature (WBGT) as an index of heat stress. Daily maximum air temperatures reached 42.7 °C in new suburbs, compared to 39.3 °C in established ones (p < 0.001). WBGT levels during heatwaves were in the “extreme caution” category in new suburbs, while remaining in the “caution” range in established ones. These findings highlight the benefits of larger green spaces, permeable surfaces, and lighter roof colours in the context of urban heat exposure. Maintaining mature trees and avoiding dark roofs can significantly reduce summer heat and improve outdoor thermal comfort across a range of conditions. Results of this work can inform bottom-up approaches to climate-responsive urban design where informed homeowners can influence development outcomes. Full article

In this paper, we investigate the target-approaching control problem for a discrete-time first-order vehicle system where the target area is modeled as a static circular region. In the absence of absolute bearing or position information, we propose a simple local controller that relies solely on range measurements to the target obtained at two consecutive sampling instants. Specifically, if the measured distance decreases between two successive samples, the vehicle maintains a constant velocity; otherwise, it rotates its velocity vector by an angle of $\pi /2$ in the clockwise direction. This control strategy guarantees convergence to the target region, ensuring that the vehicle’s velocity direction remains unchanged in the best-case scenario and is adjusted at most three times in the worst case. The effectiveness of the proposed method is theoretically established and further validated through outdoor experiments with a mobile vehicle. Full article

Accurate segmentation of point clouds into categories such as roads, buildings, and trees is critical for applications in 3D reconstruction and autonomous driving. However, large-scale point cloud segmentation encounters challenges such as uneven density distribution, inefficient sampling, and limited feature extraction capabilities. To address these issues, this paper proposes RT-Net, a novel framework that incorporates a density-based grid decimation algorithm for efficient preprocessing of outdoor point clouds. The proposed framework helps alleviate the problem of uneven density distribution and improves computational efficiency. RT-Net also introduces two modules: Local Attention Aggregation, which extracts local detailed features of points using an attention mechanism, enhancing the model’s recognition ability for small-sized objects; and Attention Residual, which integrates local details of point clouds with global features by an attention mechanism to improve the model’s generalization ability. Experimental results on the Toronto3D, Semantic3D, and SemanticKITTI datasets demonstrate the superiority of RT-Net for small-sized object segmentation, achieving state-of-the-art mean Intersection over Union (mIoU) scores of 86.79% on Toronto3D and 79.88% on Semantic3D. Full article