Search Results (51)

Integrating sensors with wireless communication capabilities into smart wireless sensing devices allows us to form a wireless sensing network. This network works in conjunction with monitors to display and control parameters at different locations or in the environment. By deploying a wireless sensing network, the system can interact with the user by sending notifications when necessary, based on the environmental conditions and user activities detected by the wireless sensors, and make corresponding adjustments to or control the environment. The advancement and widespread adoption of the internet have enabled the development of this technology. Wireless sensors are widely used in product positioning and environmental monitoring management, making the management of complex products more accurate. The Monitor and Control System (MCS), which combines network cameras and wireless sensors with neural network technology and fuzzy control systems, improves the existing positioning method and enhances positioning accuracy. Product management, which comprises comprehensive digital services and is facing serious staff shortages, has turned to digital payment to reduce labor costs. This experiment was simulated using Network Simulator 2 (NS2). In the sensing system part, the application of a ZigBee network and its status were explored, and interference was analyzed. Information on network interference simulations and their impact on normal services was compiled for network management purposes. Using NS2 network simulation, this study utilizes ZigBee with different neuron nodes and different training times to find the best network model, compares various queuing mechanisms and functions as a network interference intrusion detection system, and explores its node defense capabilities in cases of interference. Node Density: Node density is typically determined by the number of nodes in the simulation area and the size of the scene. Low Density: Sparse node distribution, prone to network partitioning, is suitable for testing latency-tolerant networks (DTNs) or route discovery capabilities. High Density: It entails dense node distribution, severe signal interference, and packet collisions. It is suitable for testing MAC layer collision prevention mechanisms (such as CSMA/CA) and the scalability of outing protocols. Configuration Method: the “set Dest” tool is used in a Tcl script to generate a mobile scene file, defining the number of nodes, range (X, Y), and time to be more significant in product management. Full article

Anthropogenic disturbance can reshape mammal communities through both long-term habitat modification and short-term direct human presence, yet these disturbance dimensions are often conflated. Using three consecutive years (2017–2019) of camera-trap data from two subtropical forest reserves in Chongqing, China (Jinfoshan and Jinyunshan), we evaluated the differential effects of human modification (HM) and human activity (HA) on mammal taxonomic diversity, functional diversity (MNTD and SES.MNTD), and diel activity patterns. HM and HA were not significantly correlated, indicating that they represent largely independent disturbance components in this system. Regression analyses showed that HM was significantly associated with reduced Shannon–Wiener diversity, while HA primarily influenced community evenness with a non-linear response (initial increase followed by decline at higher disturbance). In contrast, functional diversity metrics (MNTD and SES.MNTD) did not exhibit significant relationships with either HM or HA across the observed gradients, suggesting relative stability of trait dispersion at the community level. Activity analyses revealed guild-specific behavioral strategies: herbivores retained a predominantly crepuscular pattern but reduced activity during periods of high human presence, whereas omnivores displayed stronger temporal niche partitioning, becoming more nocturnal under higher disturbance intensity, particularly in Jinyunshan. Together, these results demonstrate that distinct disturbance types can affect mammal communities through different pathways and that integrating multidimensional diversity metrics with behavioral analyses can improve conservation planning in human-dominated landscapes. Full article

Automated optical inspection (AOI) technologies are widely used in PCB and semiconductor manufacturing to improve accuracy and reduce human error during quality inspection. While existing AOI systems can perform defect detection, they often rely on pre-defined camera positions and lack flexibility for interactive inspection, especially when the operator needs to visually verify solder pad conditions or examine specific layout regions. This study focuses on the front-end optical positioning and inspection stage of the AOI workflow, providing an automated mechanism to link digitally generated layout reports from EDA layout tools with real PCB inspection tasks. The proposed system operates on component-placement reports exported by EDA layout environments and uses them to automatically guide the camera to the corresponding PCB coordinates. Since PCB design reports may vary in format and structure across EDA tools, this study proposes a vision-based extraction approach that employs Hough transform-based region detection and a CNN-based digit recognizer to recover component coordinates from visually rendered design data. A dual-axis sliding platform is driven through a hierarchical control architecture, where coarse positioning is performed via TB6600 stepper control and Bluetooth-based communication, while fine alignment is achieved through a non-contact, gesture-based interface designed for clean-room operation. A high-resolution autofocus camera subsequently displays the magnified solder pads on a large screen for operator verification. Experimental results show that the proposed platform provides accurate, repeatable, and intuitive optical positioning, improving inspection efficiency while maintaining operator ergonomics and system modularity. Rather than replacing defect-classification AOI systems, this work complements them by serving as a positioning-assisted inspection module for interactive and semi-automated PCB quality evaluation. Full article

Display-field communication (DFC) is an imperceptible screen-to-camera technology that embeds and recovers data from the frequency domain of an image frame. Conventional DFC requires a reference frame for each data frame to estimate the channel, a method that, while reliable, is not bandwidth-efficient. Similarly, iterative DFC requires the transmission of pilot symbols for channel estimation. In this paper, we propose an implicit DFC (iDFC) scheme that eliminates the need for reference frames by estimating them using the first-order statistics of the received image. The system employs discrete Fourier-transform-based subcarrier mapping and adds data directly to the frequency coefficients of the host image. At the receiver, statistical estimation enables blind channel equalization without sacrificing the data rate. The simulation results show that iDFC achieves an achievable data rate (ADR) of up to $1.52\times {10}^5$ bps, a significant enhancement of approximately 97% and 11% compared to conventional and iterative DFC schemes, respectively. Furthermore, the analysis reveals a critical trade-off between communication robustness and visual imperceptibility; allocating 70% of signal power to the image maintains high visual quality but results in a symbol error rate (SER) floor of $1.5\times {10}^{-1}$, whereas allocating only 10% improves the SER to below ${10}^{-2}$ at the cost of visible artifacts. The findings also identify QPSK as the optimal modulation order that maximizes the data rate, showing that higher-order schemes can be detrimental due to system impairments such as signal clipping. The proposed iDFC scheme presents a more efficient and robust solution for high-capacity DFC applications by balancing the competing demands of data throughput and visual fidelity. Full article

Aiming at the real-time object detection requirements of the intelligent control system for laboratory item transportation in mobile embedded unmanned vehicles, this paper proposes a lightweight hybrid detection system based on the OpenMV vision module. The system adopts a two-stage detection mechanism: in long-distance scenarios (>32 cm), fast target positioning is achieved through red threshold segmentation based on the HSV(Hue, Saturation, Value) color space; when in close range (≤32 cm), it switches to a lightweight deep learning model for fine-grained recognition to reduce invalid computations. By integrating the MobileNetV2 backbone network with the FOMO (Fast Object Matching and Occlusion) object detection algorithm, the FOMO MobileNetV2 model is constructed, achieving an average classification accuracy of 94.1% on a self-built multi-dimensional dataset (including two variables of light intensity and object distance, with 820 samples), which is a 26.5% improvement over the baseline MobileNetV2. In terms of hardware, multiple functional components are integrated: OLED display, Bluetooth communication unit, ultrasonic sensor, OpenMV H7 Plus camera, and servo pan-tilt. Target tracking is realized through the PID control algorithm, and finally, the embedded terminal achieves a real-time processing performance of 55 fps. Experimental results show that the system can effectively and in real-time identify and track the detection targets set in the laboratory. The designed unmanned vehicle system provides a practical solution for the automated and low-power transportation of small items in the laboratory environment. Full article

This study investigates the use of Autonomous Sensing Infrastructure and Connected and Autonomous Vehicles (CAV) technologies to support infrastructure-to-vehicle (I2V) and infrastructure-to-everything (I2X) communications, including the alerting of drivers and pedestrians. It describes research findings in the following CAV functionalities: (1) Intersection-based object detection and tracking; (2) Basic Safety Message (BSM) generation and transmission; and (3) In-Vehicle BSM receipt and display, including handheld (smartphone) application BSM receipt and user presentation. The study summarizes the various software and hardware components used to create the I2V and I2X prototype solutions, which include open-source and commercial software as well as industry-standard transportation infrastructure hardware, e.g., Signal Controllers. Results from in-lab testing demonstrate effective object detection (e.g., pedestrians, bicycles) based on sample traffic camera video feeds as well as successful BSM message generation and receipt using the leveraged software and hardware components. The I2V and I2X solutions created as part of this research are scheduled to be deployed in a real-world intersection in coordination with state and local transportation agencies. Full article

Understanding the integration of newly recorded species into forest ecosystems is essential for evaluating their ecological impacts on native wildlife diversity. In this study, we examined the spatial and temporal niche dynamics of three sympatric squirrel species within the Labagoumen nature reserve, a temperate forest located in northern China. Particular emphasis was placed on the recently documented Eurasian red squirrel (Sciurus vulgaris) and its potential interactions with two native species: Père David’s rock squirrel (Sciurotamias davidianus) and the Siberian chipmunk (Tamias sibiricus). Using camera trapping data from 91 sites (2019–2024), we examined habitat use, activity rhythms, and niche overlap under contrasting levels of human disturbance. A total of 3419 independent effective photos of squirrels were recorded. S. vulgaris showed a broader spatial distribution and a higher relative abundance index (RAI) in the tourist area, while native species were more abundant in the non-tourist area. All three species showed similar annual activity patterns based on the monthly relative abundance index (MRAI), although native species exhibited an additional activity peak in June–July. Temporal niche overlap (C_ih) and the coefficient of overlap (Δ) between S. vulgaris and native species increased during the tourist season, suggesting synchronized activity under high disturbance. In contrast, lower overlap in the non-tourist season indicated stronger temporal partitioning. The daily activity rhythm of S. vulgaris remained stable, while native species displayed more variability, especially in non-tourist areas. S. vulgaris also exhibited a significantly broader spatial niche breadth (B_i), suggesting greater habitat exploitation and adaptability. Non-metric multidimensional scaling (NMDS) revealed no significant spatial segregation among the three species, indicating successful integration of S. vulgaris into the local community. Our findings emphasize the competitive advantage of S. vulgaris and demonstrate how human activities can restructure forest small mammal assemblages by altering spatiotemporal niche partitioning. We recommend long-term ecological monitoring to assess species diversity changes and guide adaptive conservation strategies. Full article

This case study aims to combine the advantage of the additive manufacturing of sensors with a mixed reality (MR) app, developed in a lab-scale workshop, to safely monitor and control the temperature of parts. Namely, the measurements were carried out in real time via a 3D-printed graphene–PLA nanocomposite sensor and communicated wirelessly using a low-power microcontroller with the IoT capability, and then transferred to the user display in the MR. In order to investigate the performance of the proposed computer-mediated reality, a user experience experiment (n = 8) was conducted. Statistical analysis results showed that the system leads to faster (>2.2 times) and more accurate (>82%) temperature control and monitoring by the users, as compared to the conventional technique using a thermal camera. Using a Holistic Presence Questionnaire (HPQ) scale, the users’ experience/training was significantly improved, while they reported less fatigue by 50%. Full article

Interspecific interactions among sympatric carnivores are critical for understanding patterns of coexistence, competition, and community structure. Among mesocarnivores, dominance hierarchies are typically shaped by differences in body size, social organization, and competitive ability. The golden jackal (Canis aureus) is generally assumed to dominate the red fox (Vulpes vulpes) across shared landscapes, particularly at high-value resources such as carcasses. However, here, we present rare behavioral evidence that challenges this prevailing assumption. Using motion-triggered camera traps deployed at a carcass in Lake Kerkini National Park, Greece, we recorded a sequence of interactions in which a golden jackal displayed clear submissive behavior toward a red fox, including lowered body posture, tail tucking, and conflict avoidance. Subsequent footage revealed two additional agonistic encounters, during which the same red fox successfully displaced two separate jackals, one of which emitted a distress vocalization while retreating. These findings represent the first documented case of interspecific submission by golden jackals toward a red fox and suggest that context-specific factors—such as immediate carcass possession, individual experience, or body condition—may modulate expected dominance outcomes. Our observations underscore the importance of fine-scale behavioral studies in revealing plasticity in interspecific relationships and contribute to a more nuanced understanding of carnivore competition under semi-natural conditions. Full article

To overcome the challenges during the crop growth process, e.g., pest infestation, inadequate environmental monitoring, and poor intelligence, this study proposes a crop growth information collection system based on a solar insecticidal lamp. The system comprises two primary modules: (1) an environmental information collection module, and (2) a multi-view image collection module. The environmental information collection module acquires crucial parameters, e.g., temperature, relative humidity, light intensity, soil conductivity, nitrogen, phosphorus, potassium content, and pH, by means of various sensors. Simultaneously, the multi-view image collection module employs three industrial cameras to capture images of the crop from the top, left, and right perspectives. The system is developed on the ESP32-S3 platform. WiFi-Mesh wireless communication technology is adopted to achieve high-frequency, real-time data transmission. Additionally, visualization software has been developed for real-time data display, data storage, and dynamic curve plotting. Field verification indicates that the proposed system effectively meets the requirements of pest control and crop growth information collection, which provides substantial support for the advancement of smart agriculture. Full article

Pod counting of rapeseed is a critical step in breeding, cultivation, and agricultural machinery research. Currently, this process relies entirely on manual labor, which is both labor-intensive and inefficient. This study aims to develop a semi-automatic counting instrument based on transmission image processing and proposes a new algorithm for processing transmission images of pods to achieve non-destructive, accurate, and rapid determination of the seed count per pod. Initially, the U-NET network was used to segment and remove the stem and beak from the pod image; subsequently, adaptive contrast enhancement was applied to adjust the contrast of the G-channel image of the pod to an appropriate range, effectively eliminating the influence of different varieties and maturity levels on the translucency of the pod skin. After enhancing the contrast, the Sauvola algorithm was employed for threshold segmentation to remove the pod skin, followed by thinning and dilation of the binary image to extract and remove the central ridge lines, detecting the number and area of connected domains. Finally, the seed count was determined based on the ratio of each connected domain’s area to the mean area of all connected domains. A transmission imaging device that mimics the human eye’s method of counting seeds was designed, incorporating an LED transmission light source, photoelectric switch-triggered imaging slot, an industrial camera, and an integrated packaging frame. Human–machine interaction software based on PyQt5 was developed, integrating functions such as communication between upper and lower machines, image acquisition, storage, and processing. Operators simply need to place the pod in an upright position into the imaging device, where its transmission image will be automatically captured and processed. The results are displayed on a touchscreen and stored in Excel spreadsheets. The experimental results show that the instrument is accurate, user-friendly, and significantly reduces labor intensity. For various varieties of rapeseed pods, the seed counting accuracy reached 97.2% with a throughput of 372 pods/h, both of which are significantly better than manual counting and have considerable potential for practical applications. Full article

A gait analysis serves as a critical tool for examining the biomechanical differences in movement patterns between trained and untrained individuals. This study investigates the nuanced differences in gait patterns between professional ballet dancers and non-dancers, with a focus on angular velocities and accelerations across key body joints. By analyzing the positions and movements of the head, neck, shoulder, spine, hip, knee, and ankle in both the sagittal (SP) and frontal (FP) planes, the study aims to identify key distinctions in joint dynamics that arise from differing levels of physical training. The study involved ten participants in total, comprising four professional female ballet dancers and six non-dancer students (three males and three females). In the first experiment, participants performed walking trials at five different speeds, while in the second experiment, the ballet dancers performed six distinct dance routines. Data were captured using a Kinetics motion capture camera system, which recorded the maximum and minimum angular velocities and accelerations during both walking and dancing. Key findings reveal significant differences in joint dynamics. For example, non-dancers’ right shoulder exhibited a maximum angular velocity of −0.47 rad/s and a minimum of 0.71 rad/s, while dancers showed a maximum of −0.09 rad/s and a minimum of 0.07 rad/s. The right knee also displayed notable differences, with angular velocities ranging from −3.88 rad/s to 2.61 rad/s for non-dancers, compared to −0.35 rad/s to 0.54 rad/s for dancers. In terms of acceleration, dancers’ left shoulder reached a maximum of 3.952 mm/s², while their right shoulder had a minimum of −0.1 mm/s². For non-dancers, the left elbow showed a maximum acceleration of 2.997 mm/s², while the right elbow had a minimum of 0.05 mm/s². These variations in angular velocity and acceleration underscore the distinct roles and movements of various joints, highlighting differences in muscle coordination and joint control. Understanding these patterns is crucial for assessing joint function, optimizing training, and developing intervention strategies for injury prevention and rehabilitation. The findings hold significant implications for the dance community and other physically active populations, offering valuable insights into performance enhancement and movement health. Full article

Display field communication (DFC) is an emerging technology that enables seamless communication between electronic displays and cameras. It utilizes the frequency-domain characteristics of image frames to embed and transmit data, which are then decoded and interpreted by a camera. DFC offers a novel solution for screen-to-camera data communication, leveraging existing displays and camera infrastructures. This makes it a cost-effective and easily deployable solution. DFC can be applied in various fields, including secure data transfer, mobile payments, and interactive advertising, where data can be exchanged by simply pointing a camera at a screen. This article provides a comprehensive survey of DFC, highlighting significant milestones achieved in recent years and discussing future challenges in establishing a fully functional DFC system. We begin by introducing the broader topic of screen–camera communication (SCC), classifying it into visible and hidden SCC. DFC, a type of spectral-domain hidden SCC, is then explored in detail. Various DFC variants are introduced, with a focus on the physical layer. Finally, we present promising experimental results from our lab and outline further research directions and challenges. Full article

In this implementation, an innovative and automated measurement and educational-demonstrative resource is proposed that estimates Brewster’s angle and the index of refraction of semitransparent materials. The apparatus, built and programmed with LEGO Mindstorms model Ev3, utilizes a micro:bit board and a machine vision camera (Huskylens cam). This camera detects the intensity extinction of a reflected laser beam at the polarization angle. The Ev3 connection cables and general input/output electronic interfaces have been modified to establish communication with the intelligent brick. Upon completion, the Brewster’s angle and the index of refraction are displayed on the intelligent brick screen. It will also be shown that the percentage error corresponding to the measurement of the refractive index of a glass and acrylic sample is 1.92% and 0.47%, respectively. According to its characteristics, this resource is suitable for use in undergraduate or graduate physics and engineering laboratories/courses. Full article

Colonoscopy has a limited field of view because it relies solely on a small camera attached to the end of the scope and a screen displayed on a monitor. Consequently, the quality and safety of diagnosis and treatment depend on the experience and skills of the gastroenterologist. When a novice attempts to insert the colonoscope during the procedure, excessive pressure can sometimes be applied to the colon wall. This pressure can cause a medical accident known as colonic perforation, which the physician should prevent. We propose an assisting device that senses the pressure applied to the colon wall, analyzes the risk of perforation, and warns the physician in real time. Flexible pressure sensors are attached to the surface of the colonoscope shaft. These sensors measure pressure signals during a colonoscopy procedure. A simple signal processor is used to collect and process the pressure signals. In the experiment, a colonoscope equipped with the proposed device was inserted into a simulated colon made from a colon extracted from a pig. The processed data were visually communicated to the gastroenterologist via displays and light-emitting diodes (LEDs). The device helps the physician continuously monitor and prevent excessive pressure on the colon wall. In this experiment, the device appropriately generated and delivered warnings to help the physicians prevent colonic perforation. In the future, the device is to be improved, and more experiments will be performed in live swine models or humans to confirm its efficacy and safety. Full article