Emergency vehicles, such as ambulances, fire trucks, and police cars, play a crucial role in road traffic management. While these vehicles typically use sirens for identification, many drivers rely primarily on visual cues. This reliance presents challenges in scenarios where the emergency vehicles are obscured or outside the observer’s field of vision, posing significant difficulties for individuals with hearing impairments or reduced ability to perceive ambient sound. This paper explores the feasibility of efficiently detecting emergency vehicle sirens on resource limited devices using innovative neural network models. Specifically, we propose (i) a hybrid model by integrating a one‐dimensional convolution neural network (CNN) with a gated recurrent unit (GRU) and (ii) a depth separable convolutional neural network to demonstrate that they are efficient models suitable for deployment on resource constrained devices such as microcontrollers (MCUs) with a Cortex‐M core, FPGAs, and TPUs. Experimental results indicate that the hybrid model achieves 98% average accuracy with 434.5 μJ energy consumption and 12.32 ms latency on STM32F411RE, enabling 52.8 h battery life in continuous monitoring applications. The depth‐wise separable convolutional neural network (DSCNN) variants provide energy‐efficient alternatives with 85% accuracy consuming 28% less energy, enabling deployment‐specific optimization for safety‐critical versus autonomous monitoring scenarios. Detailed ablation studies and Grad‐CAM visualizations establish the interpretability and novelty of the proposed architectures for transparent emergency detection on MCUs.

As the fastest‐growing economic country in the Asia Pacific, Bangladesh needs to be technologically advanced and adaptive in every sector to foster its development. In recent times, Internet of Things (IoT) has shown its potential for improving productivity and efficiency, thus contributing to a country’s economy. With technological advances, the need for low‐power, low‐cost, and secured IoT solutions has become prominent, especially for a developing country like Bangladesh. Long‐range wide‐area network (LoRaWAN) is an IoT solution that meets those criteria and provides exceptional long‐range coverage in addition. In this article, the possibilities of LoRaWAN technology have been analyzed from the perspective of Bangladesh. Initially, a technical review has been performed on its background, network topology, and compared with other leading technologies. Then a design architecture of the LoRaWAN’s end‐node and gateway has been presented. The article also investigates the possible deployment scenario and future scopes of LoRaWAN in Bangladesh. Finally, a LoRaWAN system has been demonstrated using two nodes in an urban scenario and experimentally evaluated data reception, received signal strength, and LoRa packet loss or delay over two different communication ranges. Based on the experimentation conducted, a maximum coverage of 1.094 km has been estimated by the log‐distance probabilistic approach.

Real‐time monitoring of successful shots during basketball training is crucial for coaches to assess player performance and formulate training plans. Existing visual monitoring systems are greatly affected by variations in illumination intensity and color differences, resulting in significant detection errors. To address this limitation, this study presents a self‐powered basketball hoop goal sensor based on a triboelectric nanogenerator (TENG). The sensor utilizes the basketball’s gravity to induce friction between internal aluminum and polyimide electrodes, achieving both goal detection and power generation. Experimental results demonstrate that the sensor exhibits desirable measurement characteristics, with output signal voltage and current amplitudes of 5.5 V and 60 nA, respectively. The measurement error is less than 1.5%, and the sensor operates reliably within a temperature range of −20 to 70°C and a relative humidity range of 5% to 95%. Furthermore, the sensor incorporates a power generation function, achieving a maximum output power of 46.5 nW when an external 20 MΩ resistor is connected in series.

Introduction One of the main success factors in methods such as lateral flow assay (LFA) is the binding of special reagents, such as absorption probes or antibodies to the nitrocellulose membrane surface, which depends on the immobility and stability of these reagents on the membrane. The aim of this study is to compare different immobilization methods of nucleotide probes, including baking of nucleotide probes, UV cross‐linking, and streptavidin/biotin immobilization on nitrocellulose membrane. Materials and Methods After preparation of nitrocellulose membrane, the dotted probes washed with 4x SSC buffer after exposure to UV (125 mJ/cm 2 ), heat, and the streptavidin–biotin method. Next, the solution was collected and read with a nanodrop. Also, the rolling circle amplification (RCA) method was used to check the fluorescent intensity (aminoallyl‐UTP‐X‐Cy5) in the remaining probes on the surface of nitrocellulose at the wavelengths of 643–670 nm. Results The results of this study show that 60 s‐UV and 2 h‐heat showed the lowest amount of probe removal and wastage after washing in reading with nanodrop and RCA and aminoalyl‐UTP‐X‐Cy5 method. Conclusion Our study showed the best technique to achieve the optimal binding of the probe to the nitrocellulose membrane in LFA and other methods of needing to spot the probe on this type of membrane.

Road traffic crashes (RTCs) pose a growing threat to transportation safety, particularly in rapidly developing countries like Bangladesh. This study aims to identify and analyze crash hotspots along the Dhaka–Mawa Expressway (N804), the country’s first expressway, using a geospatial approach. A total of 260 crash records from March 2022 to November 2024 were collected from local police stations. The analysis applied both qualitative and quantitative techniques, including severity index (SI) and kernel density estimation (KDE), to assess crash patterns, severity, and spatial concentration. Results revealed 154 fatalities, 259 serious injuries, and 278 minor injuries during the study period. Buses were the most frequently involved vehicle type (35.7%), and male victims accounted for the highest proportion of casualties across all severity levels. Using KDE and the SI score, this study identified 18 high‐risk black spots among 69 crash‐prone locations. The findings underscore the necessity for targeted safety interventions, enhanced infrastructure, and data‐driven enforcement strategies to decrease crash frequency and severity along high‐risk segments of the expressway.

Despite the continuous improvement in the technical performance of fiber‐optic early warning systems, their actual application results in preventing third‐party intrusion into oil and gas pipelines are often less than ideal. This issue stems largely from the lack of comprehensive postdeployment evaluation methodologies, making it difficult to identify root causes of performance deviations. To address this challenge, this study reviews and integrates relevant specifications and existing literature on pipeline fiber‐optic early warning systems, taking into account the actual characteristics of engineering projects, and addresses the limitations of existing research in terms of evaluation dimensions. It innovatively constructs the first multidimensional comprehensive application evaluation index system for pipeline fiber‐optic early warning systems, starting from both the technical characteristics of the system and its management needs in practical application. This fills the gap in the field of fiber‐optic early warning system application evaluation, which lacks a comprehensive evaluation framework that considers both technology and management. To ensure the scientific application of this index system, the analytic hierarchy process (AHP) and entropy weight method are used to determine subjective and objective weights, respectively, while a game theory combined weighting method is introduced to obtain optimal combined weights. Subsequently, the fuzzy comprehensive evaluation method is applied to empirically assess the systems at three pipeline workstations in Sichuan Province. The research findings indicate that the evaluation index system developed in this study can effectively assess the comprehensive application effect of fiber‐optic early warning systems in different pipeline stations. The evaluation results are highly consistent with the actual situation, demonstrating significant reliability and practicality.

Keeping medical images confidential while transmitting is crucial, especially in an open networking environment. One effective approach is blockchain‐based encryption, which provides strong security for sensitive healthcare data. To ensure the greatest levels of medical data integrity and authenticity, our proposed scheme employs a unique Lorenz chaotic system. The use of this system adds another degree of complexity, making it quite more difficult for cryptanalysts to break the key used for encryption. Our techniques improve security by employing unpredictable pixel permutations, 90‐degree rotations, and the intentional usage of a zigzag pattern to conceal pixel layouts. This nonlinear configuration adds to the overall encoding complexities. We integrate the Lorenz chaotic system with blockchain technology to protect medical images and prioritize patient privacy and data integrity. Our encoding performance is evaluated using multiple tests, such as key space, PSNR, correlation coefficient, and entropy, as well as key sensitivity tests.

This research aims to identify the behavioral characteristics of a biased IPMC sensor and maximize its sensitivity by optimizing the related parameters. For this purpose, an IPMC strip was stimulated with a custom setup and the experimental data was recorded. Then, a multiple linear regression model was used to determine the basic functional factors of the biased IPMC sensor. Finally, the optimal operating point of the sensor was estimated using the partial derivative method and contour plots. Statistical analysis showed that the mechanical excitation frequency, electrical bias frequency, electrical bias amplitude, and the value of bias resistance had a significant effect on the sensitivity of the IPMC sensor. Adjusted/predicted R‐squared in the proposed model was calculated 0.9498/0.9435, respectively, which indicates high accuracy in data fitting. Also, analysis of the residuals showed that the model has the required adequacy. In addition, the consistency of the optimal operating point from the optimization method with practical experiments shows the synergy of partial derivatives and plot counters can be used as an efficient method in further optimization studies.

The phenomenon of electromagnetic scattering holds significant implications for engineering across various electromagnetic domains. In this paper, a novel medium compensation method based on the finite‐difference time domain (FDTD) method is introduced, which can be used in multiantenna design for scattering control. In fact, once the electromagnetic waves irradiating the scatterer are determined, the scattering phenomenon is influenced not only by the geometric shape and material composition of the scatterer but also by the additional excitation. By introducing additional excitation sources to the scatterer, its parameters can be altered, consequently leading to changes in its scattering characteristics. Notably, in a multiantenna system, each individual antenna simultaneously plays the roles of both transmitter and scatterer. The vacuum compensation will make the scatterer invisible to the transmitter, which can eliminate mutual coupling during the transmitting mode. Furthermore, by nonvacuum compensation, the coupled scattering problem among the antennas in the antenna array can also be precisely manipulated to make better use of the mutual coupling effect. The simulation results demonstrate that the medium compensation method can efficiently eliminate or control the mutual coupling effect, and the precision at 10 −16 level leaves enough error space for engineering.