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In today's world, Bluetooth technology is integrated into almost every device we use, from wireless headsets, mice, and keyboards to cars and smart home devices. But with the convenience of this technology comes the risk of privacy and security breaches. Each Bluetooth device has potential vulnerabilities that cybercriminals can exploit and take advantage of. It is important to create awareness about various Bluetooth vulnerabilities, exploits, and ways to prevent them. This article examines the dark side of Bluetooth technology by explaining how hackers can find ways to bypass the advanced security features of laptops, phones, cars, or smart home devices to compromise the devices and steal personal sensitive data. Whether it is a casual user of Bluetooth technology or a business owner with multiple devices, understanding these risks is crucial to protecting yourself and your information.This article begins by explaining the basics of Bluetooth technology and how it works. Followed by a list of security risks involved while using Bluetooth and finally, it highlights the best practices to protect the devices and the data they contain.

A Bluetooth based battery-powered remote-controlled direct rice seeder was developed to overcome the drudgery and operational difficulties involved in direct seeding by manual drum seeder. The developed seeder consists of micro-controller unit, stepper motor, DC geared motor, motor drivers, battery, wheels and frame. The micro-controller unit is the heart of the developed mechatronic system. The micro-controller unit was designed and developed by Programming. A mobile application was designed and developed to connect the seeder to mobile through Bluetooth connectivity and operated range of 47.6 m which is sufficient for hilly region topography. The developed seeder was evaluated in laboratory conditions at different forward speeds varying from 0.5 to 3.0 km.h−1 and hopper fill levels varying from 25% to 75%. Forward speed of 0.7 km.h−1 and 75% hopper fill level were found optimum with corresponding seed rate of 20.2 kg. ha−1, missing hill index of 0%, hill spacing uniformity of 93.7%, coefficient of variance of number of seeds per hill of 0.25 and hill span of 9.4 cm. The developed seeder was evaluated in the field in puddled soil conditions in Sajong village, East Sikkim, India and the performance was compared with manual drum seeder. The field capacity and field efficiency of the developed seeder was found to be 0.017 ha.h−1 and 62% respectively as compared to 0.023 ha.h−1and 82% in case of manual drum seeder respectively. The developed seeder has reduced drudgery/cumbersome of 64% over manual drum seeder as evident from operator's heart rate and energy expenditure rate. In addition to that the operator can able to sit in a safe and comfortable environment outside the field to operate the developed drum seeder. Moreover, the developed seeder reduces the operational cost of 230 ₹. ha−1 over manual drum seeder.

In this paper, a novel method is introduced for the acquisition and transmission of critical parameters from valves used in industrial refrigeration. The parameter sensing provides local intelligence to the valve, which can be later used as a feedback signal for the controller. The hardware design includes ICS (Industrial Control Servo) valve with modifications to connect a Linear Variable Transformer (LVT) position sensor, pressure and temperature sensors. Also, a circuit board carrying the phase shift oscillator, Root Mean Square (RMS) to Direct Current (DC) converter, power supply and a dedicated Bluetooth Low Energy (BLE) module for transmitting the collected data is designed. The transmitted data can be received in a mobile phone android application and used for a secondary data calculation, alarm notification and alerting service technician. The sensor integration along with BLE connectivity creates a novel platform for data acquisition in Industrial Refrigeration (IR). The proposed method tested in real time to regulate the Helium gas flow rate and measured valve parameters is monitored by the dedicated mobile application.

In this paper, a low-cost smart system is designed and fabricated to monitor gas leakage in LPG-based cars. The implemented system consists of three gas sensors installed in the joints of the gas pipes, gas cylinders, and injectors for the purpose of gas leak monitoring. In addition, the LM 35 temperature sensor is situated over the gas cylinder to monitor its temperature. The implemented system can provide three types of alarm: the first type sends a text message to the car owner's phone and emits an audible alarm signal. The message reaches the service center also. The second type sends messages via Bluetooth to the user's phone or to the smart screen on the vehicle's dashboard, with an alert that the engine must be turned off (emergency case). The last warning sends an overheating alarm signal, utilizing a temperature sensor when the temperature of the gas cylinder exceeds 50°C to provide protection and prevent a possible explosion. In practice, it was found that gas sensors should be placed less than 5 cm from the monitored site, and the best performance at work was under 55°C. It was also found that the best performance of the GSM unit is under 55°C. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recently, there are a large number of smart lock systems that can be used in the workplace or home, but many of them depend on finding an external key, password, fingerprint, and facial recognition, where these systems suffer from weakness as the physical key may be forgotten in a place, the password can be memorized which is hard for some peoples, and the fingerprint system sometimes does not work on people who suffer from chronic diseases, such as people with diabetes and for each of these systems the person needs a free hand so that he/her can open the lock which means that is if the person carries something he/her needs to be placed somewhere. The facial recognition system cannot recognize the person's face when the place has poor lighting. This paper proposes a home door lock system that relies on the internet of things (IoT) technology and portable electronic devices Bluetooth such as a smart mobile using the device Bluetooth media access control (MAC) address as a key and the IoT for monitoring, which leads to a door lock that does not require a free hand. The proposed lock system outcome can be a good candidate for home security applications. [ABSTRACT FROM AUTHOR]

Location tracking stands for technologies that physically identify and electronically register and monitor the tracking of individuals or objects. This technology is widely implemented in the health field for tracking clinicians and patient locations. The history of visited location data is used for many purposes and is mainly applied to monitor and assess the patient's movement to provide helpful knowledge. This data is obtained using the Global positioning system (GPS), Bluetooth, and Radio-frequency identification (RFID) built into the device such as smartphones, smart watches, or wearable devices. In some Research, other technologies like Google Location History (GLH) provide the history of visited locations made by the Google Account. Location tracking can be an alternative and potentially help monitor and track Covid-19 infectee to prevent wider diffusion. This paper reviews location tracking applications in healthcare based on how the location data is obtained and analyzed. The application of location tracking was differentiated and reviewed based on the applied methods in acquiring knowledgeable data. Furthermore, the data analysis used to track location was also discussed to know what knowledge that obtained from the location history data. Getting the location and assessing the data for specific purposes was also highlighted. [ABSTRACT FROM AUTHOR]

COVID-19 has had a devastating impact worldwide, including in care homes where there have been substantial numbers of cases among a very vulnerable population. A key mechanism for managing exposure to the virus and targeting interventions is contact tracing. Unfortunately, environments such as care homes that were most catastrophically impacted by COVID-19 are also those least amenable to traditional contact tracing. A promising alternative to recall and smartphone-based contact tracing approaches is the use of discrete wearable devices that exploit Bluetooth Low Energy (BLE) and Long-Range Wide Area Network (LoRaWAN) technologies. However, the real-world performance of these devices in the context of contact tracing is uncertain. A series of experiments were conducted to evaluate the performance of a wearables system that is based on BLE and LoRaWAN technologies. In each experiment, the number of successful contacts was recorded and the physical distance between two contacts was compared to a calculated distance using the Received Signal Strength Indication (RSSI) to determine the precision, error rate, and duration of proximity. The overall average system contact detection success rate was measured as 75.5%; when wearables were used as per the manufacturer's guidelines the contact detection success rate increased to 81.5%, but when obstructed by everyday objects such as clothing or inside a bag the contact detection success rate was only 64.2%. The calculated distance using RSSI was close to the physical distance in the absence of obstacles. However, in the presence of typical obstacles found in care home settings, the reliability of detection decreased, and the calculated distance usually appeared far from the actual contact point. The results suggest that under real-world conditions there may be a large proportion of contacts that are underestimated or undetected. [ABSTRACT FROM AUTHOR]

In an endeavor to enhance consumer experience and streamline the shopping process, this study presents the design and evaluation of a smart shopping cart prototype, devised to replace conventional manual shopping carts. Customers traditionally utilize baskets to transport purchased goods to the cashier for payment processing. During peak shopping hours, queues often form, potentially detracting from the customer's overall shopping experience. Customers are typically obliged to stand adjacent to their baskets to maintain their position in the queue, a practice this innovation intends to eliminate. The proposed smart shopping cart employs Bluetooth HC-05 technology to facilitate remote operation, thereby enabling users to wait at a comfortable distance from their groceries. The remote control for the cart is designed to interface with Android smartphones, capitalizing on the ubiquity of these devices in customers' daily lives. The ease of connecting Bluetooth HC-05 with an Android device further simplifies the operation for users well-versed with smartphones. This study outlines the construction and testing of a smart shopping cart prototype, although it has not been directly implemented in a supermarket setting. The conducted tests are representative of the performance of a potential full-scale model. The remote control application, tailored to the specific commands required by the shopping cart, was developed using Kodular. It can be easily accessed and downloaded from the Kodular website. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is a crucial tool in cognitive neuroscience, enabling the study of neurophysiological function by measuring the brain's electrical activity. Its applications include perception, learning, memory, language, decision making and neural network mapping. Recently, interest has surged in extending EEG measurements to domestic environments. However, the high costs associated with traditional laboratory EEG systems have hindered accessibility for many individuals and researchers in education, research, and medicine. To tackle this, a mobile-EEG device named "DreamMachine" was developed. A more affordable alternative to both lab-based EEG systems and existing mobile-EEG devices. This system boasts 24 channels, 24-bit resolution, up to 6 h of battery life, portability, and a low price. Our open-source and open-hardware approach empowers cognitive neuroscience, especially in education, learning, and research, opening doors to more accessibility. This paper introduces the DreamMachine's design and compares it with the lab-based EEG system "asalabTM" in an eyes-open and eyes-closed experiment. The Alpha band exhibited higher power in the power spectrum during eyes-closed conditions, whereas the eyes-open condition showed increased power specifically within the Delta frequency range. Our analysis confirms that the DreamMachine accurately records brain activity, meeting the necessary standards when compared to the asalabTM system. [ABSTRACT FROM AUTHOR]

This paper introduces a survey on recent smart wearable devices used in different fields, especially healthcare applications. A discussion is presented in terms of power supply, wireless technologies, applications, and wearability of these devices. Regarding the power supply, a photovoltaic is the best harvesting energy source, while the best energy storage is a Li-ion battery. Regarding wireless technologies, Bluetooth low energy (BLE) is the best for personal usage, while Wi-Fi has preferred for Internet of Things (IoT) applications. Regarding the applications, medical and non-medical applications can be used. Regarding wearability, smart wearable devices can be positioned on a human hand or arm. Also, wearable sensors can be patched on human skin, besides, they can be placed on clothes, such as a smart suit which is preferred for heavy duties. [ABSTRACT FROM AUTHOR]

A distinct Meander Curve Based Star Shaped novel Wearable Hybrid Fractal Antenna is explored in this paper. The Meander curve is utilized to build the geometry of the antenna. A Star Shaped structure is additionally built in the middle of the patch also. It is planned over the jean substrate having dielectric constant 1.7 and having dimensions 52.3 × 58.7 × 1 mm3. The antenna is energized by microstrip line feed, placed at the base corner. The PSO technique is specially used to optimize the width of the ground plane using the fitness function. A numerical model is determined utilizing the IFS to produce the fractal geometry in MATLAB programming. The planned design is compact, mathematical engaging, and offers adequate bandwidth. It operates over 2.33–2.56 GHz and 6.20–6.44 GHz with resonant frequencies 2.44 and 6.31 GHz respectively. It provides 230 and 240 MHz bandwidth at the corresponding resonant frequencies. This antenna provides 8.84 dB and 5.77 dB gain and stable radiation patterns at resonant frequencies. HFSS software is utilized for simulating and planning the antenna. The proposed antenna is fabricated and tested, and the simulated and experimental results are compared to examine the reliability of it. The performance of this antenna is further described by analyzing the behavior using different wearable substrate materials like wash cotton, felt, polyester, etc. [ABSTRACT FROM AUTHOR]

In today's technologically advanced era, the ubiquitous use of smart mobile devices has become a significant aspect of daily life, thereby presenting a valuable opportunity for investigative purposes. These devices, when equipped with the right tools and subjected to thorough inspection methodologies, can yield a treasure trove of concealed information, which can be crucial in various investigative scenarios. Among these devices, the Apple iPhone stands out due to its widespread popularity and adoption across a diverse global user base. Its advanced features and user-friendly characteristics have made it a preferred choice for a wide array of individuals, ranging from students and teachers to business professionals and individuals from various other fields. This widespread usage underscores the importance of understanding the nuances of iPhone data in investigative contexts. This article delves into the intricate concept of identifying a potentially dangerous person by leveraging the data available on these smart devices. It meticulously discusses the importance of context in categorizing an individual as potentially dangerous and sheds light on the various factors that play a pivotal role in this classification process. To aid in this endeavor, the article introduces a comprehensive diagram that outlines the step-by-step procedure for assessing the potential danger posed by an individual. Furthermore, the article explores the fundamental techniques of mobile device forensics, particularly focusing on devices operating on the iOS platform. It presents the findings from practical research, offering insights into the type of data that can be extracted during a forensic investigation of these devices. A novel approach is proposed for classifying individuals as potentially dangerous based on the analysis of Bluetooth data obtained from their mobile devices. This method is elucidated through the presentation of pseudocode, which details the algorithmic steps involved in this classification process. To enhance the effectiveness of this method, the article suggests incorporating additional data sources. These include information pertaining to saved Wi-Fi networks that the device has connected to and GPS coordinates that have been logged during the operation of various system applications inherent to the iOS operating system. Finally, the article emphasizes the critical need for the practical implementation and rigorous testing of this proposed method. It underscores the importance of validating and refining the approach to ensure its effectiveness and reliability in identifying potentially dangerous individuals through the forensic analysis of mobile device data. This comprehensive approach not only broadens the scope of mobile device forensics but also contributes significantly to the field of security and investigative research. [ABSTRACT FROM AUTHOR]

Technology development are going so fast. One of technology development on purposed reasearch is moving item technology. Moving item can be dangerous works for human. There are some dangerous case of moving item, heavy weight items, hazardous chemical compounds, etc. Purposed research is to minimize risk from previous problem. It can reduce work load energy and minimize an accident in terms of moving items for operator, which are often encountered in the industry sector. Purposed research made bluetooth wireless transporter mecanum wheeled robot with android smartphone controller for moving item. Robot made in prototype scale. Robot size is 28x13x15 cm(s). Robot made based on arduino uno and L293D driver motor shield with android smartphone controller. Using android controller was made user easier to use. This robot design equipped with 4 mecanum wheel (4 DC motors), two 1850 battery, Arduino Uno, L293D driver motor, HC-06 bluetooth module, LCD and two M90s Servos for gripper. Gripper has two motions, shift and lift motions. After several test of purposed transporter robot, it can conclude that purposed transporter robot can controlled wireless with bluetooth from 0 to 20 meters. Purposed robot gripper has two motion Gripper test result, purposed transporter robot can shift item up to 350 grams weight load and lift an item up to 200 grams. Robot can operate up to 128 minutes with full capacity batteries . From several test, main purposed of this robot can provided. It is to moving an item to another place. Purposed robot can implements in industry sector with adjustment specification, but if weight load and dimensions match with this research, then purposed robot can be used properly.

As COVID-19 is still spreading globally, the narrow ship space makes COVID-19 easier for the virus to infect ship passengers. Tracking close contacts remains an effective way to reduce the risk of virus transmission. Therefore, indoor positioning technology should be developed for ship environments. Today, almost all smart devices are equipped with Bluetooth. The Angle of Arrival (AoA) using Bluetooth 5.1 indoor positioning technology is well suited for ship environments. But the narrow ship space and steel walls make the multipath effect more pronounced in ship environments. This also means that more noises are included in the signal. In the Uniform Rectangular Array (URA) type receiving antenna array, elevation and azimuth angles are two important parameters for the AoA indoor positioning technology. Elevation and azimuth angles are unstable because of the influence of noise. In this paper, a Self-Learning Mean Optimization Filter (SLMOF) is proposed. The goal of SLMOF is to find the optimal elevation and azimuth angles as a way to improve the Bluetooth 5.1 AoA indoor positioning accuracy. The experimental results show that the Root Mean Square Error (RMSE) of SLMOF is 0.44 m, which improves the accuracy by 72% compared to Kalman Filter (KF). This method can be applied to find the optimal average in every dataset.

Abstract： A multi-channel real-time system is designed for monitoring photoplethysmographic (PPG) using RISC-V kernel. The system takes E203 IP of RISC-V architecture as the low-power core, which connects analog front-end module and Bluetooth control module through ICB bus. The analog front-end control module controls back-to-back LEDs to realize two-channel PPG signal acquisition. Multi-channel acquisition can be realized by reusing the analog front-end control module. The Bluetooth control module is connected to E203 to deliver system control commands, and then upload PPG data to the terminal. Finally, The FPGA system verifies the 22-bit dual-channel PPG signal Internet of Things terminal application.

Puskesmas is the first level of service which is the spearhead in efforts to improve public health. especially in remote areas, puskesmas where all health activities take place. Height measurement is one of the programs carried out at the puskesmas. However, with inadequate facilities, the height measurement process does not get maximum results. At this time, technological developments have produced many tools to help humans lighten their workload. One of the solutions given to overcome this manual measurement problem is to create a digital measurement tool based on internet access. The internet system is used so that users do not need to record measurement results manually. However, is this a solution for internet blankspot areas? In fact, Indonesia still has around 45% of areas that have not been reached by internet access or blankspots. Therefore by taking advantage of technological developments, the authors designed a digital height measuring device that is connected to a thermal print. It is intended that users can perform measurements automatically and obtain accurate results. Also, this tool aims to allow users to obtain measurement results immediately after the measurement activities have been completed by printing the results on a thermal printer without requiring an internet connection. The design of a tool that is small and uses a battery is intended so that measurements can be carried out by anyone and anywhere.

A compact asymmetric coplanar strip (ACS)-fed monopole antenna is presented, which operates within the Bluetooth and UWB frequency bands with the capability to simultaneously reject the lower WLAN interfering band. The antenna consists of an inverted right triangle patch monopole loaded by open-ended L-shaped slits not only to produce the additional 2.4 GHz passband to the UWB design but also to achieve stopband characteristics around 5.2 GHz. The conceptual equivalent circuit model as well as characteristic mode analyses are carried out in the design evolution process. The proposed antenna has an overall size of only 20 mm $\times10$ mm, having the smallest area among the so far developed designs, which can be easily integrated within any wireless gadgets. A prototype is fabricated and measured to validate the design, demonstrating the predicted behavior fairly achieved by full-wave analysis. The antenna −10 dB operating bandwidth ranges from 2.38 to 2.42 GHz and from 3.35 to 11 GHz while rejecting from 4.69 to 5.2 GHz. Unlike the unwanted stopband, where the radiation characteristics are adequately deteriorated, the proposed antenna fairly provides stable omni-directional radiation patterns in the ${H}$ -plane, and has an average efficiency (gain) of 87.3% (2.6 dBi) in the desired passband. As far as the antenna transient behavior is concerned, an adequate measured (simulated) system fidelity factor of 0.7 (0.68) is achieved for the transmission of impulse-type UWB signals in the face-to-face configuration.

Future telecommunications aim to be ubiquitous and efficient, as widely deployed connectivity will allow for a variety of edge/fog based services. Challenges are numerous, e.g., spectrum overuse, energy efficiency, latency and bandwidth, battery life and computing power of edge devices. Addressing these challenges is key to compose the backbone for the future Internet-of-Things (IoT). Among IoT applications are Indoor Positioning System and indoor Real-Time-Location-Systems systems, which are needed where GPS is unviable. The Bluetooth Low Energy (BLE) 5.1 specification introduced Direction Finding to the protocol, allowing for BLE devices with antenna arrays to derive the Angle-of-Arrival (AoA) of transmissions. Well known algorithms for AoA calculation are computationally demanding, so recent works have addressed this, since the low-cost of BLE devices may provide efficient solutions for indoor localization. In this paper, we present a system topology and algorithms for self-localization where a receiver with an antenna array utilizes the AoAs from fixed battery powered beacons to self-localize, without a centralized system or wall-power infrastructure. We conduct two main experiments using a BLE receiver of our own design. Firstly, we validate the expected behaviour in an anechoic chamber, computing the AoA with an RMSE of $\mathrm {10.7~ ^{circ}}$ . Secondly, we conduct a test in an outdoor area of 12 by 12 meters using four beacons, and present pre-processing steps prior to computing the AoAs, followed by position estimations achieving a mean absolute error of $\mathrm {3.6~ \text {m}}$ for 21 map positions, with a minimum as low as $\mathrm {1.1~ \text {m}}$ .

Several Radio-Frequency technologies have been explored to evaluate the efficacy of localization algorithms in indoor environments, including Received Signal Strength (RSS), Time of Flight (ToF), and Angle of Arrival (AoA). Among these, AoA technique has been gaining interest when adopted with the Bluetooth protocol. In this work, we describe a data collection measurement campaign of AoA and RSS values collected from Bluetooth 5.1 compliant tags and a set of anchor nodes deployed in the environment. We detail the adopted methodology to collect the dataset and we report all the technical details to reproduce the data collection process. The resulting dataset and the adopted software is publicly available to the community. To collect the dataset, we deploy four anchor nodes and four Bluetooth tags and we reproduce some representative scenarios for indoor localization: calibration, static, mobility, and proximity. Each scenario is annotated with an accurate ground truth (GT). We also assess the quality of the collected data. Specifically, we compute the Mean Absolute Error (MAE) between the AoA estimated by the anchors and the corresponding GT. Additionally, we investigate the packet loss metric which measures the percentage of Bluetooth beacons lost by the anchors.

Wind energy generation plays a vital role in transitioning from fossil fuel-based energy sources and in alleviating the impacts of global warming. However, global wind energy coverage still needs to rise, while requiring a significant step up in conversion efficiency: monitoring wind flow and operational parameters of wind turbines is an essential prerequisite for coverage and conversion efficiency optimization. This paper presents a low-power, self-sustainable, and time-synchronised system for aerodynamic and acoustic measurements on operating wind turbines. It includes 40 high-accuracy barometers, 10 microphones, 5 differential pressure sensors, and implements a coarse time synchronisation on top of a Bluetooth Low Energy 5.1 protocol tuned for long-range communications. Moreover, we field-assessed the node capability to collect precise and accurate aerodynamic data with a multi-node setup. Outdoor experimental tests revealed that the system can acquire heterogeneous data with a time synchronisation error below $\mathrm {100~ \mu \text {s} }$ and sustain a data rate of 600 kbps over 400 m with up to 5 sensor nodes, enough to fully instrument a wind turbine. The proposed method does not add any traffic overhead on the Bluetooth Low Energy 5.1 protocol, fully relying only on connection events and withstands transmission discontinuity often present in long range wireless communications.

With the outbreak of Covid‐19, both people's health and the world economy are facing great challenges. Contact tracing scheme based on Bluetooth of smartphones has been regarded as a viable way to mitigate the spread of Covid‐19. The existing schemes mainly belong to the centralized or the decentralized structure, both of which have their own limitations. It is infeasible for the existing schemes to balance the different demands of governments and users for user privacy and tracing efficiency at different periods of the epidemic. In this paper, we propose a hybrid contact tracing scheme named MLCT (multi‐level contact tracing scheme) which is mainly based on short group signature. MLCT provides multiple privacy levels by applying anonymous credential technology and secret sharing technology to desensitize user identity privacy and encounter privacy. Comparing to the previous schemes, MLCT fully considers the different demands of the government, patients, and close contacts for user privacy and tracing efficiency in the different stages of Covid‐19. The experimental results show viability in terms of the required resource from both server and mobile phone perspectives. And the security analysis demonstrates that MLCT can achieve the five targets security goals. It is expected that MLCT can contribute to the design and development of contact tracing schemes. [ABSTRACT FROM AUTHOR]

In this work, a novel triband antenna is developed for wireless local area network (WLAN), worldwide interoperability for microwave access (WiMAX), and Bluetooth application. The proposed antenna is printed on a low-cost FR-4 substrate and has an overall size of 25 mm × 40 mm × 1.6 mm. Coplanar waveguide (CPW) line with characteristic impedance of 50 Ω is used as feed for the designed antenna. A prototype of this antenna is fabricated and tested to validate the simulation results. The measured result shows that the antenna has the triple-band response with frequency bands that correspond to S11<−10 dB 2.36 − 3.17, 3.8 − 4.35, and 5.69 − 6.02 GHz. The measured gains of the antenna at resonant frequencies of 2.61, 4.115 and 5.85 GHz are 0.756, 0.925 and 1.589 dBi, respectively. Maximum decrement in measured gain is only 0.671 dB which is attributed to losses from connectors and cables. A novel approach, based on a combination of a cap-shaped ground plane and gap coupling technique in the form of an interdigital capacitor (IDC), is used to achieve the characteristic of triple frequency bands. Finally, the utility of the proposed antenna is checked with a four-element MIMO antenna. [ABSTRACT FROM AUTHOR]

Repetitive Transcranial Magnetic Stimulation (rTMS) and transspinal electrical stimulation (tsES) have been proposed as a novel neurostimulation modality for individuals with incomplete spinal cord injury (iSCI). In this study, we integrated magnetic and electrical stimulators to provide neuromodulation therapy to individuals with incomplete spinal cord injury (iSCI). We designed a clinical trial comprising an 8-week treatment period and a 4-week treatment-free observation period. Cortical excitability, clinical features, inertial measurement unit and surface electromyography were assessed every 4 weeks. Twelve individuals with iSCI were recruited and randomly divided into a combined therapy group, a magnetic stimulation group, an electrical stimulation group, or a sham stimulation group. The magnetic and electric stimulations provided in this study were intermittent theta-burst stimulation (iTBS) and 2.5-mA direct current (DC) stimulation, respectively. Combined therapy, which involves iTBS and transspinal DC stimulation (tsDCS), was more effective than was iTBS alone or tsDCS alone in terms of increasing corticospinal excitability. In conclusion, the effectiveness of 8-week combined therapy in increasing corticospinal excitability faded 4 weeks after the cessation of treatment. According to the results, combination of iTBS rTMS and tsDCS treatment was more effective than was iTBS rTMS alone or tsDCS alone in enhancing corticospinal excitability. Although promising, the results of this study must be validated by studies with longer interventions and larger sample sizes. [ABSTRACT FROM AUTHOR]

Wearable devices are starting to gain popularity, which means that a large portion of the population is starting to acquire these products. This kind of technology comes with a lot of advantages, as it simplifies different tasks people do daily. However, as they recollect sensitive data, they are starting to be targets for cybercriminals. The number of attacks on wearable devices forces manufacturers to improve the security of these devices to protect them. Many vulnerabilities have appeared in communication protocols, specifically Bluetooth. We focus on understanding the Bluetooth protocol and what countermeasures have been applied during their updated versions to solve the most common security problems. We have performed a passive attack on six different smartwatches to discover their vulnerabilities during the pairing process. Furthermore, we have developed a proposal of requirements needed for maximum security of wearable devices, as well as the minimum requirements needed to have a secure pairing process between two devices via Bluetooth. [ABSTRACT FROM AUTHOR]

Featured Application: Intelligent prevention and control of infectious diseases. Infectious diseases, such as COVID-19, may have a significant impact on human daily life and social activities. One effective method to prevent and control the spread of such diseases is to accurately locate the sources of infection and limit the possible exposure to the virus. This paper presents a method, system, big data storage and analysis to control the infection based on Bluetooth technology. GPS and Bluetooth positioning are combined to track the movement trajectory of each person with a smart device, locally store the location information and close contacts, as well as periodically update it on the cloud platform. Based on the related algorithms of big data, this method can provide personal and regional risk levels, providing an alarm function which can be triggered by being close enough to a high-risk area or if the infected person's risk level is greater than the set threshold within the Bluetooth interconnection range. The system can provide a wealth of data on the location of infection sources and close contacts, offering valuable technical support for rapid and efficient epidemic prevention and control. [ABSTRACT FROM AUTHOR]

Copyright of Packaging & Food Machinery is the property of Packaging & Food Machinery Magazine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Medical Equipment Journal is the property of Chinese Medical Equipment Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Wireless short-range communication has become widespread in the modern era, partly due to the advancement of the Internet of Things (IoT) and smart technology. This technology is now utilized in various sectors, including lighting, medical, and industrial applications. This article aims to examine the historical, present, and forthcoming advancements in wireless short-range communication. Additionally, the review will analyze the modifications made to communication protocols, such as Bluetooth, RFID and NFC, in order to better accommodate modern applications. Batteryless technology, particularly batteryless NFC, is an emerging development in short-range wireless communication that combines power and data transmission into a single carrier. This modification will significantly influence the trajectory of short-range communication and its applications. The foundation of most low-power, short-range communication applications relies on an ultra-low-power microcontroller. Therefore, this study will encompass an analysis of ultra-low-power microcontrollers and an investigation into the potential limitations they might encounter in the future. In addition to offering a thorough examination of current Wireless short-range communication, this article will also attempt to forecast future patterns and identify possible obstacles that future research may address.

Wearable devices, such as headsets and activity trackers, rely heavily on the Bluetooth and/or the Bluetooth Low Energy wireless communication standard to exchange data with smartphones or other peripherals. Since these devices collect personal health and activity data, ensuring the privacy and security of the transmitted data is crucial. Therefore, we present a dataset that captures complete Bluetooth communications—including advertising, connection, data exchange, and disconnection—in an RF isolated environment using software-defined radio. We were able to successfully decode the captured Bluetooth packets using existing tools. This dataset provides researchers with the ability to fully analyze Bluetooth traffic and gain insight into communication patterns and potential security vulnerabilities.

In academic environments, students take exams simultaneously in campus examination classrooms. Due to recent advancements in technology, examination rooms are flooded with Bluetooth data traffic generated by personal devices (smartphones, smartwatches, etc.). The work presented in this article proposes a method for collecting Bluetooth traffic in an academic examination setting. The desired data were collected during several examination sessions using an Ubertooth One device, and then an in-depth post-processing analysis was performed on the collected dataset. The devices generating traffic were precisely located within the examination room, and areas with heightened data traffic were highlighted. Additionally, another goal of the current research was to provide a unique type of dataset to the academic community, facilitating its utilization in further research endeavors.