Bluetooth Low Energy Wireless Research Articles

Low cost MEMS accelerometer and microphone based condition monitoring sensor, with LoRa and Bluetooth Low Energy radio

Vibration-based Condition Monitoring (CM) is an essential tool for identifying potential defects in industrial machinery. However, the implementation of an efficient CM system often necessitates the use of high-cost accelerometers with a large bandwidth. To address this challenge, this study introduces a low-cost CM sensor composed of an ultrasonic MEMS microphone - SPH0641LU and an ADXL1002 MEMS accelerometer. The combination of these two sensor types allows for comparative analysis of the captured data. The SPH641LU microphone is capable of detecting audible vibration signals with a frequency range up to 80 kHz, while the ADXL1002 accelerometer can measure vibrations up to 21 kHz. In addition a three axis ultra low power accelerometer is included, allowing measurement of unbalance or rotating speed, below 200Hz. Moreover, the sensor is designed to operate on battery power and provides the capability for raw data transmission via Bluetooth Low Energy (BLE) or the transmission of pre-processed features from the raw data using LoRaWAN.

Circuit Design, Realization, and Test of a Bluetooth Low Energy Wireless Sensor With On-Board Computation for Remote Healthcare Monitoring

Circuit Design, Realization, and Test of a Bluetooth Low Energy Wireless Sensor With On-Board Computation for Remote Healthcare Monitoring

Modular vertically-integrated skin patch for biosignal measurements

This paper presents research on a novel and modular vertically-integrated wearable skin patch for biosignal measurements. The flexible patch consists of a disposable skin-contacting electrode layer and a durable electronics part. The durable part is designed to include a printed re-chargeable battery, a solar cell, electronics for the measurement of electrocardiogram (ECG), galvanic skin response, acceleration, temperature and humidity and a covering visually appealing jewellery-like functional crystal layer for decoration and user interaction. The patch can store measurement data and transmit it to a mobile phone via a bluetooth low-energy radio. Integration process is developed for the vertical stacking that limits the skin-patch area to achieve a desirable form factor. The sensing electrodes are printed on stretchable thermoformable polyurethane substrate with vias through the substrate to couple skin-contacting electrodes to the upper functional layers. A removable adhesive layer between the disposable and durable parts is developed to enable separating the two parts after wear and then to couple the durable part with a new disposable part. The patch is tested on body for ECG sensing.

Efficient indoor localization with wireless sensor networks via learnable sparse coding

In this study, the indoor localization problem for human movement is built as a sparse representation, and a learnable sparse coding algorithm is proposed by introducing a nonconvex penalty function as the sparse constraints. The good properties of the penalty are able to help reduce the iteration cost to find a sparse solution indicating the target locations. The sparse code can achieve its optimal value from the trained neural network model with parametrization. It is instead of a piece of algorithmic processing in the conventional methods requiring a large iteration. A real-world experiment using a Bluetooth low energy wireless sensor network validates the proposed method and shows the improvement of the error reduction at the first five iteration points on average compared to iterative shrinkage and thresholding algorithm (ISTA), and achieves competitive performance in the localization tasks for learned-ISTA-based algorithms.

Methodology for Safe and Effective Subcutaneous Implantation of Wireless Biotelemetry Sensor Devices in Rodents.

In this work, a methodology for assessing the impact of implantation surgery on laboratory mice on behavior was created. The study included the design of several implants fabricated on various printed circuit board (PCB) technologies with overall diameters between 26-28mm and weights between 4.5-6.5g. 11 adult CD1 mice were implanted with the devices and their behavior was analyzed using common behavioral benchmark tests. The results show that implants designed to be 10% of the animal's body weight showed no adverse effects on mobility or social behavior. These results illustrate a method to identify and reduce the adverse behavioral changes inherent to device implantation. Additional considerations for implant surgery are provided. These results are validated with the implantation of a Bluetooth Low Energy (BLE) wireless sensor tag. The implanted wireless tag showed an average Received Signal Strength Indicator (RSSI) of 62.96dBm with a standard deviation of 4.95dBm and a variance of 24.5 dBm2. The high RSSI and variance values show that the implant was working well inside of the mouse's body and that the mouse was fully recovered and readily exploring its surroundings.Clinical Relevance-This work 1) studies the behavioral impact of implantable wireless biopotential devices. This will help clinical researchers conducting behavioral studies using sensor implants. 2) demonstrates a working implanted BLE wireless model inside of a mouse. Various wireless connectivity metrics are studied.

Energy Autonomous Wireless Sensing Node Working at 5 Lux from a 4 cm2 Solar Cell

Harvesting energy for IoT nodes in places that are permanently poorly lit is important, as many such places exist in buildings and other locations. The need for energy-autonomous devices working in such environments has so far received little attention. This work reports the design and test results of an energy-autonomous sensor node powered solely by solar cells. The system can cold-start and run in low light conditions (in this case 20 lux and below, using white LEDs as light sources). Four solar cells of 1 cm2 each are used, yielding a total active surface of 4 cm2. The system includes a capacitive sensor that acts as a touch detector, a crystal-accurate real-time clock (RTC), and a Cortex-M3-compatible microcontroller integrating a Bluetooth Low Energy radio (BLE) and the necessary stack for communication. A capacitor of 100 μF is used as energy storage. A low-power comparator monitors the level of the energy storage and powers up the system. The combination of the RTC and touch sensor enables the MCU load to be powered up periodically or using an asynchronous user touch activity. First tests have shown that the system can perform the basic work of cold-starting, sensing, and transmitting frames at +0 dBm, at illuminances as low as 5 lux. Harvesting starts earlier, meaning that the potential for full function below 5 lux is present. The system has also been tested with other light sources. The comparator is a test chip developed for energy harvesting. Other elements are off-the-shelf components. The use of commercially available devices, the reduced number of parts, and the absence of complex storage elements enable a small node to be built in the future, for use in constantly or intermittently poorly lit places.

Use of Wireless Technologies in the Industrial Environment With Blockchain

This paper presents the development of an OpenThread network within the framework of a BMBF project, which is intended to transfer production data to a private blockchain in order to store the data in a tamper-proof and transparent manner. Among other things, special radio modules were developed for this purpose which support the OpenThread and Bluetooth Low Energy radio standards and thus additionally enable the connection of mobile devices to the private blockchain. During the conception and development of the radio modules as well as the communication protocols, emphasis was placed on ensuring that the radio network meets the high requirements for its use in an industrial environment, such as commissioning through plug & play,robustness, availability, data transfer rate, latency and, above all, IT security.

A Multifunctional Battery-Free Bluetooth Low Energy Wireless Sensor Node Remotely Powered by Electromagnetic Wireless Power Transfer in Far-Field.

This paper presents a multifunctional battery-free wireless sensing node (SN) designed to monitor physical parameters (e.g., temperature, humidity and resistivity) of reinforced concrete. The SN, which is intended to be embedded into a concrete cavity, is autonomous and can be wirelessly powered thanks to the wireless power transmission technique. Once enough energy is stored in a capacitor, the active components (sensor and transceiver) are supplied with the harvested power. The data from the sensor are then wirelessly transmitted via the Bluetooth Low Energy (BLE) technology in broadcasting mode to a device configured as an observer. The feature of energy harvesting (EH) is achieved thanks to an RF-to-DC converter (a rectifier) optimized for a low power input level. It is based on a voltage doubler topology with SMS7630-005LF Schottky diode optimized at −15 dBm input power and a load of 10 kΩ. The harvested DC power is then managed and boosted by a power management unit (PMU). The proposed system has the advantage of presenting two different power management units (PMUs) and two rectifiers working in different European Industrial, Scientific and Medical (ISM) frequency bands (868 MHz and 2.45 GHz) depending on the available power density. The PMU interfaces a storage capacitor to store the harvested power and then power the active components of the sensing node. The low power digital sensor HD2080 is selected to provide accurate humidity and temperature measurements. Resistivity measurement (not reported in this paper) can also be achieved through a current injection on the concrete probes. For wireless communications, the QN9080 system-on-chip (SoC) was chosen as a BLE transceiver thanks to its attractive features: a small package size and extremely low power consumption. For low power consumption, the SN is configured in broadcasting mode. The measured power consumption of the SN in a deep-sleep mode is 946 µJ for four advertising events (spaced at 250 ms maximum) after the functioning of sensors. It also includes voltage offset cancelling functionality for resistivity measurement. Far-field measurement operated in an anechoic chamber with the most efficient PMU (AEM30940) gives a first charging time of 48 s (with an empty capacitor) and recharge duration of 27 s for a complete measurement and data transmission cycle.

IoT Solutions for Smart Management of Hospital Buildings: A General Review towards COVID-19, Future Pandemics, and Infectious Diseases

Background: The paper aims to review existing solutions for smart building to increase hospitality levels in locations like hospitals. The answers could support features such as online appointments, smart navigation, and queue management in the building through mobile phone and navigation to the desired location by highlighting the point of interest and facilities and checking the spaces' occupancy. Methods: Such a solution addresses all mentioned issues regarding the smart building by integrating and utilizing various data sources collected by the internet of things (IoT) sensors. This solution mainly deals with location determining, also known as positioning, using Bluetooth Low Energy radio. The goal is to implement a low-power, low-cost indoor positioning system that utilizes existing hardware. Results: Positions determining is considered a significant section of these kinds of solutions. Previous attempts with indoor positioning systems intensify statistical fingerprinting methods, mainly using IEEE 802.11 (WLAN) as the platform. Conclusion: Some efforts have been made with purely signal strength-based positioning, but indoor environments have been shown to work inauspiciously for these kinds of methods.

Energy and Performance Analysis of Lossless Compression Algorithms for Wireless EMG Sensors.

Electromyography (EMG) sensors produce a stream of data at rates that can easily saturate a low-energy wireless link such as Bluetooth Low Energy (BLE), especially if more than a few EMG channels are being transmitted simultaneously. Compressing data can thus be seen as a nice feature that could allow both longer battery life and more simultaneous channels at the same time. A lot of research has been done in lossy compression algorithms for EMG data, but being lossy, artifacts are inevitably introduced in the signal. Some artifacts can usually be tolerable for current applications. Nevertheless, for some research purposes and to enable future research on the collected data, that might need to exploit various and currently unforseen features that had been discarded by lossy algorithms, lossless compression of data may be very important, as it guarantees no extra artifacts are introduced on the digitized signal. The present paper aims at demonstrating the effectiveness of such approaches, investigating the performance of several algorithms and their implementation on a real EMG BLE wireless sensor node. It is demonstrated that the required bandwidth can be more than halved, even reduced to 1/4 on an average case, and if the complexity of the compressor is kept low, it also ensures significant power savings.

A Versatile Hermetically Sealed Microelectronic Implant for Peripheral Nerve Stimulation Applications.

This article presents a versatile neurostimulation platform featuring a fully implantable multi-channel neural stimulator for chronic experimental studies with freely moving large animal models involving peripheral nerves. The implant is hermetically sealed in a ceramic enclosure and encapsulated in medical grade silicone rubber, and then underwent active tests at accelerated aging conditions at 100°C for 15 consecutive days. The stimulator microelectronics are implemented in a 0.6-μm CMOS technology, with a crosstalk reduction scheme to minimize cross-channel interference, and high-speed power and data telemetry for battery-less operation. A wearable transmitter equipped with a Bluetooth Low Energy radio link, and a custom graphical user interface provide real-time, remotely controlled stimulation. Three parallel stimulators provide independent stimulation on three channels, where each stimulator supports six stimulating sites and two return sites through multiplexing, hence the implant can facilitate stimulation at up to 36 different electrode pairs. The design of the electronics, method of hermetic packaging and electrical performance as well as in vitro testing with electrodes in saline are presented.

Smart, comfortable wearable system for recognizing Arabic Sign Language in real-time using IMUs and features-based fusion

Automatic sign language recognition systems have been presented in the literature to avail as a helpful device for deaf and mute individuals to incorporate them into the community without impediments. Gesture recognition is usually done by using vision-based techniques or hand-attached sensors that track hand and finger movements. This paper presents a sensors-based Arabic Sign Language recognition system. The proposed system depends on the information fusion from a 3-axis accelerometer and gyroscope Inertial Measurement Units (IMUs) sensors. The architecture of the proposed system consists of two main modules: a wearable device (glove), which includes sensors, a communication unit, and micro-controller unit, and a software module running on a mobile device. The proposed glove system utilizes six IMUs sensors where five of them placed at the fingers and the sixth sensor placed at the back of the palm. The collected data from sensors are transmitted to a mobile device through a Bluetooth low-energy wireless transmission for data analysis and gesture recognition. For each gesture, the beginning and endpoints of the significative gesture part are discovered automatically using the intensity of the gyroscope signal. The system employs a features-based sensor fusion that combines accelerometer and gyroscope time-domain and frequency-domain features. In a comprehensive set of experiments with seven participants, the system was trained and tested with 28 Arabic alphabets, and the best recognition accuracy achieved was 98.6% for the user-dependent data and 96% for the user-independent data under support vector machine classifier. The achieved results are outperforming existing systems that have been presented in recent decades for alphabet-level gesture recognition.

Design and Fabrication of Embedded Wireless Monitoring System Based on Bluetooth Low Energy Transmission for Potentiometric Sensors

A small embedded wireless monitoring system for potentiometric sensors was designed and fabricated. The system employed a dual precision op amp of TLC4502 as the preamplifier and a bluetooth low energy (BLE) chip of CC2541 as the main controller, and the main controller integrated 14 bits analog to digital convertor (ADC). The system used the BLE development application program (App) to establish a Bluetooth connection with the CC2541 for wireless real-time reading of sensing potentials. The monitoring system software was developed on the basis of a BLE-CC254X-1.41 protocol stack by the embedded development software of IAR Embedded Workbench. To verify the reliability and accuracy of the system, a precision regulated power supply was used for analog potential acquisition test, and a pH composite electrode was used for monitoring the pH change. The test results showed that the system could be applied to real time measurement of potential signals for three times amplification with an accuracy of 0.4 mV, and a consistent response to pH change was able to quickly output with a linear correlation coefficient of R2=0.9994. Furthermore, the concentration change of L-cysteine (L-cys) was monitored in real time by the BLE system with a self-made L-cys sensor, and the dynamic response change was consistent with that of commercial multimeter, indicating that the rapid transmission and real time monitoring of potentiometric signals could be well realized through the BLE wireless sensing system.

Compact Antenna in 3D Configuration for Rectenna Wireless Power Transmission Applications.

This work presents methods for miniaturizing and characterizing a modified dipole antenna dedicated to the implementation of wireless power transmission systems. The antenna size should respect the planar dimensions of 60 mm × 30 mm to be integrated with small IoT devices such as a Bluetooth Lower Energy Sensing Node. The provided design is based on a folded short-circuited dipole antenna, also named a T-match antenna. Faced with the difficulty of reducing the physical dimensions of the antenna, we propose a 3D configuration by adding vertical metallic arms on the edges of the antenna. The adopted 3D design has an overall size of 56 mm × 32 mm × 10 mm at 868 MHz. Three antenna-feeding techniques were evaluated to characterize this antenna. They consist of soldering a U.FL connector on the input port; vertically connecting a tapered balun to the antenna; and integrating a microstrip transition to the layer of the antenna. The experimental results of the selected feeding techniques show good agreements and the antenna has a maximum gain of +1.54 dBi in the elevation plane (E-plane). In addition, a final modification was operated to the designed antenna to have a more compact structure with a size of 40 mm × 30 mm × 10 mm at 868 MHz. Such modification reduces the radiation surface of the antenna and so the antenna gain and bandwidth. This antenna can achieve a maximum gain of +1.1 dBi in the E-plane. The two antennas proposed in this paper were then associated with a rectifier to perform energy harvesting for powering Bluetooth Low Energy wireless sensors. The measured RF-DC (radiofrequency to direct current) conversion efficiency is 73.88% (first design) and 60.21% (second design) with an illuminating power density of 3.1 µW/cm2 at 868 MHz with a 10 kΩ load resistor.

Construction Automatic Positioning System of a Moving Object Based on the Readings of Bluetooth Beacons and Modified Multelateration Method

The article discusses the solution to the problem positioning a movable mobile object in a controlled area. The proposed solution is based on the construction of a sensor network from Bluetooth Low Energy radio beacons in the controlled area. The interaction of the mobile device and the sensor network is proposed to be carried out via a Bluetooth communication channel of specification not lower than 5.0 by obtaining the values of the RSSI signal levels of each radio beacon. The room has its own absolute coordinate plane. According to the multilateration method, each triplet of beacons forms its own relative coordinate plane. The developed algorithm also considers the issue of converting relative coordinates to absolute ones. At the end of the study, a description is given of an experimental study on positioning a mobile phone in a 5 by 10-meter room.

Uric acid mouthpiece biosensor integrated with Bluetooth low energy wireless module for salivary uric acid measurement

Uric acid mouthpiece biosensor integrated with Bluetooth low energy wireless module for salivary uric acid measurement

A Multi-Channel Electromyography, Electrocardiography and Inertial Wireless Sensor Module Using Bluetooth Low-Energy

This paper proposes a wireless sensor device for the real-time acquisition of bioelectrical signals such as electromyography (EMG) and electrocardiography (ECG), coupled with an inertial sensor, to provide a comprehensive stream of data suitable for human activity detection, motion analysis, and technology-assisted nursing of persons with physical or cognitive impairments. The sensor is able to acquire up to three independent bioelectrical channels (six electrodes), each with 24 bits of resolution and a sampling rate up to 3.2 kHz, and has a 6-DoF inertial platform measuring linear acceleration and angular velocity. The bluetooth low-energy wireless link was chosen because it allows easy interfacing with many consumer electronics devices, such as smartphones or tablets, that can work as data aggregators, but also imposes data rate restrictions. These restrictions are investigated in this paper as well, together with the strategy we adopted to maximize the available bandwidth and reliability of the transmission within the limits imposed by the protocol.

Reducing Power Consumption in Smart Monitoring Systems with BLE Wireless Technology

This research focuses on alternative low power consumption in smart monitoring systems and on various techniques to facilitate access to different monitoring sensors connected via Bluetooth Low Energy (BLE). Due to high complexity and power demands that new smart monitoring equipment have, the need for reduced power consumption in the context of new regulations/architectures for the Internet of Things has occurred. Sensors can have dimensions of a few centimeters, are not required to have cabling or power supply and can transmit data for a long period of time. A network of sensors connected through BLE wireless technology with a corresponding architecture can provide a simple and versatile solution to multiple environments that need to be monitored. Data provided by the smart monitoring systems must be carried and analyzed either in upper layers of the network or close to the edge. Dedicated applications allow users to access data via smart-devices and data can be downloaded on any device, such as mobile phones. All these require communication technologies with optimized and reduced power consumption, also increasing battery lifetime and becoming more eco-friendly.

Method of indoor navigation and collaborative semi-automatic Wi-Fi radiomap construction

Introduction:An important and complicated problem related to the multilateration of Wi-Fi or Bluetooth Low Energy signals as well as Wi-Fi fingerprinting is the procedure of infrastructure adjustment which includes Wi-Fi radio map construction and Wi-Fi or Bluetooth Low Energy radio signal path loss model calibration.Purpose:Developing a method for navigation and Wi-Fi radio map construction, which would provide user’s indoor navigation, Bluetooth Low Energy path loss model calibration and Wi-Fi radio map collaborative semi-automatic construction.Results:The paper presents a collaborative semi-automatic Wi-Fi radio map construction method based on the combination of Bluetooth Low Energy multilateration, Wi-Fi fingerprinting, Wi-Fi radio map collaborative semiautomatic construction procedure and semi-automatic Bluetooth Low Energy path loss model calibration. For the semi-automatic calibration procedure of the Bluetooth Low Energy signal propagation model and for the method of collaborative semi-automatic construction of Wi-Fi radio map and indoor navigation, a calibration algorithm and an algorithm of collaborative semi-automatic construction of Wi-Fi radio map and indoor navigation were proposed, respectively. A mobile application has been developed which implements the proposed algorithms in order to test them and analyze the results.Practical relevance:The proposed method allows you to avoid time-consuming procedures of constructing a map of Wi-Fi radio signals and semi-automatic calibration of Bluetooth Low Energy signal propagation in the offline phase.

An implementation of IoT-based microwave sensing system for the evaluation of tissues moisture

Internet-of-Things (IoT) is no longer just a buzzword. “Things” that are immensely connecting to the Internet, are now creating “Smart” systems. However, heterogeneous devices and the dominance of propriety protocols are still the major challenges for practical application of such systems. This research work presents a practical application of a real-time microwave sensing system for the evaluation of tissues moisture. The work addresses two major challenges; first, the use of a highly sensitive microwave sensor to determine tissue moisture; second, to share the measurement with the remote users through an IoT-based system over the Bluetooth low-energy radio using open standards and protocols. The prototype shows significant changes in its resonance frequency, return loss and bandwidth (5.5%–26%) for the measured moisture content, which is also validated. This implementation demonstrates the feasibility of real-time monitoring of food quality. It also enables data-analytics that may help the industries to improve product quality, supply-chain and predicts demand in a more effective manner.