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![BLE frequency channels. It can be noticed that channels from 0-36 are assigned to data transmission in connections (blue), while the three remaining channels, from 37-39, are used as advertising channels, shown in orange. How channels are positioned in the frequency band is shown in the x-axis: the first channel, 37, is centered at frequency 2402 MHz, while the last one, the 39th, is centered at 2480 MHz. Adapted from [48].](profile/Jacopo-Tosi/publication/321800210/figure/fig3/AS:571500030054400@1513267633955/BLE-frequency-channels-It-can-be-noticed-that-channels-from-0-36-are-assigned-to-data.png)
BLE frequency channels. It can be noticed that channels from 0-36 are assigned to data transmission in connections (blue), while the three remaining channels, from 37-39, are used as advertising channels, shown in orange. How channels are positioned in the frequency band is shown in the x-axis: the first channel, 37, is centered at frequency 2402 MHz, while the last one, the 39th, is centered at 2480 MHz. Adapted from [48].
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Small, compact and embedded sensors are a pervasive technology in everyday life for a wide number of applications (e.g., wearable devices, domotics, e-health systems, etc.). In this context, wireless transmission plays a key role, and among available solutions, Bluetooth Low Energy (BLE) is gaining more and more popularity. BLE merges together good...
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Wearable devices used to monitor patients are classified as part of mobile health, one of the branches of e-health. They are widely used to monitor the vital signs of patients outside of the health institutions environment. The aim of this paper is to design a device that can be worn at low cost and of small size to provide comfort to the patient....
Citations
... Sensor applications include proximity-based access control [37], motion tracking [38], noise monitoring [39], and medical sensors [40], to only name a few examples. Tosi presented an extensive study of the BLE performance [41]. While data rates of BLE are often lower in practice than in theory, they generally enable low-power communication. ...
Wild and forest fires pose a threat to forests and thereby, in extension, to wild life and humanity. Recent history shows an increase in devastating damages caused by fires. Traditional fire detection systems, such as video surveillance, fail in the early stages of a rural forest fire. Such systems would see the fire only when the damage is immense. Novel low-power smoke detection units based on gas sensors can detect smoke fumes in the early development stages of fires. The required proximity is only achieved using a distributed network of sensors interconnected via 5G. In the context of battery-powered sensor nodes, energy efficiency becomes a key metric. Using AI classification combined with XAI enables improved confidence regarding measurements. In this work, we present both a low-power gas sensor for smoke detection and a system elaboration regarding energy-efficient communication schemes and XAI-based evaluation. We show that leveraging edge processing in a smart way combined with buffered data samples in a 5G communication network yields optimal energy efficiency and rating results.
... Similarly, several approaches have been proposed in the literature concerning the assessment of data transmission engines based on BLE in order to ensure reliability and efficiency across various applications. Numerous studies have investigated different aspects of BLE-based data transmission in order to understand its limitations and improve its capabilities [12]. Gomez et al. [13] focused on optimizing the piconet size, i.e., the maximum number of peripheral nodes that can be linked to a single central node. ...
In today’s health-monitoring applications, there is a growing demand for wireless and wearable acquisition platforms capable of simultaneously gathering multiple bio-signals from multiple body areas. These systems require well-structured software architectures, both to keep different wireless sensing nodes synchronized each other and to flush collected data towards an external gateway. This paper presents a quantitative analysis aimed at validating both the wireless synchronization task (implemented with a custom protocol) and the data transmission task (implemented with the BLE protocol) in a prototype wearable monitoring platform. We evaluated seven frequencies for exchanging synchronization packets (10 Hz, 20 Hz, 30 Hz, 40 Hz, 50 Hz, 60 Hz, 70 Hz) as well as two different BLE configurations (with and without the implementation of a dynamic adaptation of the BLE Connection Interval parameter). Additionally, we tested BLE data transmission performance in five different use case scenarios. As a result, we achieved the optimal performance in the synchronization task (1.18 ticks as median synchronization delay with a Min-Max range of 1.60 ticks and an Interquartile range (IQR) of 0.42 ticks) when exploiting a synchronization frequency of 40 Hz and the dynamic adaptation of the Connection Interval. Moreover, BLE data transmission proved to be significantly more efficient with shorter distances between the communicating nodes, growing worse by 30.5% beyond 8 m. In summary, this study suggests the best-performing network configurations to enhance the synchronization task of the prototype platform under analysis, as well as quantitative details on the best placement of data collectors.
... These devices can be connected using IEEE 802.15.4, Bluetooth Low Energy (BLE) [28], Zigbee [29], Low Power Wi-Fi, or wired connections. Because LLNs have the ability to gather data from the physical environment and transmit it to a central location, they are regarded as key enablers of Internet of Things [30]. ...
... In Fig. 18(d), the connected nodes in the network are shown, which indicates that the proposed method maintains more sensor nodes. According to the network lifetime, the proposed method reaches 1646 iterations, which is, 23.15 percent increase over Zhou et al. deployment,28.43 percent improvement over random deployment, and 14.16 percent improvement over line deployment. ...
... It is intended for short-range communication with minimal power consumption. Applications including wearable technology, asset tracking, and smart home systems frequently use BLE [55]. Z-Wave is a wireless communication protocol that operates in the sub-GHz frequency range. ...
Federated learning (FL) is a machine learning (ML) technique that enables collaborative model training without sharing raw data, making it ideal for Internet of Things (IoT) applications where data are distributed across devices and privacy is a concern. Wireless Sensor Networks (WSNs) play a crucial role in IoT systems by collecting data from the physical environment. This paper presents a comprehensive survey of the integration of FL, IoT, and WSNs. It covers FL basics, strategies, and types and discusses the integration of FL, IoT, and WSNs in various domains. The paper addresses challenges related to heterogeneity in FL and summarizes state-of-the-art research in this area. It also explores security and privacy considerations and performance evaluation methodologies. The paper outlines the latest achievements and potential research directions in FL, IoT, and WSNs and emphasizes the significance of the surveyed topics within the context of current technological advancements.
... Under AFH, the master device maintains a 40-bit channel-map bit vector where the value of each bit represents the condition of the corresponding communication channel. Having a '1' bit means the corresponding channel is in good condition, while having a '0' bit implies the presence of interference on that channel [4]. This information allows masters to avoid channels with poor conditions intelligently during their hopping sequence. ...
The proliferation of Bluetooth Low Energy (BLE) in diverse applications has led to a dense clustering of piconets in confined spaces. BLE operates within the congested 2.4GHz ISM band, shared by numerous short-range wireless protocols. Frequency hopping and Adaptive Frequency Hopping (AFH) mechanisms have been introduced in Bluetooth to reduce interference with other protocols in the same band. However, research shows these mechanisms are ineffective in reducing inter-piconet interferences. These studies have demonstrated the relationship between the number of piconets and the level of interference. In this paper, we investigate the relationship between the similarity of channel maps and the number of neighboring piconets in interference intensity. Then, we present a light and practical coordination framework to address this challenge. Our solution employs a BLE gateway to detect its surrounding piconet masters and computes a better channel map to reduce the impact of inter-piconet interferences. We also introduce the Isolated Channels (ICA) algorithm for channel allocation of neighboring piconets with controlled channel overlaps for BLE5. Simulation results show a 20 to 60% reduction of interference level in environments with high to moderate inter-piconet interferences. To the best of our knowledge, this is the first practical BLE5-compatible solution for mitigating the inter-piconet interference problem and does not require modifying the standard stack.
... These designs are characterized by extended battery life, facilitated through the incorporation of high-efficiency switching converters, energy-efficient components, and streamlined firmware. Bluetooth Low Energy (BLE) is employed as the communication protocol to optimize energy usage during wireless data transmission [10]. The initial version of the stethoscope features a single microphone, while the second iteration employs dual microphones to capture a broader range of acoustic information. ...
p>This study introduces a cutting-edge digital stethoscope optimized for remote health monitoring. Integrating Micro-Electromechanical Systems (MEMS) microphones with Bluetooth Low Energy (BLE) 5, the device ensures high-fidelity, real-time audio transmission. It seamlessly connects to an Internet of Things (IoT) platform through an embedded system, highlighting its potential in remote healthcare scenarios, especially during global health emergencies. Advanced features encompass Active Noise Cancellation, extended battery life, and intricate internal sound filtration. Paired with a dedicated Android application, the stethoscope streamlines the capture, storage, and visualization of auscultation data. Crucially, its integration with Electronic Health Records (EHRs) and its capability to generate vast datasets can significantly advance diagnostic precision, leveraging Digital Signal Processing and Artificial Intelligence methodologies. </p
... These designs are characterized by extended battery life, facilitated through the incorporation of high-efficiency switching converters, energy-efficient components, and streamlined firmware. Bluetooth Low Energy (BLE) is employed as the communication protocol to optimize energy usage during wireless data transmission [10]. The initial version of the stethoscope features a single microphone, while the second iteration employs dual microphones to capture a broader range of acoustic information. ...
p>This study introduces a cutting-edge digital stethoscope optimized for remote health monitoring. Integrating Micro-Electromechanical Systems (MEMS) microphones with Bluetooth Low Energy (BLE) 5, the device ensures high-fidelity, real-time audio transmission. It seamlessly connects to an Internet of Things (IoT) platform through an embedded system, highlighting its potential in remote healthcare scenarios, especially during global health emergencies. Advanced features encompass Active Noise Cancellation, extended battery life, and intricate internal sound filtration. Paired with a dedicated Android application, the stethoscope streamlines the capture, storage, and visualization of auscultation data. Crucially, its integration with Electronic Health Records (EHRs) and its capability to generate vast datasets can significantly advance diagnostic precision, leveraging Digital Signal Processing and Artificial Intelligence methodologies. </p
... Thus, the synchronized and stable transmission of multi-sensor data becomes a research challenge [14]. BLE technology is widely employed in various short-range wireless communication applications, including human motion capture systems, due to its low power consumption and high transmission rate [24]. Among these applications, the AFH (adaptive frequency hopping) ...
Wearable motion-capture systems offer promising avenues for human lower limb rehabilitation. However, unstable data transmission and attitude estimation challenge their practical application. Aiming at this problem, a reliable method utilizing wearable inertial sensors for rehabilitation applications is innovatively proposed and implemented within our designed wearable motion-capture systems tailored to patients with impaired lower limbs. A stable data transmission process based on star-type Bluetooth body sensor networks is designed by establishing a connection parameter setting method to guarantee reliable attitude estimation. Then, a robust attitude estimating method based on an improved gradient descent method is proposed to promote the anti-interference capability of the algorithm by introducing trust coefficients. Lower limb motion-capture experiments are conducted, and results show that the proposed method enables the system to maintain a package loss rate of no more than 0.24% and has a maximum coefficient of variation (CV) of 5.9% during the data transmission process. Attitude estimation reliability experiments reveal that the proposed algorithm substantially enhances anti-interference capabilities while preserving estimation accuracy. Compared to the state-of-the-art method, under acceleration shock, estimation errors decrease by up to 39.1% (roll), 42.9% (pitch), and 20.2% (yaw). When exposed to external magnetic field interference, conventional estimation algorithms falter, whereas the proposed method maintains an average error within 2°. Significance analysis underscores the method’s distinctiveness at the 0.05% significance level (
${p}< {0.05}$
). This study effectively bridges the gap between wearable inertial motion-capture systems and their application in clinical lower limb rehabilitation.
... 11 These past studies focus on the performance of perovskite cells at low levels of incident intensity in the range of <1 mW/cm 2 typical of ambient indoor lighting. 5 At low levels of illumination, however, the resulting power harvested by a perovskite cell remains at the ∼100 μW/cm 2 level-insufficient to satisfy the requirements of many internet of things (IoT) devices that demand 10-100 mW for wireless communication (e.g., Bluetooth low energy 12,13 ). Although intermittent sensing and communication combined with energy storage can extend the capabilities of these low-power systems, 5 multifunctional systems with enhanced computing and sensing functionality will demand higher power levels than can be achieved with ambient light. ...
Metal halide perovskites are a promising photovoltaic technology for energy harvesting due to their potential for low cost via high-speed manufacturing and their flexible light form factors offering high power per weight. This study presents an investigation of the energy harvesting performance of perovskite solar cells under monochromatic illumination via finite element simulations and experimental validation with high-efficiency double cation perovskite solar cells. Device performance across a broad range of illumination intensity is analyzed, providing insights into the mechanisms limiting energy harvesting in medium- and long-range wireless power transfer. The simulations also provide a guideline for compositional engineering of wide bandgap perovskites to improve the spectral match to efficient monochromatic sources. Based on these results, we show how perovskite solar cells can become a platform for efficient (>33%) medium-range wireless power transfer at the 5–50 m scale for power levels of 1 mW to 1 W.
... With the recent development of the Internet of Things (IoT) 1,2 and edge computing 3,4 technologies, the individual power source for electric devices including wireless communication for transmit sensed data with ZigBee, Bluetooth low energy (BLE), and Bluetooth classic devices are needed for more feasible deployment. The process of signal transmission consumes less than 600 mW in a Bluetooth classic device 5 , less than 100 mW in a ZigBee device 6,7 , and less than 30 mW in a BLE device [7][8][9][10][11] . Therefore, a PV system must generate at least 30 mW of power to operate a BLE device; however, most IoT devices are installed indoors, where light is dim and diffused. ...
Demand is increasing for photovoltaics (PVs) as a result of the development of the Internet of Things and edge computing technologies. As the lighting environment is different for the applications, thus, PVs must be adjustable to various light environments in which systems are installed. PVs should therefore be capable of easily changing their morphology without damaging the cells. To address this problem, in this work, a three-dimensional (3D) structure that increases power output under omnidirectional light was applied to a crystalline silicon solar cell array using a block-type method. The resultant block-type 3D indoor PV could operate a Bluetooth low-energy module in conjunction with a power management integrated circuit when the illuminance was 532 lx and 1620 lx and each PV installation area was 129.9cm² and 32.48 cm² respectively.
