Bluetooth Devices Research Articles

Performing DoS Attacks on Bluetooth Devices Paired with Google Home Mini

Performing DoS Attacks on Bluetooth Devices Paired with Google Home Mini

Toward Zero: Power consumption trends in low data rate wireless connectivity

The low power IoT market began in earnest in 1999 with the launch of the first commercial Bluetooth device. In 2021, IoT Analytics Research, a market research firm, predicted <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> a yearly 22% growth rate in the global IoT market over the next three years. By 2025, the installed base of active IoT gateways is expected to be 27 billion, not including laptops, tablets, and cellphones. In this projection, gateways are counted, not every sensor. Therefore, the number of connected radios in 2025 is going to be higher than the forecast of 27 billion, perhaps much higher. The IoT market is likely to continue growing past 2025, but this growth rate is unsustainable with today’s technology. This article discusses three limitations to IoT market growth: power, cost, and performance. Examples of innovations needed to enable the predicted market growth will be presented in each area. At the end, a prediction for IoT wireless nodes in the coming decade is presented.

Outdoor Navigation Using Bluetooth Angle-of-Arrival Measurements

The introduction of direction finding in the Bluetooth standard enabled the use of antenna arrays for locating Bluetooth devices, using carrier phase measurements to estimate the direction from the array to a moving device. In this work, this feature is utilized for outdoor localization. We show how using repeated measurements from all array elements, instead of only the initial single-element reference samples as often suggested, can contribute to an improved estimate of the signal&#x2019;s unknown carrier frequency offset, thereby improving the direction estimation performance. To run the direction-of-arrival estimation in real-time with high angular resolution on an embedded computer we propose a pseudo-spectrum peak search strategy that combines a coarse search, where the resolution is decided based on the array&#x2019;s main lobe width, with a local nonlinear optimization for estimate refinement. We consider practical aspects relating to the phase sampling configuration and demonstrate direction estimation at up to 700m range with insignificant packet loss within 500m, and without significant loss of angular precision even when the received signal is near the receiver&#x2019;s signal strength sensitivity threshold. In an open outdoor environment, using a square antenna array with 12 elements, the azimuthal performance is found to be very consistent with range, with noise standard deviation typically around 1&#x00B0;. While the elevation is significantly affected by multipath at lower elevation angles, with visible disagreement between frequency channels, it is shown to be consistent with simulations of ground reflection multipath.

The Potential of Harnessing Real-Time Occupancy Data for Improving Energy Performance of Activity-Based Workplaces

Currently, the available studies on the prediction of building energy performance and real occupancy data are typically characterized by aggregated and averaged occupancy patterns or large thermal zones of reference. Despite the increasing diffusion of smart energy management systems and the growing availability of longitudinal data regarding occupancy, these two domains rarely inform each other. This research aims at understanding the potential of employing real-time occupancy data to identify better cooling strategies for activity-based-working (ABW)-supportive offices and reduce the overall energy consumption. It presents a case study comparing the energy performance of the office when different resolutions of occupancy and thermal zoning are applied, ranging from the standard energy certification approach to real-time occupancy patterns. For the first time, one year of real-time occupancy data at the desk resolution, captured through computer logs and Bluetooth devices, is used to investigate this issue. Results show that the actual cooling demand is 9% lower than predicted, unveiling the energy-saving potential to be achieved from HVAC systems for non-assigned seating environments. This research demonstrates that harnessing real-time occupancy data for demand-supply cooling management at a fine-grid resolution is an efficient strategy to reduce cooling consumption and increase workers’ comfort. It also emphasizes the need for more data and monitoring campaigns for the definition of more accurate and robust energy management strategies.

A Stretchable and Self-Healing Hybrid Nano-Generator for Human Motion Monitoring.

Transparent stretchable wearable hybrid nano-generators present great opportunities in motion sensing, motion monitoring, and human-computer interaction. Herein, we report a piezoelectric-triboelectric sport sensor (PTSS) which is composed of TENG, PENG, and a flexible transparent stretchable self-healing hydrogel electrode. The piezoelectric effect and the triboelectric effect are coupled by a contact separation mode. According to this effect, the PTSS shows a wide monitoring range. It can be used to monitor human multi-dimensional motions such as bend, twist, and rotate motions, including the screw pull motion of table tennis and the 301C skill of diving. In addition, the flexible transparent stretchable self-healing hydrogel is used as the electrode, which can meet most of the motion and sensing requirements and presents the characteristics of high flexibility, high transparency, high stretchability, and self-healing behavior. The whole sensing system can transmit signals through Bluetooth devices. The flexible, transparent, and stretchable wearable hybrid nanogenerator can be used as a wearable motion monitoring sensor, which provides a new strategy for the sports field, motion monitoring, and human-computer interaction.

Analysis of specific absorption rate and heat transfer in human head due to mobile phones

The human body absorbs a particular proportion of radiation when introduced to an electromagnetic field. The proportion of radio repeat energy burned-through in a unit mass of a human body when introduced to a radio frequency electromagnetic field is known as the Specific Absorption Rate and is alluded to as SAR. The position and bearing of the human body concerning the wellspring of the radiation impact the SAR regard. The sort of wellspring of the RF energy moreover impacts the SAR regard. This paper-based on how Mobile phones and there are arranged while simultaneously using them contribute and impact the value of SAR. Moreover, it is seen that SAR contributed by mobile phones is higher than other RF sources like Bluetooth and Wi-Fi Devices. This is a result of the way that the yield power transmitted by cells is higher than Bluetooth and Wi-Fi contraptions. As SAR is the proportion of electromagnetic power held over a specific volume of tissue, it is directly comparative with the strength of the electromagnetic field. Consequently, cells have higher Specific Absorption Rates when diverged from Bluetooth and Wi-Fi devices. SAR spatially shows up at the midpoint of over 1 g or 10 g of human tissue. Maxwell's field conditions in time–space are used to register the SAR movement in the human head. Charged particles gain energy and falter when electromagnetic radiation is the event on the issue. The energy gained could either be immediately reradiated and appear as scattered, reflected, or sent radiation or it may get into minuscule developments inside the matter, accomplishing warm concordance and setting out a decent establishment for itself as atomic power in the material. Temperature assessed over 1 g of tissue is higher when appeared differently in relation to 10 g volume of tissue. Muscle and blood have the temperature rise lower than the skin on account of skin significance. It is seen that when the significance of invasion grows SAR reduction and thusly temperature lessens.

Sensing and analysis of spectrum holes in ISM band using USRP testbed

The spectrum frequency in the wireless communication industry is getting great attention due to the internet of things (IoT) technology's growth. However, the radio spectrum's frequency band use is limited because the primary user for specific services can cause spectrum interference as multiple users use the same spectrum frequency. Meanwhile, at each spectrum frequency, the number of users and utilization time are distinct. These will create vacancies for spectrum frequency assigned to the primary user. A new alternative in using the cognitive radio (CR) spectrum is accessible to these vacancies. This paper analyzed the frequency spectrum in the industrial, scientific and medical (ISM) band and identified spectrum holes for transmission by the secondary users. This work employed a realistic approach by measuring the spectrum using Universal Software Radio Peripheral (USRP) devices. Thus, the spectrum holes in the frequency spectrum had distinguished by using an energy detection technique. In the energy detection technique, the threshold energy level is set and then compared with the energy detector output to identify the primary user's existence (PU). The result indicates that 0.61% of spectrum holes have been detected in the 2.43-2.44 GHz range. This range is sufficient for home appliances, radio frequency peripherals (RF), and bluetooth devices.

Sistem Konfigurasi Otomatis Pada Pengendalian Nirkabel Dengan Pendekatan Context-Aware Pada Rumah Pintar

A house consists of several rooms with electronic devices inside of it. Each device has a remote control or a button to control it. With technologies have been increasing rapidly, we can control home appliances easily with our Android smartphone. However, thiscan make user uncomfortable to control, if all the devices appear simultaneously in one screen. Therefore,this project aims to develop an automatic configuration remote control system which adapts to the situation of the room to be controlled. Using Bluetooth technology in smartphone for transfering data. Usually to connect to a Bluetooth device,usermanually chooses one of the Bluetooth devicenames from the list that appears from the scan results. Therefore, the focus of this project is to develop a wireless control system that is capable of performing automatic configurationsthat suit the situation of the room. This system usesa localization method that utilizes the signal strength that Bluetooth receives or RSSI Bluetooth.The testing result of the system are able to perform automatic configuration where the system is automatically connected to the nearest room without the need for prior settings and adjust the control menu according to the situation of the room.

Rancang Bangun Sistem Pemonitor Gelombang Otak Nirkabel Berbasis Mikrokontroler

Humans are a very complex living system composed of billions of active cells working together to form tissues. The neural network that is awakened has an information transmission system based on the body's electricity or bioelectricity. All surfaces of the human skin and body parts have electrical properties and impedance that can be detected to indicate health conditions. In the biomedical field the measurement of bioelectric signals becomes one of the important aspects. Bioelectric measurements to monitor heart conditions are known as ECG (Electrocardiography), EMG (muscle electromyography), ENG (nerve electroneurography). Signals from the brain are detected from electroenchepalography (EEG) signal parameters. The study was developed by a sensor system capable of noninvasive brain waves and and capable of sending signals wirelessly through RF radio waves in real-time. The device is built using a TGAM sensor, a microcontroller interface, Bluetooth device, and the LabView application. Tests were carried out to measure the range and frequency range of the EEG. The object of measurement is a human being conditioned to some state of mind. The results show that the wireless EEG signal detection system using Bluetooth transmission has been able to transmit sensor data well, without delay and can connect automatically with Arduino. The detection results can be monitored directly on the GUI display of the LabView software and a graph of the frequency range can be seen.

A 2.4 GHz 87 μW low-noise amplifier in 65 nm CMOS for IoT applications

As the Bluetooth devices for the internet of things require extremely low-power dissipation to maintain longer battery life, a low-noise amplifier (LNA) as the main power-consuming part in the circuit needs more current-efficient topologies on power saving. This paper proposes a low-noise transconductance amplifier that combines the techniques of passive impendence transformation, [Formula: see text]-boosting technique, and current reuse, leading to a low power under the 1.2 V power supply. The transformer-based [Formula: see text]-boosted structure is applied in the four-transistor-stacked current-reuse topology leading to a [Formula: see text] power saving. The proposed LNA simulated in 65 nm CMOS shows the NF of 3.3 dB and the IIP3 of −8 dBm, respectively, while dissipating 87 [Formula: see text]W dc power. Compared to the previous low-power LNA, this design has fairly low-power consumption and low NF while other performance metrics remain competitive.

Dual Controlled Smart Wheelchair for Physically Disabled

There are many different types of wheel chairs on the market, some of which are manual, some of which are semi-automatic, and some of which are totally automatic. The development of the wheel chair system is carried out on a daily basis in order to provide support to differently abled people. In this regard, our smart wheel chair system is likewise a work in progress. Provide assistance to this group of people. The goal of this project is to create a Smart Wheel Chair System for the physically challenged. Handicapped persons at a reasonable price. An Android messenger application controls the system, which consists of for navigating aid, use the HC-06 Bluetooth module and proximity sensor. Our wheel chair system is linked to a Bluetooth module, which allows it to automatically move to the desired horizontal position. The system is controlled by an Android application. We used G-chat to link the Wheel Chair to the Bluetooth module at work, but any Bluetooth messenger application can be utilized. Two proximity sensors are installed at the back and front of the system to safeguard it from collisions. Our wheel chair assembly has a dual password security system, with the first password needed to connect the Bluetooth device and the second password used to control the wheel chair's movement.

Multi-robot formation based on RSSI power level and radiation pattern

This paper studies a formation control scheme to achieve a ‘dispersion’ of a group of robots using the Received Signal Strength Indication (RSSI) measurements of their on-board wireless nodes as feedback signals and their antenna radiation patterns (which is not omnidirectional in most of the cases) as a distance sensor between pairs of robots. In this sense, the multi-robot coordination evolves from a distance formation control to a power-based dispersion strategy. Thus, with the use of feedback through RSSI levels, the heading angle between the agents and the differences of its orientation angles, the control law becomes decentralised, avoiding the need of distance sensors. The result applies to a group of robots with a directed spanning tree topology, with root in the leader and the rest of followers are formed with respect to a unique local leader. The approach considers distinct radiation patterns found in Bluetooth or WiFi communication devices. As the approach ensures the convergence to desired values of RSSI, then a connectivity between the wireless nodes can be adjusted to maintain a desired communication data rate and wireless coverage by the robots posture. Simulations and real-time experiments illustrate the performance of the system.

Development of an inline inspection robot for the detection of pipeline defects

PurposeThe purpose of this study is to develop a robot for non-destructive testing of the pipelines to improve its reliability and reduce the loss of products due to cracks, corrosions, etc.Design/methodology/approachIn this study, an inline inspection robot was developed for crack and corrosion detection in the pipeline. The developed robot consists of ultrasonic sensors to avoid obstacles, a visual aid with high resolution to view real time images and colour sensors for corrosion detection. The Autodesk inventor software was used for the drafting and solid modelling of the robot. A dummy pipe of 500 mm diameter and 2,000 mm length with induced cracks and corrosion was fabricated to test the robot. The colour sensors placed at each side of the robot were used to detect corrosion in the dummy pipe whilst the image processing was done to analyse the crack, as well as the type and depth of corrosion present in the dummy pipe.FindingsThe results obtained show the ability of the developed robot to detect cracks and determine the crack growth in the pipeline in addition to its ability to determine corrosion.Practical implicationsHence, the study provides a diagnostic tool for detecting pipeline defects and analysing the extent of defects to determine the fatigue rate and the useful life of the pipeline.Originality/valueThe novelties of this study is based on the fact that it was designed to avoid obstacles and check for cracks, leakage and corrosion in pipelines autonomously. It has visual aid that makes it possible to see the interior of the pipe. This makes it easier to identify the defect and the location of the defects before a catastrophic failure. The device is also equipped with sensors, which can detect defects and send the signal to a control system, as well as a Bluetooth device so the operator can have real time information about the state and integrity of the pipelines. The system is also integrated with a Bluetooth device, which permits its compatibility with Android and other mobile applications. Thus, the enabled user can send a command to query the state of the pipeline at any location with the feedback received in the form of short message service. Hence, this study offers contribution in the development of an independent (self-governing) system with the capability to autonomously detect defects in pipe walls and effectively communicate feedback to the authorised users. The prototype model for the evaluation of pipeline integrity will bring about a more proactive way to detect pipeline defects so that effort can be geared towards its restoration before it becomes a major problem, which will subsequently affect productivity and incur losses.

Predicting Depressive Symptom Severity Through Individuals' Nearby Bluetooth Device Count Data Collected by Mobile Phones: Preliminary Longitudinal Study.

BackgroundResearch in mental health has found associations between depression and individuals’ behaviors and statuses, such as social connections and interactions, working status, mobility, and social isolation and loneliness. These behaviors and statuses can be approximated by the nearby Bluetooth device count (NBDC) detected by Bluetooth sensors in mobile phones.ObjectiveThis study aimed to explore the value of the NBDC data in predicting depressive symptom severity as measured via the 8-item Patient Health Questionnaire (PHQ-8).MethodsThe data used in this paper included 2886 biweekly PHQ-8 records collected from 316 participants recruited from three study sites in the Netherlands, Spain, and the United Kingdom as part of the EU Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) study. From the NBDC data 2 weeks prior to each PHQ-8 score, we extracted 49 Bluetooth features, including statistical features and nonlinear features for measuring the periodicity and regularity of individuals’ life rhythms. Linear mixed-effect models were used to explore associations between Bluetooth features and the PHQ-8 score. We then applied hierarchical Bayesian linear regression models to predict the PHQ-8 score from the extracted Bluetooth features.ResultsA number of significant associations were found between Bluetooth features and depressive symptom severity. Generally speaking, along with depressive symptom worsening, one or more of the following changes were found in the preceding 2 weeks of the NBDC data: (1) the amount decreased, (2) the variance decreased, (3) the periodicity (especially the circadian rhythm) decreased, and (4) the NBDC sequence became more irregular. Compared with commonly used machine learning models, the proposed hierarchical Bayesian linear regression model achieved the best prediction metrics (R2=0.526) and a root mean squared error (RMSE) of 3.891. Bluetooth features can explain an extra 18.8% of the variance in the PHQ-8 score relative to the baseline model without Bluetooth features (R2=0.338, RMSE=4.547).ConclusionsOur statistical results indicate that the NBDC data have the potential to reflect changes in individuals’ behaviors and statuses concurrent with the changes in the depressive state. The prediction results demonstrate that the NBDC data have a significant value in predicting depressive symptom severity. These findings may have utility for the mental health monitoring practice in real-world settings.

PENERAPAN WIRELESS COMUNICATION HC-05 PADA MODEL KENDALI ECOSYSTEM (EVAPORATIVE COOLER SYSTEM)

Abstract The interconnectedness of the times includes all aspects, one of which is the temperature of the earth which is getting warmer, the annual prediction of increasing by 1 ° to 1.5 ° Celsius. In addition, there are technological updates with ideas that are a daily necessity. Evaporative Cooler is a conventional air conditioner throughout the world with various types and types, DEC (Direct evaporative Cooler), for example works by converting sensible heat into latent heat, whose main circuit consists of an electric motor, swing cooler motor and 24V DC water pump, a actuator module used in the implementation of this system. The idea that came up was that not many people paid attention to the system its use. This research will apply one of the wireless communication, namely the Bluetooth HC-05 Module in the control model design using ECOSYSTEM (Evaporative Cooler System) where the input is integrated with an artificial application installed on a smartphone with Bluetooth devices in it with the android operating system so that it can communicate between systems. Focusing on the communication performance applied by the HC-05 with a 2.4GHz frequency as a receiver or sender of commands with a range of signal distances that can be given, equipped with an Arduino UNO ATMega328 microcontroller for core system controllers. Over-the-air communication model that does not require other media devices in the process of working. Measurement of the performance of the signal coverage is proven horizontally and vertically, intended because there is a difference in the capture power of the transceiver and receiver signals as well as the conditions when bluetooth is controlled, it is connected and not yet connected. In the test, bluetooth only captures two conditions when it is working, when it is still affordable, bluetooth will connect and remain connected with a delay of not more than 0.02 seconds or not connected at all when the range is getting farther.

Autonomous metering system for monitoring water consumption

Abstract Faced with water scarcity and its rising costs, it is necessary to use it in a rational way. This study proposes the development of an autonomous system of water monitoring in condominiums (smart houses), through meters that use turbine flow sensors and ZigBee technology for sending data to a coordinator, allowing monitoring of the consumption at various points of a building in almost real time. Users can read the consumed volume using a smartphone application. This stimulates a more rational way of using water, besides enabling alerts for leaks in pipes, faucets, showers and toilets. The accuracy of this sensor was compared with a mechanical flow meter and an ultrasonic sensor in the laboratory, all presenting errors smaller than 10% of readings for water flow above 2 L/min. The quality of the ZigBee network was analysed, in terms of interference with Wi-Fi, Bluetooth devices and a microwave oven, to assess if there are data losses in the sensor network and only Bluetooth caused losses, showing robustness in the combined ZigBee and Wi-Fi.

The Effect of Real-World Interference on CNN Feature Extraction and Machine Learning Classification of Unmanned Aerial Systems

Small unmanned aerial systems (UASs) present many potential solutions and enhancements to industry today but equally pose a significant security challenge. We only need to look at the levels of disruption caused by UASs at airports in recent years. The accuracy of UAS detection and classification systems based on radio frequency (RF) signals can be hindered by other interfering signals present in the same frequency band, such as Bluetooth and Wi-Fi devices. In this paper, we evaluate the effect of real-world interference from Bluetooth and Wi-Fi signals concurrently on convolutional neural network (CNN) feature extraction and machine learning classification of UASs. We assess multiple UASs that operate using different transmission systems: Wi-Fi, Lightbridge 2.0, OcuSync 1.0, OcuSync 2.0 and the recently released OcuSync 3.0. We consider 7 popular UASs, evaluating 2 class UAS detection, 8 class UAS type classification and 21 class UAS flight mode classification. Our results show that the process of CNN feature extraction using transfer learning and machine learning classification is fairly robust in the presence of real-world interference. We also show that UASs that are operating using the same transmission system can be distinguished. In the presence of interference from both Bluetooth and Wi-Fi signals, our results show 100% accuracy for UAV detection (2 classes), 98.1% (+/−0.4%) for UAV type classification (8 classes) and 95.4% (+/−0.3%) for UAV flight mode classification (21 classes).

An automatic air inflated tubeless safety jacket for motorbike riders

PurposeMotorcycle is one of the popular modes of transport in developing countries. However, the statistics related to accidents show that motorcycles are the most vulnerable vehicles. Research studies have revealed that half of all the possible types of motorcycle injuries could be reduced or prevented using effective protective clothing. Facts and figures emphasize that this is high time to develop a safety jacket for motorbike riders. This paper aims to develop an innovative, integrated automatic air-inflated tubeless jacket to prevent major injuries in fatal accidents.Design/methodology/approachTwo accelerometers integrated near the front axle, an angle sensor and the electronic control unit (ECU) were used to detect the collision or accident. The sensors were fixed on the bike and connected with the ECU via a bluetooth device that was always at the activated stage. The fused sensors were emulated with the ECU under laboratory conditions. The trigger signal generated by the crash discriminant algorithm triggered the chemical reaction to generate N2 gas and inflate the tubeless safety jacket.FindingsUnder laboratory conditions, it was found that the signal generated by the ECU unit ejected approximately 15 litres of N2 gas in volume to fill the jacket within 100 milliseconds, which was less than the approximate estimated falling time of the rider 120 milliseconds.Originality/valueThe existing developments of airbag systems in motorbikes are mounted on the motorbikes' frame, following the airbag systems in automobiles. These developments cannot fully protect the rider due to differentiation in crash dynamics and respective positions of the rider at the point of impact. Though few safety jackets and airbag vests are developed, the airbag deployment is activated when rider and motorbike separated during a collision using a tether-triggering mechanism. The authors designed the jacket so that inflation is activated not only by crash sensors but also on the fusion of multiple sensors based on a crash discriminative algorithm. The airbag deployment mechanism is incorporated with the jacket and acts as a safety jacket during a collision.

Design and Implementation of an Intelligent Wheelchair Controlled by Multifunctional Parameter

Physically challenged persons those who are suffering from different physical disabilities face many challenging problems in their day-to-day life for commutating from one place to another and even sometimes they need to have to be dependent on other people to move from one place to another. The purpose of this task is to make a Multi-Functional Wheelchair using Accelerometer ADXL335 and ESP32 as sensor to help physically disabled human beings in transferring from one region to any other simply by giving path from the hand, voice, Bluetooth. This Accelerometer ADXL335 and ESP32 primarily based totally challenge use Accelerometer ADXL335 and ESP32 for transferring backward path, ahead path, left path or proper path. We have advanced a Multi-useful wheelchair for medically disable human beings. We are working wheelchair by multi-feature 1) Bluetooth (Using Bluetooth device, ESP32), 2) Hand Gesture (Using Accelerometer ADXL335 MEMS), 3) Voice (ESP32). This makes challenge very powerful. The fundamental of this challenge is achieved retaining in thoughts to able the handicapped man or woman to transport round their domestic without any assist of different character.

Smartphone based ECG Acquisition and Analysis

Health monitoring and technologies related to health monitoring is an appealing area of research. The electrocardiogram (ECG) has constantly being mainstream estimation plan to evaluate and analyse cardiovascular diseases. Heart health is important for everyone. Heart needs to be monitored regularly and early warning can prevent the permanent heart damage. Also heart diseases are the leading cause of death worldwide. Hence the work presents a design of a mini wearable ECG system and it’s interfacing with the Android application. This framework is created to show and analyze the ECG signal got from the ECG wearable system. The ECG signals will be shipped off an android application via Bluetooth device. This system will automatically alert the user through SMS.