The effective utilization of real-world data is an integral part of any IoT monitoring or AI-assisted system. Thus, data collection and annotation is an important step towards the successful development and realizatio...
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ISBN:
(纸本)9781665439299
The effective utilization of real-world data is an integral part of any IoT monitoring or AI-assisted system. Thus, data collection and annotation is an important step towards the successful development and realization of such systems. Nevertheless, in order to create reliable datasets, current data collection and annotation methodologies often require a controlled environment while also the presence of the volunteer contributing to the process, or any subject for that matter, and an expert, monitoring the procedure, is mandatory. These processes are heavily restrained by the recent COVID-19 pandemic outbreak. To address such issues, in this paper we propose a human-centered web-based dataset creation and annotation tool that utilizes the web bluetooth api. The user can effectively collect gestures from a nearby device that supports the BLE protocol, assign tags to the collected data, and store them remotely, in real-time. The data storage, as well as its annotation, can also be performed remotely by an expert stakeholder. An off-the-shelf wearable sensorial device has been used indicatively for our tool demonstration purposes. To the best of our knowledge, this is the first attempt that exploits the web bluetooth api capabilities for the development of a Browser-based real-time data collection, storage, and annotation tool. Our tool can be also expanded to other applications that use the sensing device with only minor configuration changes and is also operable through any smart-device that supports a web-Browser. Furthermore, our tool's performance matches that of native applications'. Finally, the tool is successfully deployed and validated by integrating it into our ongoing ML platform that is related to allergic rhinitis gesture recognition.
bluetooth Low Energy (BLE) is currently the dominating wireless network solution for eHealth and sports. However, most BLE sensors require dedicated applications with limited development capabilities. This paper prese...
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ISBN:
(纸本)9781538642948
bluetooth Low Energy (BLE) is currently the dominating wireless network solution for eHealth and sports. However, most BLE sensors require dedicated applications with limited development capabilities. This paper presents a method for rapid development of applications in distributed BLE IoT systems for eHealth and sports. The method is implemented as a JavaScript web framework based on HTML5 canvas, webSocket and web bluetooth apis. This paper demonstrates how the framework can be applied to develop an application for monitoring physical activity and heart rate. The framework enables software and service operators to iteratively create, tune and deploy filter algorithms in distributed BLE IoT systems, without rebooting nodes or restarting programs using dynamic software updating.
IoT devices introduce unprecedented threats into home and professional networks. As they fail to adhere to security best practices, they are broadly exploited by malicious actors to build botnets or steal sensitive in...
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ISBN:
(纸本)9781538666487
IoT devices introduce unprecedented threats into home and professional networks. As they fail to adhere to security best practices, they are broadly exploited by malicious actors to build botnets or steal sensitive information. Their adoption challenges established security standard as classic security measures are often inappropriate to secure them. This is even more problematic in sensitive environments where the presence of insecure IoTs can be exploited to bypass strict security policies. In this paper, we demonstrate an attack against a highly secured network using a bluetooth smart bulb. This attack allows a malicious actor to take advantage of a smart bulb to exfiltrate data from an air gapped network.
BACKGROUND The impact of medical-grade wearable electrocardiographic (ECG) recording technology is increasing rapidly. A wide range of different portable smartphone-connected ECG and heart rate trackers is available o...
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BACKGROUND The impact of medical-grade wearable electrocardiographic (ECG) recording technology is increasing rapidly. A wide range of different portable smartphone-connected ECG and heart rate trackers is available on the market. Smart ECG devices are especially valuable to monitor either supraventricular arrhythmias or prolonged QT intervals to avoid drug-induced life-threatening arrhythmias. However, frequent false alarms or false-positive arrhythmia results from wearable devices are unwanted. Therefore, for clinical evaluation, it should be possible to measure and evaluate the biosignals of the wearables independent of the manufacturer. OBJECTIVE Unlike radiological devices that do support the universal digital imaging and communications in medicine standard, these medical-grade devices do not yet support a secure standardized exchange pathway between sensors, smartphones/smartwatches, and end services such as cloud storage or universal web-based application programming interface (api) access. Consequently, postprocessing of recorded ECGs or heart rate interval data requires a whole toolbox of customized software technologies. METHODS/RESULTS Various methods for measuring and analyzing nonstandardized ECG and heart rate data are proposed, including online measurement of ECG waveforms within a PDF, access to data using manufacturer-specific software development kits, and access to biosignals using modern webapis. CONCLUSION With the appropriate workaround, modern software technologies such as JavaScript and PHP allow health care providers and researchers to easily and instantly access necessary and important signal measurements on demand.
This thesis presents an approach for using wireless signals available on mobile devices as a method to capture and interpret objects in a three dimensional space. bluetooth signal strengths are explored with the Bluet...
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This thesis presents an approach for using wireless signals available on mobile devices as a method to capture and interpret objects in a three dimensional space. bluetooth signal strengths are explored with the bluetooth Scanner prototype, which was developed as a web-based implementation using experimental Google Chrome extensions and currently only supported by Android devices. This web application was conceived by additional research on mobile device performance, in regard to logging several data point readings at each producible tick. By diminishing overhead, a rapid approach maximized the potential to sample a high volume of RSSI values within a millisecond. Throughout the sets of experiments, the bluetooth Scanner prototype is used to capture signal strength interference between the device and an actively transmitting signal beacon. The first experiment scans a targeted object over a parallel two dimensional plane in an effort to produce a heatmap image that sets to visually represent the object using only bluetooth RSSI values. In the following experiment, interference on bluetooth signals directly caused by the orientation of the device and interaction from humans is monitored over time. The results demonstrate a consistent interpretation of an object tracked by wireless signals and highly traceable information about the device's orientation and human interaction. There is evidence to suggest that a person's use of a device can effectively be traced through common wireless signals, such as bluetooth, which leads to possibilities such as developing wireless hand interfaces.
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