Andrei Shkel
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IEEE Sensors Letters

IEEE Sensors Letters is an electronic journal dedicated to publishing short manuscripts, quickly, on the latest and most significant developments in the field of sensors.

Latest Articles

Caption Generation for Sensing-Based Activity Using Attention-Based Learning Models

Bhabanisankar Pati; Ajit Kumar Sahoo; Siba K Udgata

In recent years, sensing systems have been extensively used for motion detection, activity detection, and gesture recognition, among a few other important applications. Wearable sensors, such as smartwatches and smartphones, contain accelerometers and gyroscope sensors that sense a user's movements and activities to detect abnormal events. Inspired by recent breakthroughs in neural machine translation and the generation of image descriptions, we propose a first-of-its-kind novel attention-based encoder–decoder model to generate a caption to summarize various activities detected for a period from smartphone sensor data. The proposed model architecture consists of three layers: 1) the bidirectional long short-term memory (BiLSTM) incorporates both past and future information from the raw sensor data, then generates features; 2) an attention mechanism is used to assign different weights depending on the feature importance; and 3) an LSTM layer is used generate a sequence of activities, and then, a caption generator module is used to generate the caption. The performance of the proposed model is evaluated using two widely used public datasets (UCI-HAR and WISDM) and one experimental dataset. The model achieves good accuracy on UCI-HAR and our experimental dataset compared to WISDM dataset. The proposed model is able to achieve an average word error rate of 8.20%, accuracy of 90.75% with the UCI-HAR dataset, and an average word error rate of 10%, as well as accuracy of 90% with our experimental dataset.

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Popular Articles

Smart Glove With Fully Integrated Textile Sensors and Wireless Sensor Frontend for the Tactile Internet

In this letter, we present a smart glove for Tactile Internet applications. The individual finger motions are measured via resistive strain sensors. The strain sensors are directly integrated with the textile glove and are produced in an automated process. The sensor glove is integrated with sensor conditioning, controller, wireless frontend, and battery. We investigate the measured sensor data for a variety of gestures, demonstrating the good quality of the data allowing for easy and low-energy gesture recognition.

IoT-Enabled Sensors in Automation Systems and Their Security Challenges

Today, Internet of Things (IoT)-based sensor devices are ubiquitous. Being cost effective and easy to deploy, they are also considered for many applications outside their original domain, which was consumer electronics. Factory and process automation, smart buildings and homes, and, in general, Industry 4.0 are application fields in which the use of IoT technology is gaining popularity, often in addition to existing, classical communication architectures on the operational technology level. IoT devices, however, typically have a different philosophy for communication and data exchange, which makes them easy to use but poses security challenges by bypassing established security architectures, such as the classical defense-in-depth concept defined, for instance, in the IEC 62443 standard. This letter highlights today's security needs and concepts in industrial environments. Furthermore, it looks at possible new attack surfaces opened by IoT-based applications and shows ways how to bridge the security gap.

Sustainable Printed Chitosan-Based Humidity Sensor on Flexible Biocompatible Polymer Substrate

Humidity is one of the most relevant physical parameters to sense and control for a wide range of commercial and industrial applications. Consequently, there is continuing demand for the development of innovative and sustainable humidity sensor solutions. Here, the development and characterization of fully additively manufactured, highly sensitive, resistive Chitosan-based humidity sensors on flexible thermoplastic polyurethane (TPU) foil, as well as on a glass carrier substrate are presented. The sensors unite aspects of sustainability and high performance in a broad humidity range (20–90%rH). The humidity response follows an exponential curve progression with relative changes in the resistance per %rH of 6.9% and 5.7% for the glass carrier sensor and the TPU sensor, respectively. In absolute values, this means that the Chitosan-based sensors are particularly sensitive in the low humidity range with a vast dynamic range (ten times larger compared to commonly used capacitive humidity sensors). The flexible sensor on the TPU substrate shows great stability even after repeated bending. In addition, the combination of flexible and biocompatible materials (TPU and Chitosan) with additive manufacturing technologies makes the sensor particularly sustainable while having great potential for a plethora of biomedical applications.

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Editorial Board

Andrei Shkel
Editor-in-Chief
University of California, Irvine, USA
Deepak Uttamchandani
Associate Editor-in-Chief
Strathclyde University, Glasgow, UK
Francisco Falcone
Associate Editor-in-Chief
Univ. Publica de Navarra, Spain
Thilo Sauter
Associate Editor-in-Chief
TU Wien and Danube University, Krems, Austria
Srinivas Tadigadapa
Founding Editor-in-Chief (2017-2022)
Northeastern University, USA
David Elata
Sensor Phenomena and Modeling Topical Editor
Technion, Haifa, Israel
Michael Kraft
Sensor/Electronic Interfaces Topical Editor
University of Liège, Belgium
Doruk Senka
Associate Editor
Reality Labs, Meta, USA
Chia-Chan Chang
Associate Editor
National Chung-Cheng University, Taiwan
Karthik Shankar
Associate Editor
University of Alberta, Edmonton, Canada
Sheng-Shian Li
Associate Editor
National Tsing Hua University, Taiwan
Saakshi Dhanekar
Associate Editor
Indian Institute of Technology, Jodhpur, India
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