Special Issue "Embedded Devices in IoT"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 31 August 2020.

Special Issue Editor

Dr. Baris Aksanli
Website
Guest Editor
Electrical and Computer Engineering, San Diego State University, San Diego, CA, USA
Interests: context-aware cyber-physical systems; energy-efficient systems; embedded devices and the Internet of Things

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is a new but very common computing paradigm that has enabled vast enhancements in communication capabilities across a variety of devices, and, thus, has provided significantly improved connectivity properties compared to the traditional systems. One of the main ideas of the IoT is that any physical device or an everyday object can be connected to the Internet with the help of embedded computing devices. These embedded devices are usually small but highly capable in data collection and basic computations; and include sensors, actuators, microcontrollers, etc. Since IoT has led to an important shift from the traditional computing architectures, it also created new problems related to hardware/software design, computational capabilities, real-time task processing, security and privacy of users and their data, etc. There is a need for extensive research on the design, capabilities, and applications of the embedded devices that are widely used in IoT to address the above problems. In this Special Issue, we focus on embedded device usage in IoT.

General topics covered in this Special Issue include, but are not limited to the following:

  • New sensor/actuator design for IoT
  • Wireless sensor network design and implementation for IoT systems
  • Microcontroller design and performance analysis within IoT applications
  • Application-specific hardware designs (e.g., FPGA-based implementations) for IoT
  • Hardware–software co-design for IoT systems and applications
  • Real-time data analytics using embedded devices
  • Efficient and accurate machine learning usage with embedded devices
  • Edge computing using embedded devices
  • Novel security and privacy methods leveraging embedded device hardware and/or software
  • Embedded system design addressing one or more of the following IoT issues: energy-efficiency, resiliency, scalability, longevity, cost, device heterogeneity, and standardization
  • Emerging IoT applications using new generation embedded devices

Dr. Baris Aksanli
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Sensors
  • actuators
  • microcontrollers
  • wireless sensor networks
  • real-time computation
  • edge computing
  • hardware/software design
  • machine learning

Published Papers (2 papers)

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Research

Open AccessArticle
Design and Power Management of a Secured Wireless Sensor System for Salton Sea Environmental Monitoring
Electronics 2020, 9(4), 544; https://doi.org/10.3390/electronics9040544 - 25 Mar 2020
Abstract
An embedded system composed of commercial off the shelf (COTS) peripherals and microcontroller. The system will collect environmental data for Salton Sea, Imperial Valley, California in order to understand the development of environmental and health hazards. Power analysis of each system features (i.e. [...] Read more.
An embedded system composed of commercial off the shelf (COTS) peripherals and microcontroller. The system will collect environmental data for Salton Sea, Imperial Valley, California in order to understand the development of environmental and health hazards. Power analysis of each system features (i.e. Central Processing Unit (CPU) core, Input/Output (I/O) buses, and peripheral (temperature, humidity, and optical dust sensor) are studied. Software-based power optimization utilizes the power information with hardware-assisted power gating to control system features. The control of these features extends system uptime in a field deployed finite energy scenario. The proposed power optimization algorithm can collect more data by increasing system up time when compared to a Low Power Energy Aware Processing (LEAP) approach. Lastly, the 128 bit Advanced Encryption Standard (AES) algorithm is applied on the collected data using various parameters. A hidden peripheral requirement that must be considered during design are also noted to impact the efficacy of this method. Full article
(This article belongs to the Special Issue Embedded Devices in IoT)
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Open AccessArticle
Estimation of Displacement for Internet of Things Applications with Kalman Filter
Electronics 2019, 8(9), 985; https://doi.org/10.3390/electronics8090985 - 04 Sep 2019
Cited by 1
Abstract
In the vision of the Internet of Things, an object embedded in the physical world is recognizable and becomes smart by communicating data about itself and by accessing aggregate information from other devices. One of the most useful types of information for interactions [...] Read more.
In the vision of the Internet of Things, an object embedded in the physical world is recognizable and becomes smart by communicating data about itself and by accessing aggregate information from other devices. One of the most useful types of information for interactions among objects regards their movement. Mobile devices can infer their position by exploiting an embedded accelerometer. However, the double integration of the acceleration may not guarantee a reliable estimation of the displacement of the device (i.e., the difference in the new location). In fact, noise and measurement errors dramatically affect the assessment. This paper investigates the benefits and drawbacks of the use of the Kalman filter as a correction technique to achieve more precise estimation of displacement. The approach is evaluated with two accelerometers embedded in commercial devices: A smartphone and a sensor platform. The results show that the technique based on the Kalman filter dramatically reduces the percentage error, in comparison to the assessment made by double integration of the acceleration data; in particular, the precision is improved by up to 72%. At the same time, the computational overhead due to the Kalman filter can be assumed to be negligible in almost all application scenarios. Full article
(This article belongs to the Special Issue Embedded Devices in IoT)
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