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Embedded Systems for the New Generation of IoT Sensors

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (1 March 2022) | Viewed by 6387
Please contact the Guest Editor or the Section Managing Editor at ([email protected]) for any queries.

Special Issue Editor


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Guest Editor
Algoritmi Center, University of Minho, 4800-058 Guimarães, Portugal CeiiA - Centro de Engenharia e Desenvolvimento, 4450-017 Matosinhos, Portugal
Interests: Embedded Systems; Instrumentation Systems; Cyber-Physical Systems
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Special Issue Information

Dear Colleagues,

The growing developments in microcontrollers, the proliferation of compact digital sensors, and the advances in wireless technology have triggered research towards a new generation of powerful, yet low-power, IoT embedded devices at the network edge.

With the introduction of the Arm Cortex-M family, nowadays’ microcontrollers are being packed with more peripherals and new functionalities that previously could only be found in powerful processors and system-on-chips.

Additionally, compact commercial sensors for sampling different physical quantities with digital output and programmable configurations and interrupts are readily available, enabling an ever-increasing range of engineering applications.

Furthermore, wireless IoT end devices are supported by advances in wireless communication technologies, such as LoRA and NB-IoT, which expand battery lifetime and provide a connection link to the cloud computing infrastructure.

Reliable open-source real-time operating systems (RTOSes) for low-end microcontrollers, such as Azure ThreadX and Amazon FreeRTOS, have been made available by manufacturers and open-source communities. Such contributions truly simplify the development and maintenance of this type of embedded systems, while enabling a seamless interoperability and connectivity to the Internet.

However, the inherent consequence of connecting smart devices to the Internet strives for secure and reliable systems, while keeping them accessible from anywhere. Despite not being a new endeavor, such aspects keep attracting research to the security aspects of an always-connected IoT device.

This Special Issue of Sensors is dedicated to original research and recent developments on embedded systems for the next generation of IoT smart devices (IoT sensors).

Topics related to this Special Issue of Sensors include but are not limited to:

Sensor networks and the IoT

Novel sensor approaches for the IoT

Hardware-accelerated solutions for IoT devices

Safety, security and reliability mechanisms for embedded microcontrollers

Embedded operating systems for the IoT

Embedded intelligence (tinyML)

Emerging IoT applications with next-generation embedded devices

Prof. Jorge Cabral
Guest Editor

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Keywords

  • Internet of Things sensors
  • Embedded Systems
  • Cyber Physical Systems
  • security
  • fault-tolerance, tiny Machine Learning
  • Embedded Intelligence

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Published Papers (2 papers)

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16 pages, 2194 KiB  
Article
Validation of Embedded State Estimator Modules for Decentralized Monitoring of Power Distribution Systems Using IoT Components
by Rosvando Marques Gonzaga Junior, Sergio Márquez-Sánchez, Jorge Herrera Santos, Rodrigo Maximiano Antunes de Almeida, João Bosco Augusto London Junior and Juan Manuel Corchado Rodríguez
Sensors 2022, 22(6), 2104; https://doi.org/10.3390/s22062104 - 9 Mar 2022
Cited by 2 | Viewed by 2214
Abstract
Recent theoretical studies demonstrate the advantages of using decentralized architectures over traditional centralized architectures for real-time Power Distribution Systems (PDSs) operation. These advantages include the reduction of the amount of data to be transmitted and processed when performing state estimation in PDSs. The [...] Read more.
Recent theoretical studies demonstrate the advantages of using decentralized architectures over traditional centralized architectures for real-time Power Distribution Systems (PDSs) operation. These advantages include the reduction of the amount of data to be transmitted and processed when performing state estimation in PDSs. The main contribution of this paper is to provide lab validation of the advantages and feasibility of decentralized monitoring of PDSs. Therefore, this paper presents an advanced trial emulating realistic conditions and hardware setup. More specifically, the paper proposes: (i) The laboratory development and implementation of an Advanced Measurement Infrastructure (AMI) prototype to enable the simulation of a smart grid. To emulate the information traffic between smart meters and distribution operation centers, communication modules, that enable the use of wireless networks for sending messages in real-time, are used, bridging concepts from both IoT and Edge Computing. (ii) The laboratory development and implementation of a decentralized architecture based on Embedded State Estimator Modules (ESEMs) are carried out. ESEMs manage information from smart meters at lower voltage networks, performing real-time state estimation in PDSs. Simulations performed on a real PDS with 208 buses (considering both medium and low voltage buses) have met the aims of this paper. The results show that by using ESEMs in a decentralized architecture, both the data transit through the communication network, as well as the computational requirements involved in monitoring PDSs in real-time, are reduced considerably without any loss of accuracy. Full article
(This article belongs to the Special Issue Embedded Systems for the New Generation of IoT Sensors)
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17 pages, 5536 KiB  
Article
An 11.8-fJ/Conversion-Step Noise Shaping SAR ADC with Embedded Passive Gain for Energy-Efficient IoT Sensors
by Changhyung Choi and Jong-Wook Lee
Sensors 2022, 22(3), 869; https://doi.org/10.3390/s22030869 - 24 Jan 2022
Cited by 4 | Viewed by 3251
Abstract
Herein, we present a noise shaping successive-approximation-register (SAR) analog-to-digital converter (ADC) with an embedded passive gain multiplication technique. The noise shaping moves the in-band quantization noise from the signal band to out-of-band for improved signal-to-noise ratio (SNR). The proposed approach tackles the drawback [...] Read more.
Herein, we present a noise shaping successive-approximation-register (SAR) analog-to-digital converter (ADC) with an embedded passive gain multiplication technique. The noise shaping moves the in-band quantization noise from the signal band to out-of-band for improved signal-to-noise ratio (SNR). The proposed approach tackles the drawback of the previous active noise shaping (increased power and extra noise) and passive noise shaping (limited noise suppression and signal loss). Both noise shaping and gain multiplication are realized on-chip in an energy-efficient manner without an opamp. This approach uses only capacitors and switches in the finite impulse response (FIR) and infinite impulse response (IIR) filters. A comparator suppressing kickback noise is presented to handle the tradeoff between noise suppression and the filter capacitor size. The energy-efficient merged-capacitor switching (MCS) technique is effectively combined with rail-to-rail swing comparator and thermometer-coded capacitor array, which reduces the settling error in the digital to analog converter (DAC). The process-induced mismatch effect in the capacitive DAC is investigated using a behavioral model of the ADC. Additionally, we propose dynamic element matching (DEM) for the thermometer-coded capacitor array. The ADC is fabricated using a 0.18 μm CMOS process in an area of 0.26 mm2. Consuming 4.1 μW, the ADC achieves a signal-to-noise and distortion ratio (SNDR) of 66.5 dB and a spurious-free dynamic range (SFDR) of 79.1 dB. The figure-of-merit (FoM) of the ADC is 11.8 fJ/conversion-step. Full article
(This article belongs to the Special Issue Embedded Systems for the New Generation of IoT Sensors)
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