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IoT Sensor Systems: Design, Interfaces, Signals, Processing, and Applications

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

Deadline for manuscript submissions: 30 November 2025 | Viewed by 10882

Special Issue Editors


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Guest Editor
Department of Engineering/IEETA, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal
Interests: signal & image processing and applications; study and development of devices & systems for friendly smart environments; development of multimedia-based teaching/learning methods and tools, with particular emphasis on the use of the internet
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Research Scientist, Future Communication Networks, VTT Technical Research Centre of Finland Ltd., Oulu, Finland
Interests: industrial IoT; 5G/6G; vehicular communication; multi-access edge computing; intelligent transportation; smart cities; security in sensor networks and Internet of Things
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Internet of Things (IoT) sensor systems have already been conceptually established in the scientific world. However, this area of study continues to transform its design, interfaces, and process. As such, its applications are developing quickly. With its enormous applications in almost every branch of engineering, science and technology, it finds great relevance to more efficient organization and the management of modern communication systems. IoT sensor systems envisage smart techniques that foster the research and development of real-time, scalable and reliable networks, and pave the way to bringing about future research paradigm towards next-generation computation technology.

The objective of this Special Issue is to provide an excellent platform for this field’s academicians, researchers, engineers, and industrial participants to share their research findings with other global experts. In this Special Issue, both original research articles and reviews are welcome. Research areas may cover (but are not limited to) the following:

  • Design space exploration techniques for IoT devices and systems
  • Power, energy, efficient resource management, and energy harvesting
  • Things to cloud: computation and communication gateways
  • Miniaturization: Sensors, CPU, and network
  • IoT interconnections among ISP analysis—QoS, scalability, performance, interference
  • Semantic technologies: information and data models for interoperability
  • Virtualization: multiple sensors aggregated, or a sensor shared by multiple users
  • Privacy/security/trust/identity/anonymity target prediction
  • Design principles and best practices for IoT application development
  • Green IoT: sustainable design and technologies

Dr. Manuel José Cabral dos Santos Reis
Dr. Nishu Gupta
Guest Editors

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Published Papers (4 papers)

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Research

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20 pages, 5586 KiB  
Article
A Low-Power Complementary Metal-Oxide-Semiconductor Receiver with Quadrature Bandpass Continuous-Time Delta–Sigma Analog-to-Digital Converter for IoT Applications
by Nam-Seog Kim
Sensors 2025, 25(6), 1748; https://doi.org/10.3390/s25061748 - 12 Mar 2025
Viewed by 393
Abstract
This paper presents a low-power CMOS receiver with a complex continuous-time delta–sigma ADC designed for IoT applications in the 2.4 GHz band. The architecture employs a quadrature bandpass continuous-time delta–sigma ADC optimized for Bluetooth Low Energy (BLE) standards, achieving an ENOB of 10.9 [...] Read more.
This paper presents a low-power CMOS receiver with a complex continuous-time delta–sigma ADC designed for IoT applications in the 2.4 GHz band. The architecture employs a quadrature bandpass continuous-time delta–sigma ADC optimized for Bluetooth Low Energy (BLE) standards, achieving an ENOB of 10.9 bits while consuming only 0.81 mW from a 1.0 V supply. The receiver demonstrates impressive performance metrics, including a sensitivity of −95 dBm at a 10⁻3-bit error rate, an image rejection ratio of 54.2 dBc, and a spurious-free dynamic range of 79.8 dBc. Operating at a 1.5 MHz intermediate frequency with a 2 MHz bandwidth, the ADC achieves superior energy efficiency with a figure of merit (FOMW) of 103.2 fJ/conv. Implemented in 28 nm CMOS technology, the complete receiver occupies 0.375 mm2 for the RF front-end and 0.145 mm2 for the ADC while consuming 4.08 mW total power, making it well suited for battery-powered IoT sensor nodes requiring both power efficiency and reliable wireless connectivity. Full article
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34 pages, 10310 KiB  
Article
Loom: A Modular Open-Source Approach to Rapidly Produce Sensor, Actuator, Datalogger Systems
by William Richards, John Selker and Chet Udell
Sensors 2024, 24(11), 3466; https://doi.org/10.3390/s24113466 - 28 May 2024
Viewed by 1962
Abstract
In the face of rising population, erratic climate, resource depletion, and increased exposure to natural hazards, environmental monitoring is increasingly important. Satellite data form most of our observations of Earth. On-the-ground observations based on in situ sensor systems are crucial for these remote [...] Read more.
In the face of rising population, erratic climate, resource depletion, and increased exposure to natural hazards, environmental monitoring is increasingly important. Satellite data form most of our observations of Earth. On-the-ground observations based on in situ sensor systems are crucial for these remote measurements to be dependable. Providing open-source options to rapidly prototype environmental datalogging systems allows quick advancement of research and monitoring programs. This paper introduces Loom, a development environment for low-power Arduino-programmable microcontrollers. Loom accommodates a range of integrated components including sensors, various datalogging formats, internet connectivity (including Wi-Fi and 4G Long Term Evolution (LTE)), radio telemetry, timing mechanisms, debugging information, and power conservation functions. Additionally, Loom includes unique applications for science, technology, engineering, and mathematics (STEM) education. By establishing modular, reconfigurable, and extensible functionality across components, Loom reduces development time for prototyping new systems. Bug fixes and optimizations achieved in one project benefit all projects that use Loom, enhancing efficiency. Although not a one-size-fits-all solution, this approach has empowered a small group of developers to support larger multidisciplinary teams designing diverse environmental sensing applications for water, soil, atmosphere, agriculture, environmental hazards, scientific monitoring, and education. This paper not only outlines the system design but also discusses alternative approaches explored and key decision points in Loom’s development. Full article
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22 pages, 17380 KiB  
Article
A Real-Time Automated Defect Detection System for Ceramic Pieces Manufacturing Process Based on Computer Vision with Deep Learning
by Esteban Cumbajin, Nuno Rodrigues, Paulo Costa, Rolando Miragaia, Luís Frazão, Nuno Costa, Antonio Fernández-Caballero, Jorge Carneiro, Leire H. Buruberri and António Pereira
Sensors 2024, 24(1), 232; https://doi.org/10.3390/s24010232 - 31 Dec 2023
Cited by 12 | Viewed by 6807
Abstract
Defect detection is a key element of quality control in today’s industries, and the process requires the incorporation of automated methods, including image sensors, to detect any potential defects that may occur during the manufacturing process. While there are various methods that can [...] Read more.
Defect detection is a key element of quality control in today’s industries, and the process requires the incorporation of automated methods, including image sensors, to detect any potential defects that may occur during the manufacturing process. While there are various methods that can be used for inspecting surfaces, such as those of metal and building materials, there are only a limited number of techniques that are specifically designed to analyze specialized surfaces, such as ceramics, which can potentially reveal distinctive anomalies or characteristics that require a more precise and focused approach. This article describes a study and proposes an extended solution for defect detection on ceramic pieces within an industrial environment, utilizing a computer vision system with deep learning models. The solution includes an image acquisition process and a labeling platform to create training datasets, as well as an image preprocessing technique, to feed a machine learning algorithm based on convolutional neural networks (CNNs) capable of running in real time within a manufacturing environment. The developed solution was implemented and evaluated at a leading Portuguese company that specializes in the manufacturing of tableware and fine stoneware. The collaboration between the research team and the company resulted in the development of an automated and effective system for detecting defects in ceramic pieces, achieving an accuracy of 98.00% and an F1-Score of 97.29%. Full article
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26 pages, 6305 KiB  
Systematic Review
The Integration of IoT (Internet of Things) Sensors and Location-Based Services for Water Quality Monitoring: A Systematic Literature Review
by Rajapaksha Mudiyanselage Prasad Niroshan Sanjaya Bandara, Amila Buddhika Jayasignhe and Günther Retscher
Sensors 2025, 25(6), 1918; https://doi.org/10.3390/s25061918 - 19 Mar 2025
Viewed by 635
Abstract
The increasing demand for clean and reliable water resources, coupled with the growing threat of water pollution, has made real-time water quality (WQ) monitoring and assessment a critical priority in many urban areas. Urban environments encounter substantial challenges in maintaining WQ, driven by [...] Read more.
The increasing demand for clean and reliable water resources, coupled with the growing threat of water pollution, has made real-time water quality (WQ) monitoring and assessment a critical priority in many urban areas. Urban environments encounter substantial challenges in maintaining WQ, driven by factors such as rapid population growth, industrial expansion, and the impacts of climate change. Effective real-time WQ monitoring is essential for safeguarding public health, promoting environmental sustainability, and ensuring adherence to regulatory standards. The rapid advancement of Internet of Things (IoT) sensor technologies and smartphone applications presents an opportunity to develop integrated platforms for real-time WQ assessment. Advances in the IoT provide a transformative solution for WQ monitoring, revolutionizing the way we assess and manage our water resources. Moreover, recent developments in Location-Based Services (LBSs) and Global Navigation Satellite Systems (GNSSs) have significantly enhanced the accessibility and accuracy of location information. With the proliferation of GNSS services, such as GPS, GLONASS, Galileo, and BeiDou, users now have access to a diverse range of location data that are more precise and reliable than ever before. These advancements have made it easier to integrate location information into various applications, from urban planning and disaster management to environmental monitoring and transportation. The availability of multi-GNSS support allows for improved satellite coverage and reduces the potential for signal loss in urban environments or densely built environments. To harness this potential and to enable the seamless integration of the IoT and LBSs for sustainable WQ monitoring, a systematic literature review was conducted to determine past trends and future opportunities. This research aimed to review the limitations of traditional monitoring systems while fostering an understanding of the positioning capabilities of LBSs in environmental monitoring for sustainable urban development. The review highlights both the advancements and challenges in using the IoT and LBSs for real-time WQ monitoring, offering critical insights into the current state of the technology and its potential for future development. There is a pressing need for an integrated, real-time WQ monitoring system that is cost-effective and accessible. Such a system should leverage IoT sensor networks and LBSs to provide continuous monitoring, immediate feedback, and spatially dynamic insights, empowering stakeholders to address WQ issues collaboratively and efficiently. Full article
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