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IoT Enabled Sensing System: Technologies, Challenges, and Smart Applications

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

Deadline for manuscript submissions: 30 September 2024 | Viewed by 37828

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Dr. Md Eshrat E. Alahi

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The Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Interests: sensor design and fabrication; robust neural interface; neural recording/stimulation device for biomedical applications
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Anindya Nag

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Guest Editor

1. Faculty of Electrical and Computer Engineering, Technische Universität Dresden, 01062 Dresden, Germany
2. Centre for Tactile Internet with Human-in-the-Loop (CeTI), Technische Universität Dresden, 01069 Dresden, Germany
Interests: flexible sensors; MEMS sensors; nanotechnology
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Dr. Nasrin Afsarimanesh

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Guest Editor

School of Civil and Mechanical Engineering, Curtin University, Perth, WA 6102, Australia
Interests: flexible; electrochemical; sensors; MEMS; silicon; strain; wearable; biosensor; nanomaterials
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid development of intelligent communication and computational technologies, the Internet of Things (IoT), as a pervasive paradigm connecting the real world with the cyber world through small, interlinked devices, has shown significant advances in areas such as transport systems, digital health, and industrial automation. The fundamental pillar of those IoT-enabled applications is wireless sensing and communication technologies. However, challenges are also emerging in data management, energy efficiency, security issues, etc. Advanced technologies must be created to address the above issues in IoT development.

This Special Issue focuses on advanced research on advanced communications and sensing technologies in the IoT system. Researchers are invited to present original research on the latest findings related to current trends and challenges in advanced IoT-based application. Topics of interest include (but are not limited to):

IoT-enabled communication technologies;
IoT-enabled sensors, sensing system, data processing, fusion, and analysis;
Machine-learning/deep-learning techniques for IoT sensing;
Intelligent protocols and architecture for IoT sensing systems;
IoT-enabled sensing system for smart cities, industry, grid, transportation, and e-health;
Edge/fog/cloud computing for IoT-enabled sensing system;
Security, privacy, and trust management in an IoT-enabled sensing system.

Dr. Md Eshrat E. Alahi
Prof. Dr. Anindya Nag
Dr. Nasrin Afsarimanesh
Guest Editors

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 submissions that pass pre-check are 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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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.

Published Papers (4 papers)

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Research

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36 pages, 1306 KiB

Open AccessArticle

A Comprehensive Review of Behavior Change Techniques in Wearables and IoT: Implications for Health and Well-Being

by Carolina Del-Valle-Soto, Juan Carlos López-Pimentel, Javier Vázquez-Castillo, Juan Arturo Nolazco-Flores, Ramiro Velázquez, José Varela-Aldás and Paolo Visconti

Sensors 2024, 24(8), 2429; https://doi.org/10.3390/s24082429 - 10 Apr 2024

Viewed by 633

Abstract

This research paper delves into the effectiveness and impact of behavior change techniques fostered by information technologies, particularly wearables and Internet of Things (IoT) devices, within the realms of engineering and computer science. By conducting a comprehensive review of the relevant literature sourced from the Scopus database, this study aims to elucidate the mechanisms and strategies employed by these technologies to facilitate behavior change and their potential benefits to individuals and society. Through statistical measurements and related works, our work explores the trends over a span of two decades, from 2000 to 2023, to understand the evolving landscape of behavior change techniques in wearable and IoT technologies. A specific focus is placed on a case study examining the application of behavior change techniques (BCTs) for monitoring vital signs using wearables, underscoring the relevance and urgency of further investigation in this critical intersection of technology and human behavior. The findings shed light on the promising role of wearables and IoT devices for promoting positive behavior modifications and improving individuals’ overall well-being and highlighting the need for continued research and development in this area to harness the full potential of technology for societal benefit. Full article

(This article belongs to the Special Issue IoT Enabled Sensing System: Technologies, Challenges, and Smart Applications)

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24 pages, 5068 KiB

Open AccessArticle

Deep Ontology Alignment Using a Natural Language Processing Approach for Automatic M2M Translation in IIoT

by Saleha Javed, Muhammad Usman, Fredrik Sandin, Marcus Liwicki and Hamam Mokayed

Sensors 2023, 23(20), 8427; https://doi.org/10.3390/s23208427 - 12 Oct 2023

Viewed by 1585

Abstract

The technical capabilities of modern Industry 4.0 and Industry 5.0 are vast and growing exponentially daily. The present-day Industrial Internet of Things (IIoT) combines manifold underlying technologies that require real-time interconnection and communication among heterogeneous devices. Smart cities are established with sophisticated designs and control of seamless machine-to-machine (M2M) communication, to optimize resources, costs, performance, and energy distributions. All the sensory devices within a building interact to maintain a sustainable climate for residents and intuitively optimize the energy distribution to optimize energy production. However, this encompasses quite a few challenges for devices that lack a compatible and interoperable design. The conventional solutions are restricted to limited domains or rely on engineers designing and deploying translators for each pair of ontologies. This is a costly process in terms of engineering effort and computational resources. An issue persists that a new device with a different ontology must be integrated into an existing IoT network. We propose a self-learning model that can determine the taxonomy of devices given their ontological meta-data and structural information. The model finds matches between two distinct ontologies using a natural language processing (NLP) approach to learn linguistic contexts. Then, by visualizing the ontological network as a knowledge graph, it is possible to learn the structure of the meta-data and understand the device’s message formulation. Finally, the model can align entities of ontological graphs that are similar in context and structure.Furthermore, the model performs dynamic M2M translation without requiring extra engineering or hardware resources. Full article

(This article belongs to the Special Issue IoT Enabled Sensing System: Technologies, Challenges, and Smart Applications)

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Review

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51 pages, 1384 KiB

Open AccessReview

Fundamentals, Algorithms, and Technologies of Occupancy Detection for Smart Buildings Using IoT Sensors

by Pratiksha Chaudhari, Yang Xiao, Mark Ming-Cheng Cheng and Tieshan Li

Sensors 2024, 24(7), 2123; https://doi.org/10.3390/s24072123 - 26 Mar 2024

Viewed by 630

Abstract

Smart buildings use advanced technologies to automate building functions. One important function is occupancy detection using Internet of Things (IoT) sensors for smart buildings. Occupancy information is useful information to reduce energy consumption by automating building functions such as lighting, heating, ventilation, and air conditioning systems. The information is useful to improve indoor air quality by ensuring that ventilation systems are used only when and where they are needed. Additionally, it is useful to enhance building security by detecting unusual or unexpected occupancy levels and triggering appropriate responses, such as alarms or alerts. Occupancy information is useful for many other applications, such as emergency response, plug load energy management, point-of-interest identification, etc. However, the accuracy of occupancy detection is limited by factors such as real-time occupancy data, sensor placement, privacy concerns, and the presence of pets or objects that can interfere with sensor reading. With the rapid development of IoT sensor technologies and the increasing need for smart building solutions, there is a growing interest in occupancy detection techniques. There is a need to provide a comprehensive survey of these technologies. Although there are some exciting survey papers, they all have limited scopes with different focuses. Therefore, this paper provides a comprehensive overview of the current state-of-the-art occupancy detection methods (including both traditional algorithms and machine learning algorithms) and devices with their advantages and limitations. It surveys and compares fundamental technologies (such as sensors, algorithms, etc.) for smart buildings. Furthermore, the survey provides insights and discussions, which can help researchers, practitioners, and stakeholders develop more effective occupancy detection solutions for smart buildings. Full article

(This article belongs to the Special Issue IoT Enabled Sensing System: Technologies, Challenges, and Smart Applications)

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36 pages, 4273 KiB

Open AccessReview

Integration of IoT-Enabled Technologies and Artificial Intelligence (AI) for Smart City Scenario: Recent Advancements and Future Trends

by Md Eshrat E. Alahi, Arsanchai Sukkuea, Fahmida Wazed Tina, Anindya Nag, Wattanapong Kurdthongmee, Korakot Suwannarat and Subhas Chandra Mukhopadhyay

Sensors 2023, 23(11), 5206; https://doi.org/10.3390/s23115206 - 30 May 2023

Cited by 35 | Viewed by 33900

Abstract

As the global population grows, and urbanization becomes more prevalent, cities often struggle to provide convenient, secure, and sustainable lifestyles due to the lack of necessary smart technologies. Fortunately, the Internet of Things (IoT) has emerged as a solution to this challenge by connecting physical objects using electronics, sensors, software, and communication networks. This has transformed smart city infrastructures, introducing various technologies that enhance sustainability, productivity, and comfort for urban dwellers. By leveraging Artificial Intelligence (AI) to analyze the vast amount of IoT data available, new opportunities are emerging to design and manage futuristic smart cities. In this review article, we provide an overview of smart cities, defining their characteristics and exploring the architecture of IoT. A detailed analysis of various wireless communication technologies employed in smart city applications is presented, with extensive research conducted to determine the most appropriate communication technologies for specific use cases. The article also sheds light on different AI algorithms and their suitability for smart city applications. Furthermore, the integration of IoT and AI in smart city scenarios is discussed, emphasizing the potential contributions of 5G networks coupled with AI in advancing modern urban environments. This article contributes to the existing literature by highlighting the tremendous opportunities presented by integrating IoT and AI, paving the way for the development of smart cities that significantly enhance the quality of life for urban dwellers while promoting sustainability and productivity. By exploring the potential of IoT, AI, and their integration, this review article provides valuable insights into the future of smart cities, demonstrating how these technologies can positively impact urban environments and the well-being of their inhabitants. Full article

(This article belongs to the Special Issue IoT Enabled Sensing System: Technologies, Challenges, and Smart Applications)

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