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Sensing and Instrumentation in IoT Era
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Sensing and Instrumentation in IoT Era

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

Deadline for manuscript submissions: closed (30 January 2020) | Viewed by 20104

Special Issue Editors

Dr. Octavian Postolache

E-Mail Website
Guest Editor
Instituto de Telecomunicações, Universidade de Aveiro Campus Universitário de, R. Santiago, 3810-193 Aveiro, Portugal
Interests: internet of medical things; remote sensing solutions for healthcare; embedded AI for healthcare; smart sensors; virtual reality and mixed reality for healthcare
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Subhas Mukhopadhyay

E-Mail Website
Guest Editor
School of Engineering, Macquarie University, Sydney, NSW 2109, Australia
Interests: smart sensors; sensing technology; WSN; IoT; ICT; smart grid; energy harvesting
Special Issues, Collections and Topics in MDPI journals
Prof. Yongsheng Yang

E-Mail Website
Guest Editor
Shanghai Maritime University, No 1550 Haigang Avenue，Pudong New Area, Shanghai, 201306, China
Interests: Sensors and IoT for Smart Ports and Logistics; Indoor and Outdor localization, Algorithms for Smart Sensor Networks, IoT System Design Methodologies
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Domenico Capriglione

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Salerno, 84084 Fisciano (SA), Italy
Interests: distributed measurement systems with self-diagnostic capability; testing methods for measurement software characterization; metrological characterization of image-based measurement systems; measurement for the electromagnetic compatibility; measurements on telecomunication and internet based networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, the widespread deployment of wireless sensor networks, embedded processing cloud computing, embedded computing and inexpensive sensors has facilitated Internet of Things (IoT) technologies and fostered some emerging applications such IoT healthcare, IoT Smart Port or IoT Smart Cities. Thus, IoT is the direct motivation and driver of development in different societal areas. The IoT plays an important role in capturing information from various smart sensors associated with different environments such industrial, hospital or home environments, securely forwarding all the data to cloud centers, and processing the data using big data algorithms. The IoT can effectively detect actuation patterns, autonomously reacting to unexpected changes in monitored process.

This Special Issue invites high-quality research articles and review articles on sensing and instrumentation technologies, IoT architectures and standards, big data and optimization algorithms for IoT, wireless sensor network design and implementation, power harvesting for IoT, IoT applications for different fields such as as smart ports and smart cities, healthcare precision, and agriculture are particular topics of interest.

Papers are solicited on the following and related topics:

  • Smart Sensors and Wireless Sensor Networks for IoT;
  • Test and Automated Instrumentation for IoT;
  • Algorithms for Smart Sensor Networks;
  • Indoor and Outdoor Localization;
  • Platforms and Middleware for IoT Systems;
  • Sensors and IoT in Supply Chain Finance and Management;
  • Computer Vision and Application in IoT;
  • IoT and Wearable Solutions for Healthcare;
  • Sensor Big Data in IoT Systems;
  • Energy Harvesting and Scavenging for IoT;
  • Standards for IoT and IoT Security;
  • Sensors and IoT for Smart Ports and Logistics;
  • Industrial Internet of Things;
  • Sensors and IoT for Structural and Infrastructural Health Monitoring;
  • IoT for Healthcare;
  • IoT Applications for Smart Cities and Smart Home.

Prof. Octavian Postolache
Prof. Subhas Mukhopadhyay
Prof. Yongsheng Yang
Prof. Domenico Capriglione
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 (3 papers)

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Research

14 pages, 15615 KiB  
Article
Water Management for Sustainable Irrigation Systems Using Internet-of-Things
by André Glória, Carolina Dionisio, Gonçalo Simões, João Cardoso and Pedro Sebastião
Sensors 2020, 20(5), 1402; https://doi.org/10.3390/s20051402 - 04 Mar 2020
Cited by 38 | Viewed by 7099
Abstract
This paper introduces a new way of managing water in irrigation systems, which can be applied to gardens or agricultural fields, replacing human intervention with Wireless Sensor Networks. A typical irrigation system wastes on average 30% of the water used, due to poor [...] Read more.
This paper introduces a new way of managing water in irrigation systems, which can be applied to gardens or agricultural fields, replacing human intervention with Wireless Sensor Networks. A typical irrigation system wastes on average 30% of the water used, due to poor management and configuration. This sustainable irrigation system allows a better efficiency in the process of irrigation that can lead to savings for the end user, not only monetary but also in natural resources, such as water and energy, leading to a more sustainable environment. The system can retrieve real time data and use them to determinate the correct amount of water to be used in a garden. With this solution, it is possible to save up to 34% of water when using sensor data from temperature, humidity and soil moisture, or up to 26% when using only temperature inputs. Besides a detailed system architecture, this paper includes a real case scenario implementation and results discussion. Full article
(This article belongs to the Special Issue Sensing and Instrumentation in IoT Era)
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16 pages, 4839 KiB  
Article
Extracting Global Shipping Networks from Massive Historical Automatic Identification System Sensor Data: A Bottom-Up Approach
by Zhihuan Wang, Christophe Claramunt and Yinhai Wang
Sensors 2019, 19(15), 3363; https://doi.org/10.3390/s19153363 - 31 Jul 2019
Cited by 20 | Viewed by 4293
Abstract
The increasing availability of big Automatic Identification Systems (AIS) sensor data offers great opportunities to track ship activities and mine spatial-temporal patterns of ship traffic worldwide. This research proposes a data integration approach to construct Global Shipping Networks (GSN) from massive historical ship [...] Read more.
The increasing availability of big Automatic Identification Systems (AIS) sensor data offers great opportunities to track ship activities and mine spatial-temporal patterns of ship traffic worldwide. This research proposes a data integration approach to construct Global Shipping Networks (GSN) from massive historical ship AIS trajectories in a completely bottom-up way. First, a DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm is applied to temporally identify relevant stop locations, such as marine terminals and their associated events. Second, the semantic meanings of these locations are obtained by mapping them to real ports as identified by the World Port Index (WPI). Stop events are leveraged to develop travel sequences of any ship between stop locations at multiple scales. Last, a GSN is constructed by considering stop locations as nodes and journeys between nodes as links. This approach generates different levels of shipping networks from the terminal, port, and country levels. It is illustrated by a case study that extracts country, port, and terminal level Global Container Shipping Networks (GCSN) from AIS trajectories of more than 4000 container ships in 2015. The main features of these GCSNs and the limitations of this work are finally discussed. Full article
(This article belongs to the Special Issue Sensing and Instrumentation in IoT Era)
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32 pages, 5761 KiB  
Article
Smart Aging System: Uncovering the Hidden Wellness Parameter for Well-Being Monitoring and Anomaly Detection
by Hemant Ghayvat, Muhammad Awais, Sharnil Pandya, Hao Ren, Saeed Akbarzadeh, Subhas Chandra Mukhopadhyay, Chen Chen, Prosanta Gope, Arpita Chouhan and Wei Chen
Sensors 2019, 19(4), 766; https://doi.org/10.3390/s19040766 - 13 Feb 2019
Cited by 60 | Viewed by 7803
Abstract
Background: Ambiguities and anomalies in the Activity of Daily Living (ADL) patterns indicate deviations from Wellness. The monitoring of lifestyles could facilitate remote physicians or caregivers to give insight into symptoms of the disease and provide health improvement advice to residents; Objective: This [...] Read more.
Background: Ambiguities and anomalies in the Activity of Daily Living (ADL) patterns indicate deviations from Wellness. The monitoring of lifestyles could facilitate remote physicians or caregivers to give insight into symptoms of the disease and provide health improvement advice to residents; Objective: This research work aims to apply lifestyle monitoring in an ambient assisted living (AAL) system by diagnosing conduct and distinguishing variation from the norm with the slightest conceivable fake alert. In pursuing this aim, the main objective is to fill the knowledge gap of two contextual observations (i.e., day and time) in the frequent behavior modeling for an individual in AAL. Each sensing category has its advantages and restrictions. Only a single type of sensing unit may not manage composite states in practice and lose the activity of daily living. To boost the efficiency of the system, we offer an exceptional sensor data fusion technique through different sensing modalities; Methods: As behaviors may also change according to other contextual observations, including seasonal, weather (or temperature), and social interaction, we propose the design of a novel activity learning model by adding behavioral observations, which we name as the Wellness indices analysis model; Results: The ground-truth data are collected from four elderly houses, including daily activities, with a sample size of three hundred days plus sensor activation. The investigation results validate the success of our method. The new feature set from sensor data fusion enhances the system accuracy to (98.17% ± 0.95) from (80.81% ± 0.68). The performance evaluation parameters of the proposed model for ADL recognition are recorded for the 14 selected activities. These parameters are Sensitivity (0.9852), Specificity (0.9988), Accuracy (0.9974), F1 score (0.9851), False Negative Rate (0.0130). Full article
(This article belongs to the Special Issue Sensing and Instrumentation in IoT Era)
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