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Internet of Things Middleware Platforms and Sensing Infrastructure
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Internet of Things Middleware Platforms and Sensing Infrastructure

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

Deadline for manuscript submissions: closed (15 September 2019) | Viewed by 31250

Special Issue Editors

Dr. Charith Perera

E-Mail Website
Guest Editor
School of Computer Science and Informatics, Cardiff University, Cardiff CF10 3AT, UK
Interests: Internet of Things; sensing as a service; privacy; infrastructure and architectures; fog/edge computing
Special Issues, Collections and Topics in MDPI journals
Dr. Mahmoud Barhamgi

E-Mail Website
Guest Editor
LIRIS Laboratory, Department of Computer Science, Claude Bernard University Lyon I, 69100 Villeurbanne, France
Interests: service oriented computing; Internet of Things; privacy and securit
Special Issues, Collections and Topics in MDPI journals
Dr. Massimo Vecchio

E-Mail Website
Guest Editor
1. Fondazione Bruno Kessler, Via Sommarive 18, 38123 Trento, Italy
2. Faculty of Engineering, eCampus University, Via Isimbardi 10, 22060 Novedrate, Italy
Interests: computational intelligence; soft-computing techniques; Internet of Things; power-aware engineering design; embedded systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Júlio Cezar Estrella

E-Mail Website
Guest Editor
Laboratory of DIstributed and Concurrent Programming, University of Sao Paulo, Brazil
Interests: Internet of Things; Autonomic Computing; Cloud Computing; Service Oriented; Web Services Distributed Systems
Prof. Dr. Kuo-Hui Yeh

E-Mail Website
Guest Editor
Institute of Artificial Intelligence Innovation, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
Interests: IoT security; blockchain; mobile security; NFC/RFID security; authentication; data privacy; cryptology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is a network of networks in which, typically, a massive number of objects/things/sensors/devices are connected through communications and information infrastructure to provide value-added services. Over the last few years, a large number of Internet of Things (IoT) solutions have come to the IoT marketplace. Typically, each of these IoT solutions is designed to perform a single or minimal number of tasks (primary usage). For example, a smart sprinkler may only be activated if the soil moisture level goes below a certain level in the garden. Further, smart plugs allow users to control electronic appliances (including legacy appliances) remotely or create automated schedules. Undoubtedly, such automation not only brings convenience to their owners but also reduces resource wastage. However, these IoT solutions act as independent systems. The data collected by each of these solutions is used by them and stored in access-controlled silos. After primary usage, data is either thrown away or locked down in independent data silos. We believe a significant amount of knowledge and insights are hidden in these data silos that can be used to improve our lives; such data includes our behaviours, habits, preferences, life patterns, and resource consumption.

To discover such knowledge, it is vital to develop efficient and effective end-to-end IoT architectures that can handle big data efficiently.  IoT middleware platforms have been developed in both academic and industrial settings in order to facilitate IoT data management tasks including data analytics. However, the engineering of these general-purpose industrial-grade big data analytics platforms needs to address many challenges, as listed below, to be able to support data analytical needs in different types of IoT applications.

In addition to typical IoT-related research papers, this Special Issue specifically welcomes papers that discuss real world deployments and large IoT projects (EU projects and those on a similar scale).

Dr. Charith Perera
Dr. Mahmoud Barhamgi
Dr. Massimo Vecchio
Prof. Dr. Júlio Cezar Estrella
Dr. Kuo-Hui Yeh
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.

Keywords

  • internet of things 
  • privacy and security 
  • interoperability and semantic technologies 
  • distributed data management 
  • scalable data analytics
  • real world deployments
  • case studies 
  • large IoT projects 
  • interdisciplinary IoT projects

Published Papers (6 papers)

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Research

18 pages, 2594 KiB  
Article
Implementation of Sensing and Actuation Capabilities for IoT Devices Using oneM2M Platforms
by Jaeseok Yun, Il-Yeup Ahn, JaeSeung Song and Jaeho Kim
Sensors 2019, 19(20), 4567; https://doi.org/10.3390/s19204567 - 21 Oct 2019
Cited by 17 | Viewed by 5243
Abstract
In this paper, we present an implementation work of sensing and actuation capabilities for IoT devices using the oneM2M standard-based platforms. We mainly focus on the heterogeneity of the hardware interfaces employed in IoT devices. For IoT devices (i.e., Internet-connected embedded systems) to [...] Read more.
In this paper, we present an implementation work of sensing and actuation capabilities for IoT devices using the oneM2M standard-based platforms. We mainly focus on the heterogeneity of the hardware interfaces employed in IoT devices. For IoT devices (i.e., Internet-connected embedded systems) to perform sensing and actuation capabilities in a standardized manner, a well-designed middleware solution will be a crucial part of IoT platform. Accordingly, we propose an oneM2M standard-based IoT platform (called nCube) incorporated with a set of tiny middleware programs (called TAS) responsible for translating sensing values and actuation commands into oneM2M-defined resources accessible in Web-based applications. All the source codes for the oneM2M middleware platform and smartphone application are available for free in the GitHub repositories. The full details on the implementation work and open-source contributions are described. Full article
(This article belongs to the Special Issue Internet of Things Middleware Platforms and Sensing Infrastructure)
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18 pages, 5575 KiB  
Article
A Cloud-based Middleware for Self-Adaptive IoT-Collaboration Services
by Soojin Park and Sungyong Park
Sensors 2019, 19(20), 4559; https://doi.org/10.3390/s19204559 - 20 Oct 2019
Cited by 13 | Viewed by 5845
Abstract
The middleware framework for IoT collaboration services should provide efficient solutions to context awareness and uncertainty issues among multiple collaboration domains. However, existing middleware frameworks are mostly limited to a single system, and developing self-adaptive IoT collaboration services using existing frameworks requires developers [...] Read more.
The middleware framework for IoT collaboration services should provide efficient solutions to context awareness and uncertainty issues among multiple collaboration domains. However, existing middleware frameworks are mostly limited to a single system, and developing self-adaptive IoT collaboration services using existing frameworks requires developers to take considerable time and effort. Furthermore, the developed IoT collaboration services are often dependent on a particular domain, which cannot easily be referenced in other domains. This paper proposes a cloud-based middleware framework that provides a set of cloud services for self-adaptive IoT collaboration services. The proposed middleware framework is generic in the sense that it clearly separates domain-dependent components from the layers that leverage existing middleware frameworks. In addition, the proposed framework allows developers to upload domain-dependent components onto the cloud, search for registered components, and launch Virtual Machine (VM) running a new MAPE cycle via a convenient web-based interface. The feasibility of the proposed framework has been shown with a simulation of an IoT collaboration service that traces a criminal suspect. The performance evaluation shows that the proposed middleware framework runs with an overhead of only 6% compared to pure Java-based middleware and is scalable as the number of VMs increases up to 16. Full article
(This article belongs to the Special Issue Internet of Things Middleware Platforms and Sensing Infrastructure)
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23 pages, 4671 KiB  
Article
An Interoperable Component-Based Architecture for Data-Driven IoT System
by Sin Kit Lo, Chee Sun Liew, Kok Soon Tey and Saad Mekhilef
Sensors 2019, 19(20), 4354; https://doi.org/10.3390/s19204354 - 09 Oct 2019
Cited by 9 | Viewed by 5118
Abstract
The advancement of the Internet of Things (IoT) as a solution in diverse application domains has nurtured the expansion in the number of devices and data volume. Multiple platforms and protocols have been introduced and resulted in high device ubiquity and heterogeneity. However, [...] Read more.
The advancement of the Internet of Things (IoT) as a solution in diverse application domains has nurtured the expansion in the number of devices and data volume. Multiple platforms and protocols have been introduced and resulted in high device ubiquity and heterogeneity. However, currently available IoT architectures face challenges to accommodate the diversity in IoT devices or services operating under different operating systems and protocols. In this paper, we propose a new IoT architecture that utilizes the component-based design approach to create and define the loosely-coupled, standalone but interoperable service components for IoT systems. Furthermore, a data-driven feedback function is included as a key feature of the proposed architecture to enable a greater degree of system automation and to reduce the dependency on mankind for data analysis and decision-making. The proposed architecture aims to tackle device interoperability, system reusability and the lack of data-driven functionality issues. Using a real-world use case on a proof-of-concept prototype, we examined the viability and usability of the proposed architecture. Full article
(This article belongs to the Special Issue Internet of Things Middleware Platforms and Sensing Infrastructure)
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23 pages, 7299 KiB  
Article
Applying OGC Sensor Web Enablement Standards to Develop a TDR Multi-Functional Measurement Model
by Chih-Chung Chung, Chih-Yuan Huang, Chih-Ray Guan and Ji-Hao Jian
Sensors 2019, 19(19), 4070; https://doi.org/10.3390/s19194070 - 20 Sep 2019
Cited by 3 | Viewed by 3282
Abstract
Time-domain reflectometry (TDR) is considered as a passive monitoring technique which reveals multi-functions, such as water level, bridge scour, landslide, and suspended sediment concentration (SSC), based on a single TDR device via multiplexing and related algorithms. The current platform for revealing TDR analysis [...] Read more.
Time-domain reflectometry (TDR) is considered as a passive monitoring technique which reveals multi-functions, such as water level, bridge scour, landslide, and suspended sediment concentration (SSC), based on a single TDR device via multiplexing and related algorithms. The current platform for revealing TDR analysis and interpreted observations, however, is complex to access, thus a coherent data model and format for TDR heterogeneous data exchange is useful and necessary. To enhance the interoperability of TDR information, this research aims at standardizing the TDR data based on the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) standards. To be specific, this study proposes a TDR sensor description model and an observation model based on the Sensor Model Language (SensorML) and Observation and Measurement (O&M) standards. In addition, a middleware was developed to translate existing TDR information to a Sensor Observation Service (SOS) web service. Overall, by standardizing TDR data with the OGC SWE open standards, relevant information for disaster management can be effectively and efficiently integrated in an interoperable manner. Full article
(This article belongs to the Special Issue Internet of Things Middleware Platforms and Sensing Infrastructure)
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27 pages, 2313 KiB  
Article
On Providing Multi-Level Quality of Service for Operating Rooms of the Future
by Vinicius Facco Rodrigues, Rodrigo da Rosa Righi, Cristiano André da Costa, Björn Eskofier and Andreas Maier
Sensors 2019, 19(10), 2303; https://doi.org/10.3390/s19102303 - 18 May 2019
Cited by 4 | Viewed by 3387
Abstract
The Operating Room (OR) plays an important role in delivering vital medical services to patients in hospitals. Such environments contain several medical devices, equipment, and systems producing valuable information which might be combined for biomedical and surgical workflow analysis. Considering the sensibility of [...] Read more.
The Operating Room (OR) plays an important role in delivering vital medical services to patients in hospitals. Such environments contain several medical devices, equipment, and systems producing valuable information which might be combined for biomedical and surgical workflow analysis. Considering the sensibility of data from sensors in the OR, independently of processing and network loads, the middleware that provides data from these sensors have to respect applications quality of service (QoS) demands. In an OR middleware, there are two main bottlenecks that might suffer QoS problems and, consequently, impact directly in user experience: (i) simultaneous user applications connecting the middleware; and (ii) a high number of sensors generating information from the environment. Currently, many middlewares that support QoS have been proposed by many fields; however, to the best of our knowledge, there is no research on this topic or the OR environment. OR environments are characterized by being crowded by persons and equipment, some of them of specific use in such environments, as mobile x-ray machines. Therefore, this article proposes QualiCare, an adaptable middleware model to provide multi-level QoS, improve user experience, and increase hardware utilization to middlewares in OR environments. Our main contributions are a middleware model and an orchestration engine in charge of changing the middleware behavior to guarantee performance. Results demonstrate that adapting middleware parameters on demand reduces network usage and improves resource consumption maintaining data provisioning. Full article
(This article belongs to the Special Issue Internet of Things Middleware Platforms and Sensing Infrastructure)
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23 pages, 23067 KiB  
Article
Extending QGroundControl for Automated Mission Planning of UAVs
by Cristian Ramirez-Atencia and David Camacho
Sensors 2018, 18(7), 2339; https://doi.org/10.3390/s18072339 - 18 Jul 2018
Cited by 32 | Viewed by 7319
Abstract
Unmanned Aerial Vehicle (UAVs) have become very popular in the last decade due to some advantages such as strong terrain adaptation, low cost, zero casualties, and so on. One of the most interesting advances in this field is the automation of mission planning [...] Read more.
Unmanned Aerial Vehicle (UAVs) have become very popular in the last decade due to some advantages such as strong terrain adaptation, low cost, zero casualties, and so on. One of the most interesting advances in this field is the automation of mission planning (task allocation) and real-time replanning, which are highly useful to increase the autonomy of the vehicle and reduce the operator workload. These automated mission planning and replanning systems require a Human Computer Interface (HCI) that facilitates the visualization and selection of plans that will be executed by the vehicles. In addition, most missions should be assessed before their real-life execution. This paper extends QGroundControl, an open-source simulation environment for flight control of multiple vehicles, by adding a mission designer that permits the operator to build complex missions with tasks and other scenario items; an interface for automated mission planning and replanning, which works as a test bed for different algorithms, and a Decision Support System (DSS) that helps the operator in the selection of the plan. In this work, a complete guide of these systems and some practical use cases are provided. Full article
(This article belongs to the Special Issue Internet of Things Middleware Platforms and Sensing Infrastructure)
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