The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and "things" have evolved significantly. "Things" now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of "intelligent things" (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.

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Internet of Robotic Things Intelligent Connectivity and Platforms

Recent advancement in EHR-based (Electronic Health Record) systems has resulted in producing data at an unprecedented rate. The complex, growing, and high-dimensional data available in EHRs creates great opportunities for machine learning techniques such as clustering. Cluster analysis often requires dimension reduction to achieve efficient processing time and mitigate the curse of dimensionality. Given a wide range of techniques for dimension reduction and cluster analysis, it is not straightforward to identify which combination of techniques from both families leads to the desired result. The ability to derive useful and precise insights from EHRs requires a deeper understanding of the data, intermediary results, configuration parameters, and analysis processes. Although these tasks are often tackled separately in existing studies, we present a visual analytics (VA) system, called Visual Analytics for Cluster Analysis and Dimension Reduction of High Dimensional Electronic Health Records (VALENCIA), to address the challenges of high-dimensional EHRs in a single system. VALENCIA brings a wide range of cluster analysis and dimension reduction techniques, integrate them seamlessly, and make them accessible to users through interactive visualizations. It offers a balanced distribution of processing load between users and the system to facilitate the performance of high-level cognitive tasks in such a way that would be difficult without the aid of a VA system. Through a real case study, we have demonstrated how VALENCIA can be used to analyze the healthcare administrative dataset stored at ICES. This research also highlights what needs to be considered in the future when developing VA systems that are designed to derive deep and novel insights into EHRs.

https://www.mdpi.com/2227-9709/7/2/17/pdf

Visual Analytics for Dimension Reduction and Cluster Analysis of High Dimensional Electronic Health Records

New technologies, used in industry 4.0, have paved a way for a massive deployment of Cyber-Physical Systems (CPS). Today, we assist to new smart factory services and scenarios such as smart production, smart maintenance, smart logistic, etc. The security is one of the challenges that face the new industrial environment. Indeed, smart factory applications present many vulnerabilities that have been investigated in the literature. In this paper, we identify the IIoT applications and we present a state of the art of security issues in the industry 4.0.

Security issues in Industry 4.0

The Internet of Things (IoT) and its applications in industrial settings are set to bring in the fourth industrial revolution. The industrial environment consisting of high profile manufacturing plants and a variety of equipment is inherently characterized by high reflectiveness, causing significant multi-path components that affect the propagation of wireless communications—a challenge among others that needs to be resolved. This paper provides a detailed insight into Narrow-Band IoT (NB-IoT), Industrial IoT (IIoT), and Wireless Sensor Networks (WSN) within the context of indoor industrial environments. It presents the applications of NB-IoT for industrial settings, such as the challenges associated with these applications. Furthermore, future research directions were put forth in the areas of NB-IoT network management using self-organizing network (SON) technology, edge computing for scalability enhancement, security in NB-IoT generated data, and proposing a suitable propagation model for reliable wireless communications.

https://www.mdpi.com/1424-8220/21/16/5284/pdf

Suitability of NB-IoT for Indoor Industrial Environment: A Survey and Insights

The recent advances in technology, the increased dependence on electrical energy and the emergence of the fourth industrial revolution (Industry 4.0) were all factors in the increased need for smart, efficient and reliable energy systems. This introduced the concept of the Smart Grid (SG). A SG is a potential replacement for older power grids, capable of adapting and distributing energy based on demand. SG systems are complex. They combine various components and have high requirements for real time reliable operation. This paper attempts to provide an overview of SG systems, by outlining SG architecture and various components. It also introduces communication technologies, integration and network management tools that are involved in SG systems. In addition, the paper highlights challenges and issues that need to be addressed for a successful implementation of SG. Finally, we provide suggestions for future research directions.

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Smart grid in the context of industry 4.0: an overview of communications technologies and challenges

Data pre-processing is considered as the core stage in machine learning and data mining. Normalization, discretization, and dimensionality reduction are well-known techniques in data pre-processing. This research paper seeks to examine the effects of Min-max, Z-score, Decimal Scaling, and Logarithm to the base 2 on the accuracy of J48 classifier using the NSL-KDD dataset. Experiments were conducted using the above-listed methods and their individual results were compared to each other. Principal component analysis (PCA) and Linear Discriminant Analysis (LDA) were tested for dimensionality reduction; furthermore, a hybrid combination of PCA and LDA was attempted and the performance showed an improved classification accuracy compared to the individual methods.

The Impact of Data Pre-Processing Techniques and Dimensionality Reduction on the Accuracy of Machine Learning

The Internet of Things (IoT) concept has recently been presented as the next revolution and a part of the internet of the future. IoT consists of billions of uniquely identified smart objects ‘things’ with communication ability over the internet. These smart objects generate useful information for the provision of better services and improve the quality of life in different domains. However, there is a general lack of an integrated vision or a plan for selection and implementation of these smart objects. This paper presents the required tools and technologies (such as sensors, RFID, processors, actuators and communication models) that are essential in the IoT paradigm. The major objective of this review is to provide more detailed information about IoT smart objects, the building block of IoT, and conduct a comprehensive overview of IoT architecture with different scenarios. Moreover, this paper gives insight into IoT networking and the new type of low power wide area network (LPWAN) leading technologies in the licensed and unlicensed spectrum. Finally, this paper provides perspectives for future research and developments.

The Road to the Internet of Things: a Survey

As the Bitcoin keeps increasing in value compared to other cryptocurrencies, more attention has been given to Blockchain Technology (BT) which is the infrastructure behind the Bitcoin, especially on its role in addressing the problems of the classical centralized system. As a digital currency, Bitcoin is dependent on the decentralized cryptographic tools and peer-to-peer system. The digital currency implements a distributed ledger using Blockchain when verifying any type of transaction. In this paper, the aim is to describe how digital currency networks such as Bitcoin provides a “trust-less” platform for users to embark on money transfers without necessarily depending on any central trusted establishments such as payment services or financial institutions. Furthermore, this work comprehensively overviewed the basic principle that underly BT, such as transaction, consensus algorithms, and hashing. This study also provided a novel classification for blockchain types according to their system architecture and consensus strategy. For each type, our contribution was provided with an example which clearly describes the blockchain features and the transaction steps. Our classification intended to help researchers understand and choose the blockchain for their application. The paper ends with the discussion of the differences between each type

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The road to the blockchain technology: Concept and types

As an effective mechanism acting on the intermediate nodes to support end-to-end congestion control, Active Queue Management (AQM) takes a trade-off between link utilization and delay experienced by data packets. In this paper a linear quadratic optimal controller was designed based on linear control theory for TCP/AQM router. The design specifications, depends on choosing weighting matrices Q and R. One must carry out a trial- and- error process to choose the weighting matrices that can satisfy the design specifications. To overcome this difficulty we employ the Genetic Algorithm (GA) to find the proper weighting matrices. This idea gives a new alternative procedure in time varying feedback control to improve the stability performance. The controller simulation results show the efficiency of the proposed controller.

Sana Sabah Sabry

Papers

The Impact of Data Pre-Processing Techniques and Dimensionality Reduction on the Accuracy of Machine Learning

The Road to the Internet of Things: a Survey

Smart grid in the context of industry 4.0: an overview of communications technologies and challenges

The road to the blockchain technology: Concept and types

Optimal linear quadratic controller based on genetic algorithm for TCP/AQM router