Industry 4.0: Architecture and equipment revolution

© 2020 The Authors. Published by Tech Science Press. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://www.techscience.com/cmc/v66n2/40642The development of science and technology has led to the era of Industry 4.0. The core concept is the combination of "material and informationization." In the supply chain and manufacturing process, the "material" of the physical entity world is realized by data, identity, intelligence, and information. Industry 4.0 is a disruptive transformation and upgrade of intelligent industrialization based on the Internet-of-Things and Big Data in traditional industrialization. The goal is “maximizing production efficiency, minimizing production costs, and maximizing the individual needs of human beings for products and services.” Achieving this goal will surely bring about a major leap in the history of the industry, which will lead to the "Fourth Industrial Revolution.” This paper presents a detailed discussion of industrial big data, strategic roles, architectures, characteristics, and four types of innovative business models that can generate profits for enterprises. The key revolutionary aspect of Industry 4.0 is explained, which is the equipment revolution. Six important attributes of equipment are explained under the Industry 4.0 perspective.Authors would like to thank deanship of scientific research (DSR) at umm Al-Qura University for their partial funding the work (Grant# 17-COM-1-01-0007)

Robust Hybrid Beamforming Scheme for Millimeter-Wave Massive-MIMO 5G Wireless Networks

Wireless networks employing millimeter-wave (mmWave) and Massive Multiple-Input Multiple-Output (MIMO) technologies are a key approach to boost network capacity, coverage, and quality of service (QoS) for future communications. They deploy symmetric antennas on a large scale in order to enhance the system throughput and data rate. However, increasing the number of antennas and Radio Frequency (RF) chains results in high computational complexity and more energy requirements. Therefore, to solve these problems, this paper proposes a low-complexity hybrid beamforming scheme for mmWave Massive-MIMO 5G wireless networks. The proposed algorithm is on the basis of alternating the minimum mean square error (Alt-MMSE) hybrid beamforming technique in which the orthogonal properties of the digital matrix were designed, and then the MSE of the transmitted and received signal was reduced. The phase of the analog matrix was obtained from the updated digital matrix. Simulation results showed that the proposed hybrid beamforming algorithm had better performance than existing state-of-the-art algorithms, and similar performance with the optimal digital precoding algorithm

Cellular-D2D Resource Allocation Algorithm Based on User Fairness

As more and more mobile multimedia services are produced, end users are increasingly demanding access to high-speed, low-latency mobile communication networks. Among them, device-to-device (D2D) communication does not need the data to be forwarded through the base station relay but allows the two mobile devices adjacent to each other to establish a direct local link under control of the base station. This flexible communication method reduces the processing bottlenecks and blind spots of the base station and can be widely used in dense user communication scenarios such as transportation systems. Aiming at the problem of high energy consumption and improved quality of service demands by the D2D users, this paper proposes a new scheme to effectively improve the user fairness and satisfaction based on the user grouping into clusters. The main idea is to create the interference graph between the D2D users which is based on the graph coloring theory and constructs the color lists of the D2D users while cellular users’ requirements are guaranteed. Finally, those D2D users who can share the same channel are grouped in the same cluster. Simulation results show that the proposed scheme outperforms the existing schemes and effectively improve system performance

Design of Powering Wireless Medical Sensor Based on Spiral-Spider Coils

Biomedical sensors help patients monitor their health conditions and receive assistance anywhere and at any time. However, the limited battery capacity of medical devices limits their functionality. One advantageous method to tackle this limited-capacity issue is to employ the wireless power transfer (WPT) technique. In this paper, a WPT technique using a magnetic resonance coupling (MRC-WPT)-based wireless heart rate (WHR) monitoring system—which continuously records the heart rate of patients—has been designed, and its efficiency is confirmed through real-time implementation. The MRC-WPT involves three main units: the transmitter, receiver, and observing units. In this research, a new design of spiral-spider coil was designed and implemented for transmitter and receiver units, respectively, to supply the measurement unit, which includes a heart rate sensor, microcontroller, and wireless protocol (nRF24L01) with the operating voltage. The experimental results found that an adequate voltage of 5 V was achieved by the power component to operate the measurement unit at a 20 cm air gap between the receiver and transmitter coils. Further, the measurement accuracy of the WHR was 99.65% comparative to the benchmark (BM) instrument. Moreover, the measurements of the WHR were validated based on statistical analyses. The results of this study are superior to those of leading works in terms of measurement accuracy, power transfer, and Transfer efficiency

Efficient Modulation Scheme for Intermediate Relay-Aided IoT Networks

With the surge of ubiquitous demand for high-complexity and quality mobile Internet-of-things (IoT) services, new cooperative relaying paradigms have emerged. Motivated by the long and unpredictable end-to-end communication in relay-aided IoT networks, there is a need to introduce novel modulation schemes for very low bit error rate (BER) communications. In this paper, a practical modulation mapping scheme has been proposed to reduce decoding errors. Specifically, a hybrid automatic repeat request (HARQ) system has been used with an intermediate relay to transfer a message from a source to a destination. The design of modulation mapping has been optimized by first formulating the objective as the quadratic assignment problem. Later, the solution to the mapping problem is provided using an iterative search method. To validate the proposed solution, extensive simulations have been performed in MATLAB. The results show that the proposed solution outperforms the conventional relay retransmission and the heuristic design approaches

Accurate Fall Detection and Localization for Elderly People Based on Neural Network and Energy-Efficient Wireless Sensor Network

Falls are the main source of injury for elderly patients with epilepsy and Parkinson’s disease. Elderly people who carry battery powered health monitoring systems can move unhindered from one place to another according to their activities, thus improving their quality of life. This paper aims to detect when an elderly individual falls and to provide accurate location of the incident while the individual is moving in indoor environments such as in houses, medical health care centers, and hospitals. Fall detection is accurately determined based on a proposed sensor-based fall detection algorithm, whereas the localization of the elderly person is determined based on an artificial neural network (ANN). In addition, the power consumption of the fall detection system (FDS) is minimized based on a data-driven algorithm. Results show that an elderly fall can be detected with accuracy levels of 100% and 92.5% for line-of-sight (LOS) and non-line-of-sight (NLOS) environments, respectively. In addition, elderly indoor localization error is improved with a mean absolute error of 0.0094 and 0.0454 m for LOS and NLOS, respectively, after the application of the ANN optimization technique. Moreover, the battery life of the FDS is improved relative to conventional implementation due to reduced computational effort. The proposed FDS outperforms existing systems in terms of fall detection accuracy, localization errors, and power consumption