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)

Contactless Blood Pressure Estimation System Using a Computer Vision System

Blood pressure (BP) is one of the most common vital signs related to cardiovascular diseases. BP is traditionally measured by mercury, aneroid, or digital sphygmomanometers; however, these approaches are restrictive, inconvenient, and need a pressure cuff to be attached directly to the patient. Therefore, it is clinically important to develop an innovative system that can accurately measure BP without the need for any direct physical contact with the people. This work aims to create a new computer vision system that remotely measures BP using a digital camera without a pressure cuff. The proposed BP system extracts the optical properties of photoplethysmographic signals in two regions in the forehead captured by a digital camera and calculates BP based on specific formulas. The experiments were performed on 25 human participants with different skin tones and repeated at different times under ambient light conditions. Compared to the systolic/diastolic BP readings obtained from a commercial digital sphygmomanometer, the proposed BP system achieves an accuracy of 94.6% with a root mean square error (RMSE) of 9.2 mmHg for systolic BP readings and an accuracy of 95.4% with an RMSE of 7.6 mmHg for diastolic BP readings. Thus, the proposed BP system has the potential of being a promising tool in the upcoming generation of BP monitoring systems

Contactless Blood Pressure Estimation System Using a Computer Vision System

Blood pressure (BP) is one of the most common vital signs related to cardiovascular diseases. BP is traditionally measured by mercury, aneroid, or digital sphygmomanometers; however, these approaches are restrictive, inconvenient, and need a pressure cuff to be attached directly to the patient. Therefore, it is clinically important to develop an innovative system that can accurately measure BP without the need for any direct physical contact with the people. This work aims to create a new computer vision system that remotely measures BP using a digital camera without a pressure cuff. The proposed BP system extracts the optical properties of photoplethysmographic signals in two regions in the forehead captured by a digital camera and calculates BP based on specific formulas. The experiments were performed on 25 human participants with different skin tones and repeated at different times under ambient light conditions. Compared to the systolic/diastolic BP readings obtained from a commercial digital sphygmomanometer, the proposed BP system achieves an accuracy of 94.6% with a root mean square error (RMSE) of 9.2 mmHg for systolic BP readings and an accuracy of 95.4% with an RMSE of 7.6 mmHg for diastolic BP readings. Thus, the proposed BP system has the potential of being a promising tool in the upcoming generation of BP monitoring systems

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