Reformist Framework for Improving Human Security for Mobile Robots in Industry 4.0

Abstract

In this paper, the cooperation between human and robot companies plays a significant role in factories, contributing to greater productivity and efficiency. However, this development breaches established safety procedures when the workspaces are separated from the robot and the human being. These changes have been reflected in industrial robotic safety standards for the last 20 years. We have directed the expansion of a broad field of examination, which focuses on avoiding robotic humans’ effects and minimizing associated risks and consequences. The paper depicts an analysis of prominent safety systems projected and implemented in engineering robotic surroundings that contribute to safe, collective work between humans and robots. Besides, the current regulation has introduced a review and new concepts. The discussion includes multidisciplinary approaches such as estimating and evaluating human-robot collision injuries, mechanical equipment and software to minimize human-robot impacts, impact detection systems, and collision prevention strategies and minimizing their impact to proposed approach for Human Security with Mobile Robots in Industry 4.0 using SDN and CPS with GMM-GM machine learning model.

5G-Telecommunication Allocation Network Using IoT Enabled Improved Machine Learning Technique

“…The standard spectrum sensing algorithms are incapable of dealing with signals that utilise spread spectrum, time or frequency hopping codes, or a combination of the two. As a consequence, these sorts of signals provide a significant challenge in the detection of spectral information [12,22,50]. As a result, the sensing algorithms may be improved even more in order to discover main users of the spread spectrum.…”

“…According to the findings of the literature research, the detection performance of spectrum sensing algorithms is often affected by the noise uncertainty issue, poor signalto-noise ratio (SNR), multipath fading, and shadowing in wireless channels [12]. Due to the inefficiency of single user detection sensing algorithms in dealing with these chal-lenges, it is necessary to investigate cooperative sensing and wideband sensing methods [22]. Recognizing the modulation type of a received signal may be just as crucial in certain situations as determining whether or not a signal is present in a specific frequency range [37].…”

“…Wireless Communications and Mobile Computing carried out all around the globe to estimate the amount of spectrum white space available, and the findings reveal that there is plenty of white space available in a variety of interest bands [15,[20][21][22]. If such information is accessible for every geographical place, it will be very beneficial for new and forthcoming wireless apps to have access to it.…”

Localization for Outdoor Mobile Robot Using LiDAR and RTK-GNSS/INS

“…What used to be heavily reliant on human labor has shifted to operations that can be automated and performed with high efficiency. (1,2) For instance, in China, companies listed in the stock exchange since 2007 have increased the presence of robots in industrial production. (3) The use of these robots requires efficiency in various aspects to achieve optimal productivity.…”

Remote Big Data Management Tools, Sensing and Computing Technologies, and Visual Perception and Environment Mapping Algorithms in the Internet of Robotic Things

“…Multi-agent and decision support systems, computer vision algorithms, and machine learning techniques [77][78][79][80] are pivotal in robotic comprehension of the surrounding environment. Cloud computing technologies and IoRT sensors [81][82][83][84] enhance decisional autonomy of robot swarms by tracking, monitoring, and manipulating objects.…”