Autonomous navigation system based on a dynamic access control architecture for the internet of vehicles

P, Ramkumar M.; Ponnan, Suresh; Shelly, Siddharth; Hussain, Md. Zair; Ashraf, Mohammad; Haldorai, Anandakumar

doi:10.1016/j.compeleceng.2022.108037

Cited by 13 publications

(3 citation statements)

References 5 publications

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“…Subsequent to the publication of his theorems in 1931, Kurt Godel contested the aforementioned perspectives. According to Godel's perspective, his work was misinterpreted by mathematicians, computer scientists, and neuroscientists [43]. Mathematicians and computer scientists were refuting the notion that computers are incapable of solving propositions that are deemed unsolvable.…”

Section: Artificial Intelligence-brain Heuristic Comparisonmentioning

confidence: 99%

Theoretical Analysis of the Brain and Artificial Intelligence

Pedro

2023

JRS

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Many articles have expounded on and defended the potential advantages of co-robotics (cobots), robotics, AI, and quantum computers in the domains of research and development, clinics, community health and virology. Numerous trailblazers in the domains of artificial intelligence, robotics, and quantum computing have been recognised for their groundbreaking concepts and principles. Among these luminaries are Richard Feynman, Kurt Godel, John Nash, Norbert Wiener, Alan Turing, John von Neumann, Vannevar Bush, and John McCarthy. Theorems formulated by Kurt Godel were misinterpreted by researchers who erroneously equated computer and brain paradigms. Godel himself had recognised this misinterpretation. The individual's commendation of the brain's supremacy over computational systems was met with disapprobation. This article delineates the diverse array of artificial intelligence techniques, frameworks, and programming languages that are developed by humans and can be employed in tandem with contemporary computational systems. These advancements facilitate advancements in the realm of electrons and quantum mechanics. The process of evolution has resulted in the development of neurons in various animal species, which rely on the flow of electrons to carry out their biological functions. The identification of mirror neurons represented a significant shift in the paradigm of neuroscience. The proposed paradigm shift towards the 'hall of mirror neurons' represents a potentially effective approach to studying, warranting further investigation. The aforementioned concepts are instrumental in advancing the field of artificial intelligence and in furthering research on the intricacies of the human brain.

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Section: Artificial Intelligence-brain Heuristic Comparisonmentioning

confidence: 99%

Theoretical Analysis of the Brain and Artificial Intelligence

Pedro

2023

JRS

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“…Furthermore, according to [23], technology serves as the fundamental infrastructure for business intelligence systems, allowing organizations to obtain precise and valuable information through the utilization of big data analytics. This enables a comprehensive understanding of market positions, optimization of strategic decision-making processes, and the monitoring of organizational competitiveness.…”

Section: Big Data and Data Analyticsmentioning

confidence: 99%

Enhancing Autonomous Operations in Smart Objects and Devices through the Internet of Robotic Things

Haldorai

2023

JRS

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This study investigates the field of the Internet of Robotic Things (IoRT) and its capacity to transform the functioning of mobile context and robots’ awareness systems. IoRT facilitates autonomous operations in smart objects and devices via the use of data analytics technologies, intelligent data processing tools, deep reinforcement learning, and edge computing techniques. This article examines the use of sensor networks, cloud robotics, machine learning algorithms, and collaborative context-aware robotic networks for the purpose of enhancing job performance, decision-making skills, and operational efficiency in diverse industrial and collaborative settings. The research also investigates the incorporation of route planning tools and motion, cognitive decision-making processes, and sensor data to improve the efficiency of robotic systems in tasks involving object handling. Furthermore, this study investigates the impact of cloud computing, wireless sensor networks, and cognitive approaches on enhancing inventory allocation procedures and company performance. The main purpose of this article is to provide a scholarly contribution to the field of IoRT by exploring its technological advancements and examining its potential applications across many sectors.

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“…There is a subset of researchers that have started the exploration of including artificial landmarks as a means to enhance the mobile robots localization accuracy. One instance of a suggested visual system using 2D bar code type tags, namely AprilTag, was put out by [18]. This system enables a robot to acquire a six DOF (degrees of freedom) position by analyzing a single picture.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Robot Localization Accuracy through Neural Networks and Boosting Techniques

Argent,

Stewart

2023

JRS

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Robot localization is the computational procedure used to determine the exact spatial coordinates of a mobile robot relative to its surrounding environment. The acquisition of localization is an essential ability for an autonomous robot, since it plays a fundamental role in enabling the robot to accurately ascertain its own location. The understanding of the robot's spatial coordinates is an essential need for the robot to make well-informed decisions on its subsequent actions. In a normal scenario of robot localization, a map of the surrounding region is available, and the robot is equipped with sensors that facilitate the examination of the environment and the monitoring of its own motion. The difficulty of localization thereafter becomes the job of calculating the precise orientations and position of the robot inside the map via the use of data gathered from these sensors. To adequately handle the existence of noisy observations, it is essential for robot localization algorithms to possess the capacity to not only provide an assessment of the robot's position, but also to quantify the degree of uncertainty associated with this estimation of location. The main purpose of this study is to formulate a methodology that combines neural networks with boosting techniques to enhance the effectiveness of robot localization. The suggested methodology entails the selection and validation of neural network topologies, the extraction of pertinent features, and the use of boosting methods to augment classification performance. The objective is to get accurate and dependable robot localization via the use of these strategies.

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Autonomous navigation system based on a dynamic access control architecture for the internet of vehicles

Cited by 13 publications

References 5 publications

Theoretical Analysis of the Brain and Artificial Intelligence

Theoretical Analysis of the Brain and Artificial Intelligence

Enhancing Autonomous Operations in Smart Objects and Devices through the Internet of Robotic Things

Enhancing Robot Localization Accuracy through Neural Networks and Boosting Techniques

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