Juniper Publishers-Journal of Robotics Engineering

Juniper Publishers- Journal of Robotics Abstract Security is a critical element for IoT deployment that affects the adoption rate of IoT applications. This paper presents a Light-Weight Secure IoT Key Generator and Management Solution(LKGM) for industry automation and applications. Our solution uses minimum computing and memory resources that can be installed on half-credit-card-size embedded systems that enhances the securityof end-to-end communications for IoT nodes. A frequently changed randomly generated passphrase isused to authenticate each IoT node that is embedded with an encrypted unique authentication key. Fieldtest results were presented for an advanced manufacturing application that will only be activated whentwo authenticated IoT nodes are within the vicinity. Keywords: Authentication; Authority; Secure key; IoT; Security; Industry automation Introduction Internet of Things (IoT) is a network of physical objects t...

Juniper Publishers- Journal of Robotics Abstract The Internet of Things (IoT) is a recent revolution of the Internet which is increasingly adopted with great success in business, industry, healthcare, economic, and other sectors of modern information society. In particular, IoT supported by artificial intelligence enhances considerably the success in a large repertory of every-day applications with dominant one’s enterprise, transportation, robotics, industrial, and automation systems applications. Our aim in this article is to provide a global discussion of the main issues concerning the synergy of IoT and AI, including currently running and potential applications of great value for the society. Starting with an overview of the IoT and AI fields, the article describes what is meant by the concept of ‘IoT-AI synergy’, illustrates the factors that drive the development of ‘IoT enabled by AI’, and summarizes the concepts of ‘Industrial IoT’ (IIoT), ‘Internet of ...

Juniper Publishers- Journal of Robotics Introduction The wireless implants, so-called “Neural Dust’’ have the potential capabilities to spark the neurons in central nervous system or peripheral nervous system [1]. Such potentials can be utilized in various areas that could benefit from such technologies e.g., medical field, to hasten the progress and new future treatments developments for many diseases and disorders such as depression, dementia etc. [2]. Thus, neural dust triggered further researches to expand and increase the potential usage for these technologies in order to utilize them in brain-machine interface which will enable humans in controlling prosthetic limbs or exoskeleton to enhance normal human capabilities. Such applications of technologies provoked ethical considerations because of its violations ethical principles in medicine and other areas and because of the possibilities of usage in mischievous way as in “mind control”, since neural dus...

Juniper Publishers- Journal  of Robotics Opinion As well defined on the journal`s site Robotic Process Automation (RPA) is the application of technology that allows employees in a company to configure computer software or a “robot” to capture and illustrate existing applications for processing a transaction, managing data, provoke responses and communicating with other digital systems. Product Development Process (PDA) is a key element for implementing Industry 4.0 and as defined in literature it consists of integrating six main elements: requirement, definition, design, production, maintenance and recycling [1-3]. So, in order to implement Industry 4.0 fast and costless we need to capture and illustrate existing applications as well as new ones for processing ensuring a reliable product-life cycle [4] and to efficiently process transactions, assuring smart services, manage big data and communicate with other digital systems. In other words Industry...

Juniper Publishers- Journal of Robotics Abstract This paper provides a novel and unprecedented approach for integrating motion features in the detection and classification of moving subjects in a static environment. More specifically, we measure the impact of the use of trajectory history, rotation history, blob orientation, motion frequency in the three axes, motion acceleration, segmentation errors, and flickering scores, and how they can influence classification of moving people, pets, and other objects. We apply our method to data captured by a combined color and depth camera sensor. We find that, while some motion descriptors slightly improve accuracy, the use of them in conjunction outperforms previous approaches in the classification and tracking of real-world moving subjects in real-time. Keywords: Real-time tracking; Moving subjects; Classification; Motion signal; Motion statistics; Accelerometer; Orientation; Rgbd camera; Depth images; Computer vis...