Cloud robotics platforms: review and comparative analysis

Due to the various advantages that the cloud can offer to robots, there has been the recent emergence of the cloud robotics paradigm. Cloud robotics permits robots to unload computing and storage related tasks into the cloud, and as such, robots can be built with smaller on-board computers. The use of cloud-robotics also allows robots to share knowledge within the community over a dedicated cloud space. In order to build-up robots that benefit from the cloud-robotics paradigm, different cloud-robotics platforms have been released during recent years. This paper critically reviews and compares existing cloud robotic platforms in order to provide recommendations on future use and gaps that still need to be addressed. To achieve this, 8 cloud robotic platforms were investigated. Key findings reveal varying underlying architectures and models adopted by these platforms, in addition to different features offered to end-users

Cloud robotic architectures: directions for future research from a comparative analysis

Advances in robotics and cloud computing have led to the emergence of cloud robotics where robots can benefit from remote processing, greater memory and computational power, and massive data storage. The integration of robotics and cloud computing has often been regarded as a complex aspect due to the various components involved in such systems. In order to address this issue, different studies have attempted to create cloud robotic architectures to simplify representation into different blocks or components. However, limited study has been undertaken to critically review and compare these architectures. As such, this paper investigates and performs a comparative analysis of existing cloud robotic architectures in order to identify key limitations and recommend on the future of cloud robotic architectures. As part of this study, 7 such architectures have been reviewed and compared and results showed limited evaluation of existing architectures in favour of security weaknesses

Exploring the application and usability of NFC for promoting self-learning on energy consumption of household electronic appliances

During the past decade, the significant increase in the adoption of consumer electronics has caused a rise in energy demand within the residential and household sectors globally. Since these electronics are dependent on electricity, the impact of these sectors on the environment is also deteriorating and it becomes important to take remedial action. For this, various websites and mobile applications have emerged that provide information to household users on energy consumption of devices and as well as reduction mechanisms. However, since these platforms are limited in various ways in their endeavor to promote self-learning on energy consumption reduction, awareness still remains an important barrier thus giving rise to the need for further investigation on innovative technologies and platforms. Even though Near Field Communication (NFC) could potentially be used, limited work has been conducted in relation to energy consumption of consumer electronics. As such, this paper delves into the application and usability of NFC for promoting self-learning on energy consumption of household electronic appliances through an Android based application called NFC Energy Tracker (NET)

Using tangible user interfaces for teaching concepts of internet of things: usability and learning effectiveness

Purpose This paper aims to explore the use of tangible user interfaces for teaching concepts related to internet of things by focusing on two aspects, notably, usability and learning effectiveness. Design/methodology/approach To assess the usability of IoTTT, Nielsen’s principles were used due to its relevance and popularity for usability assessment. In the usability questionnaire, four attributes were evaluated, notably, learnability, efficiency, errors and satisfaction. As for evaluating learning effectiveness, learning assessment was conducted through pre-tests and post-tests. Two groups of 20 students participated where the first group attended conventional lectures on IoT, whereas the second group used IoTTT for learning same concepts. In the process, data was collected through the usability questionnaire and tests for usability and learning effectiveness assessment. Findings Results revealed a positive score for the usability of the TUI solution with an average rating of 3.9. Although this score demonstrated an acceptable solution, different issues were identified, based on which a set of recommendations have been made in this paper. On the other hand, in the common pre-tests, an average score of 6.40 was obtained as compared to a mean score of 7.33 in the post-tests for all participants. Knowledge gains were significantly higher for students who learnt IoT concepts through the TUI-based system where performance improved by 18 per cent. Originality/value The results revealed in this study are expected to help the research community, course designers and tutors comprehend the prospects of using tangible user interfaces to foster teaching and learning of IoT concepts. In addition, educational solution providers could consider commercialisation prospects of this technology to innovate in teaching and learning, while also building-up on limitations identified within this study