Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

Distributed Optimization in Energy Harvesting Sensor Networks with Dynamic In-network Data Processing

Energy Harvesting Wireless Sensor Networks (EH- WSNs) have been attracting increasing interest in recent years. Most current EH-WSN approaches focus on sensing and net- working algorithm design, and therefore only consider the energy consumed by sensors and wireless transceivers for sensing and data transmissions respectively. In this paper, we incorporate CPU-intensive edge operations that constitute in-network data processing (e.g. data aggregation/fusion/compression) with sens- ing and networking; to jointly optimize their performance, while ensuring sustainable network operation (i.e. no sensor node runs out of energy). Based on realistic energy and network models, we formulate a stochastic optimization problem, and propose a lightweight on-line algorithm, namely Recycling Wasted Energy (RWE), to solve it. Through rigorous theoretical analysis, we prove that RWE achieves asymptotical optimality, bounded data queue size, and sustainable network operation. We implement RWE on a popular IoT operating system, Contiki OS, and eval- uate its performance using both real-world experiments based on the FIT IoT-LAB testbed, and extensive trace-driven simulations using Cooja. The evaluation results verify our theoretical analysis, and demonstrate that RWE can recycle more than 90% wasted energy caused by battery overflow, and achieve around 300% network utility gain in practical EH-WSNs

Importance and applications of robotic and autonomous systems (RAS) in railway maintenance sector: a review

Maintenance, which is critical for safe, reliable, quality, and cost-effective service, plays a dominant role in the railway industry. Therefore, this paper examines the importance and applications of Robotic and Autonomous Systems (RAS) in railway maintenance. More than 70 research publications, which are either in practice or under investigation describing RAS developments in the railway maintenance, are analysed. It has been found that the majority of RAS developed are for rolling-stock maintenance, followed by railway track maintenance. Further, it has been found that there is growing interest and demand for robotics and autonomous systems in the railway maintenance sector, which is largely due to the increased competition, rapid expansion and ever-increasing expense

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

Position paper on realizing smart products: challenges for Semantic Web technologies

In the rapidly developing space of novel technologies that combine sensing and semantic technologies, research on smart products has the potential of establishing a research field in itself. In this paper, we synthesize existing work in this area in order to define and characterize smart products. We then reflect on a set of challenges that semantic technologies are likely to face in this domain. Finally, in order to initiate discussion in the workshop, we sketch an initial comparison of smart products and semantic sensor networks from the perspective of knowledge technologies

Video Manipulation Techniques for the Protection of Privacy in Remote Presence Systems

Systems that give control of a mobile robot to a remote user raise privacy concerns about what the remote user can see and do through the robot. We aim to preserve some of that privacy by manipulating the video data that the remote user sees. Through two user studies, we explore the effectiveness of different video manipulation techniques at providing different types of privacy. We simultaneously examine task performance in the presence of privacy protection. In the first study, participants were asked to watch a video captured by a robot exploring an office environment and to complete a series of observational tasks under differing video manipulation conditions. Our results show that using manipulations of the video stream can lead to fewer privacy violations for different privacy types. Through a second user study, it was demonstrated that these privacy-protecting techniques were effective without diminishing the task performance of the remote user.Comment: 14 pages, 8 figure

A Smartphone-Based System for Outdoor Data Gathering Using a Wireless Beacon Network and GPS Data: From Cyber Spaces to Senseable Spaces

Information and Communication Technologies (ICTs) and mobile devices are deeply influencing all facets of life, directly affecting the way people experience space and time. ICTs are also tools for supporting urban development, and they have also been adopted as equipment for furnishing public spaces. Hence, ICTs have created a new paradigm of hybrid space that can be defined as Senseable Spaces. Even if there are relevant cases where the adoption of ICT has made the use of public open spaces more “smart”, the interrelation and the recognition of added value need to be further developed. This is one of the motivations for the research presented in this paper. The main goal of the work reported here is the deployment of a system composed of three different connected elements (a real-world infrastructure, a data gathering system, and a data processing and analysis platform) for analysis of human behavior in the open space of Cardeto Park, in Ancona, Italy. For this purpose, and because of the complexity of this task, several actions have been carried out: the deployment of a complete real-world infrastructure in Cardeto Park, the implementation of an ad-hoc smartphone application for the gathering of participants’ data, and the development of a data pre-processing and analysis system for dealing with all the gathered data. A detailed description of these three aspects and the way in which they are connected to create a unique system is the main focus of this paper.This work has been supported by the Cost Action TU1306, called CYBERPARKS: Fostering knowledge about the relationship between Information and Communication Technologies and Public Spaces supported by strategies to improve their use and attractiveness, the Spanish Ministry of Economy and Competitiveness under the ESPHIA project (ref. TIN2014-56042-JIN) and the TARSIUS project (ref. TIN2015-71564-C4-4-R), and the Basque Country Department of Education under the BLUE project (ref. PI-2016-0010). The authors would also like to thank the staff of UbiSive s.r.l. for the support in developing the application

Sensor function virtualization to support distributed intelligence in the internet of things

It is estimated that-by 2020-billion devices will be connected to the Internet. This number not only includes TVs, PCs, tablets and smartphones, but also billions of embedded sensors that will make up the "Internet of Things" and enable a whole new range of intelligent services in domains such as manufacturing, health, smart homes, logistics, etc. To some extent, intelligence such as data processing or access control can be placed on the devices themselves. Alternatively, functionalities can be outsourced to the cloud. In reality, there is no single solution that fits all needs. Cooperation between devices, intermediate infrastructures (local networks, access networks, global networks) and/or cloud systems is needed in order to optimally support IoT communication and IoT applications. Through distributed intelligence the right communication and processing functionality will be available at the right place. The first part of this paper motivates the need for such distributed intelligence based on shortcomings in typical IoT systems. The second part focuses on the concept of sensor function virtualization, a potential enabler for distributed intelligence, and presents solutions on how to realize it