Usability in Public Services and Border Control: New Technologies and Challenges for People with Disability

As new security technologies are introduced in public services, such as border control and mass transportation systems, their accessibility for the disabled needs to be evaluated. A large part of the population is directly or indirectly concerned with disability of permanent or temporary nature. This report starts with a brief overview of the scale of disability and associated challenges and puts them in the context of the public policy on disability. In particular it highlights two existing policies: the EU Transport Regulation on the Disabled Air Passengers and the UN Convention on the Rights of Persons with Disability, both of which are of relevance to mass transportation. The report then analyses the usability challenges in public services and border control, including the issues of accessibility, safety and communication. These need to be addressed in future policy proposals. Technical support to the present and future policies related to disability complying public services is seen as a potentially important role for JRC. This is illustrated through a review of relevant JRC projects: VOICE, SESAMONET and Secure Airport. New technologies in public services can be viewed by the disabled from two perspectives: assistive technologies and neutral technologies. The assistive communication technologies were adopted in projects VOICE and SESAMONET to improve accessibility in public services. On the other hand, the use of biometric identification in airports and border control is to enhance security for all and therefore it is assumed to be neutral, with respect to disability. This assumption was investigated in the Secure Airport project.JRC.G.6-Security technology assessmen

Internet of Robotic Things Intelligent Connectivity and Platforms

The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and “things” have evolved significantly. “Things” now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of “intelligent things” (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.publishedVersio

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

Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities

Robotics and Artificial Intelligence (AI) have been inextricably intertwined since their inception. Today, AI-Robotics systems have become an integral part of our daily lives, from robotic vacuum cleaners to semi-autonomous cars. These systems are built upon three fundamental architectural elements: perception, navigation and planning, and control. However, while the integration of AI-Robotics systems has enhanced the quality our lives, it has also presented a serious problem - these systems are vulnerable to security attacks. The physical components, algorithms, and data that make up AI-Robotics systems can be exploited by malicious actors, potentially leading to dire consequences. Motivated by the need to address the security concerns in AI-Robotics systems, this paper presents a comprehensive survey and taxonomy across three dimensions: attack surfaces, ethical and legal concerns, and Human-Robot Interaction (HRI) security. Our goal is to provide users, developers and other stakeholders with a holistic understanding of these areas to enhance the overall AI-Robotics system security. We begin by surveying potential attack surfaces and provide mitigating defensive strategies. We then delve into ethical issues, such as dependency and psychological impact, as well as the legal concerns regarding accountability for these systems. Besides, emerging trends such as HRI are discussed, considering privacy, integrity, safety, trustworthiness, and explainability concerns. Finally, we present our vision for future research directions in this dynamic and promising field

Medical data processing and analysis for remote health and activities monitoring

Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions

A priority-based energy efficient multi-hop routing protocol with congestion control for wireless body area network

Wireless Body Area Networks (WBANs) are advanced and integrated monitoring networks for healthcare applications. In these networks, different types of Biomedical Sensor Nodes (BSNs) are used to monitor physiological parameters of the human body. The BSNs have limited resources such as energy, memory and computation power. These limited resources make the network challenging especially in terms of energy consumption. Efficient routing schemes are required to save the energy during communication processes. Additionally, the BSNs generate sensitive and non-sensitive data packets, which need to be routed according to their priority. In order to address these problems, a priority-based Energy Efficient Multihop Routing protocol with congestion control (3EMR) for wireless body area network was developed that comprises of three different schemes. First, an Optimal Next-hop Selection (ONS) scheme was developed based on the cost function of routing parameters to dynamically select best next-hop for forwarding data packets. Second, a Priority Based Routing (PBR) scheme was developed to forward data packets according to data priority, which is based on sensitivity of the data with regards to patience’s life. Third, a Congestion Avoidance and Mitigation (CAM) scheme was developed to save energy consumption and packet loss due to congestion by considering packet flow adjustment and congestion zone avoidance based strategy. It improvement is benchmarked against related solutions, and they are Healthcare-aware Optimized Congestion Avoidance (HOCA), Differentiated Rate control for Congestion (DRC), Priority based Cross Layer Routing (PCLR), Even Energy-consumption and Backside Routing (EEBR), and Energy Efficient Routing (EER) scheme. The simulation results demonstrated that the 3EMR scheme achieved significant improvement in terms of increased network lifetime by 31.4%, increased throughput by 33.2%, reduced packet loss 30.9%, increased packet delivery ratio by 21.1% and reduced energy consumption 26.8%. Thus, the proposed routing scheme has proven to be an energy efficient solution for data communication in wireless body area networks