The Internet of Robotic Things:A review of concept, added value and applications

The Internet of Robotic Things is an emerging vision that brings together pervasive sensors and objects with robotic and autonomous systems. This survey examines how the merger of robotic and Internet of Things technologies will advance the abilities of both the current Internet of Things and the current robotic systems, thus enabling the creation of new, potentially disruptive services. We discuss some of the new technological challenges created by this merger and conclude that a truly holistic view is needed but currently lacking.Funding Agency:imec ACTHINGS High Impact initiative</p

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Application-driven data processing in wireless sensor networks

Wireless sensor networks (WSNs) are composed of spatially distributed, low-cost, low-power, resource-constrained devices using sensors and actuators to cooperatively monitor and operate into the environment. These systems are being used in a wide range of applications. The design and implementation of an effective WSN requires dealing with several challenges involving multiple disciplines, such as wireless communications and networking, software engineering, embedded systems and signal processing. Besides, the technical solutions found to these issues are closely interconnected and determine the capability of the system to successfully fulfill the requirements posed by each application domain. The large and heterogeneous amount of data collected in a WSN need to be efficiently processed in order to improve the end-user comprehension and control of the observed phenomena. The thesis focuses on a) the development of centralized and distributed data processing methods optimized for the requirements and characteristics of the considered application domains, and b) the design and implementation of suitable system architectures and protocols with respect to critical application-specific parameters. The thesis comprehends a summary and nine publications, equally divided over three different application domains, i.e. wireless automation, structural health monitoring (SHM) and indoor situation awareness (InSitA). In the first one, a wireless joystick control system for human adaptive mechatronics is developed. Also, the effect of packet losses on the performance of a wireless control system is analyzed and validated with an unstable process. A remotely reconfigurable, time synchronized wireless system for SHM enables a precise estimation of the modal properties of the monitored structure. Furthermore, structural damages are detected and localized through a distributed data processing method based on the Goertzel algorithm. In the context of InSitA, the short-time, low quality acoustic signals collected by the nodes composing the network are processed in order to estimate the number of people located in the monitored indoor environment. In a second phase, text- and language-independent speaker identification is performed. Finally, device-free localization and tracking of the movements of people inside the monitored indoor environment is achieved by means of distributed processing of the radio signal strength indicator (RSSI) signals. The results presented in the thesis demonstrate the adaptability of WSNs to different application domains and the importance of an optimal co-design of the system architecture and data processing methods

Use Of Smartphones for Ensuring Vulnerable Road User Safety through Path Prediction and Early Warning: An In-Depth Review of Capabilities, Limitations and Their Applications in Cooperative Intelligent Transport Systems

The field of cooperative intelligent transport systems and more specifically pedestrians to vehicles could be characterized as quite challenging, since there is a broad research area to be studied, with direct positive results to society. Pedestrians to vehicles is a type of cooperative intelligent transport system, within the group of early warning collision/safety system. In this article, we examine the research and applications carried out so far within the field of pedestrians to vehicles cooperative transport systems by leveraging the information coming from vulnerable road users’ smartphones. Moreover, an extensive literature review has been carried out in the fields of vulnerable road users outdoor localisation via smartphones and vulnerable road users next step/movement prediction, which are closely related to pedestrian to vehicle applications and research. We identify gaps that exist in these fields that could be improved/extended/enhanced or newly developed, while we address future research objectives and methodologies that could support the improvement/development of those identified gaps

Evaluation of Nigerian public housing performance using occupants’ experience and satisfaction

There is misconception of occupants’ satisfaction and experience in building performance evaluation due to inadequacy of in-depth studies on each, which resulted to insufficiency of facts about their structure, determinant variables, effects of socioeconomic attributes and conditions under which they are connected. Objective of the study were to identify the building performance levels and differences between occupants’ satisfaction and experience, effects of socioeconomic attributes on them and propose a framework to evaluate public housing performance using occupants’ satisfaction and experience. Building Use Studies (BUS) Methodology, UK questionnaire was adapted and used on a license agreement. Systematic random sampling was used to collect data from 300 occupants of four (4) public housing estates in Gombe metropolis Nigeria. Two independent factors of tangible and intangible building features were conceptualised. Exploratory factor analysis (EFA) was used in the pilot survey to identify the factorability of the variables. The Confirmatory factor analysis (CFA) in AMOS software was used to validate the constructs and develop two structural equation models (SEM) based on occupants satisfaction and experience. The models were subjected to multi CFA moderation method to determine the effects of socioeconomic attributes of the occupants. The results indicated differences in performance of features based on occupants’ satisfaction and experience. The SEM moderation results showed that education and income moderates occupants’ satisfaction, while they does not moderates occupants’ experience. Therefore, the study concluded with emphasis on the importance of occupants experience as an objective measure of building performance against occupants’ satisfaction’s subjectivity. Based on that, a framework to evaluate public housing performance using occupants’ satisfaction and experience was proposed

Context Awareness for Navigation Applications

This thesis examines the topic of context awareness for navigation applications and asks the question, “What are the benefits and constraints of introducing context awareness in navigation?” Context awareness can be defined as a computer’s ability to understand the situation or context in which it is operating. In particular, we are interested in how context awareness can be used to understand the navigation needs of people using mobile computers, such as smartphones, but context awareness can also benefit other types of navigation users, such as maritime navigators. There are countless other potential applications of context awareness, but this thesis focuses on applications related to navigation. For example, if a smartphone-based navigation system can understand when a user is walking, driving a car, or riding a train, then it can adapt its navigation algorithms to improve positioning performance. We argue that the primary set of tools available for generating context awareness is machine learning. Machine learning is, in fact, a collection of many different algorithms and techniques for developing “computer systems that automatically improve their performance through experience” [1]. This thesis examines systematically the ability of existing algorithms from machine learning to endow computing systems with context awareness. Specifically, we apply machine learning techniques to tackle three different tasks related to context awareness and having applications in the field of navigation: (1) to recognize the activity of a smartphone user in an indoor office environment, (2) to recognize the mode of motion that a smartphone user is undergoing outdoors, and (3) to determine the optimal path of a ship traveling through ice-covered waters. The diversity of these tasks was chosen intentionally to demonstrate the breadth of problems encompassed by the topic of context awareness. During the course of studying context awareness, we adopted two conceptual “frameworks,” which we find useful for the purpose of solidifying the abstract concepts of context and context awareness. The first such framework is based strongly on the writings of a rhetorician from Hellenistic Greece, Hermagoras of Temnos, who defined seven elements of “circumstance”. We adopt these seven elements to describe contextual information. The second framework, which we dub the “context pyramid” describes the processing of raw sensor data into contextual information in terms of six different levels. At the top of the pyramid is “rich context”, where the information is expressed in prose, and the goal for the computer is to mimic the way that a human would describe a situation. We are still a long way off from computers being able to match a human’s ability to understand and describe context, but this thesis improves the state-of-the-art in context awareness for navigation applications. For some particular tasks, machine learning has succeeded in outperforming humans, and in the future there are likely to be tasks in navigation where computers outperform humans. One example might be the route optimization task described above. This is an example of a task where many different types of information must be fused in non-obvious ways, and it may be that computer algorithms can find better routes through ice-covered waters than even well-trained human navigators. This thesis provides only preliminary evidence of this possibility, and future work is needed to further develop the techniques outlined here. The same can be said of the other two navigation-related tasks examined in this thesis

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of “volunteer mappers”. Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protection

Sense and Respond

Over the past century, the manufacturing industry has undergone a number of paradigm shifts: from the Ford assembly line (1900s) and its focus on efficiency to the Toyota production system (1960s) and its focus on effectiveness and JIDOKA; from flexible manufacturing (1980s) to reconfigurable manufacturing (1990s) (both following the trend of mass customization); and from agent-based manufacturing (2000s) to cloud manufacturing (2010s) (both deploying the value stream complexity into the material and information flow, respectively). The next natural evolutionary step is to provide value by creating industrial cyber-physical assets with human-like intelligence. This will only be possible by further integrating strategic smart sensor technology into the manufacturing cyber-physical value creating processes in which industrial equipment is monitored and controlled for analyzing compression, temperature, moisture, vibrations, and performance. For instance, in the new wave of the ‘Industrial Internet of Things’ (IIoT), smart sensors will enable the development of new applications by interconnecting software, machines, and humans throughout the manufacturing process, thus enabling suppliers and manufacturers to rapidly respond to changing standards. This reprint of “Sense and Respond” aims to cover recent developments in the field of industrial applications, especially smart sensor technologies that increase the productivity, quality, reliability, and safety of industrial cyber-physical value-creating processes

Enabling technologies and cyber-physical systems for mission-critical scenarios

Programa Oficial de Doutoramento en Tecnoloxías da Información e Comunicacións en Redes Móbiles . 5029P01[Abstract] Reliable transport systems, defense, public safety and quality assurance in the Industry 4.0 are essential in a modern society. In a mission-critical scenario, a mission failure would jeopardize human lives and put at risk some other assets whose impairment or loss would significantly harm society or business results. Even small degradations of the communications supporting the mission could have large and possibly dire consequences. On the one hand, mission-critical organizations wish to utilize the most modern, disruptive and innovative communication systems and technologies, and yet, on the other hand, need to comply with strict requirements, which are very different to those of non critical scenarios. The aim of this thesis is to assess the feasibility of applying emerging technologies like Internet of Things (IoT), Cyber-Physical Systems (CPS) and 4G broadband communications in mission-critical scenarios along three key critical infrastructure sectors: transportation, defense and public safety, and shipbuilding. Regarding the transport sector, this thesis provides an understanding of the progress of communications technologies used for railways since the implantation of Global System for Mobile communications-Railways (GSM-R). The aim of this work is to envision the potential contribution of Long Term Evolution (LTE) to provide additional features that GSM-R would never support. Furthermore, the ability of Industrial IoT for revolutionizing the railway industry and confront today's challenges is presented. Moreover, a detailed review of the most common flaws found in Radio Frequency IDentification (RFID) based IoT systems is presented, including the latest attacks described in the literature. As a result, a novel methodology for auditing security and reverse engineering RFID communications in transport applications is introduced. The second sector selected is driven by new operational needs and the challenges that arise from modern military deployments. The strategic advantages of 4G broadband technologies massively deployed in civil scenarios are examined. Furthermore, this thesis analyzes the great potential for applying IoT technologies to revolutionize modern warfare and provide benefits similar to those in industry. It identifies scenarios where defense and public safety could leverage better commercial IoT capabilities to deliver greater survivability to the warfighter or first responders, while reducing costs and increasing operation efficiency and effectiveness. The last part is devoted to the shipbuilding industry. After defining the novel concept of Shipyard 4.0, how a shipyard pipe workshop works and what are the requirements for building a smart pipe system are described in detail. Furthermore, the foundations for enabling an affordable CPS for Shipyards 4.0 are presented. The CPS proposed consists of a network of beacons that continuously collect information about the location of the pipes. Its design allows shipyards to obtain more information on the pipes and to make better use of it. Moreover, it is indicated how to build a positioning system from scratch in an environment as harsh in terms of communications as a shipyard, showing an example of its architecture and implementation.[Resumen] En la sociedad moderna, los sistemas de transporte fiables, la defensa, la seguridad pública y el control de la calidad en la Industria 4.0 son esenciales. En un escenario de misión crítica, el fracaso de una misión pone en peligro vidas humanas y en riesgo otros activos cuyo deterioro o pérdida perjudicaría significativamente a la sociedad o a los resultados de una empresa. Incluso pequeñas degradaciones en las comunicaciones que apoyan la misión podrían tener importantes y posiblemente terribles consecuencias. Por un lado, las organizaciones de misión crítica desean utilizar los sistemas y tecnologías de comunicación más modernos, disruptivos e innovadores y, sin embargo, deben cumplir requisitos estrictos que son muy diferentes a los relativos a escenarios no críticos. El objetivo principal de esta tesis es evaluar la viabilidad de aplicar tecnologías emergentes como Internet of Things (IoT), Cyber-Physical Systems (CPS) y comunicaciones de banda ancha 4G en escenarios de misión crítica en tres sectores clave de infraestructura crítica: transporte, defensa y seguridad pública, y construcción naval. Respecto al sector del transporte, esta tesis permite comprender el progreso de las tecnologías de comunicación en el ámbito ferroviario desde la implantación de Global System for Mobile communications-Railway (GSM-R). El objetivo de este trabajo es analizar la contribución potencial de Long Term Evolution (LTE) para proporcionar características adicionales que GSM-R nunca podría soportar. Además, se presenta la capacidad de la IoT industrial para revolucionar la industria ferroviaria y afrontar los retos actuales. Asimismo, se estudian con detalle las vulnerabilidades más comunes de los sistemas IoT basados en Radio Frequency IDentification (RFID), incluyendo los últimos ataques descritos en la literatura. Como resultado, se presenta una metodología innovadora para realizar auditorías de seguridad e ingeniería inversa de las comunicaciones RFID en aplicaciones de transporte. El segundo sector elegido viene impulsado por las nuevas necesidades operacionales y los desafíos que surgen de los despliegues militares modernos. Para afrontarlos, se analizan las ventajas estratégicas de las tecnologías de banda ancha 4G masivamente desplegadas en escenarios civiles. Asimismo, esta tesis analiza el gran potencial de aplicación de las tecnologías IoT para revolucionar la guerra moderna y proporcionar beneficios similares a los alcanzados por la industria. Se identifican escenarios en los que la defensa y la seguridad pública podrían aprovechar mejor las capacidades comerciales de IoT para ofrecer una mayor capacidad de supervivencia al combatiente o a los servicios de emergencias, a la vez que reduce los costes y aumenta la eficiencia y efectividad de las operaciones. La última parte se dedica a la industria de construcción naval. Después de definir el novedoso concepto de Astillero 4.0, se describe en detalle cómo funciona el taller de tubería de astillero y cuáles son los requisitos para construir un sistema de tuberías inteligentes. Además, se presentan los fundamentos para posibilitar un CPS asequible para Astilleros 4.0. El CPS propuesto consiste en una red de balizas que continuamente recogen información sobre la ubicación de las tuberías. Su diseño permite a los astilleros obtener más información sobre las tuberías y hacer un mejor uso de las mismas. Asimismo, se indica cómo construir un sistema de posicionamiento desde cero en un entorno tan hostil en términos de comunicaciones, mostrando un ejemplo de su arquitectura e implementación

Innovative Wireless Localization Techniques and Applications

Innovative methodologies for the wireless localization of users and related applications are addressed in this thesis. In last years, the widespread diffusion of pervasive wireless communication (e.g., Wi-Fi) and global localization services (e.g., GPS) has boosted the interest and the research on location information and services. Location-aware applications are becoming fundamental to a growing number of consumers (e.g., navigation, advertising, seamless user interaction with smart places), private and public institutions in the fields of energy efficiency, security, safety, fleet management, emergency response. In this context, the position of the user - where is often more valuable for deploying services of interest than the identity of the user itself - who. In detail, opportunistic approaches based on the analysis of electromagnetic field indicators (i.e., received signal strength and channel state information) for the presence detection, the localization, the tracking and the posture recognition of cooperative and non-cooperative (device-free) users in indoor environments are proposed and validated in real world test sites. The methodologies are designed to exploit existing wireless infrastructures and commodity devices without any hardware modification. In outdoor environments, global positioning technologies are already available in commodity devices and vehicles, the research and knowledge transfer activities are actually focused on the design and validation of algorithms and systems devoted to support decision makers and operators for increasing efficiency, operations security, and management of large fleets as well as localized sensed information in order to gain situation awareness. In this field, a decision support system for emergency response and Civil Defense assets management (i.e., personnel and vehicles equipped with TETRA mobile radio) is described in terms of architecture and results of two-years of experimental validation