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

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Enabling High-Level Application Development for the Internet of Things

Application development in the Internet of Things (IoT) is challenging because it involves dealing with a wide range of related issues such as lack of separation of concerns, and lack of high-level of abstractions to address both the large scale and heterogeneity. Moreover, stakeholders involved in the application development have to address issues that can be attributed to different life-cycles phases. when developing applications. First, the application logic has to be analyzed and then separated into a set of distributed tasks for an underlying network. Then, the tasks have to be implemented for the specific hardware. Apart from handling these issues, they have to deal with other aspects of life-cycle such as changes in application requirements and deployed devices. Several approaches have been proposed in the closely related fields of wireless sensor network, ubiquitous and pervasive computing, and software engineering in general to address the above challenges. However, existing approaches only cover limited subsets of the above mentioned challenges when applied to the IoT. This paper proposes an integrated approach for addressing the above mentioned challenges. The main contributions of this paper are: (1) a development methodology that separates IoT application development into different concerns and provides a conceptual framework to develop an application, (2) a development framework that implements the development methodology to support actions of stakeholders. The development framework provides a set of modeling languages to specify each development concern and abstracts the scale and heterogeneity related complexity. It integrates code generation, task-mapping, and linking techniques to provide automation. Code generation supports the application development phase by producing a programming framework that allows stakeholders to focus on the application logic, while our mapping and linking techniques together support the deployment phase by producing device-specific code to result in a distributed system collaboratively hosted by individual devices. Our evaluation based on two realistic scenarios shows that the use of our approach improves the productivity of stakeholders involved in the application development

makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes

A wide gap exists between the state of the art in developing Wireless Sensor Network (WSN) software and current practices concerning the design, execution, and maintenance of business processes. WSN software is most often developed based on low-level OS abstractions, whereas business process development leverages high-level languages and tools. This state of affairs places WSNs at the fringe of industry. The makeSense system addresses this problem by simplifying the integration of WSNs into business processes. Developers use BPMN models extended with WSN-specific constructs to specify the application behavior across both traditional business process execution environments and the WSN itself, which is to be equipped with application-specific software. We compile these models into a high-level intermediate language—also directly usable by WSN developers—and then into OS-specific deployment-ready binaries. Key to this process is the notion of meta-abstraction, which we define to capture fundamental patterns of interaction with and within the WSN. The concrete realization of meta-abstractions is application-specific; developers tailor the system configuration by selecting concrete abstractions out of the existing codebase or by providing their own. Our evaluation of makeSense shows that i) users perceive our approach as a significant advance over the state of the art, providing evidence of the increased developer productivity when using makeSense; ii) in large-scale simulations, our prototype exhibits an acceptable system overhead and good scaling properties, demonstrating the general applicability of makeSense; and, iii) our prototype—including the complete tool-chain and underlying system support—sustains a real-world deployment where estimates by domain specialists indicate the potential for drastic reductions in the total cost of ownership compared to wired and conventional WSN-based solutions

Autonomic Wireless Sensor Networks: A Systematic Literature Review

Autonomic computing (AC) is a promising approach to meet basic requirements in the design of wireless sensor networks (WSNs), and its principles can be applied to efficiently manage nodes operation and optimize network resources. Middleware for WSNs supports the implementation and basic operation of such networks. In this systematic literature review (SLR) we aim to provide an overview of existing WSN middleware systems that address autonomic properties. The main goal is to identify which development approaches of AC are used for designing WSN middleware system, which allow the self-management of WSN. Another goal is finding out which interactions and behavior can be automated in WSN components. We drew the following main conclusions from the SLR results: (i) the selected studies address WSN concerns according to the self-* properties of AC, namely, self-configuration, self-healing, self-optimization, and self-protection; (ii) the selected studies use different approaches for managing the dynamic behavior of middleware systems for WSN, such as policy-based reasoning, context-based reasoning, feedback control loops, mobile agents, model transformations, and code generation. Finally, we identified a lack of comprehensive system architecture designs that support the autonomy of sensor networking

Interoperability middleware for IIoT gateways based on international standard ontologies and standardized digital representation

Recent advances in the areas of microelectronics, information technology, and communication protocols have made the development of smaller devices with greater processing capacity and lower energy consumption. This context contributed to the growing number of physical devices in industrial environments which are interconnected and communicate via the internet, enabling concepts such as Industry 4.0 and the Industrial Internet of Things (IIoT). These nodes have different sensors and actuators that monitor and control environment data. Several companies develop these devices, including diverse communication protocols, data structures, and IoT platforms, which leads to interoperability issues. In IoT scenarios, interoperability is the ability of two systems to communicate and share services. Therefore, communication problems can make it unfeasible to use heterogeneous devices, increasing the project’s financial cost and development time. In an industry, interoperability is related to different aspects, such as physical communication, divergent device communication protocols, and syntactical problems, referring to the distinct data structure. Developing a new standard for solving these matters may bring interoperability-related drawbacks rather than effectively solving these issues. Therefore, to mitigate interoperability problems in industrial applications, this work proposes the development of an interoperability middleware for Edge-enabled IIoT gateways based on international standards. The middleware is responsible for translating communication protocols, updating data from simulations or physical nodes to the assets’ digital representations, and storing data locally or remotely. The middleware adopts the IEEE industrial standard ontologies combined with assets’ standardized digital models. As a case study, a simulation replicates the production of a nutrient solution for agriculture, controlled by IIoT nodes. The use case consists of three devices, each equipped with at least five sensors or actuators, communicating in different communication protocols and exchanging data using diverse structures. The performance of the proposed middleware and its proposed translations algorithms were evaluated, obtaining satisfactory results for mitigating interoperable in industrial applications.Devido a recentes avanços nas áreas de microeletrônica, tecnologia da informação, e protocolos de comunicação tornaram possível o desenvolvimento de dispositivos cada vez menores com maior capacidade de processamento e menor consumo energético. Esse contexto contribuiu para o crescente nú- mero desses dispositivos na industria que estão interligados via internet, viabilizando conceitos como Indústria 4.0 e Internet das Coisas Industrial (IIoT). Esses nós possuem diferentes sensores e atuadores que monitoram e controlam os dados do ambiente. Esses equipamentos são desenvolvidos por diferentes empresas, incluindo protocolos de comunicação, estruturas de dados e plataformas de IoT distintos, acarretando em problemas de interoperabilidade. Em cenários de IoT, interoperabilidade, é a capacidade de sistemas se comunicarem e compartilharem serviços. Portanto, esses problemas podem inviabilizar o uso de dispositivos heterogêneos, aumentando o custo financeiro do projeto e seu tempo de desenvolvimento. Na indústria, interoperabilidade se divide em diferentes aspectos, como comunicação e problemas sintáticos, referentes à estrutura de dados distinta. O desenvolvimento de um padrão industrial pode trazer mais desvantagens relacionadas à interoperabilidade, em vez de resolver esses problemas. Portanto, para mitigar problemas relacionados a intoperabilidade industrial, este trabalho propõe o desenvolvimento de um middleware de interoperável para gateways IIoT baseado em padrões internacionais e ontologias. O middleware é responsável por traduzir diferentes protocolos de comunicação, atualizar os dados dos ativos industriais por meio de suas representações digitais, esses armazenados localmente ou remotamente. O middleware adota os padrões ontológicos industriais da IEEE combinadas com modelos digitais padronizados de ativos industriais. Como estudo de caso, são realizadas simulações para a produção de uma solução nutritiva para agricultura, controlada por nós IIoT. O processo utiliza três dispositivos, cada um equipado com pelo menos cinco sensores ou atuadores, por meio de diferentes protocolos de comunicação e estruturas de dados. O desempenho do middleware proposto e seus algoritmos de tradução foram avaliados e apresentados no final do trabalho, os quais resultados foram satisfatórios para mitigar a interoperabilidade em aplicações industriais

Middleware and Architecture for Advanced Applications of Cyber-physical Systems

In this thesis, we address issues related to middleware, architecture and applications of cyber-physical systems. The first problem we address is the cross-layer design of cyber-physical systems to cope with interactions between the cyber layer and the physical layer in a dynamic environment. We propose a bi-directional middleware that allows the optimal utilization of the common resources for the benefit of either or both the layers in order to obtain overall system performance. The case study of network connectivity preservation in a vehicular formation illustrates how this approach can be applied to a particular situation where the network connectivity drives the application layer. Next we address another aspect of cross-layer impact: the problem that arises when network performance, in this case delay performance, affects control system performance. We propose a two-pronged approach involving a flexible adaptive model identification algorithm with outlier rejection, which in turn uses an adaptive system model to detect and reject outliers, thus shielding the estimation algorithm and thereby improving reliability. We experimentally demonstrate that the outlier rejection approach which intercepts and filters the data, combined with simultaneous model adaptation, can result in improved performance of Model Predictive Control in the vehicular testbed. Then we turn to two advanced applications of cyber-physical systems. First, we address the problem of security of cyber-physical systems. We consider the context of an intelligent transportation system in which a malicious sensor node manipulates the position data of one of the autonomous cars to deviate from a safe trajectory and collide with other cars. In order to secure the safety of such systems where sensor measurements are compromised, we employ the procedure of “dynamic watermarking”. This procedure enables an honest node in the control loop to detect the existence of a malicious node within the feedback loop. We demonstrate in the testbed that dynamic watermarking can indeed protect cars against collisions even in the presence of sensor attacks. The second application of cyber-physical systems that we consider is cyber-manufacturing which is an origami-type laser-based custom manufacturing machine employing folding and cutting of sheet material to manufacture 3D objects. We have developed such a system for use in a laser-based autonomous custom manufacturing machine equipped with real-time sensing and control. The basic elements in the architecture are a laser processing machine, a sensing system to estimate the state of the workpiece, a control system determining control inputs for a laser system based on the estimated data, a robotic arm manipulating the workpiece in the work space, and middleware supporting the communication among the systems. We demonstrate automated 3D laser cutting and bending to fabricate a 3D product as an experimental result. Lastly, we address the problem of traffic management of an unmanned aerial system. In an effort to improve the performance of the traffic management for unmanned aircrafts, we propose a probability-based collision resolution algorithm. The proposed algorithm analyzes the planned trajectories to calculate their collision probabilities, and modifies individual drone starting times to reduce the probability of collision, while attempting to preserve high performance. Our simulation results demonstrate that the proposed algorithm improves the performance of the drone traffic management by guaranteeing high safety with low modification of the starting times