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

An artificial intelligence-based collaboration approach in industrial IoT manufacturing : key concepts, architectural extensions and potential applications

The digitization of manufacturing industry has led to leaner and more efficient production, under the Industry 4.0 concept. Nowadays, datasets collected from shop floor assets and information technology (IT) systems are used in data-driven analytics efforts to support more informed business intelligence decisions. However, these results are currently only used in isolated and dispersed parts of the production process. At the same time, full integration of artificial intelligence (AI) in all parts of manufacturing systems is currently lacking. In this context, the goal of this manuscript is to present a more holistic integration of AI by promoting collaboration. To this end, collaboration is understood as a multi-dimensional conceptual term that covers all important enablers for AI adoption in manufacturing contexts and is promoted in terms of business intelligence optimization, human-in-the-loop and secure federation across manufacturing sites. To address these challenges, the proposed architectural approach builds on three technical pillars: (1) components that extend the functionality of the existing layers in the Reference Architectural Model for Industry 4.0; (2) definition of new layers for collaboration by means of human-in-the-loop and federation; (3) security concerns with AI-powered mechanisms. In addition, system implementation aspects are discussed and potential applications in industrial environments, as well as business impacts, are presented

Linking circular economy and digitalisation technologies : A systematic literature review of past achievements and future promises

The circular economy (CE) has the potential to capitalise upon emerging digital technologies, such as big data, artificial intelligence (AI), blockchain and the Internet of things (IoT), amongst others. These digital technologies combined with business model innovation are deemed to provide solutions to myriad problems in the world, including those related to circular economy transformation. Given the societal and practical importance of CE and digitalisation, last decade has witnessed a significant increase in academic publication on these topics. Therefore, this study aims to capture the essence of the scholarly work at the intersection of the CE and digital technologies. A detailed analysis of the literature based on emerging themes was conducted with a focus on illuminating the path of CE implementation. The results reveal that IoT and AI play a key role in the transition towards the CE. A multitude of studies focus on barriers to digitalisation-led CE transition and highlight policy-related issues, the lack of predictability, psychological issues and information vulnerability as some important barriers. In addition, product-service system (PSS) has been acknowledged as an important business model innovation for achieving the digitalisation enabled CE. Through a detailed assessment of the existing literature, a viable systems-based framework for digitalisation enabled CE has been developed which show the literature linkages amongst the emerging research streams and provide novel insights regarding the realisation of CE benefits.© 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Sistemas de informação na indústria 4.0 : mecanismos de apoio à transferência de dados para conhecimento em ambientes Lean

The paradigm that presently emerges in the organizational context, known as Industry 4.0 (I4.0) or Fourth Industrial Revolution, promises to bring principles of connectivity and flexibility to the companies that embrace it. Industry 4.0 enhances the efficiency in adapting in real time to the customers’ requirements, through the establishment of an intelligent shop floor capable of answering in a flexible and customized way to market changes. However, during the last three decades, it is known that the adoption of the Lean philosophy was absorbed by the industrial environment, with results that proved to be exuberant, considering the simplicity of the tools. In this way, the I4.0 implementation must be prepared to preserve the existing manufacturing systems, proceeding, whenever possible, to upgrade them on a Lean excellence basis. It is said that information systems will be decisive in the foundation of the I4.0 paradigm. Of these, MES systems, with greater connection to the shop floor, will tend to be aligned with existing practices, contributing, through their connectivity, to the introduction of knowledge management practices and data visualization mechanisms. In the specification and architecture phase of these systems, understanding the processes will be crucial. Thus, their documentation is an organizational pillar, with BPMN and UML being able to guide it. However, and in addition to its usefulness in the processes’ mapping, BPMN is also likely to be applied in capturing tacit knowledge, which can be a foundation for the constitution of knowledge repositories, impacting organizational excellence. It is in this context that the present work is implanted, aiming at the creation of guidelines and mechanisms that facilitate the implementation of I4.0 strategies in Lean industrial environments. The adopted methodology first went through an exhaustive literature review, in order to find possible bilateral effects between I4.0 technologies and lean tools. Then, the development of some applications aligned with the I4.0 paradigm, as a technological engine, and the Lean philosophy, as a tool for eliminating waste and / or creating value, was contemplated. From the various development experiences in an industrial context and considering the evidence reported in the literature, this study proposes a Lean 4.0 framework oriented to the shop floor.O paradigma que atualmente emerge no contexto organizacional, conhecido como Indústria 4.0 (I4.0) ou Quarta Revolução Industrial, promete trazer princípios de conectividade e flexibilidade às empresas que a adotam. A Indústria 4.0 potencia a eficácia no ajuste em tempo real aos requisitos dos clientes, através da constituição de um chão de fábrica inteligente e capaz de responder de forma flexível e customizada às mudanças do mercado. Contudo, durante as últimas três décadas, sabe-se que a adoção da filosofia Lean foi absorvida pelo meio industrial, com resultados que se demonstraram exuberantes, tendo em conta a simplicidade das ferramentas. Deste modo, a implementação I4.0 deve ser feita no sentido da preservação dos sistemas de manufatura já existentes, procedendo, desde que possível, ao seu upgrade numa base de excelência Lean. Conta-se que os sistemas de informação serão decisivos na fundação do paradigma I4.0. Destes, os sistemas MES, com maior conexão ao chão de fábrica, tenderão a ser alinhados com as práticas já existentes, contribuindo, através da sua conectividade, para a introdução de práticas de gestão do conhecimento e mecanismos de visualização de dados. Na fase de especificação e arquitetura destes sistemas, o entendimento dos processos será crucial. Assim, a documentação dos mesmos é um pilar organizacional, estando o BPMN e a UML capazes de a orientar. Porém, e a somar à sua utilidade na ilustração de processos, o BPMN está igualmente passível de ser aplicado na captação de conhecimento tácito, o que por si pode ser uma base para a constituição de repositórios de conhecimento, contribuindo para a excelência organizacional. É neste contexto que o presente trabalho se insere, tendo como objetivo a criação de linhas orientadoras e mecanismos que facilitem a implementação de estratégias I4.0 em ambientes industriais Lean. A metodologia adotada passou, primeiramente, por uma exaustiva revisão da literatura, por forma a encontrar possíveis efeitos bilaterais entre tecnologias I4.0 e ferramentas lean. De seguida, contemplou-se o desenvolvimento de alguns aplicativos alinhados ao paradigma I4.0, enquanto motor tecnológico, e à filosofia Lean, enquanto ferramenta de eliminação de desperdícios e/ou criação de valor. Das diversas experiências de desenvolvimento em contexto industrial e considerando as evidências reportadas na literatura o presente estudo propõe uma framework Lean 4.0 orientado ao chão de fábrica.Mestrado em Engenharia e Gestão Industria

Business Process Decomposition and Distribution for Adaptive Internet of Things

Asjade internet (IoT) pakub suurt potentsiaali mitmetes erinevates valdkondades. Selleks, et seda potentsiaali realiseerida, on vaja veel palju takistusi ületada. Üheks takistusteks on see, kuidas integreerida IoT süsteemid äriportsesside juhtimiseks mõeldud standarditega. Käesoleva magistritöö esimene osa annab ülevaate erinevate äriprotsesside standardite sobivusest IoT platvormiga. Teises osas võetakse luubi alla esimeses osas sobivaimaks tunnistatud äriprotsesside juhtimise modelleerimisstandard ja keskendutakse IoT platvormi probleemidele, mis on seotud koduautomaatikaga. Esimene väljakutse on selles, et kuna turule tuleb üha uusi IoT andureid ja seadmeid, mis võimaldavad suuremaid ja keerukamaid lahendusi nagu näiteks näotuvastusel toimiv tark ukselukk, siis need seadmed nõuavad ka suuremat arvutusvõimsust. Kodused kontrollerid on aga sageli piiratud ressursiga seadmed ning on seetõttu pudelikaelaks sellistes targa kodu süsteemides. Teine väljakutse on see, et erinevad tootjad tulevad turule endakoduautomaatika süsteemidega, mis omavahel suhelda ei suuda. Seega läheb vaja mitut rakendust, et tarka kodu juhtida. Nende probleemide lahendamiseks esitan kontseptuaalse IoT terviksüsteemi, mis võimaldab protsessid lõhkuda osadeks ja need osad käivitada teistes süsteemides, et vähendada koduse kontrolleri jõudlusvajadust. IoT seadmed selles terviksüsteemis on ühendatud kasutades platvormi, mis võimaldab erinevad koduautomaatika süsteemid üheks luua. Magistritöö raames valmis laiendus Camunda töövoo juhtimise platvormile, mis realiseerib esitatud terviksüsteemi. Esitan selle laienduse nõuded ja piirangud ning ilmestan neid kasutades targa kodu protsesse.The Internet of Things (IoT) offers a great potential in many different application areas such as health care and home automation. However, in order to realize this potential, significant hurdles still have to be overcome. One of the hurdles is how to integrate IoT systems into business processes in the context of using standards such as BPMN2.0. In this thesis I present the results of a state of the art synthesis of Business Process Driven Internet of Things approaches. Based on the results, a business process modelling standard was chosen and used to overcome challenges which are related with IoT and home automation. The first challenge is the adaptiveness of the current IoT systems. For example, while new and more capable sensors enable complex applications such as smart door locks with face recognition that require significant computing resources, home controllers are often resource-constrained devices and therefore considered as a bottleneck for these complex systems. The second challenge is the interoperability of the current home automation systems because systems provided by different vendors cannot be controlled by the same application. To address these issues, this thesis proposes a software framework that enhances the adaptiveness and performance of IoT solutions. This is achieved through a novel approach where the process model is decomposed and the decomposed subparts are offloaded to an external entity. A prototype of this framework has been implemented using Camunda workflow engine. The framework supports IoT by integrating with the OpenHAB smart home system. The performance and scalability of the system is evaluated through a series of experimental case studies. Results showed that offloading can help in case of compute intensive tasks, a face recognition task performed three times faster for example

Architecture framework of IoT-based food and farm systems: A multiple case study

The Internet of Things (IoT) is expected to be a real game changer in food and farming. However, an important challenge for large-scale uptake of IoT is to deal with the huge heterogeneity of this domain. This paper develops and applies an architecture framework for modelling IoT-based systems in the agriculture and food domain. The framework comprises a coherent set of architectural viewpoints and a guideline to use these viewpoints to model architectures of individual IoT-based systems. The framework is validated in a multiple case study of the European IoF2020 project, including different agricultural sub sectors, conventional and organic farming, early adopters and early majority farmers, and different supply chain roles. The framework provides a valuable help to model, in a timely, punctual and coherent way, the architecture of IoT-based systems of this diverse set of use cases. Moreover, it serves as a common language for aligning system architectures and enabling reuse of architectural knowledge among multiple autonomous IoT-based systems in agriculture and food

The Role of Digital Technologies in Improving Energy Efficiency at Logistics Facilities: A State-of-the-Art

The logistics industry is facing increasing challenges that have been further amplified by recent disruptions. In this context, warehouses have been playing an ever-crucial role. They have been transitioning from simple storage centres into high-functional facilities where several and heterogeneous processes are performed to guarantee efficiency and service level fulfilment. These dramatic changes have often made them highly energy intensive. To cope with these changes, a wide array of digital technologies is now available and has started to be gradually introduced by companies at their logistics facilities to reduce energy consumption and improve the environmental sustainability of warehousing operations. Nevertheless, on the academic side, although a mounting number of papers have been found addressing the adoption of digital technologies at logistics facilities with an energy efficiency perspective, a clear overview of the solutions in place and their impact on warehousing processes has been largely neglected so far. This contribution aims at addressing this research gap by offering a state-of-the-art of the role of digital technologies in improving energy efficiency at logistics facilities. The study is based on a systematic review approach performed by means of the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol. The research is part of a broader Italian funded PNRR Research project “Centro Nazionale per la Mobilità Sostenibile” (MOST) – Spoke 10 “Sustainable Logistics”. Results indicate that the impact of digital technologies on warehouse processes is still underexamined, and research has mainly focused on specific technical issues or single warehousing processes rather than providing a holistic approach. The study provides a comprehensive framework offering guidance for technology implementation. Implications are discussed and streams for future investigation are identified