Improving sustainability through intelligent cargo and adaptive decision making

In the current society, logistics is faced with the challenge to meet more stringent sustainability goals. Shippers and transport service providers both aim to reduce the carbon footprint of their logistic operations. To do so, optimal use of logistics resources and physical infrastructure should be aimed for. An adaptive decision making process for the selection of a specific transport modality, transport provider and timeslot (aimed at minimisation of the carbon footprint) enables shippers to achieve this. This requires shippers to have access to up-to-date capacity information from transport providers (e.g. current and scheduled loading status of the various transport means and information on carbon footprint) and traffic information (e.g. city logistics and current traffic information). A prerequisite is an adequate infrastructure for collaboration and open exchange of information between the various stakeholders in the logistics value chain to obtain the up-to-date information. This paper gives a view on how such an advanced information infrastructure can be realised, currently being developed within the EU iCargo project. The paper describes a reference logistics value chain, including business benefits for each of the roles in the logistics value chain of aiming for sustainability. A case analysis is presented that reflects a practical situation in which the various roles collaborate and exchange information for realizing sustainability goals, using adaptive decision making for selecting a transport modality, transport provider, and timeslot. A high-level overview is provided of the requirements on and technical implementation of the supporting advanced infrastructure for collaboration and open information exchange.In the current society, logistics is faced with the challenge to meet more stringent sustainability goals. Shippers and transport service providers both aim to reduce the carbon footprint of their logistic operations. To do so, optimal use of logistics resources and physical infrastructure should be aimed for. An adaptive decision making process for the selection of a specific transport modality, transport provider and timeslot (aimed at minimisation of the carbon footprint) enables shippers to achieve this. This requires shippers to have access to up-to-date capacity information from transport providers (e.g. current and scheduled loading status of the various transport means and information on carbon footprint) and traffic information (e.g. city logistics and current traffic information). A prerequisite is an adequate infrastructure for collaboration and open exchange of information between the various stakeholders in the logistics value chain to obtain the up-to-date information. This paper gives a view on how such an advanced information infrastructure can be realised, currently being developed within the EU iCargo project. The paper describes a reference logistics value chain, including business benefits for each of the roles in the logistics value chain of aiming for sustainability. A case analysis is presented that reflects a practical situation in which the various roles collaborate and exchange information for realizing sustainability goals, using adaptive decision making for selecting a transport modality, transport provider, and timeslot. A high-level overview is provided of the requirements on and technical implementation of the supporting advanced infrastructure for collaboration and open information exchange.In the current society, logistics is faced with the challenge to meet more stringent sustainability goals. Shippers and transport service providers both aim to reduce the carbon footprint of their logistic operations. To do so, optimal use of logistics resources and physical infrastructure should be aimed for. An adaptive decision making process for the selection of a specific transport modality, transport provider and timeslot (aimed at minimisation of the carbon footprint) enables shippers to achieve this. This requires shippers to have access to up-to-date capacity information from transport providers (e.g. current and scheduled loading status of the various transport means and information on carbon footprint) and traffic information (e.g. city logistics and current traffic information). A prerequisite is an adequate infrastructure for collaboration and open exchange of information between the various stakeholders in the logistics value chain to obtain the up-to-date information. This paper gives a view on how such an advanced information infrastructure can be realised, currently being developed within the EU iCargo project. The paper describes a reference logistics value chain, including business benefits for each of the roles in the logistics value chain of aiming for sustainability. A case analysis is presented that reflects a practical situation in which the various roles collaborate and exchange information for realizing sustainability goals, using adaptive decision making for selecting a transport modality, transport provider, and timeslot. A high-level overview is provided of the requirements on and technical implementation of the supporting advanced infrastructure for collaboration and open information exchange

Cooperation platform for distributed manufacturing

The aim of the paper is to analyse contemporary trends in distributed manufacturing (DM) research and to present a concept to develop and test some task allocation, planning and scheduling algorithms for DM network organisations. Some concepts to identify key factor criteria and reasoning policies and rules for production/manufacturing decision support system are also undertaken. And finally, an aim is to draw a proposal for a development of a prototype decision support system with necessary communication and knowledge oriented modules to be implemented in an example of dynamic, DM and logistics network structure, particularly for very popular dynamic cluster forms in Poland. The developed concept of the organization of a multi-entity DM network will enable business-effective use of the system, supporting manufacturing decision making, consulting and offering information services in the control centre (the so-called Competence Centre) by constructing virtual reality and access to services in a distributed network of cloud computing type. Integration of the whole system into one information system will enable analysis and network resource optimization of manufacturing and logistics processes, new analytical functions, reduction of delays in the manufacturing system, management of changes and risks, and visualization of the current state of the DM system

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

Mapping Cloud-Edge-IoT opportunities and challenges in Europe

While current data processing predominantly occurs in centralized facilities, with a minor portion handled by smart objects, a shift is anticipated, with a surge in data originating from smart devices. This evolution necessitates reconfiguring the infrastructure, emphasising computing capabilities at the cloud's "edge" closer to data sources. This change symbolises the merging of cloud, edge, and IoT technologies into a unified network infrastructure - a Computing Continuum - poised to redefine tech interactions, offering novel prospects across diverse sectors. The computing continuum is emerging as a cornerstone of tech advancement in the contemporary digital era. This paper provides an in-depth exploration of the computing continuum, highlighting its potential, practical implications, and the adjustments required to tackle existing challenges. It emphasises the continuum's real-world applications, market trends, and its significance in shaping Europe's tech future

Internet of Things Strategic Research Roadmap

Internet of Things (IoT) is an integrated part of Future Internet including existing and evolving Internet and network developments and could be conceptually defined as a dynamic global network infrastructure with self configuring capabilities based on standard and interoperable communication protocols where physical and virtual “things” have identities, physical attributes, and virtual personalities, use intelligent interfaces, and are seamlessly integrated into the information network

Impact of COVID-19 on iot adoption in healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT

COVID-19 has disrupted normal life and has enforced a substantial change in the policies, priorities and activities of individuals, organisations and governments. These changes are proving to be a catalyst for technology and innovation. In this paper, we discuss the pandemic's potential impact on the adoption of the Internet of Things (IoT) in various broad sectors namely healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT. Our perspective and forecast of this impact on IoT adoption is based on a thorough research literature review, a careful examination of reports from leading consulting firms and interactions with several industry experts. For each of these sectors, we also provide the details of notable IoT initiatives taken in wake of COVID-19. We also highlight the challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption.Comment: This is the version accepted at Sensors 202

Design and evaluation of a scalable Internet of Things backend for smart ports

Internet of Things (IoT) technologies, when adequately integrated, cater for logistics optimisation and operations' environmental impact monitoring, both key aspects for today's EU ports management. This article presents Obelisk, a scalable and multi-tenant cloud-based IoT integration platform used in the EU H2020 PortForward project. The landscape of IoT protocols being particularly fragmented, the first role of Obelisk is to provide uniform access to data originating from a myriad of devices and protocols. Interoperability is achieved through adapters that provide flexibility and evolvability in protocol and format mapping. Additionally, due to ports operating in a hub model with various interacting actors, a second role of Obelisk is to secure access to data. This is achieved through encryption and isolation for data transport and processing, respectively, while user access control is ensured through authentication and authorisation standards. Finally, as ports IoTisation will further evolve, a third need for Obelisk is to scale with the data volumes it must ingest and process. Platform scalability is achieved by means of a reactive micro-services based design. Those three essential characteristics are detailed in this article with a specific focus on how to achieve IoT data platform scalability. By means of an air quality monitoring use-case deployed in the city of Antwerp, the scalability of the platform is evaluated. The evaluation shows that the proposed reactive micro-service based design allows for horizontal scaling of the platform as well as for logarithmic time complexity of its service time