Page 81 - ITU Journal Future and evolving technologies Volume 2 (2021), Issue 5 – Internet of Everything

ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 5

SIOT FOR COGNITIVE LOGISTICS: LEVERAGING THE SOCIAL GRAPH OF DIGITAL TWINS FOR
EFFECTIVE OPERATIONS ON REAL‑TIME EVENTS

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Miha Cimperman , Angela Dimitriou , Kostas Kalaboukas , Aziz S. Mousas , Salvatore Quattropani 5
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1 Institute Jozef Stefan, Ljubljana, Slovenia , Intrasoft International SA, Luxemburg, Technical University of Crete,
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Greece, SingularLogic SA, Greece, CNIT ‑ RU at the University of Catania, Italy
NOTE: Corresponding author: Salvatore Quattropani, Salvatore.quattropani@cnit.it
Abstract – Over the years, with the migration of organizations towards the concepts of logistics 4.0, a paradigm shift was
necessary to guarantee logistics ef iciency. The challenge is to dynamically cope in real time with vast number of shipments
and destinations, which need to be realigned both with a determined lead time and with a inite of available resources. Al‑
though a number of standards have already been adopted for the management of transport and logistics operations, tak‑
ing advantage, for instance, of Decision Support Systems and Geographic Information Systems, new models are required for
achieving effective handling of the dynamic logistics environment that is shaped today. In this paper, an integrated logistics
framework addressing the previous challenges is presented, for the irst time, as a result of the activities of the H2020 COG‑LO
project. This novel approach exploits Social Internet of Things (SIoT) and the digital twins technique to realize the concept
of the Cognitive Logistics Object (CLO). A CLO is de ined as an entity that is augmented with cognitive capabilities, it is au‑
tonomous, and bears social‑like capabilities, which enable the formulation of ad hoc communities for negotiating optimal
solutions in logistics operations.
Keywords – Cognitive logistics, collaborative logistics, digital twins, Social Internet of Things

1. INTRODUCTION identi ied limitations. The proposed solution imple-
ments dynamic optimization strategies streamlining the
The development of IoT and cyber‑physical systems [1]
burden of the decision‑making process, enhancing the
technologies lay the foundations for the evolution of lo‑
robustness of arti icial intelligence systems, and thus
gistics 4.0, in which the way of organizing supply and
allowing an increasingly pervasive approach of these
production changed drastically. The digitization process
techniques within the logistics 4.0 world.
pushes logistics operators and all interested parties to
The document is organized as follows: In Section 2, the
turn towards an approach that embraces all the techno‑
necessary background information is provided. In
logical innovations that the market offers. The aim is to
Section 3, the COG‑LO framework is introduced. In
reach the economic objectives faster and to improve logis‑
Section 4, the system’s performance is evaluated. Finally,
tics services’ quality. The new emerging logistics scenario
Section 5 concludes with some inal remarks.
requires rapid information processing with a high level of
security. The spread of big data, the expansion of the lo‑
gistics chain, the problem of route optimization, the local‑ 2. DIGITAL LOGISTICS INFRASTRUCTURE
ization of resources, and the maximization of the load fac‑
tor have become the main focus of research and develop‑ In recent years, the issues of digital transformation of
ment in the logistics sector. The challenges listed do not transport infrastructures have been of particular impor‑
only require the introduction of new logistics concepts, tance in the context of Industry 4.0. Numerous real‑time
but also need a signi icant effort to go beyond the common planning algorithms have been developed by the logistics
vision of the elements participating in the logistics chain. community over the last thirty years; these include Deci‑
The COG‑LO project [2] addresses these challenges by im‑ sion Support Systems (DSS) [5] and Geographic Informa‑
plementing innovative tools that enable logistics 4.0 [3]. tion Systems (GIS), i.e. a group of procedures that pro‑
Logistics entities become both cognitive and collabora‑ vide input, data storage and retrieval, mapping and spa‑
tive. Their level of interoperability increases signi icantly tial analysis [6], and tools to support the organization’s
thanks to the digitization of all the actors participating in decision‑making activities. In the past decades, several ef‑
the supply chain (cargo, vehicle, warehouse, parking slot, forts have been made to integrate GIS with DSS, promot‑
other transport modes, systems, etc.). This is achieved ing the concept of collaborative GIS. The GS1 [7] system
by exploiting an ad hoc dynamic social network based on of standards is currently the de initive framework widely
the Social Internet of Things (SIoT) paradigm [4]. SIoT recognized in the ield of logistics. It ensures a high de‑
enables these actors to interact and negotiate potential gree of interoperability between stakeholders and pro‑
vides a standard way to identify objects and locations.
alternative solutions to emerging logistics requirements,
taking into account their current status, needs and

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