Dataset Information

Towards an Autonomous Industry 4.0 Warehouse: A UAV and Blockchain-Based System for Inventory and Traceability Applications in Big Data-Driven Supply Chain Management.

ABSTRACT: Industry 4.0 has paved the way for a world where smart factories will automate and upgrade many processes through the use of some of the latest emerging technologies. One of such technologies is Unmanned Aerial Vehicles (UAVs), which have evolved a great deal in the last years in terms of technology (e.g., control units, sensors, UAV frames) and have significantlyr educed their cost. UAVs can help industry in automatable and tedious tasks, like the ones performed on a regular basis for determining the inventory and for preserving item traceability. In such tasks, especially when it comes from untrusted third parties, it is essential to determine whether the collected information is valid or true. Likewise, ensuring data trustworthiness is a key issue in order to leverage Big Data analytics to supply chain efficiency and effectiveness. In such a case, blockchain, another Industry 4.0 technology that has become very popular in other fields like finance, has the potential to provide a higher level of transparency, security, trust and efficiency in the supply chain and enable the use of smart contracts. Thus, in this paper, we present the design and evaluation of a UAV-based system aimed at automating inventory tasks and keeping the traceability of industrial items attached to Radio-Frequency IDentification (RFID) tags. To confront current shortcomings, such a system is developed under a versatile, modular and scalable architecture aimed to reinforce cyber security and decentralization while fostering external audits and big data analytics. Therefore, the system uses a blockchain and a distributed ledger to store certain inventory data collected by UAVs, validate them, ensure their trustworthiness and make them available to the interested parties. In order to show the performance of the proposed system, different tests were performed in a real industrial warehouse, concluding that the system is able to obtain the inventory data really fast in comparison to traditional manual tasks, while being also able to estimate the position of the items when hovering over them thanks to their tag's signal strength. In addition, the performance of the proposed blockchain-based architecture was evaluated in different scenarios.

SUBMITTER: Fernandez-Carames TM

PROVIDER: S-EPMC6566655 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Towards an Autonomous Industry 4.0 Warehouse: A UAV and Blockchain-Based System for Inventory and Traceability Applications in Big Data-Driven Supply Chain Management.

Fernández-Caramés Tiago M TM Blanco-Novoa Oscar O Froiz-Míguez Iván I Fraga-Lamas Paula P

Sensors (Basel, Switzerland) 20190525 10

Industry 4.0 has paved the way for a world where smart factories will automate and upgrade many processes through the use of some of the latest emerging technologies. One of such technologies is Unmanned Aerial Vehicles (UAVs), which have evolved a great deal in the last years in terms of technology (e.g., control units, sensors, UAV frames) and have significantlyr educed their cost. UAVs can help industry in automatable and tedious tasks, like the ones performed on a regular basis for determini ...[more]

PMID: 31130644

Similar Datasets

Project description:BackgroundAs Industry 4.0 debuted roughly a decade ago, it is now necessary to examine how it affects various aspects of the discipline. It is the responsibility of the education sector to guarantee that the next generation is equipped mentally, physically, and cognitively to face unforeseen challenges. Numerous educational institutions are outfitted with Industry 4.0 technology-based learning. Industry 4.0 fosters advancements in learning methodologies, especially for language enhancements. Learners may gain knowledge at their base, providing them an opportunity for independent study. The majority of subjects have been acquired through Industry 4.0. This research chapter explores the intersection of Industry 4.0 and education, specifically focusing on the SmallTalk AI tool. It investigates how technological and digital innovations within the context of Industry 4.0 can serve as powerful tools to enhance language learning outcomes.MethodsThis article presents a comprehensive analysis of statistical data and empirical evidence to support the positive impact of Industry 4.0 technology of SmallTalk on language acquisition particularly speaking. The study also determines the relationship among participants' usage through the technology acceptance model (TAM). Furthermore, it examines the challenges and opportunities associated with integrating these innovations into language learning pedagogies, offering insights for educators and policymakers to harness the potential of Industry 4.0 in fostering language proficiency. The research employs quantitative analysis. The data obtained from educational institutions has been analyzed using the SPSS and AMOS software.ResultsThe results indicate that Industry 4.0 has had an important effect on English language acquisition. This self-supported adaptable system of education facilitates effective student learning. This study also suggests that future research into the utility of Industry 4.0 be conducted elsewhere internationally.

Project description:Clinical trial consent for protocols and their revisions should be transparent for patients and traceable for stakeholders. Our goal is to implement a process allowing for collection of patients' informed consent, which is bound to protocol revisions, storing and tracking the consent in a secure, unfalsifiable and publicly verifiable way, and enabling the sharing of this information in real time. For that, we build a consent workflow using a trending technology called Blockchain. This is a distributed technology that brings a built-in layer of transparency and traceability. From a more general and prospective point of view, we believe Blockchain technology brings a paradigmatical shift to the entire clinical research field. We designed a Proof-of-Concept protocol consisting of time-stamping each step of the patient's consent collection using Blockchain, thus archiving and historicising the consent through cryptographic validation in a securely unfalsifiable and transparent way. For each protocol revision, consent was sought again. We obtained a single document, in an open format, that accounted for the whole consent collection process: a time-stamped consent status regarding each version of the protocol. This document cannot be corrupted and can be checked on any dedicated public website. It should be considered a robust proof of data. However, in a live clinical trial, the authentication system should be strengthened to remove the need for third parties, here trial stakeholders, and give participative control to the peer users. In the future, the complex data flow of a clinical trial could be tracked by using Blockchain, which core functionality, named Smart Contract, could help prevent clinical trial events not occurring in the correct chronological order, for example including patients before they consented or analysing case report form data before freezing the database. Globally, Blockchain could help with reliability, security, transparency and could be a consistent step toward reproducibility.

Project description:The growing global concern with sustainability has driven companies to rethink their business model and seek new ways to operate and face this challenge. Industry 4.0 (I4.0) has shown itself capable of contributing to the development or reformulation of organizational processes to make them more competitive and sustainable. Thus, this article aims to propose drivers for the development of corporate sustainability via I4.0. To this end, a literature review and content analysis were used as research methods to identify and analyze, in recent scientific literature, boosting elements that enable organizational processes to become more sustainable via I4.0. Based on these elements, six drivers were systematized and proposed: strategy; product and process design; energy and material resources; people; smart production; and supply chain. Each driver was discussed in light of the scientific literature to generate recommendations for companies to develop the economic, social, and environmental dimensions of sustainability. The main theoretical-scientific contribution of this work is the deepening and expansion of the knowledge block that articulates corporate sustainability with I4.0, which strengthens the basis for the development of new research on these topics and creates a reference for the analysis and discussion of empirical studies. As an applied-managerial contribution, the drivers proposed in this work will provide organizations and their managers with a point of reference to effectively move towards sustainability, making their businesses greener, fairer, and more profitable. A limitation of this study is that the proposed drivers were based on the 30 most cited articles and did not consider other sources, such as documentation from companies. Therefore, for future studies, we suggest increasing the article base and include organizational repositories and identify how SMEs can become sustainable through I4.0 in a way that strengthens the social dimension of sustainability.

Dataset Information

Towards an Autonomous Industry 4.0 Warehouse: A UAV and Blockchain-Based System for Inventory and Traceability Applications in Big Data-Driven Supply Chain Management.

Publications

Towards an Autonomous Industry 4.0 Warehouse: A UAV and Blockchain-Based System for Inventory and Traceability Applications in Big Data-Driven Supply Chain Management.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets