A review of logistics Internet-of-Things: Current trends and scope for future research

Supply Chain processes are continuously marred by myriad factors including varying demands, changing routes, major disruptions, and compliance issues. Therefore, supply chains require monitoring and ongoing optimization. Data science uses real-time data to provide analytical insights, leading to automation and improved decision making. RFID is an ideal technology to source big data, particularly in supply chains, because RFID tags are consumed across supply chain process, which includes scanning raw materials, completing products, transporting goods, and storing products, with accuracy and speed. This study carries out a systematic literature review of research articles published during the timeline (2000-2021) that discuss the role of RFID technology in developing decision support systems that optimize supply chains in light of Industry 4.0. Furthermore, the study offers recommendations on operational efficiency of supply chains while reducing the costs of implementing the RFID technology. The core contribution of this paper is its analysis and evaluation of various RFID implementation methods in supply chains with the aim of saving time effectively and achieving cost efficiencies. 

Enhancing supply chain performance using RFID technology and decision support systems in the industry 4.0-A systematic literature review

This study addresses the emerging concept of Industry 5.0, which aims to tackle societal concerns associated with the ongoing digital industrial transformation. However, there is still a lack of consensus on the definition and scope of Industry 5.0, as well as limited understanding of its technological components, design principles, and intended values. To bridge these knowledge gaps, the study conducts a content-centric review of relevant literature and synthesizes evidence to develop an architectural design for Industry 5.0. The findings reveal that Industry 5.0 represents the future of industrial transformation, offering potential solutions to socio-economic and environmental issues that were inadequately addressed or exacerbated by Industry 4.0. The study provides managers, industrialists, and policymakers with a comprehensive overview of Industry 5.0, including its technological constituents, design principles, and smart components, emphasizing the importance of stakeholder involvement and integration for effective governance of digital industrial transformation within this framework. 

Behind the definition of Industry 5.0: a systematic review of technologies, principles, components, and values

: Technological growth is changing our everyday living, making it smarter and more convenient day by day; Smart society 5.0, Healthcare 5.0, Agriculture 5.0 are only a few examples indicative of our fast-evolving lifestyle. The Industrial Revolution 5.0 (IR 5.0) encapsulates future industry development trends to achieve prosperity beyond jobs by incorporating more intelligence in our everyday living with the help of cutting-edge technologies such as Explainable Artificial Intelligence. This paper reviews the enabling technologies for Industry 5.0 and suggests some pertinent research areas requiring more focus. The transition of manufacturing processes from mass production to mass personalization, the anticipated reliance on Cyber-Physical Systems (CPS) and digital twins is visualized, to identify the gaps in fully realizing the revolution. The operations of smart factories to enhance the overall productivity, modern workforce comprising of human-machine collaboration, means of heterogeneous data transmission & data interoperability, and security & privacy issues are reviewed to identify hot research spots, that will eventually fill in the gaps within societal domains to realize Industry 5.0. The potential of the new domain of Explainable Artificial intelligence to understand the application of right tools in a data connected Industry 5.0 compliant smart society is explored. Altogether, this research explores several research challenges and opportunities linked with IR 5.0.

/pdf/towards-industrial-revolution-5-0-and-explainable-artificial-15wbjel6.pdf

Towards Industrial Revolution 5.0 and Explainable Artificial Intelligence: Challenges and Opportunities

Warehouse management will be the focus of this article, which aims to examine the benefits and issues & challenges of using Industry 4.0 technologies to achieve Sustainable Development Goals (SDGs) by the United Nations (UN). We conducted a Systematic Literature Review (SLR) evaluation of the published literature from credible peer-reviewed journals in the major databases Scopus and Web of Science. The analysis of literature will be a frequency analysis of the literature by considering the year of publications, the contribution of leading journals and publishers, and the methodology adopted and the content analysis of literature to get the benefits, issues & challenges of the implementation of industry 4.0 on warehouses in accordance to SDGs that were identified from the literature. Industry 4.0 research on logistics and supply chain management, as well as warehouse management, showed a significant increase in research papers in the past two years. But, the study on industry 4.0 in warehousing toward SDGs is still in its early stages, with just a few articles contributing to sustainable practices. Our findings from the literature reveal that the major benefits of implementing industry 4.0 in warehouse management as per SDGs are “SDG – 2 (Zero Hunger)”, “SDG – 4 (Quality Education)”, “SDG – 7 (Affordable and Clean Energy)”, “SDG − 9 (Industry, Innovation, and Infrastructure)”, “SDG – 12 (Ensure Sustainable Consumption and Production Patterns)”, and “SDG – 13 (Climate Action)”. Lack of government support, legal issues, lack of skilled manpower, political issues, and old/traditional warehouses are the major issues & challenges of industry 4.0 in warehouses to avert the deed of achieving SDGs in developing countries. This study is one of those that apply industry 4.0 in the context of warehouse management, thus it will reveal insights and implications for future research. 

A systematic literature review of integration of industry 4.0 and warehouse management to achieve Sustainable Development Goals (SDGs)

Smart logistics is an effective way to meet the challenges of fast-changing customer expectations, take opportunities brought by new technologies, and facilitate new business models. This review pa...

Smart logistics based on the internet of things technology: an overview

Federated learning (FL) attempts to train a global model by aggregating local models from distributed devices under the coordination of a central server. However, the existence of a large number of heterogeneous devices makes FL vulnerable to various attacks, especially the stealthy backdoor attack. Backdoor attack aims to trick a neural network to misclassify data to a target label by injecting specific triggers while keeping correct predictions on original training data. Existing works focus on client-side attacks which try to poison the global model by modifying the local datasets. In this work, we propose a new attack model for FL, namely Data-Agnostic Backdoor attack at the Server (DABS), where the server directly modifies the global model to backdoor an FL system. Extensive simulation results show that this attack scheme achieves a higher attack success rate compared with baseline methods while maintaining normal accuracy on the clean data.

DABS: Data-Agnostic Backdoor attack at the Server in Federated Learning

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Smart logistics based on the internet of things technology: an overview

DABS: Data-Agnostic Backdoor attack at the Server in Federated Learning