Communication-efficient federated learning for digital twin systems of industrial internet of things

With the rapid development and deployment of Industrial Internet of Things technology, it promotes interconnection and edge applications in smart manufacturing. However, challenges remain, such as yet-to-improve communication efficiency and trade-offs between computing power and energy consumption, which limits the application and further development of IIoT technology. This paper proposes the digital twin systems into the IIoT to build model between physical objects and digital virtual systems to optimize the structure of IIoT. And we further introduce federal learning to train the digital twins model and to improve the communication efficiency of IIoT. In this paper, we first establish the digital twins model of IIoT based on industrial scenario. Moreover, to optimize the communication overhead allocation problem, this paper proposes an improved communication-efficient distribution algorithm, which speeds up the training performance of federated model and ensures the performance of industrial system model by changing the update training mode of client and server and allowing some industrial equipment to participate in federated training. This paper simulates the real-word intelligent camera detection to validate the proposed method. Comparing our proposed method with the existing traditional methods, the results show the advantages of the proposed method can improve the communication performance of the training model

Systematic Review of Internet of Things Security

The Internet of Things has become a new paradigm of current communications technology that requires a deeper overview to map its application domains, advantages, and disadvantages. There have been a number of in-depth research efforts to study various aspects of IoT. However, to the best of our knowledge, there is no literature that have discussed specifically and deeply about the security and privacy aspects of IoT. To that end, this paper aims at providing a more comprehensive and systematic review of IoT security based on the survey result of the most recent literature over the past three years (2015 to 2017). We have classified IoT security research based on the research objectives, application domains, vulner-abilities/threats, countermeasures, platforms, proto-cols, and performance measurements. We have also provided some security challenges for further research

Inter-organizational social capital of firms in developing economies and industry 4.0 readiness: the role of innovative capability and absorptive capacity Author-1

The globalization of markets provides opportunities for firms to collaborate on various activities. These collaborations are the resource of social capital for firms to achieve sustainable competitiveness. This study aims to investigate how social capital (i.e., structural, relational, and cognitive social capital) between firms in a developing economy and developed economy strengthens their innovation capability and enhance their industry 4.0 readiness. Using Smart PLS-SEM to analyse the data collected from 320 managers representing 81 manufacturing firms in Pakistan, we found that social capital is positively associated with industry 4.0 readiness, and innovative capability mediates this relationship. The study contributes to the existing knowledge of understanding industry 4.0 readiness and provides useful insights for firms in developing economy to improves their innovation capability during the industry 4.0 era. This study likewise reveals the significance of three dimensions of social capital, which can facilitate to bring in digital knowledge from developed economies to developed economies to get ready for the fourth industrial revolution.IGA/FaME/2021/006, IGA/FaME/2022/005, IGA/FaME/2022/008; Univerzita Tomáše Bati ve ZlíněInternal Grant Agency of Faculty of Management and Economics through Tomas Bata University in Zln. Czech Republic [IGA/FaME/2021/006, IGA/FaME/2022/005, IGA/FaME/2022/008

Interorganizational social capital of firms in developing economies and Industry 4.0 readiness: the role of innovative capability and absorptive capacity.

The globalization of markets provides opportunities for firms to collaborate on various activities. These collaborations are the resource of social capital for firms to achieve sustainable competitiveness. This study aims to investigate how social capital (i.e., structural, relational, and cognitive social capital) between firms in a developing economy and developed economy strengthens their innovation capability and enhance their industry 4.0 readiness. Using Smart PLS-SEM to analyse the data collected from 320 managers representing 81 manufacturing firms in Pakistan, we found that social capital is positively associated with industry 4.0 readiness, and innovative capability mediates this relationship. The study contributes to the existing knowledge of understanding industry 4.0 readiness and provides useful insights for firms in developing economy to improves their innovation capability during the industry 4.0 era. This study likewise reveals the significance of three dimensions of social capital, which can facilitate to bring in digital knowledge from developed economies to developed economies to get ready for the fourth industrial revolution

Unmanned Ground Vehicles for Smart Farms

Forecasts of world population increases in the coming decades demand new production processes that are more efficient, safer, and less destructive to the environment. Industries are working to fulfill this mission by developing the smart factory concept. The agriculture world should follow industry leadership and develop approaches to implement the smart farm concept. One of the most vital elements that must be configured to meet the requirements of the new smart farms is the unmanned ground vehicles (UGV). Thus, this chapter focuses on the characteristics that the UGVs must have to function efficiently in this type of future farm. Two main approaches are discussed: automating conventional vehicles and developing specifically designed mobile platforms. The latter includes both wheeled and wheel-legged robots and an analysis of their adaptability to terrain and crops

CPS Data Streams Analytics based on Machine Learning for Cloud and Fog Computing: A Survey

Cloud and Fog computing has emerged as a promising paradigm for the Internet of things (IoT) and cyber-physical systems (CPS). One characteristic of CPS is the reciprocal feedback loops between physical processes and cyber elements (computation, software and networking), which implies that data stream analytics is one of the core components of CPS. The reasons for this are: (i) it extracts the insights and the knowledge from the data streams generated by various sensors and other monitoring components embedded in the physical systems; (ii) it supports informed decision making; (iii) it enables feedback from the physical processes to the cyber counterparts; (iv) it eventually facilitates the integration of cyber and physical systems. There have been many successful applications of data streams analytics, powered by machine learning techniques, to CPS systems. Thus, it is necessary to have a survey on the particularities of the application of machine learning techniques to the CPS domain. In particular, we explore how machine learning methods should be deployed and integrated in cloud and fog architectures for better fulfilment of the requirements, e.g. mission criticality and time criticality, arising in CPS domains. To the best of our knowledge, this paper is the first to systematically study machine learning techniques for CPS data stream analytics from various perspectives, especially from a perspective that leads to the discussion and guidance of how the CPS machine learning methods should be deployed in a cloud and fog architecture

Industry 4.0 technologies for manufacturing sustainability: A systematic review and future research directions

Recent developments in manufacturing processes and automation have led to the new industrial revolution termed “Industry 4.0”. Industry 4.0 can be considered as a broad domain which includes: data management, manufacturing competitiveness, production processes and efficiency. The term Industry 4.0 includes a variety of key enabling technologies i.e., cyber physical systems, Internet of Things, artificial intelligence, big data analytics and digital twins which can be considered as the major contributors to automated and digital manufacturing environments. Sustainability can be considered as the core of business strategy which is highlighted in the United Nations (UN) Sustainability 2030 agenda and includes smart manufacturing, energy efficient buildings and low-impact industrialization. Industry 4.0 technologies help to achieve sustainability in business practices. However, very limited studies reported about the extensive reviews on these two research areas. This study uses a systematic literature review approach to find out the current research progress and future research potential of Industry 4.0 technologies to achieve manufacturing sustainability. The role and impact of different Industry 4.0 technologies for manufacturing sustainability is discussed in detail. The findings of this study provide new research scopes and future research directions in different research areas of Industry 4.0 which will be valuable for industry and academia in order to achieve manufacturing sustainability with Industry 4.0 technologies

Sustainability through digital transformation: a systematic literature review for research guidance

Motivated by the rising attention of businesses and regulators towards how digital transformation can assist sustainability improvement, this paper sheds light on the relationships between these two phenomena. Specifically, this research pioneers the study of ‘digital sustainability’ through a systematic review of 153 academic articles aimed to 1) consolidate the existing research, 2) understand the thematic connections amongst the different studies, and 3) identify research gaps to move forward in the development of the topic. The suggested research agenda has important theoretical and practical implications. Through the identified gaps, this study acknowledges the management scholarship of pitfalls and delays on the research topic, providing detailed guidance to develop this new stream of subject area. The opportunistic approach of this paper responds to the practical call for support in understanding the use of digitalization for sustainability-related goals. This research directly impacts a wide range of practitioners, including managers, consultants, and policymakers. Received 10 May 2021, Revised 26 April 2022, Accepted 5 May 2022, Available online 18 May 2022, Version of Record 18 May 2022

Agronomy

Climate change is a serious threat to field crop production and food security. It has negative effects on food, water, and energy security due to change in weather patterns and extreme events such as floods, droughts, and heat waves, all of which reduce crop productivity. Over six chapters, this book presents a comprehensive picture of the importance of agronomy as it relates to the United Nations’ Sustainable Development Goals. With an emphasis on the goals of Zero Hunger and Climate Change, this volume examines sustainable agronomic practices to increase crop productivity and improve environmental health