Search Results (43)

Autonomous Vehicles (AV) have been extensively studied in both scientific and social contexts. Over the past two decades, there has been a significant rise in their real-world applications, including neural networks, Blockchain, Internet of Things, autonomous navigation, computer vision, automation processes, and various other areas. Hence, it is imperative to investigate the interplay between software, hardware, and individuals. To guarantee secure and unaffected interactions within autonomous vehicle devices and networks, decentralized Blockchain technology is proposed. This study presents the introduction of a framework we named “DEMU-NAV” for an ecosystem that includes Artificial Intelligence (AI), humans, and robots. The framework makes use of a decentralized Blockchain, Smart-Contract (SC), and Internet of things (IoT) network. Our framework was implemented using Ethereum and Python, enabling us to oversee Blockchain, Smart-Contracts, and the IoT for the facilitation of autonomous vehicle navigation. Full article

Industrial Internet Platforms (IIPs) provide critical value for supply chain management. The motivation for value creation and capture by supplier firms increasingly depends on acquiring and processing customer-oriented information, with geographical distance to customers being a key factor in assessing costs and benefits. This study investigates whether firms’ IIP adoption increases or decreases the geographical distance to their customers, utilizing supply chain data and digital transformation metrics from China’s A-share listed firms in the new energy vehicle industry. The study finds that an increased adoption level of IIPs by focal firms leads to a greater average geographical distance to their customers. This conclusion remains valid after addressing endogeneity concerns and performing several robustness checks. Moreover, the effect of IIP adoption on expanding the geographic scope of sales is significant when the focal firm is more specialized in the supply chain, more socially embedded, located in China’s eastern region, or acts as an upstream/downstream complement to complete vehicle manufacturers. No significant difference in the impact of IIP adoption is observed between private and state-owned enterprises. This study combines platform innovation and transaction cost theories, offering new insights and policy implications regarding the spatial impact of digital technology adoption in advanced manufacturing and related service industries. Full article

With the gradual application of blockchain technology in the domain of Social Internet of Vehicles (SIoV), the increasing volume of blockchain data has imposed significant storage pressure on roadside units (RSUs). Collaborative storage schemes, which organize RSUs into clusters to jointly store content for vehicles, have been explored. However, existing collaborative storage solutions in IoV primarily focus on caching content and are not well-suited to the deployment constraints of blockchain networks. Building on blockchain’s decentralized characteristics and data integrity mechanisms, this paper proposes a collaborative storage scheme that reduces RSU storage loads while sustaining distributed ledger operations in SIoV. Specifically, the RSU Access Preference-based Spectral Clustering Algorithm (RAPSCA) is proposed to address RSU clustering by analyzing both the RSUs’ access preferences for blockchain data and their resource availability. Subsequently, the Vehicle Service Priority-based Greedy Block Allocation Algorithm (VSPGBAA) is devised for intra-cluster storage allocation, which considers vehicles’ dwell times and block access probabilities to reduce overall access costs. Experimental results indicate that, compared to baseline algorithms, the proposed method achieves a 27.7% reduction in cost and a 3.5-fold decrease in execution time, thereby demonstrating the feasibility of collaborative storage optimization in blockchain-enabled SIoV. Full article

Agricultural cooperatives are the main vehicle for farmers to engage in green agriculture. With the digital transformation in rural areas, it is crucial to explore how cooperative members can effectively access online information and integrate it into green production decision-making processes. Based on the survey data of 530 members of rice planting cooperatives in Heilongjiang Province in China, this paper selected eight green production behaviors commonly used by rice farmers as explained variables, and constructed an ordered probit model. Using the social capital theory, the impact and mechanism of internet use on cooperative members’ green production behavior were examined. The results showed the following: (1) Internet use facilitates the cooperative members’ green production behavior. This conclusion remains valid even after addressing the endogeneity test and robustness test. (2) The heterogeneity analysis revealed that the internet is particularly effective in enhancing the green production behaviors of farmers who are less educated, middle-aged, and those with strong connections to cooperatives. (3) A further mechanism test indicates that internet use not only significantly influences farmers’ trust in cooperatives but also aids them in comprehending the cooperative’s production specifications, thereby further advancing the improvement in green production behaviors. (4) Members’ satisfaction with cooperative sales can serve as a substitute for the internet in influencing their green production behavior. Full article

The transportation system has a big impact on daily lifestyle and it is essential to energy transition and decarbonization initiatives. Stabilizing the grid and incorporating sustainable energy sources require technologies like the Internet of Energy (IoE) and Internet of Vehicles (IoV). Electric vehicles (EVs) are essential for cutting emissions and reliance on fossil fuels. According to research on flexible charging methods, allowing EVs to trade electricity can maximize travel distances and efficiently reduce traffic. In order to improve grid efficiency and vehicle coordination, this study suggests an ideal method for energy trading in the Internet of Vehicles (IoV) in which EVs bid for electricity and Road Side Units (RSUs) act as buyers. The Taylor Social Optimization Algorithm (TSOA) is employed for this auction process, focusing on energy and pricing to select the best Charging Station (CS). The TSOA integrates the Taylor series and Social Optimization Algorithm (SOA) to facilitate flow redirection post-trading, evaluating each RSU’s redirection factor to identify overloaded or underloaded CSs. The Flow-DNET model determines redirection policies for overloaded CSs. The TSOA + Flow-DNET approach achieved a pricing improvement of 0.816% and a redirection success rate of 0.918, demonstrating its effectiveness in optimizing electricity trading and flow management within the IoV framework. Full article

Emerging distributed intelligence paradigms for the Internet of Things (IoT) call for flexible and dynamic reconfiguration of elementary services, resources and devices. In order to achieve such capability, this paper faces complex interoperability and autonomous decision problems by proposing a thorough framework based on the integration of the Semantic Web of Things (SWoT) and Social Internet of Things (SIoT) paradigms. SWoT enables low-power knowledge representation and autonomous reasoning at the edge of the network through carefully optimized inference services and engines. This layer provides service/resource management and discovery primitives for a decentralized collaborative social protocol in the IoT, based on the Linked Data Notifications(LDN) over Linked Data Platform on Constrained Application Protocol (LDP-CoAP). The creation and evolution of friend and follower relationships between pairs of devices is regulated by means of novel dynamic models assessing trust as a usefulness reputation score. The close SWoT-SIoT integration overcomes the functional limitations of existing proposals, which focus on either social device or semantic resource management only. A smart mobility case study on Plug-in Electric Vehicles (PEVs) illustrates the benefits of the proposal in pervasive collaborative scenarios, while experiments show the computational sustainability of the dynamic relationship management approach. Full article

Charging stations and electric vehicle (EV) charging networks signify a significant advancement in technology as a frontier application of the Social Internet of Things (SIoT), presenting both challenges and opportunities for current 6G wireless networks. One primary challenge in this integration is limited wireless network resources, particularly when serving a large number of users within distributed EV charging networks in the SIoT. Factors such as congestion during EV travel, varying EV user preferences, and uncertainties in decision-making regarding charging station resources significantly impact system operation and network resource allocation. To address these challenges, this paper develops a novel framework harnessing the potential of emerging technologies, specifically reconfigurable intelligent surfaces (RISs) and causal-structure-enhanced asynchronous advantage actor–critic (A3C) reinforcement learning techniques. This framework aims to optimize resource allocation, thereby enhancing communication support within EV charging networks. Through the integration of RIS technology, which enables control over electromagnetic waves, and the application of causal reinforcement learning algorithms, the framework dynamically adjusts resource allocation strategies to accommodate evolving conditions in EV charging networks. An essential aspect of this framework is its ability to simultaneously meet real-world social requirements, such as ensuring efficient utilization of network resources. Numerical simulation results validate the effectiveness and adaptability of this approach in improving wireless network efficiency and enhancing user experience within the SIoT context. Through these simulations, it becomes evident that the developed framework offers promising solutions to the challenges posed by integrating the SIoT with EV charging networks. Full article

In this article, I explore the ways that women of the Korean diaspora engage in cultural meaning-making through material culture in efforts to redefine what it means for people, things, and ideas to be considered “authentically Korean”. Using the case study of famous internet chef Maangchi, I examine one of her best-selling cookbooks and her digital presence to identify the tactics she uses to exert agency in the meaning-making and community-building process, using Korean food and her role as a maternal figure as vehicles for analysis. Due to her roles as a mother and her positioning as a quintessential immigrant subject in the US context, I argue that Maangchi challenges colonial and Eurocentric models of cultural authenticity as part of a long history of women of color that actively disrupt social perceptions of value, expertise, and knowledge production. By exploring her business ventures, I consider how embedded pieces of knowledge, racialization, perceived expertise, and cultural assumptions are all connected to challenge the historical concepts and applications of authenticity in favor of a more inclusive, radical, and politically potent understanding of what truly makes something “Korean”. Full article

As a result of the new telecommunication ecosystem landscape, wireless communication has become an interdisciplinary field whose future is shaped by several interacting dimensions. These interacting dimensions, which form the cyber–physical convergence, closely link the technological perspective to its social, economic, and cognitive sciences counterparts. Beyond the current operational framework of the Internet of Things (IoT), network devices will be equipped with capabilities for learning, thinking, and understanding so that they can autonomously make decisions and take appropriate actions. Through this autonomous operation, wireless networking will be ushered into a paradigm that is primarily inspired by the efficient and effective use of (i) AI strategies, (ii) big data analytics, as well as (iii) cognition. This is the Cognitive Internet of People Processes Data and Things (CIoPPD&T), which can be defined in terms of the cyber–physical convergence. In this article, through the discussion of how the cyber–physical convergence and the interacting dynamics of the socio-technical ecosystem are enablers of digital twins (DTs), the network DT (NDT) is discussed in the context of 6G networks. Then, the design and realization of edge computing-based NDTs are discussed, which culminate with the vehicle-to-edge (V2E) use cases. Full article

Smallholder farmers play an important role in ensuring world food security. In addition to food security, small-scale farming also provides numerous other direct and indirect environmental, social, cultural, and economic benefits by improving crop diversification, job security, and self-sufficiency. However, small-scale agriculture faces several challenges which are further exacerbated by climate change, population increase, water scarcity, and soil degradation. Agriculture has seen a lot of technological advancements in the last few decades. However, access to these advancements has not always been economically viable for small or medium farm operations. This article aimed to review the major barriers to small-scale farming and to review the status and potential opportunities offered by advanced technologies that can benefit small-scale holders. Based on the review, we found that economics, marketing, climate change, lack of awareness, educational resources, infrastructure, information, and technology are the major challenges to small-scale farming. Technologies such as unmanned aerial vehicles (UAVs), the IoT (internet of things), irrigation automation, and the use of smartphones are already becoming mainstream in small-scale farming and other technologies like robotics, artificial intelligence (AI), yield monitoring, and food traceability have potential opportunities to solve the challenges that hamper the success of small-scale growers. Full article

This project investigates English–Spanish codeswitching in internet memes posted to the Facebook page, We are mitú (mitú), and analyzes how lexical insertions and quotatives contribute to the enregisterment of linguistic patterns and the construction of collective identity among U.S. Latinx millennials in virtual social spaces. Data include instances of lexical insertion (n = 280) and quotative mixed codes (n = 114) drawn from a collected corpus of 765 image–text memes. The most frequent lexical insertions included food items (e.g., elote and pozole), kinship terms (e.g., abuelita and tía), and culturally specific artifacts or practices (e.g., quinceañera and lotería), which reflect biculturalism and rely on a shared set of references for the construction of a group identity. Additionally, the quotatives in the data construct Spanish-speaking characterological figures that enregister a particular brand of U.S. Latinx millennial identity that includes being bilingual, having Spanish-speaking parents, and having strong ties to Latinx culture. Overall, this work highlights not only internet memes as a vehicle for enregisterment, but also, and more importantly, how the language resources employed within them work to enregister linguistic and cultural norms of U.S. Latinx millennials, and thereby, play a role in identity construction in virtual social spaces. Full article

The number of people owning vehicles has been steadily growing, resulting in increased numbers of vehicles on the roads, making roads more congested, and increasing the risk of accidents. In addition, heavy rain, snow, and fog have increased due to abnormal weather caused by global warming. These bad weather conditions can also affect the safety of vehicles and drivers. The need to disseminate safety messages on the social Internet of Vehicles due to these problems has been steadily increasing. In this paper, we propose an efficient safety message dissemination scheme that focuses on urban environments with high vehicle density and mobility to address these problems. The proposed scheme reduces packet loss by considering frequent cluster departures and subscriptions through an efficient cluster management technique. In a vehicle-to-vehicle environment, the dissemination of safety messages is divided into intracluster and intercluster emergencies, as well as a general safety message dissemination technique. In a vehicle-to-infrastructure environment, the proposed scheme reduces the number of processing requests and duplicate messages made to roadside units (RSUs) through a request operation process for each vehicle and an RSU scheduling technique. We conducted several performance evaluations of message packet loss and the number of RSU processing requests to demonstrate the superiority of the proposed scheme. Full article

Due to the high mobility of vehicles and the high dynamics of SIoV network topology, the communication between users will be frequently interrupted, thus affecting the service quality of users. In addition, due to the open nature of the SIoV wireless channel, any user can broadcast messages in the system. However, unreliable users pose serious security threats to other users on the network. In order to solve these problems, we propose a feature cluster-based secure data transmission method (FC-SDTM) to ensure safe and stable data transmission between vehicles. This method creates feature clusters according to the feature similarity of users, which provides the stability of communication between users and improves users’ reliability in the cluster. Second, consortium blockchains store the transmission data sent by the sender in the cluster for the receiver to verify, further ensuring the security of intra-cluster communication. Finally, the random number key reduces the running time of the proposed method and solves the security problem caused by cluster topology updates. The experimental results demonstrate that this method can reduce the system running time and the message exposure rate, while also improving transmission accuracy. Full article

The types of artificial intelligence, artificial intelligence integration to the food value and supply chain, other technologies embedded with artificial intelligence, artificial intelligence adoption barriers in the food value and supply chain, and solutions to overcome these barriers were analyzed by the authors. It was demonstrated by the analysis that artificial intelligence can be integrated vertically into the entire food supply and value chain, owing to its wide range of functions. Different phases of the chain are affected by developed technologies such as robotics, drones, and smart machines. Different capabilities are provided for different phases by the interaction of artificial intelligence with other technologies such as big data mining, machine learning, the Internet of services, agribots, industrial robots, sensors and drones, digital platforms, driverless vehicles and machinery, and nanotechnology, as revealed by a systematic literature analysis. However, the application of artificial intelligence is hindered by social, technological, and economic barriers. These barriers can be overcome by developing the financial and digital literacy of farmers and by disseminating good practices among the participants of the food supply and value chain. Full article

The Internet of Vehicles (IoV) has generated great interest among researchers from different disciplines as it is multidisciplinary research. Sustainability for the IoV requires solutions from different perspectives, particularly in the context of environmental, social, and corporate governance. This review paper examines each of the mentioned perspectives of IoV research which were conducted among at least one of these three perspectives. On the one hand, this allows determining how widely research on the IoV system has been conducted. Moreover, it shows the directions of research on the IoV. On the other hand, it determines whether and how the IoV research is linked to each of the perspectives separately and analyses this link from a global perspective as well; i.e., it analyses the survey data in terms of the data’s relationship to all the perspectives as a group. As one of the research results, a conceptual model of IoV systems allocating the ESG perspectives was developed. The current research has shown that consideration of IoV systems in the context of these three perspectives (treated both individually and collectively) is still limited. A balanced approach towards these IoV systems is still required. Therefore, the paper consists of a survey of the current research related to the sustainability of the IoV from the three mentioned perspectives, aiming to give a balanced view of the importance of the three perspectives for IoV systems. Full article