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In the context of smart cities, ensuring road safety is crucial due to increasing urbanization and the interconnected nature of contemporary urban environments. Leveraging innovative technologies is essential to mitigate risks and create safer communities. Thus, there is a compelling imperative to develop advanced solutions to enhance road safety within smart city frameworks. In this article, we introduce a comprehensive vehicle safety framework tailored specifically for smart cities in the realm of Artificial Intelligence of Things (AIoT). This framework seamlessly integrates a variety of sensors, including eye blink, ultrasonic, and alcohol sensors, to bolster road safety. The utilization of eye blink sensor serves to promptly detect potential hazards, alerting drivers through audible cues and thereby enhancing safety on smart city roads. Moreover, ultrasonic sensors provide real time information about surrounding vehicle speeds, thereby facilitating smoother traffic flow. To address concerns related to alcohol consumption and its potential impact on road safety, our framework incorporates a specialized sensor that effectively monitors the driver’s alcohol levels. In instances of high alcohol content, the system utilizes GPS and GSM technology to automatically adjust the vehicle’s speed while simultaneously notifying pertinent authorities for prompt intervention. Additionally, our proposed system optimizes inter-vehicle communication in smart cities by leveraging Li-Fi technology, enabling faster and more efficient data transmission via visible light communication (VLC). The integration of Li-Fi enhances connectivity among connected vehicles, contributing to a more cohesive and intelligent urban transportation network. Through the structured integration of AIoT technologies, our framework lays a robust foundation for a safer, smarter, and more sustainable future in smart city transportation. It offers significant advancements in road safety and establishes the groundwork for further enhancement in intelligent urban transportation networks.
In the context of smart cities, ensuring road safety is crucial due to increasing urbanization and the interconnected nature of contemporary urban environments. Leveraging innovative technologies is essential to mitigate risks and create safer communities. Thus, there is a compelling imperative to develop advanced solutions to enhance road safety within smart city frameworks. In this article, we introduce a comprehensive vehicle safety framework tailored specifically for smart cities in the realm of Artificial Intelligence of Things (AIoT). This framework seamlessly integrates a variety of sensors, including eye blink, ultrasonic, and alcohol sensors, to bolster road safety. The utilization of eye blink sensor serves to promptly detect potential hazards, alerting drivers through audible cues and thereby enhancing safety on smart city roads. Moreover, ultrasonic sensors provide real time information about surrounding vehicle speeds, thereby facilitating smoother traffic flow. To address concerns related to alcohol consumption and its potential impact on road safety, our framework incorporates a specialized sensor that effectively monitors the driver’s alcohol levels. In instances of high alcohol content, the system utilizes GPS and GSM technology to automatically adjust the vehicle’s speed while simultaneously notifying pertinent authorities for prompt intervention. Additionally, our proposed system optimizes inter-vehicle communication in smart cities by leveraging Li-Fi technology, enabling faster and more efficient data transmission via visible light communication (VLC). The integration of Li-Fi enhances connectivity among connected vehicles, contributing to a more cohesive and intelligent urban transportation network. Through the structured integration of AIoT technologies, our framework lays a robust foundation for a safer, smarter, and more sustainable future in smart city transportation. It offers significant advancements in road safety and establishes the groundwork for further enhancement in intelligent urban transportation networks.
Aim/purpose – This research aims to design an analytical framework to investigate the dimensions, factors, and key indicators affecting the green supply chain based on the innovative technology of Artificial Intelligence of Everything (AIoE). Understanding the cause-and-effect relationships of all actors in this smart and sustainable system is also one of the critical goals of this research. Also, examining the key features of AIoE tech- nology as a new hybrid technology is one of this research’s most essential features. Design/methodology/approach – This research has tried to extract and refine the most critical parameters affecting the green supply chain based on technology by reviewing the literature and examining the opinions of active experts in the field of study. Then, by using the focus group, it has been tried to provide an analytical framework to express the cause-and-effect relationships of all actors active in this system by examining the basic features of AIoE. Finally, this framework was validated and approved using experts’ opinions and the focus group, emphasizing integrity, comprehensiveness, and effectiveness. Findings – This research identified the dimensions, components, and indicators affecting the smart, green, and sustainable supply chain based on Artificial Intelligence (AI). It also presented an analytical framework that shows the cause-and-effect relationships of all active actors in this system. Research implications/limitations – This research simultaneously offers significant insights into implementing intelligent and sustainable process-oriented systems. However, it is important to note the limitations. One of the most significant challenges in presenting the framework was finding experts with sufficient awareness, knowledge, and experi- ence and participants to analyze cause-and-effect relationships. Originality/value/contribution – This research provides a practical analysis of AIoE technology for the first time. The results strongly support the argument that hybrid AIoE technology can tremendously impact the sustainability and greenness of supply chain processes. Keywords: green supply chain, sustainable supply chain, Artificial Intelligence of Eve- rything (AIoE), AIoE-based supply chain. JEL Codes: O32
In today's world and with the development of advanced industrial generations, the internet of things as an epidemic technology has caused a huge change and transformation in all aspects of daily life, including business. This technology has affected all dimensions and components of the organization's value chain, and a new concept called intelligent and interactive marketing based on the internet of things has also been formed. Considering the importance of sales and marketing in the organization's supply chain, it is necessary to understand the dimensions and components of this type of marketing. The internet of things is one of the most important sources of big data production from marketing processes and it seems that businesses' emphasis on this type of marketing can guarantee business growth.
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