USE OF ARTIFICIAL INTELLIGENCE AND MODERN INFORMATION TECHNOLOGIES IN THE CITY LOGISTICS SYSTEM
Abstract
The article is devoted to the topic of using modern information technologies and artificial intelligence in urban logistics systems. It was studied how in the conditions of globalization, logistics is one of the key factors of the costs of enterprises and the search for solutions for environmentally friendly delivery in cities. Considered how innovative solutions in logistics change the methods of transportation and delivery of goods. Research has been conducted on how the implementation of such technologies as IoT, Big Data, predictive analytics, cloud computing and crowdsourcing platforms affect the future of urban logistics systems. Was examined current trends and transformational changes in urban logistics systems that allow logistics companies to better manage supplies, improve fuel economy and deliver better economies of scale. Outlined how the rapid development of e-commerce is changing the way of goods purchasing and complicating supply chains due to limited delivery times. The article also focuses on the shift from location-based delivery via fleet networks to «market-based» or «application-oriented» models that are not asset-based. Also authors analyzed the advantages of introducing artificial intelligence into logistics and warehouse automation. Considerable attention is paid to changing the paradigm of logistics operations using artificial intelligence. The advantages of using artificial intelligence in urban logistics systems was described . An analysis of the protection of information transmission during the operation of computer networks to the administrators of logistics enterprises was carried out. As a result was created an original mathematical model of the functioning of the network device based on integral indicators extracted from the fields of network packets. As a tool for obtaining results, was used an algorithm for structuring network traffic and forming integral indicators of the functioning of network devices. Based on the results of the research, was built a mathematical model of the object of analysis of the decision-making system for the detection of network anomalies during the automation of urban logistics routes.
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