THE CLOUD GNSS DATA FUSION APPROACH BASED ON THE MULTI-AGENT AUTHENTICATION PROTOCOLS’ ANALYSIS IN THE CORPORATE LOGISTICS MANAGEMENT SYSTEMS

Abstract

Context. Modern corporate logistics management systems or tracking systems consist of wireless positioning systems. Typically, mobile technologies use signal receivers of satellites of GNSS. However, there is the general problem of data transmitting issues to analytic centers for further in the corporate logistics management systems. The object of the study was to develop the solutions alternative to GNSS.
 Objective. The goal of the work is the increasing vehicle location access control accuracy, based on the multi-agent authentication protocols’ analysis.
 Method. The study proposes the cloud data fusion platform offers to collect and archive data about all movable objects that can be on the road between departments inside the same warehouse area. Since there are operations with different wireless base stations' participation, so, the movable object can don’t enough time for a movement trajectory analysis in real-time. Thus, data processing must fulfill in the cloud dispatching center and data flow fusion is needed. An equations system that identifies the vehicles' location based on the method of multi-agent authentication process analysis after the GPS signal loss, was proposed. The multi-sectional configuration of the recursive neural network and the usage of cloud data fusion made it possible to increase the accuracy of vehicle location determination.
 Results. The developed method has been implemented in software and investigated for solving the problems of vehicle location control accuracy in the corporate logistics management systems.
 Conclusions. The conducted experiments have confirmed the proposed approach and allow recommending it for use in practice for solving the problems of improving the efficiency of vehicle location determination via the role-based access control integrated with multi-agent authentication service.