Abstract: Indoor positioning on a Wi-Fi network belongs to a class of tasks in which the dependence of output characteristics on input variables is influenced by many parameters and external factors. When solving such problems, it is necessary to take into account that in determining the location, it is of significant interest not only to determine the static coordinates of an object, but also to predict the vector of its movements. In the case where the location of an object is determined only by the level of signal power received from several access points on a Wi-Fi network, the use of signal attenuation models that take into account the conditions of propagation of radio waves indoors is difficult due to the need for reliable information about the material of ceilings, floors and ceilings, the presence of fixed and mobile shading objects, etc. Since the electromagnetic environment inside the room varies depending on many factors, the above-mentioned models have to be adjusted to these changes. Since finding patterns in a large amount of data requires non-standard algorithms, artificial neural networks can be used to solve the positioning problem. It is important to choose a neural network architecture that can take into account changes in the signal strength received by a mobile device from Wi-Fi access points. Before training a neural network, statistical data is preprocessed. For example, abnormal cases are excluded from the machine learning dataset when the device detects a signal from less than three access points at one measuring point.
As a result of the analysis of statistical data, it was found that the same distance between the measuring points leads to the fact that the neural network incorrectly determines the location of the object. The paper shows that in order to increase the accuracy of positioning the location in conditions of complex radio placement, when compiling radio maps, it is necessary to determine the optimal varying distances between measuring points. The conducted experimental studies, taking into account the proposed approach to optimizing the distances between measuring points, prove that the accuracy of location determination in the vast majority of measuring points reaches 100%.

Abstract: One of the topical areas of the digital economy is the development of services based on the use of systems for local positioning of objects. The article presents the results of analytical modeling of a positioning system built on the equipment of the IEEE 802.15.4 standard. The purpose of this study is to evaluate the efficiency of data transmission in a ZigBee network. As a modeling tool, the mathematical apparatus of queuing networks (CeMO) was selected, which has proven its effectiveness for calculating the characteristics of various infocommunication systems. The method of analysis of average values was chosen by the authors to assess the quality of service indicators due to its computational simplicity and the adequacy of the results obtained. The authors have developed a structural diagram of the investigated positioning system. On the basis of the network architecture, a conceptual, algorithmic and software model in the form of a closed homogeneous queuing network has been developed and its characteristics have been calculated. The parameters obtained as a result of modeling make it possible to evaluate and analyze the quality of service indicators in the telecommunications segment of the local positioning system under study, such as latency, performance, network load factor and the probability of losses, which can be used for efficient traffic management in the telecommunications segment of the geolocation system based on IEEE 802.15.4 standard.

Abstract: The article presents the results of the analysis of the error in calculating the coordinates of a mobile subscriber using three Wi-Fi access points, based on measuring the received signal power. The purpose of the study was to develop a geographic system for large storage facilities and a preliminary assessment of the accuracy of calculations in conditions close to real ones. The principles of local and global positioning based on the measurement of various physical characteristics of signal propagation were considered, a method was selected for the implementation of a positioning system. The authors developed a test bench layout of a map on the IEEE 802.11 standard mobile network and software for solving this problem using the trilateration mechanism. To simulate the surrounding electromagnetic environment, a parameter imitating additive white Gaussian noise was added to the calculation formulas. In the course of the work, graphical dependences of the error of measuring the coordinates of the object on the signal / noise ratio in the channel and on the distance from the reference access point are obtained. The results showed that even in the worst operating conditions, the developed system surpasses most systems on the market in terms of measurement accuracy.