Journal of Mobile Multimedia

Editorial

Yuriy P. Kondratenko — 2024-05-06

Dear Readers,
It is a great pleasure for me to introduce this Special Issue of the Journal of Mobile Multimedia “Control and Decision-making Systems with Mobile Applications”.
This Special Issue aims to present the systematized research, description, and analysis of new theoretical results and applications of modern mobile technologies in various control and decision-making systems for increasing their efficiency. Optimization of ship operations, decision support system for ballasting floating docks, face recognition for access control in security systems, control of unmanned aerial vehicles in meteorological measure- ments, conception and strategy of the artificial intelligence development relating to mobile technologies, neural networks for objects classification, machine learning for recognition of image components, mobile approach to uncertainty and color optical networks in decision-making processes are considered by authors among the priority directions in applications of pub- lished research results. This Special Issue is published in collaboration with authors from different countries (Ukraine, the United States of America, and Uzbekistan) who represent the universities and research institutes and who have great experience in the development of international research projects on control systems, artificial intelligence, decision support systems, mobile technologies, cyber-physical systems, the internet of things, robotics, and soft computing.

Some Aspects of Artificial Intelligence Development Strategy for Mobile Technologies

Vadym Slyusar — 2024-05-06

The article addresses hardware-software and other key aspects of the artificial intelligence development strategy for mobile technologies. The proposed components of the strategy include a series of approaches to address issues related to the development and deployment of large language models on mobile devices, as well as suggestions for improving connectivity, memory management, and data security.

Intelligent IoT-based Control System of the UAV for Meteorological Measurements

Oleksiy Kozlov — 2024-05-06

This study focuses on the creation and examination of an intelligent automated control system for UAVs utilized in meteorological measurements based on the Internet of Things (IoT) and mobile technologies. The proposed system enables the achievement of commendable flight control standards for UAVs during meteorological data gathering, thereby markedly enhancing the overall effectiveness of meteorological stations. Notably, this system is constructed on the foundation of three integrated principles: (a) a hierarchical two-level approach for control and data collection based on IoT and mobile technologies, (b) a straightforward and dependable fuzzy logic control characterized by high performance, and (c) the effective optimization of fuzzy control components through the application of bio-inspired multi-agent computing techniques. To assess the performance of the suggested intelligent system, this study involves the creation and bioinspired optimization of the climb speed fuzzy controller. Subsequent simulation experiments are conducted to evaluate the automatic control of UAV’s flight processes under different modes. The analysis of the simulation results indicates that the developed system, utilizing fuzzy control, exhibits superior efficiency and higher quality metrics when compared to existing counterparts, especially in diverse flight scenarios such as uniform climbing, gradual approach to designated altitude levels, and smooth landing during meteorological measurements.

A Mobile Application of a Decision Support System for Ballasting a Floating Dock

Andriy Topalov — 2024-05-06

This paper is devoted to increasing the automation level of docking operations through the development of a mobile application for a decision support system capable of determining the optimal option for loading ballast into floating dock compartments when setting up and launching ships. The proposed decision support system and the mobile application allow implementing effective ballasting of the floating dock before docking the ship based on mathematical calculations of the impact of the ship on the floating dock and the ballasting rules. To test the developed system, the paper presents the functioning of the mobile application for a case of calculation of the docking up process of a 4,100-ton ship. In particular, the load forces of this ship are calculated with a graphical display of the distribution of the influence of 20 sections of the ship on 6 pontoons of the floating dock. As a result, this decision support system with the implemented mobile application has the characteristics of a convenient interface and is easy to operate. It can provide the dockmaster data and suggestions for decision-making, and during its operation, it is actively replenished with a database of the docked up ships.

Ship Operation Analysis and Optimization via Mobile Application

Yuriy Zhukov — 2024-05-06

This paper is devoted to studying the structure and prospects of ship operations analysis and optimization via mobile applications, focusing on integrating multiple existing onboard monitoring and control systems. The main parts of the paper describe the current state of the most essential components of future overall shipping and ship design optimization using onboard and cloud-based monitoring systems from a dual transition point of view. Special attention is paid to the ship’s and its equipment’s efficiency improvements, fuel consumption and emissions reduction, cost-effectiveness enhancement, metrological accuracy, and compliance with current regulations. Timely development and deployment of the proposed onboard monitoring systems, in combination with up-to-date mobile applications and cloud computing, should play a crucial role in promoting sustainable and environmentally friendly shipping practices, improving operational performance, and reducing risks to human life at sea and the environmental impact of shipping. Another objective of this research is to review the current state of infrastructure used for fuel control, focusing on measurement systems and related analytics using appropriate mobile applications. The recommendations for integrating new and adopting existing monitoring systems and equipment for promising alternative fuels must be given to meet current regulations and provide required safety levels and measurement quality.

From Fuzzy to Mobile Fuzzy

Olga Kosheleva — 2024-05-06

The main limitation of mobile computing in comparison with regular computing is the need to make sure that the battery lasts as long as possible – and thus, the number of computational steps should be as small as possible. In this paper, we analyze how this affects fuzzy computations. We show that the need for the fastest computations leads to triangular membership functions and simplest “and”- and “or”-operations: min and max. It also leads to the need to limit ourselves to a few-bit description of fuzzy degrees – which leads to 3-bit descriptions similar to optical implementation of fuzzy computing.

Just-in-Accuracy: Mobile Approach to Uncertainty

Martine Ceberio — 2024-05-06

To make a mobile device last longer, we need to limit computations to a bare minimum. One way to do that, in complex control and decision making problems, is to limit precision with which we do computations, i.e., limit the number of bits in the numbers’ representation. A problem is that often, we do not know with what precision should we do computations to get the desired accuracy of the result. What we propose is to first do computations with very low precision, then, based on these computations, estimate what precision is needed to achieve the given accuracy, and then perform computations with this precision.

Logical Platforms for Mobile Application in Decision Support Systems Based on Color Information Processing

Victor Timchenko — 2024-05-06

This work is devoted to the creation of mobile applications for a wide class of decision-making problems with large databases based on effective optical logical systems. Such systems use (a) the representation of color as a carrier of logical fuzzy information and (b) the construction of logical decisions by transforming the light emitter with appropriate color filters. Optical processing of fuzzy information is carried out using the proposed block diagram of fuzzy logic gates (logical coloroid). Input data is generated based on expert assessments. The fuzzy database is formed by defining the corresponding color as a quantum (set) of information. The article discusses (a) the main steps in the synthesis of logical inference procedures for decision-making systems and (b) a generalized block diagram of an optical logical coloroid as the basis for creating multi-level mobile decision-making systems with artificial intelligence components. The use of color as a carrier of logical information allows the creation of high-speed mobile devices with convenient visualization.

Mobile Recognition of Image Components Based on Machine Learning Methods

Galyna Kondratenko — 2024-05-06

This paper is related to the recognition of certain components in images using machine learning methods and mobile technologies. The main result of this work is a developed system for recognizing the presence of a mask on the face using an image, which provides all the necessary information in real-time about the presence or absence of a mask on the face. When the program is turned off, statistics about the presence/absence of the mask will be recorded in the database. To achieve the goal, the following tasks were solved: the current state of the task of recognizing the presence of a mask on a person’s face was analysed; existing analogs of the systems were analysed; the necessary neural network architecture was selected as one of the machine learning methods; developed a system for recognizing the presence of a mask on the face using the necessary libraries; a user graphical interface, a database model for recording statistics and additional functionality have been developed; conduct testing. Practical application has a fairly wide range, in particular, the developed intelligent system is intended for use in the subway, industrial enterprises, state institutions, educational institutions, offices, and other public places. The developed system recognizes and records statistics about the presence of a mask on a person’s face using neural networks.

Neural Technologies for Objects Classification with Mobile Applications

Ievgen Sidenko — 2024-05-06

This paper is related to the study of the features of the neural technologies’ application, in particular, ResNet neural networks for the classification of objects in photographs. The work aims to increase the accuracy of recognition and classification of objects in photographs by using various models of the ResNet neural network. The paper analyzes the features of the application of the corresponding models in comparison with other architectures of deep neural networks and evaluates their efficiency and accuracy in the classification of objects in photographs. The process of data formation for training neural networks, their processing and sorting is described. A web application and a mobile application for recognizing and classifying objects in a photo were also developed. A system for classifying objects, in particular airplanes in photographs, was developed using neural network technologies. It gives a recognition and classification accuracy of about 95%. Research results of ResNet models are of great practical importance, as they can improve the classification accuracy of various images. Features of ResNet, such as the use of skip connections or residual connections, make it effective in the relevant tasks. The results of the study will help to implement ResNet in various fields, including medicine, automatic pattern recognition and other areas where the classification of objects in photographs is an important task.

An Ensemble Approach To Face Recognition In Access Control Systems

Volodymyr Mykolaevich Opanasenko — 2024-05-06

The article proposes a method for recognizing faces in mobile devices, based on an ensemble approach to solving the problem of pattern recognition, which ensures high accuracy of results. According to this approach, the basic algorithm is decomposed into two operators: a recognition operator and a decision rule. The recognition operator calculates estimates of the proximity of the tested object to the given classes. The decision rule, based on these estimates, determines whether the tested object belongs to one of the given classes. The ensemble of recognizing operators is formed in the form of a linear polynomial. The values of the polynomial parameters are calculated based on the solution of the multiparameter optimization problem. Experimental studies were carried out using open databases of facial images. When conducting experiments, it was assumed that two options for using basic algorithms would be implemented: separate and ensemble. The accuracy of recognizing objects in the control sample using an ensemble of recognition operators turned out to be higher compared to the accuracy of the best basic recognition algorithm.

The proposed face recognition method can be used in mobile devices, in particular, to verify users when remotely accessing information resources that limited access status.