Resource saving Approach of visual tracking fiducial marker recognition for unmanned aerial vehicle

Unmanned aerial vehicle (UAV) tracking fiducial marker is a challenging problem, because of camera system vibration, which causes visible frame-to-frame jitter in the airborne videos and unclear marker vision. Multirotors have very limited weight carrying, controller, and battery power resources. While obtaining and processing motion blurred images, which have no useful information, requires much more image processing subsystem resources. The paper presents blurry image frame elimination based approach of UAV resource saving fiducial marker visual tracking. The proposed approach integrates accelerometer and visual data processing algorithms to predict image blur and skip blurred frames. Experiments have been performed to verify the validity of the proposed approach

Eismo srautų prognozavimo modelis

The paper presents a mathematical model based on multicriteria decision making method of the Analytic Hierarchy Process for determining the critical network of railway lines, which prevented the flow of traffic growth, the line bandwidth, traffic volume and train speed. The presented model using real data and expert evaluation can be used for the renovation work schedules of railway lines (infrastructure, telecommunications, etc.).Darbe pateikiamas matematinis modelis, paremtas daugiakriterinio sprendimo priėmimo metodo analitiniu hierarchiniu procesu, leidžiantis nustatyti kritines geležinkelio tinklo linijas, kurios ateityje stabdys eismo srautų augimą, linijos pralaidumą, eismo intensyvumą bei traukinių judėjimo greitį, eismo linijas, kurios reikalauja atnaujinimo

Development of the real time situation identification model for adaptive service support in vehicular communication networks domain

The article discusses analyses and assesses the key proposals how to deal with the situation identification for the heterogeneous service support in vehicular cooperation environment. This is one of the most important topics of the pervasive computing. Without the solution it is impossible to adequately respond to the user's needs and to provide needed services in the right place at the right moment and in the right way. In this work we present our developed real time situation identification model for adaptive service support in vehicular communication networks domain. Our solution is different from the others as it uses additional virtual context information source - information from other vehicles which for our knowledge is not addressed in the past. The simulation results show the promising context exchange rate between vehicles. The other vehicles provided additional context source in our developed model helps to increase situations identification level

Deep reinforcement learning based optimization of automated guided vehicle time and energy consumption in a container terminal

The energy efficiency of port container terminal equipment and the reduction of CO2 emissions are among one of the biggest challenges facing every seaport in the world. The article pre sents the modeling of the container transportation process in a terminal from the quay crane to the stack using battery-powered Automated Guided Vehicle (AGV) to estimate the energy consump tion parameters. An AGV speed control algorithm based on Deep Reinforcement Learning (DRL) is proposed to optimize the energy consumption of container transportation. The results obtained and compared with real transportation measurements showed that the proposed DRL based approach dynamically changing the driving speed of the AGV reduces energy consumption by 4.6%. The obtained results of the research provide the prerequisites for further research in order to find optimal strategies for autonomous vehicle movement including context awareness and infor mation sharing with other vehicles in the terminal.Web of Science6740739

Cloud interconnected affect reward based automation ambient comfort controller

The paper presents the human Affect Reward Based Automation Ambient Comfort Controller (ACARBC) as the interconnected cloud computing intelligent services that provide intelligent calculus for any instrumented interconnected environment sense and control system. The ACARBC has been modelled and, as the experimental results show, that an environmental state characteristics that create an optimum ambient comfort can be obtained by ACAR index. The ACAR index is dependent on human physiological parameters: the temperature, the ECG- electrocardiogram and the EDA-electro-dermal activity. The fuzzy logic is used to approximate the ACAR index function by defining two fuzzy inference systems: the Arousal-Valence System, and the Ambient Comfort Affect Reward (ACAR) System. The Radial Basis Neural Network is used as the main component of the ACARBC to performing of two roles - the policy structure, known as the Actor, used to select actions, and the estimated value function, known as the Critic that criticizes the actions made by the Actor. The Critic in this paper was used as a value function approximation of the continuous learning tasks of the ACARBC

Development of an autonomous framework for emotion recognition

An approach of development of an autonomous emotion re-cognition system for creating of an intelligent e-health care environment is described. The process of emotion recognition is based on measurements of very small physiological signals taken from electrodes noninvasively attached on human body. The amplified ECG, EDA, and human’s body temperature si-gnals are used in the model for emotion recognition. The ECG, EDA, and human’s body temperature data acquisition module is designed based on usage of AD620 type instrumentation ampli-fier and ATmega16 microcontroller. To realizing actual emotion recognition process, the following data pre-processing steps are described in this paper: the phases of amplifying, discrimina-tion, filtering, recording, and storing into database of the sys-tem. The steps of development of recently proposed of new experimental environment for digital data acquisition and repre-sentation, the multi-chanel oscilloscope called as Atmega Osci-lografas are described in this paper. The original 10 bit data transferring algorithm has been discussed based on incremental usage of 8 bit data for effectively realizing of USART protocol of Atmel microcontrollers

Intelligent containers network concept

In this paper, a novel approach is presented to increase the security of shipping containers transportation and storage in container yards. This approach includes wireless sensors networks with programmable modules to increase the effectiveness of the decision support functionality for operators’ onsite. This approach is closely related to the Container Security Initiative and is intended to deepen knowledge in the intelligent transportation research area. This paper examines an urgent challenge - secure of cargo transportation in containers, i.e., how quickly it is possible to detect dangerous goods in shipping containers without changing their tightness and hence rationally implements international security regulations all around the world. This paper contributes to the development of new approaches of shipping containers handling and monitoring in terms of smart cities and smart ports (for the development of the Smart Port initiative) for ports that have higher levels of security violations. This contribution is addressed as an informative measure to the general public working in the Information and Communications Technologies (ICT) research area