Search results for: autonomous tow trucks
372 Reducing The Frequency of Flooding Accompanied by Low pH Wastewater In 100/200 Unit of Phosphate Fertilizer 1 Plant by Implementing The 3R Program (Reduce, Reuse and Recycle)
Authors: Pradipta Risang Ratna Sambawa, Driya Herseta, Mahendra Fajri Nugraha
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In 2020, PT Petrokimia Gresik implemented a program to increase the ROP (Run Of Pile) production rate at the Phosphate Fertilizer 1 plant, causing an increase in scrubbing water consumption in the 100/200 area unit. This increase in water consumption causes a higher discharge of wastewater, which can further cause local flooding, especially during the rainy season. The 100/200 area of the Phosphate Fertilizer 1 plant is close to the warehouse and is often a passing area for trucks transporting raw materials. This causes the pH in the wastewater to become acidic (the worst point is up to pH 1). The problem of flooding and exposure to acidic wastewater in the 100/200 area of Phosphate Fertilizer Plant 1 was then resolved by PT Petrokimia Gresik through wastewater optimization steps called the 3R program (Reduce, Reuse, and Recycle). The 3R (Reduce, reuse, and recycle) program consists of an air consumption reduction program by considering the liquid/gas ratio in scrubbing unit of 100/200 Phosphate Fertilizer 1 plant, creating a wastewater interconnection line so that wastewater from unit 100/200 can be used as scrubbing water in the Phonska 1, Phonska 2, Phonska 3 and unit 300 Phosphate Fertilizer 1 plant and increasing scrubbing effectiveness through scrubbing effectiveness simulations. Through a series of wastewater optimization programs, PT Petrokimia Gresik has succeeded in reducing NaOH consumption for neutralization up to 2,880 kg/day or equivalent in saving up to 314,359.76 dollars/year and reducing process water consumption up to 600 m3/day or equivalent in saving up to 63,739.62 dollars/year.Keywords: fertilizer, phosphate fertilizer, wastewater, wastewater treatment, water management
Procedia PDF Downloads 17371 Quadrotor in Horizontal Motion Control and Maneuverability
Authors: Ali Oveysi Sarabi
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In this paper, controller design for the attitude and altitude dynamics of an outdoor quadrotor, which is constructed with low cost actuators and drivers, is aimed. Before designing the controller, the quadrotor is modeled mathematically in Matlab-Simulink environment. To control attitude dynamics, linear quadratic regulator (LQR) based controllers are designed, simulated and applied to the system. Two different proportional-integral-derivative action (PID) controllers are designed to control yaw and altitude dynamics. During the implementation of the designed controllers, different test setups are used. Designed controllers are implemented and tuned on the real system using xPC Target. Tests show that these basic control structures are successful to control the attitude and altitude dynamics.Keywords: helicopter balance, flight dynamics, autonomous landing, control robotics
Procedia PDF Downloads 501370 A Survey of Semantic Integration Approaches in Bioinformatics
Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir
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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.Keywords: biological ontology, linked data, semantic data integration, semantic web
Procedia PDF Downloads 443369 Improving Waste Recycling and Resource Productivity by Integrating Smart Resource Tracking System
Authors: Atiq Zaman
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The high contamination rate in the recycling waste stream is one of the major problems in Australia. In addition, a lack of reliable waste data makes it even more difficult for designing and implementing an effective waste management plan. This article conceptualizes the opportunity to improve resource productivity by integrating smart resource tracking system (SRTS) into the Australian household waste management system. The application of the smart resource tracking system will be implemented through the following ways: (i) mobile application-based resource tracking system used to measure the household’s material flow; (ii) RFID, smart image and weighing system used to track waste generation, recycling and contamination; (iii) informing and motivating manufacturer and retailers to improve their problematic products’ packaging; and (iv) ensure quality and reliable data through open-sourced cloud data for public use. The smart mobile application, imaging, radio-frequency identification (RFID) and weighing technologies are not new, but the very straightforward idea of using these technologies in the household resource consumption, waste bins and collection trucks will open up a new era of accurately measuring and effectively managing our waste. The idea will bring the most urgently needed reliable, data and clarity on household consumption, recycling behaviour and waste management practices in the context of available local infrastructure and policies. Therefore, the findings of this study would be very important for decision makers to improve resource productivity in the waste industry by using smart resource tracking system.Keywords: smart devices, mobile application, smart sensors, resource tracking, waste management, resource productivity
Procedia PDF Downloads 139368 Methodology to Affirm Driver Engagement in Dynamic Driving Task (DDT) for a Level 2 Adas Feature
Authors: Praneeth Puvvula
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Autonomy in has become increasingly common in modern automotive cars. There are 5 levels of autonomy as defined by SAE. This paper focuses on a SAE level 2 feature which, by definition, is able to control the vehicle longitudinally and laterally at the same time. The system keeps the vehicle centred with in the lane by detecting the lane boundaries while maintaining the vehicle speed. As with the features from SAE level 1 to level 3, the primary responsibility of dynamic driving task lies with the driver. This will need monitoring techniques to ensure the driver is always engaged even while the feature is active. This paper focuses on the these techniques, which would help the safe usage of the feature and provide appropriate warnings to the driver.Keywords: autonomous driving, safety, adas, automotive technology
Procedia PDF Downloads 82367 Simulation and Optimization of Hybrid Energy System Autonomous PV-Diesel-Wind Power with Battery Storage for Relay Antenna Telecommunication
Authors: Tahri Toufik, Bouchachia Mohamed, Braikia Oussama
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The objective of this work is the design and optimization of a hybrid PV-Diesel-Wind power system with storage in order to power a relay antenna telecommunication isolated in Chlef region. The aim of the simulation of this hybrid system by the HOMER software is to determine the size and the number of each element of the system and to determine the optimal technical and economic configuration using monthly average values per year for a fixed charge antenna relay telecommunication of 22kWh/d.Keywords: HOMER, hybrid, PV-diesel-wind system, relay antenna telecommunication
Procedia PDF Downloads 509366 Deep Reinforcement Learning Approach for Trading Automation in The Stock Market
Authors: Taylan Kabbani, Ekrem Duman
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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent
Procedia PDF Downloads 174365 Challenges in Video Based Object Detection in Maritime Scenario Using Computer Vision
Authors: Dilip K. Prasad, C. Krishna Prasath, Deepu Rajan, Lily Rachmawati, Eshan Rajabally, Chai Quek
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This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here.Keywords: autonomous maritime vehicle, object detection, situation awareness, tracking
Procedia PDF Downloads 445364 Proposal to Increase the Efficiency, Reliability and Safety of the Centre of Data Collection Management and Their Evaluation Using Cluster Solutions
Authors: Martin Juhas, Bohuslava Juhasova, Igor Halenar, Andrej Elias
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This article deals with the possibility of increasing efficiency, reliability and safety of the system for teledosimetric data collection management and their evaluation as a part of complex study for activity “Research of data collection, their measurement and evaluation with mobile and autonomous units” within project “Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants”. Possible weaknesses in existing system are identified. A study of available cluster solutions with possibility of their deploying to analysed system is presented.Keywords: teledosimetric data, efficiency, reliability, safety, cluster solution
Procedia PDF Downloads 507363 Artificial Intelligence-Aided Extended Kalman Filter for Magnetometer-Based Orbit Determination
Authors: Gilberto Goracci, Fabio Curti
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This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field
Procedia PDF Downloads 98362 Women's Contemporary Dystopias: Feminist Protagonists Taking Back Control
Authors: Natalia Fontes De Oliveira
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The Canadian author Margaret Atwood deconstructs the tainted dichotomies between women and men by embracing the disorder throughout her dystopias. In Atwood’s The Testaments, nature can be seen as a background to the story as well as a metaphorical expression of the characters’ state of mind, nevertheless, the protagonists’ nature writing portrays conveys a curiosity to the pre-established sanctions of a docile garden, viewing nature as an autonomous entity, especially when they are away from the confinements of Gilead’s regime. The three narrating protagonists, Agnes, Aunt Lydia, and Nicole, use nature writing subversively as a form of rebellion. This paper investigates how the three protagonists narrate nature through an intimist point of view, with sensibility to observe the multiple relationships among humanity, nature, and the impositions of a theocratic ultra conservative patriarchal society.Keywords: contemporary literature, dystopias, feminism, women’s writing
Procedia PDF Downloads 160361 Data Presentation of Lane-Changing Events Trajectories Using HighD Dataset
Authors: Basma Khelfa, Antoine Tordeux, Ibrahima Ba
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We present a descriptive analysis data of lane-changing events in multi-lane roads. The data are provided from The Highway Drone Dataset (HighD), which are microscopic trajectories in highway. This paper describes and analyses the role of the different parameters and their significance. Thanks to HighD data, we aim to find the most frequent reasons that motivate drivers to change lanes. We used the programming language R for the processing of these data. We analyze the involvement and relationship of different variables of each parameter of the ego vehicle and the four vehicles surrounding it, i.e., distance, speed difference, time gap, and acceleration. This was studied according to the class of the vehicle (car or truck), and according to the maneuver it undertook (overtaking or falling back).Keywords: autonomous driving, physical traffic model, prediction model, statistical learning process
Procedia PDF Downloads 250360 Integrating Radar Sensors with an Autonomous Vehicle Simulator for an Enhanced Smart Parking Management System
Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes
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The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models
Procedia PDF Downloads 74359 Review, Analysis and Simulation of Advanced Technology Solutions of Selected Components in Power Electronics Systems (PES) of More Electric Aircraft
Authors: Lucjan Setlak, Emil Ruda
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The subject of this paper is to review, comparative analysis and simulation of selected components of power electronic systems (PES), consistent with the concept of a more electric aircraft (MEA). Comparative analysis and simulation in software environment MATLAB / Simulink were carried out based on a group of representatives of civil aircraft (B-787, A-380) and military (F-22 Raptor, F-35) in the context of multi-pulse converters used in them (6- and 12-pulse, and 18- and 24-pulse), which are key components of high-tech electronics on-board power systems of autonomous power systems (ASE) of modern aircraft (airplanes of the future).Keywords: converters, electric machines, MEA (more electric aircraft), PES (power electronics systems)
Procedia PDF Downloads 487358 Autonomous Quantum Competitive Learning
Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally
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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.Keywords: competitive learning, quantum gates, quantum gates, winner-take-all
Procedia PDF Downloads 462357 ARGO: An Open Designed Unmanned Surface Vehicle Mapping Autonomous Platform
Authors: Papakonstantinou Apostolos, Argyrios Moustakas, Panagiotis Zervos, Dimitrios Stefanakis, Manolis Tsapakis, Nektarios Spyridakis, Mary Paspaliari, Christos Kontos, Antonis Legakis, Sarantis Houzouris, Konstantinos Topouzelis
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For years unmanned and remotely operated robots have been used as tools in industry research and education. The rapid development and miniaturization of sensors that can be attached to remotely operated vehicles in recent years allowed industry leaders and researchers to utilize them as an affordable means for data acquisition in air, land, and sea. Despite the recent developments in the ground and unmanned airborne vehicles, a small number of Unmanned Surface Vehicle (USV) platforms are targeted for mapping and monitoring environmental parameters for research and industry purposes. The ARGO project is developed an open-design USV equipped with multi-level control hardware architecture and state-of-the-art sensors and payloads for the autonomous monitoring of environmental parameters in large sea areas. The proposed USV is a catamaran-type USV controlled over a wireless radio link (5G) for long-range mapping capabilities and control for a ground-based control station. The ARGO USV has a propulsion control using 2x fully redundant electric trolling motors with active vector thrust for omnidirectional movement, navigation with opensource autopilot system with high accuracy GNSS device, and communication with the 2.4Ghz digital link able to provide 20km of Line of Sight (Los) range distance. The 3-meter dual hull design and composite structure offer well above 80kg of usable payload capacity. Furthermore, sun and friction energy harvesting methods provide clean energy to the propulsion system. The design is highly modular, where each component or payload can be replaced or modified according to the desired task (industrial or research). The system can be equipped with Multiparameter Sonde, measuring up to 20 water parameters simultaneously, such as conductivity, salinity, turbidity, dissolved oxygen, etc. Furthermore, a high-end multibeam echo sounder can be installed in a specific boat datum for shallow water high-resolution seabed mapping. The system is designed to operate in the Aegean Sea. The developed USV is planned to be utilized as a system for autonomous data acquisition, mapping, and monitoring bathymetry and various environmental parameters. ARGO USV can operate in small or large ports with high maneuverability and endurance to map large geographical extends at sea. The system presents state of the art solutions in the following areas i) the on-board/real-time data processing/analysis capabilities, ii) the energy-independent and environmentally friendly platform entirely made using the latest aeronautical and marine materials, iii) the integration of advanced technology sensors, all in one system (photogrammetric and radiometric footprint, as well as its connection with various environmental and inertial sensors) and iv) the information management application. The ARGO web-based application enables the system to depict the results of the data acquisition process in near real-time. All the recorded environmental variables and indices are presented, allowing users to remotely access all the raw and processed information using the implemented web-based GIS application.Keywords: monitor marine environment, unmanned surface vehicle, mapping bythometry, sea environmental monitoring
Procedia PDF Downloads 129356 Game-Based Learning in a Higher Education Course: A Case Study with Minecraft Education Edition
Authors: Salvador Antelmo Casanova Valencia
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This study documents the use of the Minecraft Education Edition application to explore immersive game-based learning environments. We analyze the contributions of fourth-year university students who are pursuing a degree in Administrative Computing at the Universidad Michoacana de San Nicolas de Hidalgo. In this study, descriptive data and statistical inference are detailed using a quasi-experimental design using the Wilcoxon test. The instruments will provide data validation. Game-based learning in immersive environments necessarily implies greater student participation and commitment, resulting in the study, motivation, and significant improvements, promoting cooperation and autonomous learning.Keywords: game-based learning, gamification, higher education, Minecraft
Procedia PDF Downloads 158355 Semi-Autonomous Surgical Robot for Pedicle Screw Insertion on ex vivo Bovine Bone: Improved Workflow and Real-Time Process Monitoring
Authors: Robnier Reyes, Andrew J. P. Marques, Joel Ramjist, Chris R. Pasarikovski, Victor X. D. Yang
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Over the past three decades, surgical robotic systems have demonstrated their ability to improve surgical outcomes. The LBR Med is a collaborative robotic arm that is meant to work with a surgeon to streamline surgical workflow. It has 7 degrees of freedom and thus can be easily oriented. Position and torque sensors at each joint allow it to maintain a position accuracy of 150 µm with real-time force and torque feedback, making it ideal for complex surgical procedures. Spinal fusion procedures involve the placement of as many as 20 pedicle screws, requiring a great deal of accuracy due to proximity to the spinal canal and surrounding vessels. Any deviation from intended path can lead to major surgical complications. Assistive surgical robotic systems are meant to serve as collaborative devices easing the workload of the surgeon, thereby improving pedicle screw placement by mitigating fatigue related inaccuracies. Moreover, robotic spinal systems have shown marked improvements over conventional freehanded techniques in both screw placement accuracy and fusion quality and have greatly reduced the need for screw revision, intraoperatively and post-operatively. However, current assistive spinal fusion robots, such as the ROSA Spine, are limited in functionality to positioning surgical instruments. While they offer a small degree of improvement in pedicle screw placement accuracy, they do not alleviate surgeon fatigue, nor do they provide real-time force and torque feedback during screw insertion. We propose a semi-autonomous surgical robot workflow for spinal fusion where the surgeon guides the robot to its initial position and orientation, and the robot drives the pedicle screw accurately into the vertebra. Here, we demonstrate feasibility by inserting pedicle screws into ex-vivo bovine rib bone. The robot monitors position, force and torque with respect to predefined values selected by the surgeon to ensure the highest possible spinal fusion quality. The workflow alleviates the strain on the surgeon by having the robot perform the screw placement while the ability to monitor the process in real-time keeps the surgeon in the system loop. The approach we have taken in terms of level autonomy for the robot reflects its ability to safely collaborate with the surgeon in the operating room without external navigation systems.Keywords: ex vivo bovine bone, pedicle screw, surgical robot, surgical workflow
Procedia PDF Downloads 165354 Investigation of Optical Requirements for Power System Assets Monitoring with Unmanned Aerial Vehicles
Authors: Ioana Pisica, Dimitrios Gkritzapis
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The significance of UAS in scientific applications has been amply demonstrated in recent years. The combinations of portability and quasi-static positioning by means of flying in close loop path make them versatile and efficient in the inspection of power systems infrastructure. In this paper, we critically assess several platforms and sensor capabilities to identify their pros and cons in relation to the power systems assets to be monitored. In this respect, it is paramount the flights to be conducted by using UAS which bear certain suitable features, such as responsive and easy control, video capturing in real time, autonomous routing of pre-planned flight programming with differentiating payloads. The outcome of this research is a set of optimal requirements for power system assets monitoring with UAS.Keywords: platforms, power system, sensors, UAVs
Procedia PDF Downloads 280353 Radar-Based Classification of Pedestrian and Dog Using High-Resolution Raw Range-Doppler Signatures
Authors: C. Mayr, J. Periya, A. Kariminezhad
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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.Keywords: machine learning, radar, signal processing, autonomous driving
Procedia PDF Downloads 234352 Sustainable Tourism from a Multicriteria Analysis Perspective
Authors: Olga Blasco-Blasco, Vicente Liern
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The development of tourism since the mid-20th century has raised problems of overcrowding, indiscriminate construction in seaside areas and gentrification. Increasingly, the World Tourism Organisation and public institutions are promoting policies that encourage sustainability. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism and sustainable impact tourism. Measuring sustainability is complex due to its multiple dimensions of different relative importance and diversity in nature. In order to try to answer this problem and to identify the benefits of applying policies that promote sustainable tourism, a decision-making analysis will be carried out through the application of a multicriteria analysis method. The proposal is applied to hotel reservations and to the evaluation and management of tourism sustainability in the Spanish Autonomous Communities.Keywords: sustainable tourism, multicriteria analysis, flexible optimization, composite indicators
Procedia PDF Downloads 303351 The Nuclear Power Plant Environment Monitoring System through Mobile Units
Authors: P. Tanuska, A. Elias, P. Vazan, B. Zahradnikova
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This article describes the information system for measuring and evaluating the dose rate in the environment of nuclear power plants Mochovce and Bohunice in Slovakia. The article presents the results achieved in the implementation of the EU project–Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants. The objectives included improving the system of acquisition, measuring and evaluating data with mobile and autonomous units applying new knowledge from research. The article provides basic and specific features of the system and compared to the previous version of the system, also new functions.Keywords: information system, dose rate, mobile devices, nuclear power plant
Procedia PDF Downloads 372350 Survey on Energy Efficient Routing Protocols in Mobile Ad-Hoc Networks
Authors: Swapnil Singh, Sanjoy Das
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Mobile Ad-Hoc Network (MANET) is infrastructure less networks dynamically formed by autonomous system of mobile nodes that are connected via wireless links. Mobile nodes communicate with each other on the fly. In this network each node also acts as a router. The battery power and the bandwidth are very scarce resources in this network. The network lifetime and connectivity of nodes depends on battery power. Therefore, energy is a valuable constraint which should be efficiently used. In this paper, we survey various energy efficient routing protocol. The energy efficient routing protocols are classified on the basis of approaches they use to minimize the energy consumption. The purpose of this paper is to facilitate the research work and combine the existing solution and to develop a more energy efficient routing mechanism.Keywords: delaunay triangulation, deployment, energy efficiency, MANET
Procedia PDF Downloads 608349 Impairments Correction of Six-Port Based Millimeter-Wave Radar
Authors: Dan Ohev Zion, Alon Cohen
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In recent years, the presence of short-range millimeter-wave radar in civil application has increased significantly. Autonomous driving, security, 3D imaging and high data rate communication systems are a few examples. The next challenge is the integration inside small form-factor devices, such as smartphones (e.g. gesture recognition). The main challenge is implementation of a truly low-power, low-complexity high-resolution radar. The most popular approach is the Frequency Modulated Continuous Wave (FMCW) radar, with an analog multiplication front-end. In this paper, we present an approach for adaptive estimation and correction of impairments of such front-end, specifically implemented using the Six-Port Device (SPD) as the multiplier element. The proposed algorithm was simulated and implemented on a 60 GHz radar lab prototype.Keywords: radar, FMCW Radar, IQ mismatch, six port
Procedia PDF Downloads 147348 RoboWeedSupport-Semi-Automated Unmanned Aerial System for Cost Efficient High Resolution in Sub-Millimeter Scale Acquisition of Weed Images
Authors: Simon L. Madsen, Mads Dyrmann, Morten S. Laursen, Rasmus N. Jørgensen
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Recent advances in the Unmanned Aerial System (UAS) safety and perception systems enable safe low altitude autonomous terrain following flights recently demonstrated by the consumer DJI Mavic PRO and Phamtom 4 Pro drones. This paper presents the first prototype system utilizing this functionality in form of semi-automated UAS based collection of crop/weed images where the embedded perception system ensures a significantly safer and faster gathering of weed images with sub-millimeter resolution. The system is to be used when the weeds are at cotyledon stage and prior to the harvest recognizing the grass weed species, which cannot be discriminated at the cotyledon stage.Keywords: weed mapping, UAV, DJI SDK, automation, cotyledon plants
Procedia PDF Downloads 305347 Energy Management Techniques in Mobile Robots
Authors: G. Gurguze, I. Turkoglu
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Today, the developing features of technological tools with limited energy resources have made it necessary to use energy efficiently. Energy management techniques have emerged for this purpose. As with every field, energy management is vital for robots that are being used in many areas from industry to daily life and that are thought to take up more spaces in the future. Particularly, effective power management in autonomous and multi robots, which are getting more complicated and increasing day by day, will improve the performance and success. In this study, robot management algorithms, usage of renewable and hybrid energy sources, robot motion patterns, robot designs, sharing strategies of workloads in multiple robots, road and mission planning algorithms are discussed for efficient use of energy resources by mobile robots. These techniques have been evaluated in terms of efficient use of existing energy resources and energy management in robots.Keywords: energy management, mobile robot, robot administration, robot management, robot planning
Procedia PDF Downloads 260346 Teacher Professional Development with Collaborative Action Research: Teachers' Responses to Research
Authors: Sumaya Saqr
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Although many teachers regard academic research as the inclusive domain of academic researchers, teachers should contribute to the body of research guiding their own practice. Drawing on the qualitative analysis of 20 teachers’ reflection journals and interviews, this case study sheds light on the personal and professional benefits of teachers’ applications of collaborative action research in English language teaching context. The findings reveal that several aspects of teacher identity and classroom practice were changed. The present paper aspires to reveal the way in which collaborative action research process, as a learner-centered approach to staff development, would help teachers to become more independent and professionally autonomous and hence effecting change that is far greater than its initial purpose.Keywords: change, collaborative action research, personal and professional benefits, professional development
Procedia PDF Downloads 173345 Economic and Technical Study for Hybrid (PV/Wind) Power System in the North East of Algeria
Authors: Nabila Louai, Fouad Khaldi, Houria Benharchache
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In this paper, the case of meeting a household’s electrical energy demand with hybrid systems has been examined. The objective is to study technological feasibility and economic viability of the electrification project by a hybrid system (PV/ wind) of a residential home located in Batna-Algeria and to reduce the emissions from traditional power by using renewable energy. An autonomous hybrid wind/photovoltaic (PV)/battery power system and a PV/Wind grid connected system, has been carried out using Hybrid Optimization Model for Electric Renewable (HOMER) simulation software. As a result, it has been found that electricity from the grid can be supplied at a lower price than electricity from renewable energy at this moment.Keywords: batna, household, hybrid system, renewable energy, techno-economy
Procedia PDF Downloads 591344 Neural Network Motion Control of VTAV by NARMA-L2 Controller for Enhanced Situational Awareness
Authors: Igor Astrov, Natalya Berezovski
Abstract:
This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for vectored thrust aerial vehicle (VTAV). With the SA strategy, we proposed a neural network motion control procedure to address the dynamics variation and performance requirement difference of flight trajectory for a VTAV. This control strategy with using of NARMA-L2 neurocontroller for chosen model of VTAV has been verified by simulation of take-off and forward maneuvers using software package Simulink and demonstrated good performance for fast stabilization of motors, consequently, fast SA with economy in energy can be asserted during search-and-rescue operations.Keywords: NARMA-L2 neurocontroller, situational awareness, vectored thrust aerial vehicle, aviation
Procedia PDF Downloads 414343 Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) Control of Quadcopters: A Comparative Analysis
Authors: Anel Hasić, Naser Prljača
Abstract:
In the domain of autonomous or piloted flights, the accurate control of quadrotor trajectories is of paramount significance for large numbers of tasks. These adaptable aerial platforms find applications that span from high-precision aerial photography and surveillance to demanding search and rescue missions. Among the fundamental challenges confronting quadrotor operation is the demand for accurate following of desired flight paths. To address this control challenge, among others, two celebrated well-established control strategies have emerged as noteworthy contenders: Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) control. In this work, we focus on the extensive examination of MPC and PID control techniques by using comprehensive simulation studies in MATLAB/Simulink. Intensive simulation results demonstrate the performance of the studied control algorithms.Keywords: MATLAB, MPC, PID, quadcopter, simulink
Procedia PDF Downloads 45