Search results for: localized intelligent parking system

Authors: P. N. Salini, B. Anish Kini, R. Ashalatha

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At signalized intersections with heterogeneous traffic, the percentage share of different vehicle categories have a bearing on the inter-vehicle space utilization, which eventually impacts the saturation flow. This paper analyzed the impact of the percentage share of various vehicle categories in the traffic stream on the saturation flow at signalized intersections by video graphing major intersections with varying geometry in Kerala, India. It was found that as the percentage share of two-wheelers increases, the saturation flow at signalized intersections increases and vice-versa for the percentage share of cars. The effect of bus blockage and parking maneuvers on the saturation flow were also studied. As the distance of bus blockage increases from the stop line, the effect on the saturation flow decreases, while with more buses stopping at the same bus stop, the saturation flow reduces further. The study revealed that with higher kerbside parking maneuvers on the upstream, the saturation flow reduces, and with an increase in the distance of the parking maneuver from the stop line, the effect on the saturation flow decreases. The adjustment factors for bus blockage due to bus stops within 75m downstream and parking maneuvers within 75m upstream of the intersection have been established for mixed traffic conditions. These adjustment factors could empower the urban planners, enforcement personnel and decision-makers to estimate the reduction in the capacity of signalized intersections for suggesting improvements in the form of parking restrictions/ bus stop relocation for existing intersections or make design changes for planned intersections.

Keywords: signalized intersection, saturation flow, adjustment factors, capacity

Procedia PDF Downloads 88

Authors: Andrés C. Cuervo Pinilla, Christian G. Quintero M., Chinthaka Premachandra

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This paper considers people’s driving skills diagnosis under real driving conditions. In that sense, this research presents an approach that uses GPS signals which have a direct correlation with driving maneuvers. Besides, it is presented a novel expert-driving-criteria approximation using fuzzy logic which seeks to analyze GPS signals in order to issue an intelligent driving diagnosis. Based on above, this works presents in the first section the intelligent driving diagnosis system approach in terms of its own characteristics properties, explaining in detail significant considerations about how an expert-driving-criteria approximation must be developed. In the next section, the implementation of our developed system based on the proposed fuzzy logic approach is explained. Here, a proposed set of rules which corresponds to a quantitative abstraction of some traffics laws and driving secure techniques seeking to approach an expert-driving- criteria approximation is presented. Experimental testing has been performed in real driving conditions. The testing results show that the intelligent driving diagnosis system qualifies driver’s performance quantitatively with a high degree of reliability.

Keywords: driver support systems, intelligent transportation systems, fuzzy logic, real time data processing

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Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

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There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

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Authors: Getachew Demeissie Ayalew, Yongtao Sun, Yang Yang

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The spiral welded pipe manufacturing industry requires strict production standards for automated grinders for welding seams. However, traditional grinding machines in this sector are insufficient due to a lack of quality control protocols and inconsistent performance. This research aims to improve the quality of spiral welded pipes by developing intelligent automated abrasive belt grinding equipment. The system has equipped with six degrees of freedom (6 DOF) KUKA KR360 industrial robots, enabling concurrent grinding operations on both internal and external welds. The grinding robot control system is designed with a PLC, and a human-machine interface (HMI) system is employed for operations. The system includes an electric speed controller, data connection card, DC driver, analog amplifier, and HMI for input data. This control system enables the grinding of spiral welded pipe. It ensures consistent production quality and cost-effectiveness by reducing the product life cycle and minimizing risks in the working environment.

Keywords: Intelligent Systems, Spiral Welded Pipe, Grinding, Industrial Robot, End-Effector, PLC Controller System, 3D Laser Sensor, HMI.

Procedia PDF Downloads 237

Authors: Shih-Ting Yang, Chih-Yun Lin, Ming-Yu Li, Jhong-Ting Syue, Wei-Ming Huang

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Global positioning system (GPS) has become increasing precise in recent years, and the location-based service (LBS) has developed rapidly. Take the example of finding a parking lot (such as Parking apps). The location-based service can offer immediate information about a nearby parking lot, including the information about remaining parking spaces. However, it cannot provide expected search results according to the requirement situations of users. For that reason, this paper develops a “Location-based Search Approach according to Users’ Application Scenario” according to the location-based search and demand determination to help users obtain the information consistent with their requirements. The “Location-based Search Approach based on Users’ Application Scenario” of this paper consists of one mechanism and three kernel modules. First, in the Information Pre-processing Mechanism (IPM), this paper uses the cosine theorem to categorize the locations of users. Then, in the Information Category Evaluation Module (ICEM), the kNN (k-Nearest Neighbor) is employed to classify the browsing records of users. After that, in the Information Volume Level Determination Module (IVLDM), this paper makes a comparison between the number of users’ clicking the information at different locations and the average number of users’ clicking the information at a specific location, so as to evaluate the urgency of demand; then, the two-dimensional space is used to estimate the application situations of users. For the last step, in the Location-based Search Module (LBSM), this paper compares all search results and the average number of characters of the search results, categorizes the search results with the Manhattan Distance, and selects the results according to the application scenario of users. Additionally, this paper develops a Web-based system according to the methodology to demonstrate practical application of this paper. The application scenario-based estimate and the location-based search are used to evaluate the type and abundance of the information expected by the public at specific location, so that information demanders can obtain the information consistent with their application situations at specific location.

Keywords: data mining, knowledge management, location-based service, user application scenario

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Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lorenço

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The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in a smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore relying on fixed operational models would be inappropriate. This paper presents a study on developing an Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose an Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

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Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lourenço

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The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore, relying on fixed operational models would be inappropriate. This paper presents a study on developing a Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose a Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

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Authors: Changchun Liang, Xiaodong Zhang, Xin Liu, Pengfei Sun

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Space intelligent robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the tracking and capturing technology, becomes research hot in recent years. In this paper, the authors propose a vision servo control system for target capturing. Robotic manipulator will be an intelligent robotic system with large-scale movement, functional agility, and autonomous ability, and it can be operated by astronauts in the space station or be controlled by the ground operator in the remote operation mode. To realize the autonomous movement and capture mission of SRM, a kind of autonomous programming strategy based on multi-camera vision fusion is designed and the selection principle of object visual position and orientation measurement information is defined for the better precision. Distributed control system hierarchy is designed and reliability is considering to guarantee the abilities of control system. At last, a ground experiment system is set up based on the concept of robotic control system. With that, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm, and demonstrates that the control system can fulfill the needs of function, real-time and reliability.

Keywords: control system, on-orbital service, space robot, vision servo

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Authors: Mohammad Nadeem, Haider Banka, R. Venugopal

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Granulation or agglomeration is a size enlargement process to transform the fine particulates into larger aggregates since the fine size of available materials and minerals poses difficulty in their utilization. Though a long list of methods is available in the literature for the modeling of granulation process to facilitate the in-depth understanding and interpretation of the system, there is still scope of improvements using novel tools and techniques. Intelligent techniques, such as artificial neural network, fuzzy logic, self-organizing map, support vector machine and others, have emerged as compelling alternatives for dealing with imprecision and complex non-linearity of the systems. The present study tries to review the applications of intelligent techniques in the modeling of size enlargement process for fine materials.

Keywords: fine material, granulation, intelligent technique, modelling

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Authors: G. Valentis, Q. Berthelot

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Nowadays the trend to develop ever more intelligent and autonomous systems often takes its inspiration in the living beings on Earth. Some simple isolated systems are able, once brought together, to form a strong and reliable system. When trying to adapt the idea to man-made systems it is not possible to include in their program everything the system may encounter during its life cycle. It is, thus, necessary to make the system able to take decisions based on other criteria such as its past experience, i.e. to make the system learn on its own. However, at some point the acquired knowledge depends also on environment. So the question is: if system environment is modified, how could the system respond to it quickly and appropriately enough? Here, starting from reinforcement learning to rate its decisions, and using adaptive learning algorithms for gain and loss reward, the system is made able to respond to changing environment and to adapt its knowledge as time passes. Application is made to a robot finding an exit in a labyrinth.

Keywords: reinforcement learning, neural network, autonomous systems, adaptive learning, changing environment

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Authors: Ferenc Kovács, Gábor Hosszú

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The paper presents an advanced control system for tennis ball throwing machines to improve their accuracy according to the ball impact points. A further advantage of the system is the much easier calibration process involving the intelligent solution of the automatic adjustment of the stroking parameters according to the ball elasticity, the self-calibration, the use of the safety margin at very flat strokes and the possibility to placing the machine to any position of the half court. The system applies mathematical methods to determine the exact ball trajectories and special approximating processes to access all points on the aimed half court.

Keywords: control system, robot programming, robot control, sports equipment, throwing machine

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Authors: Hamed Hossein Afshari, Shahrzad Jalali, Amir Hossein Ghods, Bijan Raahemi

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This paper introduces an automated clustering solution that applies to WiFi/Bluetooth sensing data and is later used for traffic management applications. The paper initially summarizes a number of clustering approaches and thereafter shows their performance for noise removal. In this context, clustering is used to recognize WiFi and Bluetooth MAC addresses that belong to passengers traveling by a public urban transit bus. The main objective is to build an intelligent system that automatically filters out MAC addresses that belong to persons located outside the bus for different routes in the city of Ottawa. The proposed intelligent system alleviates the need for defining restrictive thresholds that however reduces the accuracy as well as the range of applicability of the solution for different routes. This paper moreover discusses the performance benefits of the presented clustering approaches in terms of the accuracy, time and space complexity, and the ease of use. Note that results of clustering can further be used for the purpose of the origin-destination estimation of individual passengers, predicting the traffic load, and intelligent management of urban bus schedules.

Keywords: WiFi-Bluetooth sensing, cluster analysis, artificial intelligence, traffic management

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Authors: Prateek Saxena, Sanjeev Singh, Julius Roy

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The security of the power distribution grid remains a paramount to the utility professionals while enhancing and making it more efficient. The most serious threat to the system can be maintaining the transformers, as the load is ever increasing with the addition of elements like electric vehicles. In this paper, intelligent transformer monitoring and grid management has been proposed. The engineering is done to use the evolving data from the smart meter for grid analytics and diagnostics for preventive maintenance. The two-tier architecture for hardware and software integration is coupled to form a robust system for the smart grid. The proposal also presents interoperable meter standards for easy integration. Distribution transformer analytics based on real-time data benefits utilities preventing outages, protects the revenue loss, improves the return on asset and reduces overall maintenance cost by predictive monitoring.

Keywords: electric vehicle charging, transformer monitoring, data analytics, intelligent grid

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Authors: Joaquin Navarro Perales, Ana Lidia Franzoni Velázquez, Francisco Cervantes Pérez

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The Mexican educational system faces diverse challenges related with the quality and coverage of education. The development of Intelligent Tutoring Systems (ITS) may help to solve some of them by helping teachers to customize their classes according to the performance of the students in online courses. In this work, we propose the adaptation of a functional ITS based on Bloom’s taxonomy called Sistema de Apoyo Generalizado para la Enseñanza Individualizada (SAGE), to measure student’s metacognition and their emotional response based on Marzano’s taxonomy. The students and the system will share the control over the advance in the course, so they can improve their metacognitive skills. The system will not allow students to get access to subjects not mastered yet. The interaction between the system and the student will be implemented through Natural Language Processing techniques, thus avoiding the use of sensors to evaluate student’s response. The teacher will evaluate student’s knowledge utilization, which is equivalent to the last cognitive level in Marzano’s taxonomy.

Keywords: intelligent tutoring systems, student modelling, metacognition, affective computing, natural language processing

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Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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Authors: Hyeon-Seung Kim, Bit-Na Cho, Tae-Woon Jeong, Soo-Young Yoon, Leen-Seok Kang

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Recently, a construction project has been large in the size and complicated in the site work. The web-cameras are used to manage the construction site of such a large construction project. They can be used for monitoring the construction schedule as compared to the actual work image of the planned work schedule. Specially, because the 4D CAD system that the construction appearance is continually simulated in a 3D CAD object by work schedule is widely applied to the construction project, the comparison system between the real image of actual work appearance by web-camera and the simulated image of planned work appearance by 3D CAD object can be an intelligent construction schedule management system (ICON). The delayed activities comparing with the planned schedule can be simulated by red color in the ICON as a virtual reality object. This study developed the ICON and it was verified in a real bridge construction project in Korea. To verify the developed system, a web-camera was installed and operated in a case project for a month. Because the angle and zooming of the web-camera can be operated by Internet, a project manager can easily monitor and assume the corrective action.

Keywords: 4D CAD, web-camera, ICON (intelligent construction schedule management system), 3D object image

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Authors: Ayman M. Mansour

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In this paper, we propose an intelligent system that is used for monitoring the health conditions of Patients. Monitoring the health condition of Patients is a complex problem that involves different medical units and requires continuous monitoring especially in rural areas because of inadequate number of available specialized physicians. The proposed system will Improve patient care and drive costs down comparing to the existing system in Jordan. The proposed system will be the start point to Faster and improve the communication between different units in the health system in Jordan. Connecting patients and their physicians beyond hospital doors regarding their geographical area is an important issue in developing the health system in Jordan. The propose system will provide an intelligent system that will generate initial diagnosing to the patient case. This will assist and advice clinicians at the point of care. The decision is based on demographic data and laboratory test results of patient data. Using such system with the ability of making medical decisions, the quality of medical care in Jordan and specifically in Tafial is expected to be improved. This will provide more accurate, effective, and reliable diagnoses and treatments especially if the physicians have insufficient knowledge.

Keywords: GSM, SMS, patient, monitoring system, fuzzy logic, multi-agent system

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Authors: Pocholo Rodriguez, Anne Bernadine Ocampo, Ian Benedict Chan, Janric Micah Gray

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The state of an electric power system may be classified as either stable or unstable. The borderline of stability is at any condition for which a slight change in an unfavourable direction of any pertinent quantity will cause instability. Voltage instability in power distribution systems could lead to voltage collapse and thus power blackouts. The researchers will present an intelligent system using back propagation algorithm that can detect voltage instability and output voltage of a power distribution and classify it as stable or unstable. The researchers’ work is the use of parameters involved in voltage instability as input parameters to the neural network for training and testing purposes that can provide faster detection and monitoring of the power distribution system.

Keywords: back-propagation algorithm, load instability, neural network, power distribution system

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Authors: Rita Garcia

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Intelligent Programming Tutors, IPTs, are supplemental educational devices that assist in teaching software development. These systems provide customized learning allowing the user to select the presentation pace, pedagogical strategy, and to recall previous and additional teaching materials reinforcing learning objectives. In addition, IPTs automatically records individual’s progress, providing feedback to the instructor and student. These tutoring systems have an advantage over Tutoring Systems because Intelligent Programming Tutors are not limited to one teaching strategy and can adjust when it detects the user struggling with a concept. The Intelligent Programming Tutor is a category of Intelligent Tutoring Systems, ITS. ITS are available for many fields in education, supporting different learning objectives and integrate into other learning tools, improving the student's learning experience. This study provides a comparison of the IPTs currently adopted by the educational community and will focus on the different teaching methodologies and programming languages. The study also includes the ability to integrate the IPT into other educational technologies, such as massive open online courses, MOOCs. The intention of this evaluation is to determine one system that would best serve in a larger ongoing research project and provide findings for other institutions looking to adopt an Intelligent Programming Tutor.

Keywords: computer education tools, integrated software development assistance, intelligent programming tutors, tutoring systems

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Authors: Cheng Zeng, Xia Luo

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Passenger organization has always been an essential part of China's metro operation and management. Facing the massive passenger flow, stations need to improve their intelligence and automation degree by an appropriate integrated system. Based on the existing integrated supervisory control system (ISCS) and simulation software (Anylogic), this paper designs an intelligent passenger organization system (IPOS) for metro stations. Its primary function includes passenger information acquisition, data processing and computing, visualization management, decision recommendations, and decision response based on interlocking equipment. For this purpose, the logical structure and intelligent algorithms employed are particularly devised. Besides, the structure diagram of information acquisition and application module, the application of Anylogic, the case library's function process are all given by this research. Based on the secondary development of Anylogic and existing technologies like video recognition, the IPOS is supposed to improve the response speed and address capacity in the face of emergent passenger flow of metro stations.

Keywords: anylogic software, decision-making support system, intellectualization, ISCS, passenger organization

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Authors: Xiyue Wen

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With the rapid development of the city, old communities in the city are facing a series of problems. On one hand, aging facilities, obsolete spatial patterns, aging populations arouse in the aging of the community. On the other hand, public space is reduced and is taking up by cars parking or facilities setting, which lead to the collapse of traditional life in the old communities. That is to say, modern amenities haven’t helped to reform the old community, but have leading to tedious and inefficient, when it is not accommodated in the traditional space. Exploring a way is imminent to the east the contradiction between modern living facilities and spatial patterns of traditional. We select a typical site-GeDa Community in Xi’an, built in 70-80s，and carry out a concept calling 'Raising Landscape', which enables a convenient and efficient space for parking, as well as a high-quality yard for activities. In addition, the design implements low cost, simple construction, resident participation, so that it can be spread in the same texture of urban space.

Keywords: old communities, renewal strategy, raising landscape, public space, parking space

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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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

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Authors: Parul Kapoor, Dheeraj Bhardwaj

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Delhi and other Indian cities accommodate thousands of Central Government employees in housing complexes called ‘General Pool Residential Accommodation’ (GPRA), located in prime parcels of the city. These residential colonies are now undergoing redevelopment at a massive scale, significantly impacting the ecology of the surrounding areas. Essentially, these colonies were low-rise, low-density planned developments with a dense tree cover and minimal parking requirements. But with increasing urbanisation and spike in parking demand, the proposed built form is an aggregate of high-rise gated complexes, redefining the skyline of the city which is a huge departure from the mediocre setup of Low-rise Walk-up apartments. The complexity of these developments is further aggravated by the need for parking which necessitates cutting huge number of trees to accommodate multiple layers of parking beneath the structures thus sidelining the authentic character of these areas which is laden with a dense tree cover. The aftermath of this whole process is the generation of a huge carbon footprint on the surrounding areas, which is unaccounted for, in the planning and design practice. These developments are currently planned as mix-use compounds with large commercial built-up spaces which have additional parking requirements over and above the residential parking. Also, they are perceived as gated complexes and not as neighborhood units, thus project isolated images of high-rise, dense systems with little context to the surroundings. The paper would analyze case studies of GPRA Redevelopment projects in Delhi, and the lack of relevant development control regulations which have led to abnormalities and complications in the entire redevelopment process. It would also suggest policy guidelines which can establish comprehensive codes for effective planning of these settlements.

Keywords: gated complexes, GPRA Redevelopment projects, increased densities, huge carbon footprint, mixed-use development

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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In this paper, we treat a model that falls in the area of protecting targeted systems from intelligent threats including terrorism. We introduce the concept of system survivability, in the context of continuous attacks, as the probability that a system under attack will continue operation up to some fixed time t. We define a constant attack rate (CAR) process as an attack on a targeted system that follows an exponential distribution. We consider the superposition of several CAR processes. From the attacker side, we determine the optimal attack strategy that minimizes the system survivability. We also determine the optimal strengthening strategy that maximizes the system survivability under limited defensive resources. We use operations research techniques to identify optimal strategies of each antagonist. Our results may be used as interesting starting points to develop realistic protection strategies against intentional attacks.

Keywords: CAR processes, defense/attack strategies, exponential failure, survivability

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Mohd N. Ahmad, Lariyah Mohd Sidek

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The study had shown that Sungai Penchala (urban) was experiencing localized rainfall and hazardous air pollution due to urbanization. The high rainfall that partly added by localized rain had been seen as a threat of causing the flash floods and water quality deterioration in the area. The air pollution that consisted of mainly particulate matter (PM10), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) gave an alarming air pollution index (API) to the surrounding area. Comparison among urban area (Sungai Penchala), sub-urban (Gombak), and green areas (Jerantut plus Temerloh) with respect to the rainfall parameters and air pollutants, it was found that the degree of intensities of the parameters was positively related with the urbanization. The air pollutants especially NO2, SO2, and CO were in tandem with the increase of the rainfall. Specifically, if the water catchment area is physically near to the urban area, then the authorities need to look into related urban development program by considering the management of emitted pollutants with respect to the ecological setting of the urban area.

Keywords: urbanization, green area localized rainfall, air pollution, sub-urban area

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Authors: Shivam Dwivedi, Sumit Prakash Gupta, Durga Toshniwal

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It is a challenging task in today’s date to keep defence forces in the highest state of combat readiness with budgetary constraints. A huge amount of time and money is squandered in the unnecessary and expensive traditional maintenance activities. To overcome this limitation Defence Intelligent Mission Readiness and Maintenance Scheduling System has been proposed, which ameliorates the maintenance system by diagnosing the condition and predicting the maintenance requirements. Based on new data mining algorithms, this system intelligently optimises mission readiness for imminent operations and maintenance scheduling in repair echelons. With modified data mining algorithms such as Weighted Feature Ranking Genetic Algorithm and SVM-Random Forest Linear ensemble, it improves the reliability, availability and safety, alongside reducing maintenance cost and Equipment Out of Action (EOA) time. The results clearly conclude that the introduced algorithms have an edge over the conventional data mining algorithms. The system utilizing the intelligent condition-based maintenance approach improves the operational and maintenance decision strategy of the defence force.

Keywords: condition based maintenance, data mining, defence maintenance, ensemble, genetic algorithms, maintenance scheduling, mission capability

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Authors: Shi Qi Koo, Ahmad Beng Hong Kueh

Abstract:

In the present work, the finite element formulation for the investigation of the effects of a localized interfacial degeneration on the dynamic behavior of the [90˚/0˚] laminated composite plate employing the state-space technique is performed. The stiffness of the laminate is determined by assembling the stiffnesses of sub-elements. This includes an introduction of an interface layer adopting the virtually zero-thickness formulation to model the interfacial degeneration. Also, the kinematically consistent mass matrix and proportional damping have been formulated to complete the free vibration governing expression. To simulate the interfacial degeneration of the laminate, the degenerated areas are defined from the center propagating outwards in a localized manner. It is found that the natural frequency, damped frequency and damping ratio of the plate decreases as the degenerated area of the interface increases. On the contrary, the loss factor increases correspondingly.

Keywords: dynamic finite element, localized interface degeneration, proportional damping, state-space modeling

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Authors: Ahmad Fahad Alotaibi, Khalid Hamed Hajri, Humoud Hudiban Rashidi

Abstract:

Intelligent information technology infrastructure is considered one of the enablers to enhance digital transformation in the gas and oil fields to optimize IT infrastructure reliability by supporting operations and maintenance in a safe and secure method to optimize resources. Smart IT buildings, communication rooms and shelters with intelligent technologies can strengthen the performance and profitability of gas and oil companies by ensuring business continuity. This paper describes the advantages of deploying intelligent IT infrastructure in the oil and gas industry by illustrating its positive impacts on some development aspects, for instance, operations, maintenance, safety, security and resource optimization. Moreover, it highlights the challenges and difficulties of providing smart IT services in a remote area and proposes solutions to overcome such difficulties.

Keywords: intelligent IT infrastructure, remote areas, oil and gas field, digitalization

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