Search results for: camera network

Authors: Kang Won Lee, Jung Won Lee

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Characterizing the network flow is of fundamental importance to understand the complex dynamics of networks. And passenger flow characteristics of the subway network are very relevant for an effective transportation management in urban cities. In this study, passenger flow of Seoul metropolitan subway network is investigated and characterized through statistical analysis. Traditional betweenness centrality measure considers only topological structure of the network and ignores the transportation factors. This paper proposes a weighted betweenness centrality measure that incorporates monthly passenger flow volume. We apply the proposed measure on the Seoul metropolitan subway network involving 493 stations and 16 lines. Several interesting insights about the network are derived from the new measures. Using Kolmogorov-Smirnov test, we also find out that monthly passenger flow between any two stations follows a power-law distribution and other traffic characteristics such as congestion level and throughflow traffic follow exponential distribution.

Keywords: betweenness centrality, correlation coefficient, power-law distribution, Korea traffic DB

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Authors: Nisarg A. Patel, Hiren B. Patel

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Quantum cryptography is described as a point-to-point secure key generation technology that has emerged in recent times in providing absolute security. Researchers have started studying new innovative approaches to exploit the security of Quantum Key Distribution (QKD) for a large-scale communication system. A number of approaches and models for utilization of QKD for secure communication have been developed. The uncertainty principle in quantum mechanics created a new paradigm for QKD. One of the approaches for use of QKD involved network fashioned security. The main goal was point-to-point Quantum network that exploited QKD technology for end-to-end network security via high speed QKD. Other approaches and models equipped with QKD in network fashion are introduced in the literature as. A different approach that this paper deals with is using QKD in existing protocols, which are widely used on the Internet to enhance security with main objective of unconditional security. Our work is towards the analysis of the QKD in Mobile ad-hoc network (MANET).

Keywords: cryptography, networking, quantum, encryption and decryption

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: Bohuslava Juhasova, Igor Halenar, Martin Juhas

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The wireless communication is one of the widely used methods of data transfer at the present days. The benefit of this communication method is the partial independence of the infrastructure and the possibility of mobility. In some special applications it is the only way how to connect. This paper presents some problems in the implementation of a sensor network connection for measuring environmental parameters in the area of manufacturing plants.

Keywords: network, communication, reliability, sensors

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Authors: Ali Vaezi, Jyotirmoy Dalal, Manish Verma

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The railroad is one of the primary transportation modes for hazardous materials (hazmat) shipments in North America. Installing an emergency response network capable of providing a commensurate response is one of the primary levers to contain (or mitigate) the adverse consequences from rail hazmat incidents. To this end, we propose a two-stage stochastic program to determine the location of and equipment packages to be stockpiled at each response facility. The raw input data collected from publicly available reports were processed, fed into the proposed optimization program, and then tested on a realistic railroad network in Ontario (Canada). From the resulting analyses, we conclude that the decisions based only on empirical datasets would undermine the effectiveness of the resulting network; coverage can be improved by redistributing equipment in the network, purchasing equipment with higher containment capacity, and making use of a disutility multiplier factor.

Keywords: hazmat, rail network, stochastic programming, emergency response

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Authors: Sonia Sassi, Mostapha Tarfaoui, Hamza Ben Yahia

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In this investigation, an experimental technique in which the dynamic response, damage kinetic and heat dissipation are measured simultaneously during high strain rates on adhesively bonded joints materials. The material used in this study is widely used in the design of structures for military applications. It was composed of a 45° Bi-axial fiber-glass mat of 0.286 mm thickness in a Polyester resin matrix. In adhesive bonding, a NORPOL Polyvinylester of 1 mm thickness was used to assemble the composite substrate. The experimental setup consists of a compression Split Hopkinson Pressure Bar (SHPB), a high-speed infrared camera and a high-speed Fastcam rapid camera. For the dynamic compression tests, 13 mm x 13 mm x 9 mm samples for out-of-plane tests were considered from 372 to 1030 s-1. Specimen surface is controlled and monitored in situ and in real time using the high-speed camera which acquires the damage progressive in specimens and with the infrared camera which provides thermal images in time sequence. Preliminary compressive stress-strain vs. strain rates data obtained show that the dynamic material strength increases with increasing strain rates. Damage investigations have revealed that the failure mainly occurred in the adhesive/adherent interface because of the brittle nature of the polymeric adhesive. Results have shown the dependency of the dynamic parameters on strain rates. Significant temperature rise was observed in dynamic compression tests. Experimental results show that the temperature change depending on the strain rate and the damage mode and their maximum exceed 100 °C. The dependence of these results on strain rate indicates that there exists a strong correlation between damage rate sensitivity and heat dissipation, which might be useful when developing damage models under dynamic loading tacking into account the effect of the energy balance of adhesively bonded joints.

Keywords: adhesive bonded joints, Hopkinson bars, out-of-plane tests, dynamic compression properties, damage mechanisms, heat dissipation

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Authors: Ivan Belik, Kurt Jornsten

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We construct the coauthorship network based on the scientific collaboration between the faculty members at the Norwegian School of Economics (NHH) and based on their international academic publication experience. The network structure is based on the NHH faculties’ publications recognized by the ISI Web of Science for the period 1950 – Spring, 2014. The given network covers the publication activities of the NHH faculty members (over six departments) based on the information retrieved from the ISI Web of Science in Spring, 2014. In this paper we analyse the constructed coauthorship network in different aspects of the theory of social networks analysis.

Keywords: coauthorship networks, social networks analysis, Norwegian School of Economics, ISI

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Authors: Supriya H. S., Chandrakala B. M.

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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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Authors: Navdeep Singh Randhawa, Shally Sharma

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Wireless Sensor Network is an autonomous technology emanating in the current scenario at a fast pace. This technology faces a number of defiance’s and energy management is one of them, which has a huge impact on the network lifetime. To sustain energy the different types of routing protocols have been flourished. The classical routing protocols are no more compatible to perform in complicated environments. Hence, in the field of routing the intelligent algorithms based on nature systems is a turning point in Wireless Sensor Network. These nature-based algorithms are quite efficient to handle the challenges of the WSN as they are capable of achieving local and global best optimization solutions for the complex environments. So, the main attention of this paper is to develop a routing algorithm based on some swarm intelligent technique to enhance the performance of Wireless Sensor Network.

Keywords: wireless sensor network, routing, swarm intelligence, MPRSO

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Authors: Svitov David, Alyamkin Sergey

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The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax

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Authors: Anurag Sharma, Manoj Kumar, Ashima, Sooraj Parkash

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The work in this paper presents simulative comparison for different modulation formats such as NRZ, Manchester and CRZ in a 100 subscribers at 5 Gbps bit rate Gigabit Ethernet Passive Optical Network (GEPON) FTTH network. It is observed from the simulation results that the CRZ modulation format is best suited for the designed system. A link design for 1:100 splitter is used as Passive Optical Network (PON) element which creates communication between central offices to different users. The Bit Error Rate (BER) is found to be 2.8535e-10 at 5 Gbit/s systems for CRZ modulation format.

Keywords: PON , FTTH, OLT, ONU, CO, GEPON

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Authors: Tushar Bhardwaj

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Internet of Things (IoT) possesses a dynamic network where the network nodes (mobile devices) are added and removed constantly and randomly, hence the traffic distribution in the network is quite variable and irregular. The basic but very important part in any network is route searching. We have many conventional route searching algorithms like link-state, and distance vector algorithms but they are restricted to the static point to point network topology. In this paper we propose a model that uses the Ant Colony Algorithm for route searching. It is dynamic in nature and has positive feedback mechanism that conforms to the route searching. We have also embedded the concept of Non-Deterministic Finite Automata [NDFA] minimization to reduce the network to increase the performance. Results show that Ant Colony Algorithm gives the shortest path from the source to destination node and NDFA minimization reduces the broadcasting storm effectively.

Keywords: routing, ant colony algorithm, NDFA, IoT

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Authors: Shehnila Kanwal

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Murree-Kotli Sattian-Kahta National Park (MKKNP) was declared in 2009. However, not much is known about the diversity and relative abundance of the mammalian fauna of this park. In the current study, we used field sign survey and infrared camera trapping techniques to get an insight into the diversity of mammalian species and their relative abundance. We conducted field surveys in different areas of the park at various elevations from April 2023 up to March 2024 to record the field signs (scats, pug marks etc.) of the mammals’ species; in addition, we deployed a total of 22 infrared trail camera traps in different areas of the park, for 116 nights. We obtained a total of 5201 photographs using camera trapping. Results of camera trapping coupled with field sign surveys confirmed the presence of a total of twenty-one different mammalian species (large, meso and small mammals) recorded in the study area. The common leopard was recorded at four different sites in the park, with an altitudinal range between 648m-1533m. Distribution of Asiatic jackal and a red fox was recorded positive at all the sites surveyed in the park with an altitudinal range between 498m-1287m and 433m-2049m, respectively. Leopard cats were recorded at two different sites within the altitudinal range between 498m-894m. Jungle cat was recorded at three sites within an altitudinal range between 498m-846. Asian palm civets and small Indian civets were both recorded at three sites. Grey mongoose and small Indian mongoose were recorded at four and three sites. We also collected a total of 75 scats of different mammal species in the park to further confirm their occurrence. For the Indian pangolin, we recorded three field burrows at two different sites. Diversity index (H’=2.369960) and species evenness (E=0.81995) were calculated. Analysis of data revealed that wild boar (Sus sucrofa) was the most abundant species in the park; most of the mammal species were found nocturnal; these remain active from dusk throughout the night, and some of them remain active at dawn time. Leopard and Asian palm civets were highly overlapping species in the study area. Their temporal activity pattern overlapped 61%. Barking deer and Indian crested porcupine were also found to be nocturnal species they remained active throughout the night.

Keywords: MKKNP, diversity, abundance, evenness, distribution, mammals, overlapped

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Authors: Daniel Pastor, Hyo-Sang Shin

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This paper presents a novel method to use optical flow navigation for long-term navigation. Unlike standard SLAM approaches for augmented reality, OFLAAM is designed for Micro Air Vehicles (MAV). It uses an optical flow camera pointing downwards, an IMU and a monocular camera pointing frontwards. That configuration avoids the expensive mapping and tracking of the 3D features. It only maps these features in a vocabulary list by a localization module to tackle the loss of the navigation estimation. That module, based on the well-established algorithm DBoW2, will be also used to close the loop and allow long-term navigation in confined areas. That combination of high-speed optical flow navigation with a low rate localization algorithm allows fully autonomous navigation for MAV, at the same time it reduces the overall computational load. This framework is implemented in ROS (Robot Operating System) and tested attached to a laptop. A representative scenarios is used to analyse the performance of the system.

Keywords: vision, UAV, navigation, SLAM

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Authors: Moataz Ammar, Ahdab Elmorshedy

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The distributed generation hosting capacity of a distribution network is typically limited at a given connection point by the upper voltage limit that can be violated due to the injection of active power into the distribution network. The upper voltage limit violation concern becomes more important as the network equivalent resistance increases with respect to its equivalent reactance. This paper investigates the impact of modifying the distribution network equivalent reactance at the point of connection such that the upper voltage limit is violated at a higher distributed generation penetration, than it would without the addition of series reactive compensation. The results show that series reactive compensation proves efficient in certain situations (based on the ratio of equivalent network reactance to equivalent network resistance at the point of connection). As opposed to the conventional case of capacitive compensation of a distribution network to reduce voltage drop, inductive compensation is seen to be more appropriate for alleviation of distributed-generation-induced voltage rise.

Keywords: distributed generation, distribution networks, series compensation, voltage rise

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Authors: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez

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The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.

Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB

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Authors: Tariq A. El Shheibia, Halima Mohamed Belhamad

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This paper is considered securing data based on multi-path protocol (SDMP) in mobile ad hoc network utilizing OPNET simulator modular 14.5, including the AODV routing protocol at the network as based multi-path algorithm for message security in MANETs. The main idea of this work is to present a way that is able to detect the attacker inside the MANETs. The detection for this attacker will be performed by adding some effective parameters to the network.

Keywords: MANET, AODV, malicious node, OPNET

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Authors: Muazzam A. Khan

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In order to avoid dangerous environmental disasters, robots are being recognized as good entrants to step in as human rescuers. Robots has been gaining interest of many researchers in rescue matters especially which are furnished with advanced sensors. In distributed wireless robot system main objective for a rescue system is to track the location of the object continuously. This paper provides a novel idea to track and locate human in disaster area using stereo vision system and ZigBee technology. This system recursively predict and updates 3D coordinates in a robot coordinate camera system of a human which makes the system cost effective. This system is comprised of ZigBee network which has many advantages such as low power consumption, self-healing low data rates and low cost.

Keywords: stereo vision, segmentation, classification, human tracking, ZigBee module

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Authors: Rei-Heng Cheng, Wen-Pinn Fang

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A wireless sensor network (WSN) is composed by a large number of sensors and one or a few base stations, where the sensor is responsible for detecting specific event information, which is sent back to the base station(s). However, how to save electricity consumption to extend the network lifetime is a problem that cannot be ignored in the wireless sensor networks. Since the sensor network is used to monitor a region or specific events, how the information can be reliably sent back to the base station is surly important. Network coding technique is often used to enhance the reliability of the network transmission. When a node needs to send out M data packets, it encodes these data with redundant data and sends out totally M + R packets. If the receiver can get any M packets out from these M + R packets, it can decode and get the original M data packets. To transmit redundant packets will certainly result in the excess energy consumption. This paper will explore relationship between the quality of wireless transmission and the number of redundant packets. Hopefully, each sensor can overhear the nearby transmissions, learn the wireless transmission quality around it, and dynamically determine the number of redundant packets used in network coding.

Keywords: energy consumption, network coding, transmission reliability, wireless sensor networks

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Authors: Wang Xue, Fan Liwei

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The trust and use of social network platforms by users are instrumental factors that contribute to the platform’s sustainable development. Studying the influential factors of the use of social network platforms is beneficial for developing and maintaining a large user base. This study constructed an extended unified theory of acceptance and use of technology (UTAUT2) moderating model with perceived privacy risks to analyze the factors affecting the trust and use of social network platforms. 444 participants completed our 35 surveys, and we verified the survey results by structural equation model. Empirical results reveal the influencing factors that affect the trust and use of social network platforms, and the extended UTAUT2 model with perceived privacy risks increases the applicability of UTAUT2 in social network scenarios. Social networking platforms can increase their use rate by increasing the economics, functionality, entertainment, and privacy security of the platform.

Keywords: perceived privacy risk, social network, trust, use, UTAUT2 model

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Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

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Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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Authors: Yichao Lv, Minmin Cai, Yanqiang Tao, Xinyuan Zou, Chao Zhang, Xiangping Liu

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Objective: This study aims to explore the network structure of personality traits and mental health and identify key factors for effective intervention strategies. Methods: All participants (N = 6,067; 3,368 females) underwent the Eysenck Personality Scale (EPQ) to measure personality traits and the Symptom Self-rating Scale (SCL-90) to measure psychiatric symptoms. Using the mean value of the SCL-90 total score plus one standard deviation as the cutoff, 854 participants (14.08%; 528 females) were categorized as individuals exhibiting potential psychological symptoms and were included in the follow-up network analysis. The structure and bridge centrality of the network for dimensions of EPQ and SCL-90 were estimated. Results: Between the EPQ and SCL-90, psychoticism (P), extraversion (E), and neuroticism (N) showed the strongest positive correlations with somatization (Som), interpersonal sensitivity (IS), and hostility (Hos), respectively. Extraversion (E), somatization (Som), and anxiety (Anx) were identified as the most important bridge factors influencing the overall network. Conclusions: This study explored the network structure and complex connections between mental health and personality traits from a network perspective, providing potential targets for intervening in adolescent personality traits and mental health.

Keywords: EPQ, SCL-90, Chinese adolescents, network analysis

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Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

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The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

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Authors: Ebenezer Obaloluwa Olaniyi

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In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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Authors: Ege Can Onal, Enver Ersen, Meltem Elitas

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Laparoscopy is a surgical operation, well known as keyhole surgery. The operation is performed through small holes, hence, scars of a patient become much smaller, patients can recover in a short time and the hospital stay becomes shorter in comparison to an open surgery. Several tools are used at laparoscopic operations; among them, the laparoscope has a crucial role. It provides the vision during the operation, which will be the main focus in here. Since the operation area is very small, motion of the surgical tools might be limited in laparoscopic operations compared to traditional surgeries. To overcome this limitation, most of the laparoscopic tools have become more precise, dexterous, multi-functional or automated. Here, we present a robotic-assisted laparoscope that is controlled with pedals directly by a surgeon. Thus, the movement of the laparoscope might be controlled better, so there will not be a need to calibrate the camera during the operation. The need for an assistant that controls the movement of the laparoscope will be eliminated. The duration of the laparoscopic operation might be shorter since the surgeon will directly operate the camera.

Keywords: laparoscope, laparoscopy, low-cost, minimally invasive surgery, robotic-assisted surgery

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Authors: Ji-Hoon Hong, Dong-Hee Kim, Nam-Uk Kim, Tai-Myoung Chung

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Smartphone users are increasing rapidly. Accordingly, many companies are running BYOD (Bring Your Own Device: Policies to bring private-smartphones to the company) policy to increase work efficiency. However, smartphones are always under the threat of malware, thus the company network that is connected smartphone is exposed to serious risks. Most smartphone malware detection techniques are to perform an independent detection (perform the detection of a single target application). In this paper, we analyzed a variety of intrusion detection techniques. Based on the results of analysis propose an agent using the network IDS.

Keywords: android malware detection, software-defined network, interaction environment, android malware detection, software-defined network, interaction environment

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Authors: Alireza Alesaadi

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Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed.

Keywords: reliability, adaptive genetic algorithm, electrical network, communication engineering

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Authors: Katherine Carl Payne, Moshe Dror

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The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes.

Keywords: topograph, RPE, routing, GIS

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Authors: Borhan Marzougui

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Road and Transport Authority (RTA) is moving ahead with the implementation of the leader’s vision in exploring all avenues that may bring better security and safety services to the community. Smart transport means using smart technologies such as IoT (Internet of Things). This technology continues to affirm its important role in the context of Information and Transportation Systems. In fact, IoT is a network of Internet-connected objects able to collect and exchange different data using embedded sensors. With the growth of IoT, Distributed Denial of Service (DDoS) attacks is also growing exponentially. DDoS attacks are the major and a real threat to various transportation services. Currently, the defense mechanisms are mainly passive in nature, and there is a need to develop a smart technique to handle them. In fact, new IoT devices are being used into a botnet for DDoS attackers to accumulate for attacker purposes. The aim of this paper is to provide a relevant understanding of dangerous types of DDoS attack related to IoT and to provide valuable guidance for the future IoT security method. Our methodology is based on development of the distributed algorithm. This algorithm manipulates dedicated intelligent and cooperative agents to prevent and to mitigate DDOS attacks. The proposed technique ensure a preventive action when a malicious packets start to be distributed through the connected node (Network of IoT devices). In addition, the devices such as camera and radio frequency identification (RFID) are connected within the secured network, and the data generated by it are analyzed in real time by intelligent and cooperative agents. The proposed security system is based on a multi-agent system. The obtained result has shown a significant reduction of a number of infected devices and enhanced the capabilities of different security dispositives.

Keywords: IoT, DDoS, attacks, botnet, security, agents

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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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