Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231882
K. Cahyono, Iwan Kurnianto Wibowo, M. Bachtiar
Technological advances that occur today also have an impact on the development of technology in the world of robotics, on the world scale there is an international scale research organization called Robocup which focuses on the development of soccer robots. The RoboCup organization itself has a vision and goal to build a football robot team that will be competed with the winners of the world cup in 2050. The Robocup Competition has several divisions, one of which is the Middle Size League (MSL) which matches the wheeled soccer robot. The wheeled soccer robot itself has various abilities such as searching the ball, determining the goal point, avoiding the opponent, feed the ball to a friend s robot until the execution process kicking the ball into the opponent's goal. The ability to kick the ball is something that must be possessed by a soccer robot. The focus of this project is to create a new kicker system to be able to improve the ability to kick the ball on the wheeled soccer robot which is then controlled using the implementation of the fuzzy logic controller method, the method serves as the controller of a system or process by using fuzzy logic as a way of making decisions, so robots can kick with variations in distance and height of the ball that has been determined. The decision-making process with fuzzy logic was then given two inputs namely the falling ball distance and the height of the ball which is processed with a fuzzy logic method then produces an output power of kicking and touch angle kicker with the ball. The power of the kick is divided into 5 parts, namely very slow in the numbers 0 - 170 RPM, slow is in the numbers 180-220 RPM, middle 230-270 RPM, fast in numbers 280 - 320 RPM, and very fast in numbers 330 - 400 RPM. With maximum kick power and kicker angle of 50o produces a maximum distance of 110 cm and a maximum height of 30 cm, the minimum distance that can be taken is 10 cm and a minimum height of 1 cm with a speed of 200 RPM and kicker angle of 65o. Based on the results of testing the kick to the ball using the fuzzy logic controller method has an average error of 0.008%
{"title":"A New Kicker System of Wheeled Soccer Robot ERSOW Using Fuzzy Logic Method","authors":"K. Cahyono, Iwan Kurnianto Wibowo, M. Bachtiar","doi":"10.1109/IES50839.2020.9231882","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231882","url":null,"abstract":"Technological advances that occur today also have an impact on the development of technology in the world of robotics, on the world scale there is an international scale research organization called Robocup which focuses on the development of soccer robots. The RoboCup organization itself has a vision and goal to build a football robot team that will be competed with the winners of the world cup in 2050. The Robocup Competition has several divisions, one of which is the Middle Size League (MSL) which matches the wheeled soccer robot. The wheeled soccer robot itself has various abilities such as searching the ball, determining the goal point, avoiding the opponent, feed the ball to a friend s robot until the execution process kicking the ball into the opponent's goal. The ability to kick the ball is something that must be possessed by a soccer robot. The focus of this project is to create a new kicker system to be able to improve the ability to kick the ball on the wheeled soccer robot which is then controlled using the implementation of the fuzzy logic controller method, the method serves as the controller of a system or process by using fuzzy logic as a way of making decisions, so robots can kick with variations in distance and height of the ball that has been determined. The decision-making process with fuzzy logic was then given two inputs namely the falling ball distance and the height of the ball which is processed with a fuzzy logic method then produces an output power of kicking and touch angle kicker with the ball. The power of the kick is divided into 5 parts, namely very slow in the numbers 0 - 170 RPM, slow is in the numbers 180-220 RPM, middle 230-270 RPM, fast in numbers 280 - 320 RPM, and very fast in numbers 330 - 400 RPM. With maximum kick power and kicker angle of 50o produces a maximum distance of 110 cm and a maximum height of 30 cm, the minimum distance that can be taken is 10 cm and a minimum height of 1 cm with a speed of 200 RPM and kicker angle of 65o. Based on the results of testing the kick to the ball using the fuzzy logic controller method has an average error of 0.008%","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132687148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231673
Muhammad Adib Majdi, Bima Sena Bayu Dewantara, M. Bachtiar
Good management of the supply of products at a supermarket is crucial to help the staff working effectively. The information about product availability in real-time is needed to know when a product needs to be updated, either layout or refill So that the product is always available on the shelf when customers require it This research focuses on the display management of the product in a supermarket, which is to find out which goods are nearly empty and misplaced. We used a camera, installed in front of the rack, to capture all displayed product on the rack. Deep learning was employed to detect and recognize each product All detected products were then compared with a preconfigured product mapping that was previously prepared by the supermarket's manager. The results of the products detection and recognition are then informed to the responsible staff. The product 's existence is correct if the product matches the place of mapping. With this system, refilling products can be easier for staff and customers can easily find the items they seek. The progress in collecting image datasets, labeling them, taking pictures on shelves, and recognizing products using tiny YOLOv3 has been made. The shelf segmentation process uses virtual lines that are used horizontally to recalculate the number of product lines. The accuracy of 97.61% for product recognition and almost empty detection, 76.67% accuracy for misplacement detection.
{"title":"Product Stock Management Using Computer Vision","authors":"Muhammad Adib Majdi, Bima Sena Bayu Dewantara, M. Bachtiar","doi":"10.1109/IES50839.2020.9231673","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231673","url":null,"abstract":"Good management of the supply of products at a supermarket is crucial to help the staff working effectively. The information about product availability in real-time is needed to know when a product needs to be updated, either layout or refill So that the product is always available on the shelf when customers require it This research focuses on the display management of the product in a supermarket, which is to find out which goods are nearly empty and misplaced. We used a camera, installed in front of the rack, to capture all displayed product on the rack. Deep learning was employed to detect and recognize each product All detected products were then compared with a preconfigured product mapping that was previously prepared by the supermarket's manager. The results of the products detection and recognition are then informed to the responsible staff. The product 's existence is correct if the product matches the place of mapping. With this system, refilling products can be easier for staff and customers can easily find the items they seek. The progress in collecting image datasets, labeling them, taking pictures on shelves, and recognizing products using tiny YOLOv3 has been made. The shelf segmentation process uses virtual lines that are used horizontally to recalculate the number of product lines. The accuracy of 97.61% for product recognition and almost empty detection, 76.67% accuracy for misplacement detection.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115191406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231792
Maudy Arini Fitria Chakiki, I. Astawa, Anang Budikarso
The MIMO (Multiple Input Multiple Output) system works very well on multipath components. Some multipath components are exploited to increase bandwidth diversity and efficiency. In addition, this system also provides a significant increase in data throughput and communication coverage without expand the frequency and transmit power. Even so, this system is still vulnerable to InterSymbol Interference. Low Density Parity Check (LDPC) technique which is has the ability to correct errors near the Shannon limit (theoretical maximum error correction limit) and Maximum likelihood (ML) detection which is able to provide performance minimum bit errors are believed to be able to handle interference arising when passing through a channel.This research made a MIMO 2X2 simulation system on DVB-T2 technology with LDPC coding technique and Maximum Likelihood detector. The results obtained from running this simulation system indicate that the system which is has smaller rate is the better system. The ideal system without error correction code shows the Maximum Likelihood performance forming a waterfall curve and no more errors at 20 dB. While the system with LDPC and Maximum Likelihood is able to reaches BER (bit error rate) 10-2 at SNR (Signal to Noise Ratio) around 1 dB from the 1/2 rate system, and the 3/4 rate system reaches BER 10-2 at around 4 dB, and the 5/6 rate system reaches BER 10-2 at SNR around 6 dB.
{"title":"Performance Analysis of DVB-T2 System Based on MIMO Using Low Density Parity Check (LDPC) Code Technique and Maximum Likelihood (ML) Detection","authors":"Maudy Arini Fitria Chakiki, I. Astawa, Anang Budikarso","doi":"10.1109/IES50839.2020.9231792","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231792","url":null,"abstract":"The MIMO (Multiple Input Multiple Output) system works very well on multipath components. Some multipath components are exploited to increase bandwidth diversity and efficiency. In addition, this system also provides a significant increase in data throughput and communication coverage without expand the frequency and transmit power. Even so, this system is still vulnerable to InterSymbol Interference. Low Density Parity Check (LDPC) technique which is has the ability to correct errors near the Shannon limit (theoretical maximum error correction limit) and Maximum likelihood (ML) detection which is able to provide performance minimum bit errors are believed to be able to handle interference arising when passing through a channel.This research made a MIMO 2X2 simulation system on DVB-T2 technology with LDPC coding technique and Maximum Likelihood detector. The results obtained from running this simulation system indicate that the system which is has smaller rate is the better system. The ideal system without error correction code shows the Maximum Likelihood performance forming a waterfall curve and no more errors at 20 dB. While the system with LDPC and Maximum Likelihood is able to reaches BER (bit error rate) 10-2 at SNR (Signal to Noise Ratio) around 1 dB from the 1/2 rate system, and the 3/4 rate system reaches BER 10-2 at around 4 dB, and the 5/6 rate system reaches BER 10-2 at SNR around 6 dB.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116409536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231840
I. Syarif, Rico Fajar Afandi, Ferry Astika Saputra
High-dimensional data requires a lengthy computation time and is more difficult to model, analyze and visualize. Feature selection algorithm is needed in order to obtain the best features and eliminate irrelevant ones. In this paper, we implement a feature selection algorithm for network intrusion data, in order to detect intrusions on real time network traffic using high accuracy and real time speed. This is very difficult to do if the processed data has a very large number of features.Feature selection algorithm generally consists of two parts: attribute evaluation and search method. Attribute evaluation is the process of scoring the different feature subsets while search methods is used to propose new feature subsets. We apply a Cuckoo Search (CS) as feature selection algorithm into three intrusion datasets: KDD Cup 99, NSL-KDD and Botnet ISCX 2017. We compare the performance of the Cuckoo Search (CS) algorithm with other two Evolutionary Algorithms: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Our experiments show that CS is better than GA and PSO in reducing the number of intrusion dataset features (ISCX2017) from 79 attributes to 11 (13.9% of the original attributes). In the KDDCup '99 dataset, the CS algorithm reduces the number of attributes from 41 to 13 (31.7% of the original attribute) and in the NSL-KDD dataset, the CS algorithm reduces the number of attributes from 41 to 9 (21.9% of the original attribute). In terms of classification performance, CS is better than PSO in the ISCX2017 botnet dataset, while PSO is superior to CS and GA in the KDDCup '99 and NSL-KDD intrusion datasets.
高维数据需要较长的计算时间，并且更难以建模、分析和可视化。为了获得最佳特征并剔除不相关的特征，需要进行特征选择算法。本文实现了一种针对网络入侵数据的特征选择算法，以高精度和实时性检测实时网络流量中的入侵。如果处理的数据具有非常多的特征，这是非常困难的。特征选择算法一般包括属性评估和搜索方法两部分。属性评估是对不同的特征子集进行评分的过程，而搜索方法则是提出新的特征子集。我们将布谷鸟搜索(CS)作为特征选择算法应用于三个入侵数据集:KDD Cup 99、NSL-KDD和Botnet ISCX 2017。我们比较了布谷鸟搜索(CS)算法与其他两种进化算法:遗传算法(GA)和粒子群优化(PSO)的性能。我们的实验表明，CS在将入侵数据集特征(ISCX2017)的数量从79个属性减少到11个(原始属性的13.9%)方面优于GA和PSO。在KDDCup '99数据集中，CS算法将属性数从41个减少到13个(占原始属性的31.7%)，在NSL-KDD数据集中，CS算法将属性数从41个减少到9个(占原始属性的21.9%)。在分类性能方面，CS在ISCX2017僵尸网络数据集中优于PSO，而PSO在KDDCup '99和NSL-KDD入侵数据集中优于CS和GA。
{"title":"Feature Selection Algorithm For Intrusion Detection Using Cuckoo Search Algorithm","authors":"I. Syarif, Rico Fajar Afandi, Ferry Astika Saputra","doi":"10.1109/IES50839.2020.9231840","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231840","url":null,"abstract":"High-dimensional data requires a lengthy computation time and is more difficult to model, analyze and visualize. Feature selection algorithm is needed in order to obtain the best features and eliminate irrelevant ones. In this paper, we implement a feature selection algorithm for network intrusion data, in order to detect intrusions on real time network traffic using high accuracy and real time speed. This is very difficult to do if the processed data has a very large number of features.Feature selection algorithm generally consists of two parts: attribute evaluation and search method. Attribute evaluation is the process of scoring the different feature subsets while search methods is used to propose new feature subsets. We apply a Cuckoo Search (CS) as feature selection algorithm into three intrusion datasets: KDD Cup 99, NSL-KDD and Botnet ISCX 2017. We compare the performance of the Cuckoo Search (CS) algorithm with other two Evolutionary Algorithms: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Our experiments show that CS is better than GA and PSO in reducing the number of intrusion dataset features (ISCX2017) from 79 attributes to 11 (13.9% of the original attributes). In the KDDCup '99 dataset, the CS algorithm reduces the number of attributes from 41 to 13 (31.7% of the original attribute) and in the NSL-KDD dataset, the CS algorithm reduces the number of attributes from 41 to 9 (21.9% of the original attribute). In terms of classification performance, CS is better than PSO in the ISCX2017 botnet dataset, while PSO is superior to CS and GA in the KDDCup '99 and NSL-KDD intrusion datasets.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127432925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231634
M. U. Harun Al Rasyid, Ferry Astika Saputra, Agung Kurniawan
Thievery is the most common criminal activity. It holds the record of the most happening crime. It needs much effort to do for prevention for a place with a dense population and growing economic. One of the solutions is to implement CCTV system. However, CCTV operations suck a lot of resources such as electricity usage, storage usage, and video output supervisors. This research aim is to improve the current CCTV system by implementing Internet of Things (IoT) technology so the goal of automation and advanced data processing can be achieved. The proposed system is composed of sensor node that has implemented a motion sensor whose role is to detect movement and inform it, the gateway as the core/controller of other components, and camera node to capture images from the environment. The experiment results show that the proposed system allows being accessible from anywhere and at any time with the support of web servers that are on the internet network.
{"title":"Surveillance Monitoring System based on Internet of Things","authors":"M. U. Harun Al Rasyid, Ferry Astika Saputra, Agung Kurniawan","doi":"10.1109/IES50839.2020.9231634","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231634","url":null,"abstract":"Thievery is the most common criminal activity. It holds the record of the most happening crime. It needs much effort to do for prevention for a place with a dense population and growing economic. One of the solutions is to implement CCTV system. However, CCTV operations suck a lot of resources such as electricity usage, storage usage, and video output supervisors. This research aim is to improve the current CCTV system by implementing Internet of Things (IoT) technology so the goal of automation and advanced data processing can be achieved. The proposed system is composed of sensor node that has implemented a motion sensor whose role is to detect movement and inform it, the gateway as the core/controller of other components, and camera node to capture images from the environment. The experiment results show that the proposed system allows being accessible from anywhere and at any time with the support of web servers that are on the internet network.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127175684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231674
Risma Dian Alarmi, Ali Husein Alasiry, Novian Fajar Satria, B. Sumantri
Gait is one of the main factors in build humanoid robot. Exactly, it will be different if the humanoid robot is walking on slope. This domain problem can be overcome by shifting the center of gravity (COG) of the robot, either leaning forwards or backwards to maintain its balanced body position. In this case, tilt detection system is needed. But it is not enough, because the sensor data also have a noise. So it needs an algorithm to minimize the noise of the sensor data, which it can be solved by adding a sensor fusion algorithm. Sensor fusion has the concept of combining data from several sensors to minimize uncertainty due to the noise. The IMU (Measurement Inertia Unit) is used as a tilt detection sensor. There are accelerometer sensor and gyroscopic sensor that is used in sensor fusion algorithm of the humanoid robot. This paper implements sensor fusion algorithm in balancing the robot on the slope. The test results show the addition of the sensor fusion algorithm in reading data, gives the robot capability of walking on the slope with maximum tilt 12°.
{"title":"A Sensor Fusion Algorithm in Humanoid Robot PD Balancing Control for Walking on Slope","authors":"Risma Dian Alarmi, Ali Husein Alasiry, Novian Fajar Satria, B. Sumantri","doi":"10.1109/IES50839.2020.9231674","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231674","url":null,"abstract":"Gait is one of the main factors in build humanoid robot. Exactly, it will be different if the humanoid robot is walking on slope. This domain problem can be overcome by shifting the center of gravity (COG) of the robot, either leaning forwards or backwards to maintain its balanced body position. In this case, tilt detection system is needed. But it is not enough, because the sensor data also have a noise. So it needs an algorithm to minimize the noise of the sensor data, which it can be solved by adding a sensor fusion algorithm. Sensor fusion has the concept of combining data from several sensors to minimize uncertainty due to the noise. The IMU (Measurement Inertia Unit) is used as a tilt detection sensor. There are accelerometer sensor and gyroscopic sensor that is used in sensor fusion algorithm of the humanoid robot. This paper implements sensor fusion algorithm in balancing the robot on the slope. The test results show the addition of the sensor fusion algorithm in reading data, gives the robot capability of walking on the slope with maximum tilt 12°.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130552953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231920
Khanun Roisatul Ummah, R. Sigit, Heny Yuniarti, A. Anwar
Heart disease is still the leading cause of death in the world; therefore, a regular heart check needs to be done to find out the health of the heart. Echocardiographic tests that show heart rate movements are commonly used by doctors to analyze heart performance. Heart health conditions can be analyzed based on the movement of the heart wall and the area of the heart wall during diastolic or systolic conditions. This analysis process depends on the accuracy and observation experience of a doctor, and sometimes causes different analysis of each doctor. This study focuses on the use of a system that can track the movement of the heart wall using the Optical Flow from various points of view. First, the echocardiographic video will be captured into several frames. High boost filters and median filters are used to improve image quality. Next, the heart cavity wall will be segmented using the watershed method. After that, a good feature point is determined in the heart cavity. These good features point is the point that will be tracked. The tracking process in this research uses two methods of Optical Flow as a comparison, they are Optical Flow Lucas - Kanade and Optical Flow Farneback. Lucas-Kanade is one of the sparse Optical Flow method that can provide the flow vector of some interesting features within the frame. Whereas Farneback is one of dense Optical Flow method that tracks every pixel in a frame. Based on the experimental results of this study, with 30 data tested, the Lucas Kanade Optical Flow method has a higher average value than the Optical Flow Farneback method with the average accuracy of Optical Flow Lucas Kanade is 90.73% and an average accuracy of Optical Flow Farneback is 90.04%. In the experiment with each point of view, from 9 displacement data, Optical Flow Lucas Kanade has a higher average accuracy value than the Optical Flow Farneback.
{"title":"Tracking Multidimensional Echocardiographic Image using Optical Flow","authors":"Khanun Roisatul Ummah, R. Sigit, Heny Yuniarti, A. Anwar","doi":"10.1109/IES50839.2020.9231920","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231920","url":null,"abstract":"Heart disease is still the leading cause of death in the world; therefore, a regular heart check needs to be done to find out the health of the heart. Echocardiographic tests that show heart rate movements are commonly used by doctors to analyze heart performance. Heart health conditions can be analyzed based on the movement of the heart wall and the area of the heart wall during diastolic or systolic conditions. This analysis process depends on the accuracy and observation experience of a doctor, and sometimes causes different analysis of each doctor. This study focuses on the use of a system that can track the movement of the heart wall using the Optical Flow from various points of view. First, the echocardiographic video will be captured into several frames. High boost filters and median filters are used to improve image quality. Next, the heart cavity wall will be segmented using the watershed method. After that, a good feature point is determined in the heart cavity. These good features point is the point that will be tracked. The tracking process in this research uses two methods of Optical Flow as a comparison, they are Optical Flow Lucas - Kanade and Optical Flow Farneback. Lucas-Kanade is one of the sparse Optical Flow method that can provide the flow vector of some interesting features within the frame. Whereas Farneback is one of dense Optical Flow method that tracks every pixel in a frame. Based on the experimental results of this study, with 30 data tested, the Lucas Kanade Optical Flow method has a higher average value than the Optical Flow Farneback method with the average accuracy of Optical Flow Lucas Kanade is 90.73% and an average accuracy of Optical Flow Farneback is 90.04%. In the experiment with each point of view, from 9 displacement data, Optical Flow Lucas Kanade has a higher average accuracy value than the Optical Flow Farneback.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133318684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231951
Febby Ronaldo, D. Pramadihanto, Amang Sudarsono
Drone service is an Unmanned Aerial Vehicle (UAV) whose function is to deliver goods using air routes. Drone services sometimes have to travel long distances with a guaranteed security system to get to the customer's location and return safely to the base. But in fact, in the use of an insecure Internet of Drone (IoD) environment, there will be many attacks that try to manipulate the approximate location or interrupt transmission of data from fake nodes. Therefore, this paper focuses on a reliable data communication security system between drone services and server. Because the drone service uses a lightweight device, we propose a Hybrid cryptographic security scheme that has simple computing but a high level of security. It has layered encryption using AES- 256, ECC, and SHA256 which are provides high data authentication and encryption services for each node. The proposed scheme is efficient in terms of processing time so that it will not significantly affect the realtime sensor data from the drone. The experimental results show that the proposed system reaches 88.61 milliseconds to encrypt and decrypt messages using the Raspberry Fi device.
{"title":"Secure Communication System of Drone Service using Hybrid Cryptography over 4G/LTE Network","authors":"Febby Ronaldo, D. Pramadihanto, Amang Sudarsono","doi":"10.1109/IES50839.2020.9231951","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231951","url":null,"abstract":"Drone service is an Unmanned Aerial Vehicle (UAV) whose function is to deliver goods using air routes. Drone services sometimes have to travel long distances with a guaranteed security system to get to the customer's location and return safely to the base. But in fact, in the use of an insecure Internet of Drone (IoD) environment, there will be many attacks that try to manipulate the approximate location or interrupt transmission of data from fake nodes. Therefore, this paper focuses on a reliable data communication security system between drone services and server. Because the drone service uses a lightweight device, we propose a Hybrid cryptographic security scheme that has simple computing but a high level of security. It has layered encryption using AES- 256, ECC, and SHA256 which are provides high data authentication and encryption services for each node. The proposed scheme is efficient in terms of processing time so that it will not significantly affect the realtime sensor data from the drone. The experimental results show that the proposed system reaches 88.61 milliseconds to encrypt and decrypt messages using the Raspberry Fi device.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133537805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231796
Nadhifah Amaliah Putri Rofiva, Novita Astin, A. Nurindiyani
Lego is a colorful plastic toy that can be disassembled to the liking accordingly. In general, lego forms on the market already, with interactive Lego for Kids can create new rides for children, which can make children more creative and imagination high in making Lego shapes according to the wishes of children. Interactive Lego can also execute forward and backward using an infrared remote control connected to the Arduino inside Lego. This research aims to learn learning outcomes and describe children's intelligent through interactive games can be used as a medium to develop cognitive abilities and motor abilities in children.
{"title":"The Development Of Interactive Lego For Kids","authors":"Nadhifah Amaliah Putri Rofiva, Novita Astin, A. Nurindiyani","doi":"10.1109/IES50839.2020.9231796","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231796","url":null,"abstract":"Lego is a colorful plastic toy that can be disassembled to the liking accordingly. In general, lego forms on the market already, with interactive Lego for Kids can create new rides for children, which can make children more creative and imagination high in making Lego shapes according to the wishes of children. Interactive Lego can also execute forward and backward using an infrared remote control connected to the Arduino inside Lego. This research aims to learn learning outcomes and describe children's intelligent through interactive games can be used as a medium to develop cognitive abilities and motor abilities in children.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133804389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Exam cheating one of the most critical problems of inefficiency and unproductiveness that continuing from primary education to the latest stages of higher education. To overcome the number of test cheating, a system is needed to detect fraud in the exam. In this research, a system was made to detect the exam participants’ movement using the background subtraction method. Movements are classified based on what is considered reasonable, and movements that are considered suspicious during the exam. The results of testing the success of 96% were obtained.
{"title":"Implementation of Background Subtraction Method to Detect Movement of Examination Participants","authors":"Yulistia Khoirotul Aini, Akuwan Saleh, Haryadi Amran Darwito","doi":"10.1109/IES50839.2020.9231922","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231922","url":null,"abstract":"Exam cheating one of the most critical problems of inefficiency and unproductiveness that continuing from primary education to the latest stages of higher education. To overcome the number of test cheating, a system is needed to detect fraud in the exam. In this research, a system was made to detect the exam participants’ movement using the background subtraction method. Movements are classified based on what is considered reasonable, and movements that are considered suspicious during the exam. The results of testing the success of 96% were obtained.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115560604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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