Pub Date : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350784
Ahmad Andi Akmal Almafaluti, S. M. S. Nugroho, M. Purnomo
Islamic Boarding Schools (pesantren in Indonesian language) often need government funding grants for improving education services, i.e. rehabilitation aid. Many affecting variables such as the number of student, pesantren activity type, and infrastructure condition need further examination, in addition to the large number of institutions. Because of those complex variables and the absence of definite variables pattern about correlation with the target classes, this research proposed two neural network based model for classifying beneficiaries to determine rehabilitation aid for the pesantren institutions and compared which is the best. 15 input variables were used as the features in learning model are accordance with 4 target classes. Neural Network formed from the learning process can generate new data classification as much as 100% for Backpropagation with accuration value 0.5, and 94.45489% for Radial Basis Function with accuration value 0.428571429.
{"title":"Classifying beneficiaries of islamic boarding school rehabilitation aid based on neural network approaches: A case of the religious affair ministry of East Java, Indonesia","authors":"Ahmad Andi Akmal Almafaluti, S. M. S. Nugroho, M. Purnomo","doi":"10.1109/ICOIACT.2018.8350784","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350784","url":null,"abstract":"Islamic Boarding Schools (pesantren in Indonesian language) often need government funding grants for improving education services, i.e. rehabilitation aid. Many affecting variables such as the number of student, pesantren activity type, and infrastructure condition need further examination, in addition to the large number of institutions. Because of those complex variables and the absence of definite variables pattern about correlation with the target classes, this research proposed two neural network based model for classifying beneficiaries to determine rehabilitation aid for the pesantren institutions and compared which is the best. 15 input variables were used as the features in learning model are accordance with 4 target classes. Neural Network formed from the learning process can generate new data classification as much as 100% for Backpropagation with accuration value 0.5, and 94.45489% for Radial Basis Function with accuration value 0.428571429.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"9 1","pages":"454-459"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86931252","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 : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350750
N. Hassan, H. Zamzuri, M. Ariff
This paper presents a modelling approach of human driving behavior in emergency rear-end collision avoidance focusing on steering maneuver. The target scenario is set up under real experimental environment and the naturalistic data from the experiment are collected. Dynamic Artificial Neural Network which is Focused Time Delay Neural Network (FTDNN) is used to model drivers steering behaviour. From the obtain results, it can be concluded that the FTDNN model able to simulate drivers steering maneuver in rear-end collision avoidance with the accuracy of which the coefficient determination is 99% (0.99). With further study, this model would beneficial to design motion control strategy to improve Advance Driver Assistance System (ADAS) in collision avoidance system.
{"title":"Modelling of driver's steering behaviour control in emergency collision avoidance by using focused time delay neural network","authors":"N. Hassan, H. Zamzuri, M. Ariff","doi":"10.1109/ICOIACT.2018.8350750","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350750","url":null,"abstract":"This paper presents a modelling approach of human driving behavior in emergency rear-end collision avoidance focusing on steering maneuver. The target scenario is set up under real experimental environment and the naturalistic data from the experiment are collected. Dynamic Artificial Neural Network which is Focused Time Delay Neural Network (FTDNN) is used to model drivers steering behaviour. From the obtain results, it can be concluded that the FTDNN model able to simulate drivers steering maneuver in rear-end collision avoidance with the accuracy of which the coefficient determination is 99% (0.99). With further study, this model would beneficial to design motion control strategy to improve Advance Driver Assistance System (ADAS) in collision avoidance system.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"67 1","pages":"730-734"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87262971","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 : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350801
T. Badriyah, Sefryan Azvy, Wiratmoko Yuwono, I. Syarif
Development of technology causes many business industries to migrate from offline business systems to the e-commerce world. One of the most popular e-commerce frequented by potential buyers is the property site. Considering that the property is one of the essential requirements for living, and furthermore it is also one of the most prized assets one can have. In this research, we develop a web-based recommendation system in choosing a property using content-based filtering method. The recommendation system provides property information based on user behavior by searching advertising content previously searched by the user. Each time the user selects the contents of the ad to display, this information will be stored into the database to be processed further in order to provide a recommendation. The application system will present the same product recommendation, in accordance to the profile / criteria and preference of the prospective buyer. Therefore, the recommendation system will assist prospective buyers in determining the choice of property product they want to buy, and this process can be provided by the recommendation system in a short time.
{"title":"Recommendation system for property search using content based filtering method","authors":"T. Badriyah, Sefryan Azvy, Wiratmoko Yuwono, I. Syarif","doi":"10.1109/ICOIACT.2018.8350801","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350801","url":null,"abstract":"Development of technology causes many business industries to migrate from offline business systems to the e-commerce world. One of the most popular e-commerce frequented by potential buyers is the property site. Considering that the property is one of the essential requirements for living, and furthermore it is also one of the most prized assets one can have. In this research, we develop a web-based recommendation system in choosing a property using content-based filtering method. The recommendation system provides property information based on user behavior by searching advertising content previously searched by the user. Each time the user selects the contents of the ad to display, this information will be stored into the database to be processed further in order to provide a recommendation. The application system will present the same product recommendation, in accordance to the profile / criteria and preference of the prospective buyer. Therefore, the recommendation system will assist prospective buyers in determining the choice of property product they want to buy, and this process can be provided by the recommendation system in a short time.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"52 1","pages":"25-29"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89398455","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 : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350808
A. Rahman, R. Sarno, Yutika Amelia Effendi
The services of port in Indonesia are increasing from year to year. The traffic of port is increasingly crowded with the number of boats coming to load and unload processes. A lot of ship queues result in delay when exceeding due date from the date of the agreement will cause the higher cost to be issued which is called demurrage. To reduce the costs incurred and the length of queue time on the scheduling at the port, we used Goal Programming (GP). Goal Programming is an algorithm that solves linear programming problems using mathematical formulation to get solutions in getting goals. In this study, optimizing 43 activities and 7 trace variations on loading and unloading activities of container terminal services from events log. The goal programming model from 43 activities has been implemented using Lingo software to obtain objective value in achieving the objectives of each activity used to determine activities that have a major influence on the delay in loading and unloading activities. The result of Goal Programming is that there are two activities which have very high deviation, therefore both of activities are evaluated in performance on container activity.
{"title":"Goal programming to optimize time and cost for each activity in port container handling","authors":"A. Rahman, R. Sarno, Yutika Amelia Effendi","doi":"10.1109/ICOIACT.2018.8350808","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350808","url":null,"abstract":"The services of port in Indonesia are increasing from year to year. The traffic of port is increasingly crowded with the number of boats coming to load and unload processes. A lot of ship queues result in delay when exceeding due date from the date of the agreement will cause the higher cost to be issued which is called demurrage. To reduce the costs incurred and the length of queue time on the scheduling at the port, we used Goal Programming (GP). Goal Programming is an algorithm that solves linear programming problems using mathematical formulation to get solutions in getting goals. In this study, optimizing 43 activities and 7 trace variations on loading and unloading activities of container terminal services from events log. The goal programming model from 43 activities has been implemented using Lingo software to obtain objective value in achieving the objectives of each activity used to determine activities that have a major influence on the delay in loading and unloading activities. The result of Goal Programming is that there are two activities which have very high deviation, therefore both of activities are evaluated in performance on container activity.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"57 1","pages":"866-871"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85959426","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 : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350728
Sitti Wetenriajeng Sidehabi, A. Suyuti, I. Areni, I. Nurtanio
This purpose of this study is to identify the level of ripeness of the passion fruit. The levels are classified into three distinguished stages: fruit in a ripe stage, a nearly ripe stage, and an unripe stage. The passion fruit-sorting system with artificial intelligence is an innovation of fruit sorting technology for industrial markets because it is very cost efficient and effective for a large production process instead of relying on manual labor process. The method used in this research is K-Means Clustering to perform passion fruit segmentation and Artificial Neural Network for classification based on RGB and A features. The input data is passion fruit video from 6 different sides. This study uses 75 passion fruit videos as training data and 20 videos as data testing with duration 5 seconds per video. The result achieves system accuracy of 90% with classification errors occur in the nearly ripe and unripe fruit due to the color closeness.
{"title":"Classification on passion fruit's ripeness using K-means clustering and artificial neural network","authors":"Sitti Wetenriajeng Sidehabi, A. Suyuti, I. Areni, I. Nurtanio","doi":"10.1109/ICOIACT.2018.8350728","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350728","url":null,"abstract":"This purpose of this study is to identify the level of ripeness of the passion fruit. The levels are classified into three distinguished stages: fruit in a ripe stage, a nearly ripe stage, and an unripe stage. The passion fruit-sorting system with artificial intelligence is an innovation of fruit sorting technology for industrial markets because it is very cost efficient and effective for a large production process instead of relying on manual labor process. The method used in this research is K-Means Clustering to perform passion fruit segmentation and Artificial Neural Network for classification based on RGB and A features. The input data is passion fruit video from 6 different sides. This study uses 75 passion fruit videos as training data and 20 videos as data testing with duration 5 seconds per video. The result achieves system accuracy of 90% with classification errors occur in the nearly ripe and unripe fruit due to the color closeness.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"54 1","pages":"304-309"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80426209","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 : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350744
Y. Yamasari, S. M. S. Nugroho, R. Harimurti, M. Purnomo
In the student clustering, the high cluster validity is very important because of this cause clarity a student in a cluster. Furthermore, it becomes easier for a teacher to do the best learning process. This paper focuses on the improvement of cluster validity applied by a suitable feature selection method, especially student's psychomotor domain. Here, we propose the feature selection by the random method. In addition, we apply k-means as the popular clustering method in educational data mining by the two initial of cluster center point: k-means++ and random. For cluster evaluation stage, silhouette coefficient is used on Manhattan distance. The experimental result indicates that feature selection is able to enhance the cluster validity which has shown that our methods have higher silhouette value than original k-means. In terms of the maximum silhouette value, our method can reach higher than original_kmeans++ and original_random on average 0.033–0.106. In terms of the minimum silhouette value, our method can achieve higher than original_kmeans++ and original_random on average 0.123–0.240.
{"title":"Improving the cluster validity on student's psychomotor domain using feature selection","authors":"Y. Yamasari, S. M. S. Nugroho, R. Harimurti, M. Purnomo","doi":"10.1109/ICOIACT.2018.8350744","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350744","url":null,"abstract":"In the student clustering, the high cluster validity is very important because of this cause clarity a student in a cluster. Furthermore, it becomes easier for a teacher to do the best learning process. This paper focuses on the improvement of cluster validity applied by a suitable feature selection method, especially student's psychomotor domain. Here, we propose the feature selection by the random method. In addition, we apply k-means as the popular clustering method in educational data mining by the two initial of cluster center point: k-means++ and random. For cluster evaluation stage, silhouette coefficient is used on Manhattan distance. The experimental result indicates that feature selection is able to enhance the cluster validity which has shown that our methods have higher silhouette value than original k-means. In terms of the maximum silhouette value, our method can reach higher than original_kmeans++ and original_random on average 0.033–0.106. In terms of the minimum silhouette value, our method can achieve higher than original_kmeans++ and original_random on average 0.123–0.240.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"84 1","pages":"460-465"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82405694","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 : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350709
Yuda Dian Harja, R. Sarno
Medical service has become important aspect nowadays. When we have an emergency condition, we are often confronted with unknown variables such as travel distance and time of the medical services near us. This paper aims to develop a location-based service for medical purpose, which considers two major variables: travel distance and time. This system is using Haversine algorithm to find medical services around us within a certain radius. Then using Google Map API to calculate travel distance and time. TOPSIS algorithm is used to determine the best option for the results. By using this method, the whole system shows this research result give better method in decision making over previous studies.
{"title":"Determine the best option for nearest medical services using Google maps API, Haversine and TOPSIS algorithm","authors":"Yuda Dian Harja, R. Sarno","doi":"10.1109/ICOIACT.2018.8350709","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350709","url":null,"abstract":"Medical service has become important aspect nowadays. When we have an emergency condition, we are often confronted with unknown variables such as travel distance and time of the medical services near us. This paper aims to develop a location-based service for medical purpose, which considers two major variables: travel distance and time. This system is using Haversine algorithm to find medical services around us within a certain radius. Then using Google Map API to calculate travel distance and time. TOPSIS algorithm is used to determine the best option for the results. By using this method, the whole system shows this research result give better method in decision making over previous studies.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"70 1","pages":"814-819"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77398762","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 : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350717
Aziz Fajar, R. Sarno, A. Fauzan
Event log obtained from Port Container Terminal (PCT) Surabaya is an asynchronous event log. This event log needs to be run in a simulation to reflect the real world performance which contains both time and cost. From the event log we gathered, we use forecast methods to predict the number of container for the following month. Several forecasting methods are evaluated; whereas discrete event simulation and agent based simulation are compared to handle asynchronous processes. The results of the experiments show that moving average have the lowest MSE compared to other forecast methods such as Simple Exponential Smoothing, Double Exponential Smoothing, and Linear Regression. Then, from the forecast results we successfully generate the event log for the following month and simulate it using agent based simulation and Discrete Event Simulation. The results of the simulation show that agent based simulation can handle the communication process which discrete event simulation cannot handle. Both the simulation results are depicted in Gantt charts.
{"title":"Comparison of discrete event simulation and agent based simulation for evaluating the performance of port container terminal","authors":"Aziz Fajar, R. Sarno, A. Fauzan","doi":"10.1109/ICOIACT.2018.8350717","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350717","url":null,"abstract":"Event log obtained from Port Container Terminal (PCT) Surabaya is an asynchronous event log. This event log needs to be run in a simulation to reflect the real world performance which contains both time and cost. From the event log we gathered, we use forecast methods to predict the number of container for the following month. Several forecasting methods are evaluated; whereas discrete event simulation and agent based simulation are compared to handle asynchronous processes. The results of the experiments show that moving average have the lowest MSE compared to other forecast methods such as Simple Exponential Smoothing, Double Exponential Smoothing, and Linear Regression. Then, from the forecast results we successfully generate the event log for the following month and simulate it using agent based simulation and Discrete Event Simulation. The results of the simulation show that agent based simulation can handle the communication process which discrete event simulation cannot handle. Both the simulation results are depicted in Gantt charts.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"208 1","pages":"259-265"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77418411","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 : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350691
Irfani Zuhrufillah, Farikhin, R. Isnanto
In Indonesia, the performance evaluation of Civil Servant is assessed based on SKP and Work Behavior. The proposed evaluation system is focusing on work behavior of civil servants through evaluating the subcriteria against the main criteria for each employee. The DEAHP model as a tool for the formation of multicriteria hierarchies and determining the weights by using efficient and inefficient of each alternative. DEAHP alone is not enough to earn the objective assessment so that the proposed using the 360-degree Feedback technique as a multi evaluator technique combined with DEAHP, this makes the evaluation more powerful. In the final process of DEA, in this case, proposed to aggregate by summing the subcriteria value against the main criteria on each DMU to obtain the final rank of the employee. At the final result generated rank data for each subcriteria and main criteria of each DMU. This performance evaluation has the lowest score for the main criteria is 13.6% and the highest 39.8%. The result obtains valid based on government regulation that the value of work behavior has not more than 40%. So the proposed model could be used as an evaluation tool for the performance of civil servant's behavior to support decision making of the decision maker.
{"title":"Civil servant behaviors performance evaluation: Combining DEAHP and 360-degree feedback","authors":"Irfani Zuhrufillah, Farikhin, R. Isnanto","doi":"10.1109/ICOIACT.2018.8350691","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350691","url":null,"abstract":"In Indonesia, the performance evaluation of Civil Servant is assessed based on SKP and Work Behavior. The proposed evaluation system is focusing on work behavior of civil servants through evaluating the subcriteria against the main criteria for each employee. The DEAHP model as a tool for the formation of multicriteria hierarchies and determining the weights by using efficient and inefficient of each alternative. DEAHP alone is not enough to earn the objective assessment so that the proposed using the 360-degree Feedback technique as a multi evaluator technique combined with DEAHP, this makes the evaluation more powerful. In the final process of DEA, in this case, proposed to aggregate by summing the subcriteria value against the main criteria on each DMU to obtain the final rank of the employee. At the final result generated rank data for each subcriteria and main criteria of each DMU. This performance evaluation has the lowest score for the main criteria is 13.6% and the highest 39.8%. The result obtains valid based on government regulation that the value of work behavior has not more than 40%. So the proposed model could be used as an evaluation tool for the performance of civil servant's behavior to support decision making of the decision maker.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"39 1","pages":"280-285"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79358811","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 : 2018-03-01DOI: 10.1109/ICOIACT.2018.8350739
Prabhu Jyot Singh, Rohan de Silva
Unmanned Aerial Vehicle (UAV) industry has introduced different types of UAVs to the market. The UAV industry is growing very fast due to the use of UAVs in commercial areas as well. Communication between UAVs make them more powerful and plays a vital role in the success of their commercial applications. Furthermore, UAV communication networks provide a more flexible and robust infrastructure for their use in commercial applications. In this paper, we present the design and implementation of a testbed UAV network. Since in these commercial applications, all UAVs are owned by the same organization, the communication can be simply achieved by switching through the nodes. We enabled spanning tree algorithm to prevent looping. We undertook different tests to verify the communication paths through the network.
{"title":"Design and implementation of an experimental UAV network","authors":"Prabhu Jyot Singh, Rohan de Silva","doi":"10.1109/ICOIACT.2018.8350739","DOIUrl":"https://doi.org/10.1109/ICOIACT.2018.8350739","url":null,"abstract":"Unmanned Aerial Vehicle (UAV) industry has introduced different types of UAVs to the market. The UAV industry is growing very fast due to the use of UAVs in commercial areas as well. Communication between UAVs make them more powerful and plays a vital role in the success of their commercial applications. Furthermore, UAV communication networks provide a more flexible and robust infrastructure for their use in commercial applications. In this paper, we present the design and implementation of a testbed UAV network. Since in these commercial applications, all UAVs are owned by the same organization, the communication can be simply achieved by switching through the nodes. We enabled spanning tree algorithm to prevent looping. We undertook different tests to verify the communication paths through the network.","PeriodicalId":6660,"journal":{"name":"2018 International Conference on Information and Communications Technology (ICOIACT)","volume":"19 1","pages":"168-173"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75248521","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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