2017 2nd International Conference On Emerging Computation and Information Technologies (ICECIT)最新文献

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Interference and Delay Aware Routing Algorithm for Cognitive Radio Sensor Networks 认知无线电传感器网络的干扰和延迟感知路由算法
Kumaresh Sheelavant, R. Sumathi
{"title":"Interference and Delay Aware Routing Algorithm for Cognitive Radio Sensor Networks","authors":"Kumaresh Sheelavant, R. Sumathi","doi":"10.1109/ICECIT.2017.8453436","DOIUrl":"https://doi.org/10.1109/ICECIT.2017.8453436","url":null,"abstract":"Cognitive Radio Sensor Networks (CRSN) consists of cognitive devices capable of changing their transmission parameters on a real time, based on the spectrum available in the environment. These capabilities brings-up the possibility of designing flexible and dynamic spectrum strategies with the purpose of opportunistically accessing the portion of the spectrum temporarily vacated by the primary users, due to this there will be increased complexity in the design of communication protocols. The characteristic of CRSN that is opportunistic access of spectrum raises interference problem in the communication networks. On account of this problem the performance of the network will be degraded like increase in consumption of energy, switching delay, reducing the reliability of a network. To overcome all these challenges we developed an interference and delay aware routing algorithm which selects a best path to route the data from source to the destination.","PeriodicalId":331200,"journal":{"name":"2017 2nd International Conference On Emerging Computation and Information Technologies (ICECIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125568352","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}
引用次数: 0
A Low Cost Multi Sensorial Data Fusion for High Speed Obstacle Avoidance Using 3-D Point Clouds and Image Processing in Self Balancing Robots 基于三维点云和图像处理的自平衡机器人高速避障低成本多感官数据融合
K. M. Mithil, G. S. Thejas, Sanjeev Kaushik Ramani, S. S. Iyengar
{"title":"A Low Cost Multi Sensorial Data Fusion for High Speed Obstacle Avoidance Using 3-D Point Clouds and Image Processing in Self Balancing Robots","authors":"K. M. Mithil, G. S. Thejas, Sanjeev Kaushik Ramani, S. S. Iyengar","doi":"10.1109/ICECIT.2017.8453439","DOIUrl":"https://doi.org/10.1109/ICECIT.2017.8453439","url":null,"abstract":"This paper investigates the challenges related to a very fundamental problem of efficient obstacle avoidance on roads in the modern world, with respect to the self balancing robot. The amalgamation of navigation in self balancing robot pose newer challenges in circumvention of traffic congestion. Comprehensive research has been done on the obstacle avoidance of the four wheeled vehicles, but we have other problems to address in the case of self balancing robots on two wheels. Speed is becoming a predominant factor in the present day automotive industry. In this paper we address this very issue and propose a model driven by the outputs from multi sensorial data generated using various sensors and image processing techniques. The distinguishing feature of our technique is how we tackle the high speed obstacles. The paper channelizes its focus on avoiding high speed obstacles by tracking the object in real time using image processing techniques and then creating a 3-D point cloud of the object and its static surroundings through a matrix of arrays, using the Light Detection And Ranging (LiDAR) module.","PeriodicalId":331200,"journal":{"name":"2017 2nd International Conference On Emerging Computation and Information Technologies (ICECIT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124533888","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}
引用次数: 4
An Enhanced method for Streaming Multimedia data to achieve the Quality of Service Support using SDN. 一种利用SDN实现流媒体数据服务质量支持的增强方法。
M. Vandana, H. Kallinatha
{"title":"An Enhanced method for Streaming Multimedia data to achieve the Quality of Service Support using SDN.","authors":"M. Vandana, H. Kallinatha","doi":"10.1109/ICECIT.2017.8453366","DOIUrl":"https://doi.org/10.1109/ICECIT.2017.8453366","url":null,"abstract":"Abstract-from past few years due to the rapid growth in the real time applications requires preserving the Quality of Service (QOS). Preserving the QoS in streaming the video files from source to destination is a major challenge. The problem’s solution proposed here addresses the challenge with the help of Scalable Video Coding (SVC) technology in conjunction with the Software defined Networking (SDN). SVC is a standard that compresses the video data which has the subsets of video, this consists of video formats (such as. gif, .fly, mpg, 3gp etc.). To preserve the QoS especially for these video files we should take extra care due to the massive forms of videos available today. Taking into account the type of the devices to which the clients are connected; in SVC the base layer of the video will be connected to number of sub layers. These sub layers will be divided based on the quality of video. These videos will be streamed according to the type of device that the client is using to access the data. In this way we can preserve the QOS while streaming the data from source to destination.","PeriodicalId":331200,"journal":{"name":"2017 2nd International Conference On Emerging Computation and Information Technologies (ICECIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129598557","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}
引用次数: 1
A Low Cost Multi Sensorial Data Fusion for High Speed Obstacle Avoidance Using 3-D Point Clouds and Image Processing in Self Balancing Robots 基于三维点云和图像处理的自平衡机器人高速避障低成本多感官数据融合
K. M. Mithil, G. S. Thejas, Sanjeev Kaushik Ramani, S. S. Iyengar
{"title":"A Low Cost Multi Sensorial Data Fusion for High Speed Obstacle Avoidance Using 3-D Point Clouds and Image Processing in Self Balancing Robots","authors":"K. M. Mithil, G. S. Thejas, Sanjeev Kaushik Ramani, S. S. Iyengar","doi":"10.1109/icecit.2017.8454957","DOIUrl":"https://doi.org/10.1109/icecit.2017.8454957","url":null,"abstract":"This paper investigates the challenges related to a very fundamental problem of efficient obstacle avoidance on roads in the modern world, with respect to the self balancing robot. The amalgamation of navigation in self balancing robot pose newer challenges in circumvention of traffic congestion. Comprehensive research has been done on the obstacle avoidance of the four wheeled vehicles, but we have other problems to address in the case of self balancing robots on two wheels. Speed is becoming a predominant factor in the present day automotive industry. In this paper we address this very issue and propose a model driven by the outputs from multi sensorial data generated using various sensors and image processing techniques. The distinguishing feature of our technique is how we tackle the high speed obstacles. The paper channelizes its focus on avoiding high speed obstacles by tracking the object in real time using image processing techniques and then creating a 3-D point cloud of the object and its static surroundings through a matrix of arrays, using the Light Detection And Ranging (LiDAR) module.","PeriodicalId":331200,"journal":{"name":"2017 2nd International Conference On Emerging Computation and Information Technologies (ICECIT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131749075","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}
引用次数: 0
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