{"title":"Energy Efficient Clustering in Heterogeneous Environment","authors":"Piyush Rawat, S. Chauhan","doi":"10.1109/ICICCT.2018.8473296","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473296","url":null,"abstract":"In WSN the lifetime of the sensors is very less, so the battery should be used efficiently. In order to lengthen the network lifetime, various clustering approaches are used. In this paper, we are taking the heterogeneous type of network. We are assuming that some of the sensors are furnished with some extra energy. In proposed clustering technique the weighted election probabilities are applied to choose the cluster head. The nodes in the network are classified into three categories as per their energy levels. The proposed technique uses a threshold function which uses the energy ratio of the nodes for cluster head (CH) determination. Simulation results prove that the suggested method has increased the network lifetime and increased the stability period.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130256592","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}
{"title":"Performance Analysis of Various Combination Sorting Algotirthms for Large Dataset to fit to a Multi-Core Architecture","authors":"Aparna Suresh, A. George","doi":"10.1109/ICICCT.2018.8472956","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8472956","url":null,"abstract":"A data structure is a specific and systematic way of storing and organizing data in a computer so that it can be accessed and revised efficiently. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data. An algorithm is a finite sequence of steps for solving a problem. All sorting algorithms apply to specific kind of problems. Some sorting algorithms apply to less number of elements, and others for large number of data. Likewise, some sorting algorithm are used for data with duplicate values and some are for floating point numbers. The increasing computation power in modern computers in the form of several cores per processor and more processors, makes it necessary to rethink or to redesign sequential algorithms and data structures. In this paper we introduce 3 new modified algorithms. They are Ins-merge, Quick-merge and Binary Search Tree with duplicate keys (BSTD). The goal of this paper is to develop modified algorithms for sorting on large data and to define an “n” which can be an absolute value or a function of total number of elements in data set and to make it fit into a multi-core processor to improve the computational performance.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123997240","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}
Wasudeo Rahane, Sayali P. Patil, Komal Dhondkar, Tanvi Mate
{"title":"Artificial Intelligence Based Solarbot","authors":"Wasudeo Rahane, Sayali P. Patil, Komal Dhondkar, Tanvi Mate","doi":"10.1109/ICICCT.2018.8473172","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473172","url":null,"abstract":"A chatbot (Also known as Chatterbox) is a computer program which conducts communication between a human and machine, commonly through aural or textual methods. Chatbots are becoming popular since they have the potential to save any individual's hassle and time by automating mundane errands. Chatbots have been witnessing an era of highest demand powered by either a set of responses and rules that are already predefined or artificial intelligence method such as Natural Language Processor. Chatbots are often built-in into the chat systems, for example automated online assistants, which gives them the power for small talk or informal conversations secluded to the scopes of their prime expert systems. Solar power in India is rapid developing industry. As of December 2017 the country's solar power had 17.05 GW total capacities. It has been seen that using solar power is better than using electricity as it is an unlimited and renewable source. More and more people prefer using solar energy, they are being more curious about the uses of solar panels. They find it difficult to acquire information related to solar panels and their facilities. To ease their work a Solarbot can be designed that would provide them with all the necessary information they need quickly and without any hassle. The chatbot provides an interface as a platform for communication between the bot and the client. For pattern matching database is used for storing data and as per for functions and procedures. Pattern matching looks for definite patterns for words in the user's input, compares it with the database and responds to the consumer. A system that would provide facilities to the user very quickly and with least amount of work would be very beneficial.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121534125","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}
{"title":"An Intelligent Software defined Network Controller for preventing Distributed Denial of Service Attack","authors":"Aditya Prakash, R. Priyadarshini","doi":"10.1109/ICICCT.2018.8473340","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473340","url":null,"abstract":"Software Defined Network (SDN) architecture is a new and novel way of network management mechanism. In SDN, switches do not process the incoming packets like conventional network computing environment. They match for the incoming packets in the forwarding tables and if there is none it will be sent to the controller for processing which is the operating system of the SDN. A Distributed Denial of Service (DDoS) attack is a biggest threat to cyber security in SDN network. The attack will occur at the network layer or the application layer of the compromised systems that are connected to the network. In this paper a machine learning based intelligent method is proposed which can detect the incoming packets as infected or not. The different machine learning algorithms adopted for accomplishing the task are Naive Bayes, K-Nearest neighbor (KNN) and Support vector machine (SVM) to detect the anomalous behavior of the data traffic. These three algorithms are compared according to their performances and KNN is found to be the suitable one over other two. The performance measure is taken here is the detection rate of infected packets.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132550621","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}
{"title":"Fifth Generation (5G) Wireless Technology “Revolution in Telecommunication”","authors":"A. Jain, Rupesh Acharya, S. Jakhar, Tarun Mishra","doi":"10.1109/ICICCT.2018.8473011","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473011","url":null,"abstract":"After the up rise of 4G wireless mobile technology takes place; researchers, mobile operator industries representative, academic institutions have started to look into the advancement (technological) towards 5G communication networks due to some main demands that are meliorated data rates, better capacity, minimized latency and better QoS (Quality of Service). To established the 5G mobile communication technological foundation, various research works or projects entailing main mobile infrastructure manufacturers, academia and international mobile network operators have been introduced recently. Nevertheless, 5G mobile services to be made available for use, their architecture, and their performance have not been evidently explicated. In this paper, we represent thorough overview of 5G the next generation mobile technology. We mainly throws light on 5G network architecture, 5G radio spectrum, ultra-dense radio access networks (UDRAN), traffic offloading of mobile, cognitive radio (CR), software defined radio (SDR), software defined networking (SDN), mixed infrastructure, and 5G network impact on the society.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"300 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115927900","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}
Fouzia, R. Roopalakshmi, J. A. Rathod, A. Shetty, K. Supriya
{"title":"Driver Drowsiness Detection System Based on Visual Features","authors":"Fouzia, R. Roopalakshmi, J. A. Rathod, A. Shetty, K. Supriya","doi":"10.1109/ICICCT.2018.8473203","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473203","url":null,"abstract":"Nowadays, Driver drowsiness is one of the maj or cause for most of the accidents in the world. Detecting the driver eye tiredness is the easiest way for measuring the drowsiness of driver. The existing systems in the literature, are providing slightly less accurate results due to low clarity in images and videos, which may result due to variations in the camera positions. In order to solve this problem, a driver drowsiness detection system is proposed in this paper, which makes use of eye blink counts for detecting the drowsiness. Specifically, the proposed framework, continuously analyzes the eye movement of the driver and alerts the driver by activating the vibrator when he/she is drowsy. When the eyes are detected closed for too long time, a vibrator signal is generated to warn the driver. The experimental results of the proposed system, which is implemented on Open CV and Raspberry Pi environment with a single camera view, illustrate the good performance of the system in terms of accurate drowsiness detection results and thereby reduces the road accidents.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115587007","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}
{"title":"Indian Sign Language Numeral Recognition Using Region of Interest Convolutional Neural Network","authors":"T. D. Sajanraj, M. Beena","doi":"10.1109/ICICCT.2018.8473141","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473141","url":null,"abstract":"Communication provide interaction among the people to exchange the feelings and ideas. The deaf community suffer a lot to interact with the community. Sign language is the way through which the people communicate with each other. In order to provide interaction with normal people there is a system which can convert the sign languages to the understandable form. The purpose of this work is to provide a real-time system which can convert Indian Sign Language (ISL) to the text. Most of the work based on handcrafted feature. In this we are introducing a deep learning approach which can classify the sign using the convolutional neural network. In the first phase we make a classifier model using the numeral signs using the Keras implementation of convolutional neural network using python. In phase two another real-time system which used skin segmentation to find the Region of Interest in the frame which shows the bounding box. The segmented region is feed to the classifier model to predict the sign. The system has attained an accuracy of 99.56% for the same subject and 97.26% in the low light condition. The classifier found to be improving with different background and the angle of the image captured. Our method focus on the RGB camera system.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126900344","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}
{"title":"Objects Talk - Object Detection and Pattern Tracking Using TensorFlow","authors":"Rasika Phadnis, Jaya Mishra, S. Bendale","doi":"10.1109/ICICCT.2018.8473331","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473331","url":null,"abstract":"Objects in household that are frequently in use often follow certain patterns with respect to time and geographical movement. Analysing these patterns can help us keep better track of our objects and maximise efficiency by minimizing time wasted in forgetting or searching for them. In our project, we used TensorFlow, a relatively new library from Google, to model our neural network. The TensorFlow Object Detection API is used to detect multiple objects in real-time video streams. We then introduce an algorithm to detect patterns and alert the user if an anomaly is found. We consider the research presented by Laube et al., Finding REMO-detecting relative motion patterns in geospatial lifelines, 201–214, (2004)[1].","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126087710","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}
Mohit Vasuja, A. Mishra, Udbhav Singh Chauhan, Deeksha Chandola, S. Kapoor
{"title":"Image Transmission Using Li-Fi","authors":"Mohit Vasuja, A. Mishra, Udbhav Singh Chauhan, Deeksha Chandola, S. Kapoor","doi":"10.1109/ICICCT.2018.8473033","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473033","url":null,"abstract":"We went from 56kbps wired ARPANET connections limited to the US military in the 1960s, to unimaginably fast wireless 100 Mbps connections in the 2010s. But what the future holds will certainly blow your mind 1Gbps or more and that is still an understatement LIGHT FIDELITY it is or popularly known as Li-Fi. The two-major prospect being aimed is extension or enhancement of the wireless services and to support the number of the exponentially growing user which the RF spectrum is unable to provide due to a limited spectrum of radio waves. So, Li-fi that is based on the visible light spectrum is being designed. It uses a LED and a photodiode or phototransistor to transmit and receive data respectively. Li-fi can be compared with the existing wireless technology i.e. Wi-Fi in terms of speed and security which the former provides better. The aspiration of this research paper is cunning a prototype of Li-fi transmitter and receiver to transmit data. The schematic design was made using Proteus 8 professional. Software coding was done on C language and PIC microcontroller is used. Successful transfer of image and text were achieved. As a deduction, this work gives an originative way of scheming a Li-Fi Prototype.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123770680","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}
Viken Parikh, Madhura Keskar, Dhwanil Dharia, P. Gotmare
{"title":"A Tourist Place Recommendation and Recognition System","authors":"Viken Parikh, Madhura Keskar, Dhwanil Dharia, P. Gotmare","doi":"10.1109/ICICCT.2018.8473077","DOIUrl":"https://doi.org/10.1109/ICICCT.2018.8473077","url":null,"abstract":"Tourism, these days involves mass availability and mass participation in holidays. But many times, a tourist cannot decide which place to visit, or where to stay. In this paper, we propose a mobile application, which will take the user's interest and recommend attractions, restaurants, and hotels. The system is trained using the dataset of TripAdvisor. The clustering of the training dataset is done using K-modes clustering which is an unsupervised learning algorithm. The application Travigate, not only recommends new places to the user, but it also helps them to recognize new places. With the use of Convolutional Neural Networks, reverse image search is done for a dataset created by web scraping images from Google. The application receives the data in the JSON format from the MySQL Database using Python Flask Server.","PeriodicalId":334934,"journal":{"name":"2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131350769","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}