2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)最新文献

{"title":"Big Data Ensure Homologous Patient Enduring Therapy Time Forecast Algorithm by Healing Facility Echelon Recommendation","authors":"T. Sandeep, K. Manoj, N. Reddy, R. R. Kumar","doi":"10.1109/ICGCIOT.2018.8753079","DOIUrl":"https://doi.org/10.1109/ICGCIOT.2018.8753079","url":null,"abstract":"Effective patient line organization to constrain tolerance hold-up deferrals and patient overcrowdings is one of the genuine troubles increased by mending offices. Senseless and irritating sitting tight for long extends result in imperative human asset and time wastage and improvement of the oversight continued by patients. For every patient in the line, the aggregate therapy time of the indispensable number of patients before him is the time that he should hold-up. It would be significant and best if the patients could get the fit treatment design and know the standard holding up time through an adaptable application that updates endlessly. Consequently, we propose a patient enduring therapy time forecast to imagine the sitting tight time for each treatment undertaking for a patient. We use sensible patient data from various workplaces to get a patient therapy time show up for each endeavor. In setting of this widescale, sensible dataset, the therapy time for each patient in the present line of every errand is ordinary. In setting of the ordinary holding up time, a healing facility echelon recommendation structure is made. Healing facility echelon recommendation finds and predicts a fit and obliging therapy design proposed for the patient. By virtue of the monstrous scale, achievable data set and the necessity for resolute response, the patient enduring therapy time forecast estimation and healing facility echelon recommendation structure sort out plentifulness and low-lethargy response. We use an Apache Spark execution to fulfill the starting and ending targets. Wide experimentation and reenactment work outs as expected demonstrate the sensibility and congruity of our proposed model to recommend preparation of a practical treatment for patients to confine their hold-up times in recouping center interests.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116122758","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":"Beast to Beauty data in Virtual Analytics","authors":"Deepa Gupta, Vaibhav Sharma, Praveen Kumar","doi":"10.1109/ICGCIOT.2018.8753051","DOIUrl":"https://doi.org/10.1109/ICGCIOT.2018.8753051","url":null,"abstract":"In the current scenario, ninety percent of the data present in the world right now is created in past two years only. As the world relentlessly turns out to be more associated with a consistently expanding number of electronic gadgets, which also results in exponential growth of data created, this is just set to become over the coming years. All in all, the Internet populace has developed by 7.5 percent since 2016 and now incorporates more than 3.75 billion people. As far as information utilization, that is one serious strain. By and large, the only us releases 2,657,700 gigabytes of Internet information consistently. The advancement of Internet-based media stages and organizations are having their day in the sun, yet not all. Amazon, YouTube, and Netflix are a segment of the best customers of Internet information transmission. While Amazon is getting a charge out of record benefits (around 258,751 deals every moment, up from 222,283 a year ago) and YouTube is gushing like never before (4.14 million recordings viewed every moment), Netflix has seen a 20 percent diminish in the quantity of \"hours\" their watchers watched demonstrates every moment contrasted with 2016.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129339525","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":"Predictive Analysis for Modeling Travel Decision Making","authors":"R. Keerthi, P. Lakshmi","doi":"10.1109/ICGCIOT.2018.8753103","DOIUrl":"https://doi.org/10.1109/ICGCIOT.2018.8753103","url":null,"abstract":"The exponential rise in technologies has opened up a gigantic scope to exploit the data for better decision making. The evolution of social media has contributed humungous information including ratings, reviews and comments. Considering the significance of an efficient predictive analysis model for the tourist destination prediction, in the proposed work robust technologies have been applied to perform the destination prediction. This work contributes to the technique of developing a novel Destination Prediction Model that corresponds to the tourist’s preferences.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133640124","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":"Color Features and KNN in Classification of Raw Arecanut images","authors":"S. Siddesha, S. Niranjan, V. N. Manjunath Aradhya","doi":"10.1109/ICGCIOT.2018.8753075","DOIUrl":"https://doi.org/10.1109/ICGCIOT.2018.8753075","url":null,"abstract":"Arecanut is one of the important cash crops of Southern India. Classification of raw arecanut is one of the major tasks in grading, which is a vital part of crop management. In this work we proposed a model which classifies the raw arecanut. We used color histogram and color moments as features with K-NN classifier. Experiment is conducted on a dataset of 800 images of four classes using two color features and four distance measures with K-NN. A classification accuracy of 98.13% is achieved for 20% training with K value of 3 and Euclidean distance measure for color histogram features.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"04 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127189272","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":"Analysis Through Machine Learning Techniques: A Survey","authors":"R. Reddy, G. Shyam","doi":"10.1109/ICGCIOT.2018.8753050","DOIUrl":"https://doi.org/10.1109/ICGCIOT.2018.8753050","url":null,"abstract":"Analysis and search for meaningful associations in customer purchase data are considered as best applications of data mining techniques. Machine learning is the fundamental nature of imitation of intelligence. The machine learns from the past information to improve the performance of intelligent programs. We consider unsupervised machine learning techniques to analyze various sort of the data. Techniques used are clustering, feature extraction and classification. Machine learning is mainly employed to exhibit accurate estimate. The major objective of this paper is to present the outline of machine learning and discuss unsupervised machine-learning techniques for various applications. Further, this paper reviews the different machine learning techniques.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115038402","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":"EnviDron — A drone that purifies air","authors":"Kiran V Parvatekar, Shebin M Zacharia, Shreya V Sheelvant, Tanya Nanaiah, K. Ambika","doi":"10.1109/ICGCIOT.2018.8753058","DOIUrl":"https://doi.org/10.1109/ICGCIOT.2018.8753058","url":null,"abstract":"Our world has been polluted in many ways over the years and the most dangerous one is air pollution which causes depletion of the ozone layer leading to greenhouse effect and global warming. The developed product is a drone that aims at purifying air by first monitoring the amount of toxins in it and then filtering them out, thereby releasing relatively purer air. A single drone purifies a very small percentage of air. Therefore, to bring about a difference in the air conditions, they need to be used in swarm robotics.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123226037","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":"Control of Stand-alone Hybrid Renewable Energy Generation System Using Fuzzy Controller","authors":"Sandeep S R, Rudranna Nandihalli","doi":"10.1109/ICGCIOT.2018.8753066","DOIUrl":"https://doi.org/10.1109/ICGCIOT.2018.8753066","url":null,"abstract":"The paper proposes a novel method for fulfilling the load demands using the two renewable generation system such as wind and solar. The fuzzy logic controller is used to control the generation of the generating station. The power reference of each renewable source is calculated and provided to the fuzzy controller; it generates the control signals to alter the generation power. The controller is intelligent enough to make the decision for the dynamic change in the operating point of the solar and wind. MATLAB SIMULINK tool is used to implement the proposed system.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124659728","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":"A Holistic Approach For Patient Health Care Monitoring System Through IoT","authors":"S. Nandyal, Aishwarya R Gada","doi":"10.1109/ICGCIOT.2018.8753098","DOIUrl":"https://doi.org/10.1109/ICGCIOT.2018.8753098","url":null,"abstract":"Health care is the most important aspect of any society and is fundamental need for every citizen of every country. However, most developing countries face lack of proper health care resources to cater to the needs of every citizen. In critical cases, the patients have to be continuously monitored for their bio-parameters and immediate response from doctors is essential. So, it is most essential to improve the healthcare infrastructure. The emerging trend in healthcare sector is to change the existing healthcare services and change the routine medical check-ups from hospital centric to person centric. Here, A Holistic Approach for the Development of Real Time Patient Health Monitoring and Alerting through IOT is proposed and implemented using ThingSpeak site as the cloud. This work presents the design and construction of a working prototype for smart health care system using Internet of Things which can provide Quality Health Care to everyone. In this system, the prototype developed uses an embedded system built using Atmega328 microcontroller and it is programmed using Arduino IDE. The prototype gathers biomedical and orientation information from sensors and location information from GPS of the monitored person and convey them to healthcare cloud system utilizing IOT platform. The sensor data is sent to the network through Wi-Fi link. The Thingspeak channel is updated at regular intervals and helps to maintain the medical history of the patient. The Thingspeak cloud computing handles authentication, privateness, safety, and data management and provides accessibility. The system obtains the parameter valus and compares them with the standard values and in the case of an emergency, a local alarm is triggered and an SMS text message is sent to the doctor with the details of authentication. The data from cloud platform can be accessed by the concerned doctor anytime, after a proper authentication and diagnosis and decisions can be made. The data can be accessed only by the authorized user (doctor) through password authentication.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"126 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114088597","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":"Techniques for Visual Analysis of Eye Tracking Data","authors":"Shantanu V. Kulkarni, Sangeeta K","doi":"10.1109/ICGCIOT.2018.8753026","DOIUrl":"https://doi.org/10.1109/ICGCIOT.2018.8753026","url":null,"abstract":"Eye tracking is the process of estimating as well as recording gaze positions and eye movements of an individual. Eye tracking technology has many statistical factors which are significant in generating knowledge and values. In most of the approaches an insight is presented with the help of traditional attention maps as well as gaze plots. There is no any single visualization type for all possible requirements. The appropriate choice of a visualization method depends on the format of the data, analysis task specific to the requirements. The objective of this work is to visualize eye tracking data using various visualization especially 3D visuals and animation of eye gazes. These implementations have respective benefits over the other methods of eye tracking visualizations and can be used to generate more knowledge and value extraction from eye tracking metrics.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116059906","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":"Applicability of Wearable Smart Glass for Solar Power Plant Operation and Maintenance","authors":"Nallapaneni Manoj Kumar, P. Das, Jayanna Kanchikere","doi":"10.1109/ICGCIOT.2018.8752998","DOIUrl":"https://doi.org/10.1109/ICGCIOT.2018.8752998","url":null,"abstract":"Wearable Devices and their relevant intelligent and integrated computing techniques are presently being discovered to promote extensive claims in many areas. Smart Glass is one such wearable device which attracted many sectors since its official launch as Google Glass in 2014. Currently, no resource exists in the literature that supports the use of Smart Glass for the solar industry. For the first time, this article seeks to expand the Smart Glass applications into the solar power industry especially for addressing the solar power plant operation and maintenance issues. Applicability and scope for possible operations were explored by studying the technology and integrated computing techniques. Various sensors were embedded in smart glass, and they are a camera, microphone, global navigation system (GPS), magnetometer, light sensor, and a tangible interface. These embedded sensors can do works that are most important in monitoring few relevant parameters and addressing the challenges in solar power plant and its system components. Few computing technologies which could be integrated with the smart glass specifically in the view of solar were proposed. The theoretical study was carried out in monitoring the feasibilities of capturing images of the photovoltaic (PV) module for addressing dust and temperature problems, identifying the location of the power plant, noise monitoring of the system components, detection of power cables using magnetometers, tracking of visually enriched images under light conditions etc. Also, with the help of tangible sensors, the operator can use and interact with any digital interface available for displaying the monitor parameters. Hence, it is felt that the smart glass could be a great assent for solar power plant operation and maintenance.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"389 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122878791","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}