Pub Date : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969067
Mukul Diwanji, S. Hisvankar, C. Khandelwal
This paper examines and leverages the potential of automation in hazardous but important occupation as firefighting. Robots are designed to find the location of fire, before it goes out of control. It could be used to work with fire fighters to reduce the risk of injury to victims. This paper presents the Fire Fighting Robot. The development of robot is divided into three elements which is the hardware, electronic, and programming. The robot has two DC motors for driving system and castor wheel for giving direction. A 12 Volt DC pump for suction and spraying of water. Servo Motor (SG90) for axial spraying of water.(0 degrees to 60 degrees)Various sensors are also interfaced with Arduino Uno Board. For the programming part, Arduino IDE language was used to determine the robot movement from the sensors input.
本文考察和利用自动化在危险但重要的职业，如消防的潜力。机器人的设计目的是在火灾失去控制之前找到火灾的位置。它可以与消防员一起工作，以减少受害者受伤的风险。本文介绍了消防机器人。机器人的发展分为硬件、电子和编程三个方面。该机器人具有两个直流电机驱动系统和用于指示方向的脚轮。用于吸水和喷水的12伏直流泵。伺服电机(SG90)轴向喷水。(0度到60度)各种传感器也与Arduino Uno Board接口。在编程部分，使用Arduino IDE语言根据传感器的输入判断机器人的运动。
{"title":"Autonomous Fire Detecting and Extinguishing Robot","authors":"Mukul Diwanji, S. Hisvankar, C. Khandelwal","doi":"10.1109/ICCT46177.2019.8969067","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969067","url":null,"abstract":"This paper examines and leverages the potential of automation in hazardous but important occupation as firefighting. Robots are designed to find the location of fire, before it goes out of control. It could be used to work with fire fighters to reduce the risk of injury to victims. This paper presents the Fire Fighting Robot. The development of robot is divided into three elements which is the hardware, electronic, and programming. The robot has two DC motors for driving system and castor wheel for giving direction. A 12 Volt DC pump for suction and spraying of water. Servo Motor (SG90) for axial spraying of water.(0 degrees to 60 degrees)Various sensors are also interfaced with Arduino Uno Board. For the programming part, Arduino IDE language was used to determine the robot movement from the sensors input.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130108412","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969012
Vartika, C. Krishna, Ravin Kumar, Yogita
The services of Indian Railway are availed by many people in the country. It is an important mode of transportation. Most of the users of Indian Railway express their views about it on different social media sites like Twitter, Facebook etc. It leads to generation of large amount of data and sentimental analysis of that data can be very helpful in understanding public opinions towards Indian Railway and in decision making. In this paper, the lexicon based sentimental analysis technique has been applied to the twitter data collected corresponding to three train accidents namely Puri-Haridwar-Kalinga Utkal Express, Delhi-bound Kaifiyat Express and Mumbai-Nagpur Duranto Express which took place on 19/08/2017, 23/08/2017 and 29/08/2017 respectively. Further, tweets are classified into different categories and analyzed in terms of percentage frequency. The results present the pattern how the sentiments of the public fluctuate with time as when derailment happens the negative tweets has high frequency of occurrence but with passage of time frequency of occurrence of neutral tweets become high.
{"title":"Sentiment Analysis of Train Derailment in India: A Case Study from Twitter Data","authors":"Vartika, C. Krishna, Ravin Kumar, Yogita","doi":"10.1109/ICCT46177.2019.8969012","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969012","url":null,"abstract":"The services of Indian Railway are availed by many people in the country. It is an important mode of transportation. Most of the users of Indian Railway express their views about it on different social media sites like Twitter, Facebook etc. It leads to generation of large amount of data and sentimental analysis of that data can be very helpful in understanding public opinions towards Indian Railway and in decision making. In this paper, the lexicon based sentimental analysis technique has been applied to the twitter data collected corresponding to three train accidents namely Puri-Haridwar-Kalinga Utkal Express, Delhi-bound Kaifiyat Express and Mumbai-Nagpur Duranto Express which took place on 19/08/2017, 23/08/2017 and 29/08/2017 respectively. Further, tweets are classified into different categories and analyzed in terms of percentage frequency. The results present the pattern how the sentiments of the public fluctuate with time as when derailment happens the negative tweets has high frequency of occurrence but with passage of time frequency of occurrence of neutral tweets become high.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124315879","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 : 2019-09-01DOI: 10.1109/icct46177.2019.8969022
J. Chaudhari, Asmita A. Desai, S. Gavarskar
This paper describes the line following robot using arduino for surveying, inspecting and enhancing the transportation of necessary materials inside the healthcare institutions, industries also. The proposed system spot the black path and proceed in its direction on to the ground. This system eases the work of material conveyance as well as minimizes the manpower. This technology targets on the secured, punctual and constructing transportation of goods. This paper aims to implement controlled movement of robot by tuning control parameters and thus achieve better performance. This robot is predominantly design to proceed in a predefined path. To locate this path two sensors are used. Robots like this are mainly used in industrial plants comprising of pick and place facility. This robot carries components from desired source to destination by following fixed path. Recently lot of research has been done to empower the automation in hospitals as well in industries. This robot is made to supply the essential goods such injections, medicine, etc. This paper is divided into hardware and software modules.
{"title":"Line Following Robot Using Arduino for Hospitals","authors":"J. Chaudhari, Asmita A. Desai, S. Gavarskar","doi":"10.1109/icct46177.2019.8969022","DOIUrl":"https://doi.org/10.1109/icct46177.2019.8969022","url":null,"abstract":"This paper describes the line following robot using arduino for surveying, inspecting and enhancing the transportation of necessary materials inside the healthcare institutions, industries also. The proposed system spot the black path and proceed in its direction on to the ground. This system eases the work of material conveyance as well as minimizes the manpower. This technology targets on the secured, punctual and constructing transportation of goods. This paper aims to implement controlled movement of robot by tuning control parameters and thus achieve better performance. This robot is predominantly design to proceed in a predefined path. To locate this path two sensors are used. Robots like this are mainly used in industrial plants comprising of pick and place facility. This robot carries components from desired source to destination by following fixed path. Recently lot of research has been done to empower the automation in hospitals as well in industries. This robot is made to supply the essential goods such injections, medicine, etc. This paper is divided into hardware and software modules.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"478 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120869335","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969052
Bhagyashree Rajendra Gaidhani, R. R.Rajamenakshi, Samadhan Sonavane
For the last few decades, machine learning is used to analyze medical dataset. Recently, deep learning technology gaining success in many domain including computer vision, image recognition, natural language processing and especially in medical field of radiology. This research attempts to diagnose brain stroke from MRI using CNN and deep learning models. The proposed methodology is to classify brain stroke MRI images into normal and abnormal images and delineate abnormal regions using semantic segmentation [4]. In particular, two types of convolutional neural network that are LeNet [2] and SegNet are used. For classification, we passed pre-processed stroke MRI for training, trained all layers of LeNet and classify normal and abnormal patient. Then this abnormal patient data stored into two dimensional array and passed this two dimensional array to SegNet which is auto encoder decoder [3] model for segmentation, trained all layers of SegNet except fully connection layer. The experimental result show that classification model achieve accuracy between 9697% and segmentation model achieve accuracy between 8587%.Through experimental results, we found that deep learning models not only used in non-medical images but also give accurate result on medical image diagnosis, especially in brain stroke detection.
{"title":"Brain Stroke Detection Using Convolutional Neural Network and Deep Learning Models","authors":"Bhagyashree Rajendra Gaidhani, R. R.Rajamenakshi, Samadhan Sonavane","doi":"10.1109/ICCT46177.2019.8969052","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969052","url":null,"abstract":"For the last few decades, machine learning is used to analyze medical dataset. Recently, deep learning technology gaining success in many domain including computer vision, image recognition, natural language processing and especially in medical field of radiology. This research attempts to diagnose brain stroke from MRI using CNN and deep learning models. The proposed methodology is to classify brain stroke MRI images into normal and abnormal images and delineate abnormal regions using semantic segmentation [4]. In particular, two types of convolutional neural network that are LeNet [2] and SegNet are used. For classification, we passed pre-processed stroke MRI for training, trained all layers of LeNet and classify normal and abnormal patient. Then this abnormal patient data stored into two dimensional array and passed this two dimensional array to SegNet which is auto encoder decoder [3] model for segmentation, trained all layers of SegNet except fully connection layer. The experimental result show that classification model achieve accuracy between 9697% and segmentation model achieve accuracy between 8587%.Through experimental results, we found that deep learning models not only used in non-medical images but also give accurate result on medical image diagnosis, especially in brain stroke detection.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123127034","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969029
Pai Manohara M. M., S. Kolekar, R. Pai
Foot complications are considered to be a serious consequence of Diabetes Mellitus (DM), posing a major medical and economical threat. This paper discusses about a device which generates the temperature profiling which is useful to detect the foot complications at early stage. Using the developed device, the temperature of the plantar area is measured periodically at twenty-three strategic points and based on the temperature difference between the two feet, the abnormality is reported. The device is easy to use and can used in home to capture real time data without going through medical follow-ups.
{"title":"Temperature Profiling for Early Detection of Foot Complications","authors":"Pai Manohara M. M., S. Kolekar, R. Pai","doi":"10.1109/ICCT46177.2019.8969029","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969029","url":null,"abstract":"Foot complications are considered to be a serious consequence of Diabetes Mellitus (DM), posing a major medical and economical threat. This paper discusses about a device which generates the temperature profiling which is useful to detect the foot complications at early stage. Using the developed device, the temperature of the plantar area is measured periodically at twenty-three strategic points and based on the temperature difference between the two feet, the abnormality is reported. The device is easy to use and can used in home to capture real time data without going through medical follow-ups.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127634445","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8968777
M. M. Manohara Pai, S. Kolekar, R. Pai
Foot ulcers are the most common medical complications seen in patients with diabetes with an estimated prevalence of 12-15 percent among all individuals with diabetes [1]. Patients suffering with diabetic foot ulcers are more susceptible to hospitalizations than any other complication of diabetes. Ulceration can have potential devastating complications as they cause up to 90 percent of lower extremity amputations in patients with diabetes. Thus it is essential for early diagnosis of foot ulceration among diabetic patients. The main aim of this paper is to build a wearable Smart Sole based prediction system capable of analyzing the plantar pressure at different strategic locations of the foot in real time and provide these results to the doctors for making the required decisions based on additional captured clinical data of the patients.
{"title":"Development of Smart Sole based Foot Ulcer Prediction System","authors":"M. M. Manohara Pai, S. Kolekar, R. Pai","doi":"10.1109/ICCT46177.2019.8968777","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8968777","url":null,"abstract":"Foot ulcers are the most common medical complications seen in patients with diabetes with an estimated prevalence of 12-15 percent among all individuals with diabetes [1]. Patients suffering with diabetic foot ulcers are more susceptible to hospitalizations than any other complication of diabetes. Ulceration can have potential devastating complications as they cause up to 90 percent of lower extremity amputations in patients with diabetes. Thus it is essential for early diagnosis of foot ulceration among diabetic patients. The main aim of this paper is to build a wearable Smart Sole based prediction system capable of analyzing the plantar pressure at different strategic locations of the foot in real time and provide these results to the doctors for making the required decisions based on additional captured clinical data of the patients.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116317988","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969021
K. Gurrala, Lenin Yemineni, Krupa Spandan Raj Rayana, Lokesh Kumar Vajja
Detecting plant diseases automatically with the help of symptoms present on leaves at earlier stage yields more productivity in agriculture. In this paper, a novel plant disease diagnosis method is proposed for the plants using image processing techniques and SVM classifier. Here, disease diagnosis is carried based on features extracted from the segmented image after pre-processing the image of the leaves which are affected with diseases. Modified color processing detection algorithm (CPDA) is used as segmentation method to extract the features. SVM classifier is trained with a dataset of about 100 images of diseased leaves to identify the diseases like anthracnose, leafspot, leafblight, scab. For disease detection, the performance of proposed segmentation technique is better when compared to the K-means clustering segmentation.
{"title":"A New Segmentation method for Plant Disease Diagnosis","authors":"K. Gurrala, Lenin Yemineni, Krupa Spandan Raj Rayana, Lokesh Kumar Vajja","doi":"10.1109/ICCT46177.2019.8969021","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969021","url":null,"abstract":"Detecting plant diseases automatically with the help of symptoms present on leaves at earlier stage yields more productivity in agriculture. In this paper, a novel plant disease diagnosis method is proposed for the plants using image processing techniques and SVM classifier. Here, disease diagnosis is carried based on features extracted from the segmented image after pre-processing the image of the leaves which are affected with diseases. Modified color processing detection algorithm (CPDA) is used as segmentation method to extract the features. SVM classifier is trained with a dataset of about 100 images of diseased leaves to identify the diseases like anthracnose, leafspot, leafblight, scab. For disease detection, the performance of proposed segmentation technique is better when compared to the K-means clustering segmentation.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121126328","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969059
P. Tiwari, Rishi Gupta, R. Gupta
Presently days, audit destinations are increasingly more defied with the spread of falsehood, i.e., assessment spam, which goes for advancing or harming some objective organizations, by deceiving either human peruses, or computerized feeling mining and opinion investigation frameworks. Thus, in the most recent years, a few information-driven methodologies have been proposed to survey the believability of client created content diffused through online life as on-line audits. Particular methodologies frequently think about various subsets of qualities, i.e., highlights, associated with the two audits and commentators, just as to the system structure connecting unmistakable elements on the survey site in test. This work goes for giving an examination of the fundamental audit and commentator driven highlights that have been proposed up to now in the writing to identify counterfeit surveys, specifically from those methodologies that utilize directed AI systems. These arrangements furnish when all is said in done better outcomes concerning simply unsupervised methodologies, which are frequently founded on chart-based strategies that think about social ties in audit destinations. besides, this work proposes and assesses.
{"title":"Feature Analysis for Fake Review Detection through Supervised Classification","authors":"P. Tiwari, Rishi Gupta, R. Gupta","doi":"10.1109/ICCT46177.2019.8969059","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969059","url":null,"abstract":"Presently days, audit destinations are increasingly more defied with the spread of falsehood, i.e., assessment spam, which goes for advancing or harming some objective organizations, by deceiving either human peruses, or computerized feeling mining and opinion investigation frameworks. Thus, in the most recent years, a few information-driven methodologies have been proposed to survey the believability of client created content diffused through online life as on-line audits. Particular methodologies frequently think about various subsets of qualities, i.e., highlights, associated with the two audits and commentators, just as to the system structure connecting unmistakable elements on the survey site in test. This work goes for giving an examination of the fundamental audit and commentator driven highlights that have been proposed up to now in the writing to identify counterfeit surveys, specifically from those methodologies that utilize directed AI systems. These arrangements furnish when all is said in done better outcomes concerning simply unsupervised methodologies, which are frequently founded on chart-based strategies that think about social ties in audit destinations. besides, this work proposes and assesses.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127156703","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969058
T. Roshini, P. Sireesha, Dhanush Parasa, Shahana Bano
Social media is one of the most important aspects of our day to day life. For you my wonder what exactly is social media. Social media is nothing more than a website or an application that is used to create and share content among a social networking. Recent studies claim that an average person spends roughly 142 minutes per day on some form of social media. Now that may seem like a small number but considering how many people are addicted to social media might make the number far larger. Over the past few years the daily usage of social media for an average person has increased from a mere 100 minutes per day to its current 142 minutes per day. Although people around the world are spending a chunk of their day on social media platforms it is hard to identify whether such platforms are a boon or a con for mankind. Although most people argue that social media is purely a waste of time, a recent study was able to establish a conclusion that people who use social media have lower stress levels. A women who used social media several times a day scored 21% less stress levels then that of a women who had no interest of social media at all. However there are many argument out there to support that it is a bad influence among people as well. One of the most popular one being the fact that people simply are so caught up with social media that they forget the value or even how to interact with someone face to face. We weren't particularly interested in the effects of social media but we wanted to learn what types of social media platforms people preferred. Considering the fact that we live in a digital era where any data on the internet can be easily manipulated we wanted to find out how secure people felt on each social media platform. Keeping all these in mind we decided to learn more about people's approach to social media platforms. “How Do People React and Feel Towards Their Social Media Platforms?”
{"title":"Social Media Survey using Decision Tree and Naive Bayes Classification","authors":"T. Roshini, P. Sireesha, Dhanush Parasa, Shahana Bano","doi":"10.1109/ICCT46177.2019.8969058","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969058","url":null,"abstract":"Social media is one of the most important aspects of our day to day life. For you my wonder what exactly is social media. Social media is nothing more than a website or an application that is used to create and share content among a social networking. Recent studies claim that an average person spends roughly 142 minutes per day on some form of social media. Now that may seem like a small number but considering how many people are addicted to social media might make the number far larger. Over the past few years the daily usage of social media for an average person has increased from a mere 100 minutes per day to its current 142 minutes per day. Although people around the world are spending a chunk of their day on social media platforms it is hard to identify whether such platforms are a boon or a con for mankind. Although most people argue that social media is purely a waste of time, a recent study was able to establish a conclusion that people who use social media have lower stress levels. A women who used social media several times a day scored 21% less stress levels then that of a women who had no interest of social media at all. However there are many argument out there to support that it is a bad influence among people as well. One of the most popular one being the fact that people simply are so caught up with social media that they forget the value or even how to interact with someone face to face. We weren't particularly interested in the effects of social media but we wanted to learn what types of social media platforms people preferred. Considering the fact that we live in a digital era where any data on the internet can be easily manipulated we wanted to find out how secure people felt on each social media platform. Keeping all these in mind we decided to learn more about people's approach to social media platforms. “How Do People React and Feel Towards Their Social Media Platforms?”","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127185992","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8968786
Lavina Nagpal, Meghna Jaglan, Anuraj Kathait, Aakil Mathur, A. Vichare
This paper explores the realms of creating a user-friendly and highly interactive environment for e-learning. It offers an in depth explanation about how a web based application along with Unity can be built to allow the user to learn myriad of subjects with ease. The end user can access a farrago of e-learning modes such as basic mode, game mode, fast track mode, and certification mode for a wide range of concepts and their topics. The paper gives detailed information about the requirement specifications for building such an e-learning portal and its proposed architecture and flow diagrams. It then further explains how to build these modes in Unity using C# to write the scripts and then embed them into a web application subsequently. The paper concludes by offering critical analysis on developing such an e-learning application and the benefits of each mode.
{"title":"SOUL: Simulation of Objects in Unity for Learning","authors":"Lavina Nagpal, Meghna Jaglan, Anuraj Kathait, Aakil Mathur, A. Vichare","doi":"10.1109/ICCT46177.2019.8968786","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8968786","url":null,"abstract":"This paper explores the realms of creating a user-friendly and highly interactive environment for e-learning. It offers an in depth explanation about how a web based application along with Unity can be built to allow the user to learn myriad of subjects with ease. The end user can access a farrago of e-learning modes such as basic mode, game mode, fast track mode, and certification mode for a wide range of concepts and their topics. The paper gives detailed information about the requirement specifications for building such an e-learning portal and its proposed architecture and flow diagrams. It then further explains how to build these modes in Unity using C# to write the scripts and then embed them into a web application subsequently. The paper concludes by offering critical analysis on developing such an e-learning application and the benefits of each mode.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125968013","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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