Pub Date : 2020-02-18DOI: 10.1109/ICCDW45521.2020.9318678
Shreyas Kulkarni, Namrata Walavalkar, Varoon Chhatre, Pratiksha Singh, P. Sharma
Electric vehicles (EV) and Hybrid Electric Vehicles (HEV) contribute to substantially decrease the carbon footprint of the present means of transport. Battery is a critical component in every EV topology. The reliable and safe operation of a battery requires the presence of an independent controlling platform which is often referred to as Battery Management System (BMS). The state monitoring and charge optimization functionalities are to be incorporated in the BMS, to ensure the safety and reliability of the energy source which is battery. Due to the irregular operating parameters of the battery the overall system may be jeopardized. The paper herein offers a review to the up-to-date technologies on Battery Management System observing the State Evaluation of the battery including state of charge (SOC), State of Health (SOH), Depth of Discharge (DOD) and State of Life of the battery.
电动汽车(EV)和混合动力电动汽车(HEV)有助于大幅减少现有交通工具的碳足迹。电池是电动汽车拓扑结构中的关键部件。电池的可靠和安全运行需要一个独立的控制平台，通常被称为电池管理系统(BMS)。在BMS中加入状态监测和充电优化功能，以确保电池能源的安全可靠。由于电池的运行参数不规律，可能会对整个系统造成危害。本文综述了电池状态监测系统的最新技术，包括电池的充电状态(SOC)、健康状态(SOH)、放电深度(DOD)和寿命状态(State of Life)。
{"title":"Review of Optimization of Charge on VRLA Battery and Lithium Ion Battery Operated Bike","authors":"Shreyas Kulkarni, Namrata Walavalkar, Varoon Chhatre, Pratiksha Singh, P. Sharma","doi":"10.1109/ICCDW45521.2020.9318678","DOIUrl":"https://doi.org/10.1109/ICCDW45521.2020.9318678","url":null,"abstract":"Electric vehicles (EV) and Hybrid Electric Vehicles (HEV) contribute to substantially decrease the carbon footprint of the present means of transport. Battery is a critical component in every EV topology. The reliable and safe operation of a battery requires the presence of an independent controlling platform which is often referred to as Battery Management System (BMS). The state monitoring and charge optimization functionalities are to be incorporated in the BMS, to ensure the safety and reliability of the energy source which is battery. Due to the irregular operating parameters of the battery the overall system may be jeopardized. The paper herein offers a review to the up-to-date technologies on Battery Management System observing the State Evaluation of the battery including state of charge (SOC), State of Health (SOH), Depth of Discharge (DOD) and State of Life of the battery.","PeriodicalId":282429,"journal":{"name":"2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129727163","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 : 2020-02-18DOI: 10.1109/ICCDW45521.2020.9318672
Sanyog Vyawahare, Kaustubh Chakradeo
This work demonstrates an experimental implementation of a helper bot using IBM Watson. It is primarily aimed at people who know English as a second language. With the help of IBM Watson Assistant tool, the chatbot uses APIs like Google Translate API, Text to Speech API, SimpleWIki and Musixmatch API, to provide features like rich responses, translation to regional languages, text to speech conversion facilities, useful information in simpler English, and displaying music lyrics for music in regional languages. This is particularly helpful for those who are newly learning English and are more comfortable in their regional language.
这项工作演示了使用IBM Watson的助手机器人的实验性实现。它主要是针对那些把英语作为第二语言的人。在IBM Watson Assistant工具的帮助下，聊天机器人使用谷歌Translate API、Text to Speech API、SimpleWIki和Musixmatch API等API，提供丰富的响应、区域语言翻译、文本到语音转换设施、简单英语的有用信息以及显示区域语言音乐的歌词等功能。这对那些刚开始学习英语的人特别有帮助，他们对当地的语言更熟悉。
{"title":"Chatbot Assistant for English as a Second Language Learners","authors":"Sanyog Vyawahare, Kaustubh Chakradeo","doi":"10.1109/ICCDW45521.2020.9318672","DOIUrl":"https://doi.org/10.1109/ICCDW45521.2020.9318672","url":null,"abstract":"This work demonstrates an experimental implementation of a helper bot using IBM Watson. It is primarily aimed at people who know English as a second language. With the help of IBM Watson Assistant tool, the chatbot uses APIs like Google Translate API, Text to Speech API, SimpleWIki and Musixmatch API, to provide features like rich responses, translation to regional languages, text to speech conversion facilities, useful information in simpler English, and displaying music lyrics for music in regional languages. This is particularly helpful for those who are newly learning English and are more comfortable in their regional language.","PeriodicalId":282429,"journal":{"name":"2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126274023","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 : 2020-02-18DOI: 10.1109/ICCDW45521.2020.9318701
Pooja Khatri, S. Kadge, Uday. P. Chhatre
Humans are not able to detect all kinds of visible objects' movement. The human eyes can detect large motions like passing of vehicles, trains, waves of water, etc. and their ears are capable of catching smaller and faster movement of sound. So the human can notice the motion that are large and that can change the average shape or location of objects. The motion that does not change the average shape or location of the object is unnoticed or unseen by the naked human eye. These small and minute motions of the visible object are known as vibration. The unnoticed movement of the visible object are silent but carry an enormous amount of information and that is unknown by humans. The objects surface vibrates when a wave of sound hits an object or when it is under the influence of some unknown forces or wind. The information from these vibrating objects surface can be gathered with the use of many traditional vibration sensors. With the technological advancements in the field of computer vision and graphics shows how a camera can serve as a tool for extracting and analyzing the vibrations from the visible objects surface. This information from the vibrating visible objects surface can be very useful in many applications ranging from audio recovery to structural health monitoring and non-destructive testing of the civil structures. This review paper focuses on the use of the camera as a vibration sensor for extracting the information from vibrating objects surface and explains how this extracted information can be useful in numerous applications such as Extraction of the sound from video, recovery of speech, CCTV surveillance, structural health monitoring of the various objects, non-destructive testing, approximating the material properties of the various fabrics, predicting the properties of the various rods or objects under the influence of unknown forces and many more.
{"title":"Review of Different Applications Using Visual Vibration Analysis","authors":"Pooja Khatri, S. Kadge, Uday. P. Chhatre","doi":"10.1109/ICCDW45521.2020.9318701","DOIUrl":"https://doi.org/10.1109/ICCDW45521.2020.9318701","url":null,"abstract":"Humans are not able to detect all kinds of visible objects' movement. The human eyes can detect large motions like passing of vehicles, trains, waves of water, etc. and their ears are capable of catching smaller and faster movement of sound. So the human can notice the motion that are large and that can change the average shape or location of objects. The motion that does not change the average shape or location of the object is unnoticed or unseen by the naked human eye. These small and minute motions of the visible object are known as vibration. The unnoticed movement of the visible object are silent but carry an enormous amount of information and that is unknown by humans. The objects surface vibrates when a wave of sound hits an object or when it is under the influence of some unknown forces or wind. The information from these vibrating objects surface can be gathered with the use of many traditional vibration sensors. With the technological advancements in the field of computer vision and graphics shows how a camera can serve as a tool for extracting and analyzing the vibrations from the visible objects surface. This information from the vibrating visible objects surface can be very useful in many applications ranging from audio recovery to structural health monitoring and non-destructive testing of the civil structures. This review paper focuses on the use of the camera as a vibration sensor for extracting the information from vibrating objects surface and explains how this extracted information can be useful in numerous applications such as Extraction of the sound from video, recovery of speech, CCTV surveillance, structural health monitoring of the various objects, non-destructive testing, approximating the material properties of the various fabrics, predicting the properties of the various rods or objects under the influence of unknown forces and many more.","PeriodicalId":282429,"journal":{"name":"2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126415163","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 : 2020-02-18DOI: 10.1109/ICCDW45521.2020.9318713
Udit Doshi, Vaibhav Barot, Sachin Gavhane
The usage of social media platform such as Facebook, Instagram, Flicker, etc. is rising day by day wherein images play a major role. It is said “An image is worth a thousand words”, people these days upload certain images on these sites to display their sentiments and emotions in the form of picture on almost every occasion. Images play the most important role in today's generation where it has become a major part of everyone's lives. Most of the prevailing research have focused on sentiment analyses of textual data, but only limited researches have focused on analyzing sentiment of visual data. In this project, we have explored the possibilities of Convolutional Neural Networks (CNN) to predict the various emotions (happiness, surprise, sadness, fear, anger and neutral) depicted by an image. These sort of predictions can be useful in applications for automatic tag predictions of the visual data available on social media platforms and understanding sentiments of the people and their emotions.
{"title":"Emotion Detection and Sentiment Analysis of Static Images","authors":"Udit Doshi, Vaibhav Barot, Sachin Gavhane","doi":"10.1109/ICCDW45521.2020.9318713","DOIUrl":"https://doi.org/10.1109/ICCDW45521.2020.9318713","url":null,"abstract":"The usage of social media platform such as Facebook, Instagram, Flicker, etc. is rising day by day wherein images play a major role. It is said “An image is worth a thousand words”, people these days upload certain images on these sites to display their sentiments and emotions in the form of picture on almost every occasion. Images play the most important role in today's generation where it has become a major part of everyone's lives. Most of the prevailing research have focused on sentiment analyses of textual data, but only limited researches have focused on analyzing sentiment of visual data. In this project, we have explored the possibilities of Convolutional Neural Networks (CNN) to predict the various emotions (happiness, surprise, sadness, fear, anger and neutral) depicted by an image. These sort of predictions can be useful in applications for automatic tag predictions of the visual data available on social media platforms and understanding sentiments of the people and their emotions.","PeriodicalId":282429,"journal":{"name":"2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122829501","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 : 2020-02-18DOI: 10.1109/ICCDW45521.2020.9318707
Nidhi Gupta
For estimating the software reliability, it is required to observe its failure intensity. As failure intensity depends upon the number of faults, so to find the number of faults we are using the adaptive resonance theory (ART) of ANN, which is based on the best match strategy of competitive learning. The ART is able to incorporate the two different modes i.e. plasticity and stability [1]. This method provides the direct mapping between existing similarities so that the networks find the sufficiently closed match with the input pattern and the corresponding number of faults can be estimated. If the unknown prototype input pattern belongs to any generated category of the network then network displays the accretive behavior. In this case the corresponding number of faults will be same as the already defined number of faults for that group through the predictive unit. If the presented prototype input pattern does not belong to any generated category of the network that the network shows the interpolative behavior, the corresponding faults for this prototype input pattern can be determined from the average of the faults in the neighboring groups of already trained pattern. This new group will be neighbor of all the groups that shows the approximate same orientation.
{"title":"Software Reliability Estimation with ART Network of Artificial Neural Network Using Execution Time Model","authors":"Nidhi Gupta","doi":"10.1109/ICCDW45521.2020.9318707","DOIUrl":"https://doi.org/10.1109/ICCDW45521.2020.9318707","url":null,"abstract":"For estimating the software reliability, it is required to observe its failure intensity. As failure intensity depends upon the number of faults, so to find the number of faults we are using the adaptive resonance theory (ART) of ANN, which is based on the best match strategy of competitive learning. The ART is able to incorporate the two different modes i.e. plasticity and stability [1]. This method provides the direct mapping between existing similarities so that the networks find the sufficiently closed match with the input pattern and the corresponding number of faults can be estimated. If the unknown prototype input pattern belongs to any generated category of the network then network displays the accretive behavior. In this case the corresponding number of faults will be same as the already defined number of faults for that group through the predictive unit. If the presented prototype input pattern does not belong to any generated category of the network that the network shows the interpolative behavior, the corresponding faults for this prototype input pattern can be determined from the average of the faults in the neighboring groups of already trained pattern. This new group will be neighbor of all the groups that shows the approximate same orientation.","PeriodicalId":282429,"journal":{"name":"2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116985288","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 : 2020-02-18DOI: 10.1109/ICCDW45521.2020.9318718
Sachin Gavhane, Amruta Pokhare, S. Shitole
Images caught in darker area builds complexities in handling and removing essential data. Improvement of such pictures encourages us to recover significant information. ANN based error back propagation (BP) algorithm is used for enhancing shadow region of an image. Dataset used in this paper is a shadow image with its enhanced output (log transformed), so that model will be able to learn to enhance the shadow region of any given image. Darker locale in an image are successfully reduced in the results obtained. Still there is a scope of improvement through adjustments and variations into various parameters of proposed non-parametric approach.
{"title":"Non-Parametric Method for Enhancement of Darker Portion in an Image","authors":"Sachin Gavhane, Amruta Pokhare, S. Shitole","doi":"10.1109/ICCDW45521.2020.9318718","DOIUrl":"https://doi.org/10.1109/ICCDW45521.2020.9318718","url":null,"abstract":"Images caught in darker area builds complexities in handling and removing essential data. Improvement of such pictures encourages us to recover significant information. ANN based error back propagation (BP) algorithm is used for enhancing shadow region of an image. Dataset used in this paper is a shadow image with its enhanced output (log transformed), so that model will be able to learn to enhance the shadow region of any given image. Darker locale in an image are successfully reduced in the results obtained. Still there is a scope of improvement through adjustments and variations into various parameters of proposed non-parametric approach.","PeriodicalId":282429,"journal":{"name":"2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124250367","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 : 2020-02-18DOI: 10.1109/ICCDW45521.2020.9318666
S. Malik, Ruchir Chauhan
The Internet of Things facilitates integration of massive group of devices into networks to provide data for an ever-growing number of applications. The current and future IoT applications holds promise to improve the convenience and comfort for the user but are prone to various types of security threats namely Denial of Service (DoS), Man-in-the-Middle, spoofing, Jamming, Eavesdropping and software attacks. Therefore, it becomes crucial to address these security challenges. In this paper, we discuss major security threats that exist at IoT layers and review Machine Learning based IoT security systems with a focus on Supervised Learning.
{"title":"Securing the Internet of Things using Machine Learning: A Review","authors":"S. Malik, Ruchir Chauhan","doi":"10.1109/ICCDW45521.2020.9318666","DOIUrl":"https://doi.org/10.1109/ICCDW45521.2020.9318666","url":null,"abstract":"The Internet of Things facilitates integration of massive group of devices into networks to provide data for an ever-growing number of applications. The current and future IoT applications holds promise to improve the convenience and comfort for the user but are prone to various types of security threats namely Denial of Service (DoS), Man-in-the-Middle, spoofing, Jamming, Eavesdropping and software attacks. Therefore, it becomes crucial to address these security challenges. In this paper, we discuss major security threats that exist at IoT layers and review Machine Learning based IoT security systems with a focus on Supervised Learning.","PeriodicalId":282429,"journal":{"name":"2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129753857","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 : 2020-02-18DOI: 10.1109/ICCDW45521.2020.9318655
Darshan Makwana, Divyesh Khandhedia, Shubham Gamre, Shankar Warang, K. Nikum
The electricity requirement of the world including India is increasing at alarming rate and the power demand has been running ahead of supply. In current scenario electricity generation in the world is 60 percent by conventional sources and remaining by renewable sources. The main limitation of renewable energy sources on various geographical conditions to generate electricity is fluctuating power and conventional resources present in a limited quantity. It is important to solve the problem of conventional and renewable power sources in order to reduce the amount of electricity used from conventional power plants leads to reduce the burden on fossil fuels. This paper is about generation of electricity from gravitational energy called ‘GRAVITATOR’ which increases reliability and its power generation is inexhaustible. The proposed solution includes development of mechanical design model for gravitator. The arrangement converts the gravitational energy into mechanical energy and resulting in electrical energy.
{"title":"Gravitator - A Gravity Based Power Generator","authors":"Darshan Makwana, Divyesh Khandhedia, Shubham Gamre, Shankar Warang, K. Nikum","doi":"10.1109/ICCDW45521.2020.9318655","DOIUrl":"https://doi.org/10.1109/ICCDW45521.2020.9318655","url":null,"abstract":"The electricity requirement of the world including India is increasing at alarming rate and the power demand has been running ahead of supply. In current scenario electricity generation in the world is 60 percent by conventional sources and remaining by renewable sources. The main limitation of renewable energy sources on various geographical conditions to generate electricity is fluctuating power and conventional resources present in a limited quantity. It is important to solve the problem of conventional and renewable power sources in order to reduce the amount of electricity used from conventional power plants leads to reduce the burden on fossil fuels. This paper is about generation of electricity from gravitational energy called ‘GRAVITATOR’ which increases reliability and its power generation is inexhaustible. The proposed solution includes development of mechanical design model for gravitator. The arrangement converts the gravitational energy into mechanical energy and resulting in electrical energy.","PeriodicalId":282429,"journal":{"name":"2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127554859","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 : 2020-02-18DOI: 10.1109/ICCDW45521.2020.9318640
Joslyn Benalva Gracias
Human nerve signal are being extensively studied in recent times due to their undeniable control on human physiological system. These Myoelectric signals have been and continue to be analyzed for medical data processing devices and human assistance robots. In this paper, a prospective procedure to analyze EMG signals has been proposed which synthesizes the techniques that have been evaluated individually to perform designed processing. Initially the paper briefly reviews the conventional EMG acquisition method followed by the overview of the proposed data analysis techniques that involve the segmenting data, disregarding redundant data and classification of significant data. The paper briefly reviews KF-LDA design that assembles KF's ability to estimate non-linear progressions and stable steady state LDA classification. The proposed evaluation system synthesizes the use of ANN and KF-LDA for data classification. Furthermore, the broad areas of application for EMG evaluation are listed followed by a summarized conclusion.
{"title":"Prospective Synthesis for Evaluation System of EMG Information Signal-An Overview","authors":"Joslyn Benalva Gracias","doi":"10.1109/ICCDW45521.2020.9318640","DOIUrl":"https://doi.org/10.1109/ICCDW45521.2020.9318640","url":null,"abstract":"Human nerve signal are being extensively studied in recent times due to their undeniable control on human physiological system. These Myoelectric signals have been and continue to be analyzed for medical data processing devices and human assistance robots. In this paper, a prospective procedure to analyze EMG signals has been proposed which synthesizes the techniques that have been evaluated individually to perform designed processing. Initially the paper briefly reviews the conventional EMG acquisition method followed by the overview of the proposed data analysis techniques that involve the segmenting data, disregarding redundant data and classification of significant data. The paper briefly reviews KF-LDA design that assembles KF's ability to estimate non-linear progressions and stable steady state LDA classification. The proposed evaluation system synthesizes the use of ANN and KF-LDA for data classification. Furthermore, the broad areas of application for EMG evaluation are listed followed by a summarized conclusion.","PeriodicalId":282429,"journal":{"name":"2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)","volume":"448 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134542627","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 : 2020-02-18DOI: 10.1109/ICCDW45521.2020.9318673
S. Vishwanath, Saurabh Sharma, K. Deshpande, Sneha Kanchan
Due to the increasing population in urban cities, there is an exponential rise in the number of vehicles which is leading to major problems leading to poor traffic management and congestion. Another major problem faced by the vehicle owners is the availability of parking space. The idea of Smart Cities is slowly gaining pace with the ever increasing technologies. Therefore, in the proposed parking system we are integrating the Wireless Sensor Technology with the Android Application so that the user can book or pre-book a slot. The vehicle owner will be able to reserve a slot for his/her vehicle from anywhere and will be provided with a QR code which will be scanned on the entry of the parking area. Another feature our system provides is providing information about the near-by parking areas which comes handy when the current parking area is full.
{"title":"Vehicle Parking Management System","authors":"S. Vishwanath, Saurabh Sharma, K. Deshpande, Sneha Kanchan","doi":"10.1109/ICCDW45521.2020.9318673","DOIUrl":"https://doi.org/10.1109/ICCDW45521.2020.9318673","url":null,"abstract":"Due to the increasing population in urban cities, there is an exponential rise in the number of vehicles which is leading to major problems leading to poor traffic management and congestion. Another major problem faced by the vehicle owners is the availability of parking space. The idea of Smart Cities is slowly gaining pace with the ever increasing technologies. Therefore, in the proposed parking system we are integrating the Wireless Sensor Technology with the Android Application so that the user can book or pre-book a slot. The vehicle owner will be able to reserve a slot for his/her vehicle from anywhere and will be provided with a QR code which will be scanned on the entry of the parking area. Another feature our system provides is providing information about the near-by parking areas which comes handy when the current parking area is full.","PeriodicalId":282429,"journal":{"name":"2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130770098","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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