Pub Date : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987787
Laxmi Kumari, Anjana Jain
Voltage Source Inverters (VSI) and Current Source Inverters (CSI) are very widely fit for industry. VSI have limited output AC voltage and requirement of a blanking time whereas Current Source Inverters always boost up the voltage and their use are restricted for drive applications. To overcome these limitations Impedance Network or Z-Source Inverters (ZSI) are utilized. Ideally Z-Source Inverters are the ones which have output voltage ranging from zero to infinity. This Buck-Boost capability along with regeneration in single stage configuration makes these inverters ideally suited for hybrid electric vehicles and drive applications. The rotor side power of an induction generator can be utilized by slip power recovery (SPR) controlled technique based on (ZSI). This paper presents the design of ZSI for improving the voltage level of SPR. The system of ZSI is simulated using MATLAB-Simulink platform and the pulse width modulation (PWM) for the inverter is generated using DSPIC microcontroller.
{"title":"Slip power recovery drive using Z-source inverter","authors":"Laxmi Kumari, Anjana Jain","doi":"10.1109/ICSSIT46314.2019.8987787","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987787","url":null,"abstract":"Voltage Source Inverters (VSI) and Current Source Inverters (CSI) are very widely fit for industry. VSI have limited output AC voltage and requirement of a blanking time whereas Current Source Inverters always boost up the voltage and their use are restricted for drive applications. To overcome these limitations Impedance Network or Z-Source Inverters (ZSI) are utilized. Ideally Z-Source Inverters are the ones which have output voltage ranging from zero to infinity. This Buck-Boost capability along with regeneration in single stage configuration makes these inverters ideally suited for hybrid electric vehicles and drive applications. The rotor side power of an induction generator can be utilized by slip power recovery (SPR) controlled technique based on (ZSI). This paper presents the design of ZSI for improving the voltage level of SPR. The system of ZSI is simulated using MATLAB-Simulink platform and the pulse width modulation (PWM) for the inverter is generated using DSPIC microcontroller.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133802999","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 : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987827
N. Patil, A. Parveen
In general, Wireless Sensor network comprises of many sensor nodes that are used to sense and transmit that data to the nearer node. Likewise, the data is transferred to the destination or base station. Sensor network faces resource constraints & they are susceptible to environmental conditions which decrease the lifespan of the node. Our objective is to enhance the battery life of the sensor node based on data analyses technique (DAT), which is based on a comparative method. This technique will reduce the number of data transfer between sensor nodes, which in turn will enhance battery lifetime.
{"title":"Data Processing in a wireless sensor network using a data analytical technique (DAT)","authors":"N. Patil, A. Parveen","doi":"10.1109/ICSSIT46314.2019.8987827","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987827","url":null,"abstract":"In general, Wireless Sensor network comprises of many sensor nodes that are used to sense and transmit that data to the nearer node. Likewise, the data is transferred to the destination or base station. Sensor network faces resource constraints & they are susceptible to environmental conditions which decrease the lifespan of the node. Our objective is to enhance the battery life of the sensor node based on data analyses technique (DAT), which is based on a comparative method. This technique will reduce the number of data transfer between sensor nodes, which in turn will enhance battery lifetime.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129468705","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 : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987960
S. Ramya
Music is defined as an art which arranges the sounds to provide the inner feeling of happiness. Carnatic music is based on a Raga (Tune), Bhava (Emotion), Thala (Rhythm) and also characterized by Saptha swara (musical note), Sthayi and reference note (Shruthi). In this proposed work, an attempt is made to identify the swaras in Madhya Sthayi and constant Shruthi. The recorded music samples are analyzed in the frequency domain by using digital signal processing. The features are extracted and input to the probabilistic neural-network for the note identification. The performance of the system is verified for 25 samples for each note. The system success rate is above 90%.
{"title":"Smart Carnatic Music Note Identification (CMNI) System using Probabilistic Neural Network","authors":"S. Ramya","doi":"10.1109/ICSSIT46314.2019.8987960","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987960","url":null,"abstract":"Music is defined as an art which arranges the sounds to provide the inner feeling of happiness. Carnatic music is based on a Raga (Tune), Bhava (Emotion), Thala (Rhythm) and also characterized by Saptha swara (musical note), Sthayi and reference note (Shruthi). In this proposed work, an attempt is made to identify the swaras in Madhya Sthayi and constant Shruthi. The recorded music samples are analyzed in the frequency domain by using digital signal processing. The features are extracted and input to the probabilistic neural-network for the note identification. The performance of the system is verified for 25 samples for each note. The system success rate is above 90%.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114244208","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 : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987783
Asad Ali Jecko, Md. Zabir Arkam Akhond, S. Biswas, M. M. Rahman, S. Akter, Yeasin Ahmed Siam
Drinking pure water and using clean water are the most important factors for human body. It is observed commonly in our country that people are not aware of using water in households. Besides the natural sources of clean and pure water on the earth surface is decreasing day by day. On the other hand, the demand for clean and pure water is increasing due to rapid population growth in our country. It is observed in households that much water is being wasted due to overflow in water tank. Besides, much electric power is being lost due to lack of water pump controlling system. In this project, a calculation has been shown on economic effect due to overflow of water. To address the problem, a water level and water pump controlling system has been designed. In the development of the system a float switch, two indicator lamps, a relay, a magnetic contactor and an alarm have been used. In this project, relay plays an important role in safety which keeps the whole system out of power when accidently or due system fault the water is electrified. Though whole system goes out of power, relay will remain active by taking power from supply though itself. The system has gone under many trials. Finally, a successful and effective operation has been observed under different environments. The main advantages of the sophisticated system are environmentally friendliness, easiness of installation and maintenance, cost effectiveness and availability of its parts.
{"title":"Design and Implementation of Wireless Monitor and Controlling System for the identification of water level","authors":"Asad Ali Jecko, Md. Zabir Arkam Akhond, S. Biswas, M. M. Rahman, S. Akter, Yeasin Ahmed Siam","doi":"10.1109/ICSSIT46314.2019.8987783","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987783","url":null,"abstract":"Drinking pure water and using clean water are the most important factors for human body. It is observed commonly in our country that people are not aware of using water in households. Besides the natural sources of clean and pure water on the earth surface is decreasing day by day. On the other hand, the demand for clean and pure water is increasing due to rapid population growth in our country. It is observed in households that much water is being wasted due to overflow in water tank. Besides, much electric power is being lost due to lack of water pump controlling system. In this project, a calculation has been shown on economic effect due to overflow of water. To address the problem, a water level and water pump controlling system has been designed. In the development of the system a float switch, two indicator lamps, a relay, a magnetic contactor and an alarm have been used. In this project, relay plays an important role in safety which keeps the whole system out of power when accidently or due system fault the water is electrified. Though whole system goes out of power, relay will remain active by taking power from supply though itself. The system has gone under many trials. Finally, a successful and effective operation has been observed under different environments. The main advantages of the sophisticated system are environmentally friendliness, easiness of installation and maintenance, cost effectiveness and availability of its parts.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115177123","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 : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987588
Shweta S. Meshram, N. Kolhare
In recent years, Software defined radio has become a cost efficient and reliable communication paradigm where it's RF front end is simplest as compared to the conventional SCR (software controlled radio). In this paper, we studied the technological revolution that is SDR communication system consists of an antenna contained with the RTL SDR USB dongle RTLU3832 and freeware GNU radio software support which highly reduce the limitations of the controlled radio. The SDR device are widely used to examine the radio Spectrum and digitize I/Q signals that are being transmitted in the range 25 MHz to 1.75 GHz by the digital communications community. The frequency bands that contains signals such as FM radio, ISM signals, GSM, 3G and LTE mobile radio, GPS, and so on can be sampled in this wide operating range. SDR give us wide scope to hold the experimentations on the real world signals with cost efficient hardware solution and GNU radio flowgraph. FM reception with SDR model is studied and illustrated with an example extent so that one can demonstrate and explore the desired frequency spectrum.
{"title":"The advent software defined radio: FM receiver with RTL SDR and GNU radio","authors":"Shweta S. Meshram, N. Kolhare","doi":"10.1109/ICSSIT46314.2019.8987588","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987588","url":null,"abstract":"In recent years, Software defined radio has become a cost efficient and reliable communication paradigm where it's RF front end is simplest as compared to the conventional SCR (software controlled radio). In this paper, we studied the technological revolution that is SDR communication system consists of an antenna contained with the RTL SDR USB dongle RTLU3832 and freeware GNU radio software support which highly reduce the limitations of the controlled radio. The SDR device are widely used to examine the radio Spectrum and digitize I/Q signals that are being transmitted in the range 25 MHz to 1.75 GHz by the digital communications community. The frequency bands that contains signals such as FM radio, ISM signals, GSM, 3G and LTE mobile radio, GPS, and so on can be sampled in this wide operating range. SDR give us wide scope to hold the experimentations on the real world signals with cost efficient hardware solution and GNU radio flowgraph. FM reception with SDR model is studied and illustrated with an example extent so that one can demonstrate and explore the desired frequency spectrum.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114460599","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 : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987967
B. Pushpa, M. Kamarasan
This paper presents a new video summarization (VS) model, which summarizes the original and generally captured videos. The intention lies in the creation of precise summary which will convey the entire information. The summary includes the attractive and representative of the original video series. The earlier techniques are mainly based on simple considerations and optimizations. At the same time, they have utilized a hand-oriented objective which undergo sequential optimization by taking hard decisions. It restricts the usage in wide applicability. In this paper, a Submodular Convex Optimization (SCX) and dynamic support vector machine (DSVM) based VS model called Submodular Dynamical Video Summarization (SDVS) model is introduced. SCX is used for subset selection and DSVM is applied to classify the video summary. At the initial level, video sequence is given as input to the SDVS model. The transformation of input videos takes place to a set of frames. Next, extraction of key frames is carried out form the entire frame count for the generation of the video summary. For measuring the goodness of the SDVS model, a set of 8 videos are gathered from the Internet sources. The simulation outcome pointed out that the presented model achieved a maximum precision of 88.54, recall of 89.32 and accuracy of 88.91 respectively.
{"title":"Video Summarization using Submodular Convex Optimization with Dynamic Support Vector Machine for Forest Fire Sequence Classification","authors":"B. Pushpa, M. Kamarasan","doi":"10.1109/ICSSIT46314.2019.8987967","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987967","url":null,"abstract":"This paper presents a new video summarization (VS) model, which summarizes the original and generally captured videos. The intention lies in the creation of precise summary which will convey the entire information. The summary includes the attractive and representative of the original video series. The earlier techniques are mainly based on simple considerations and optimizations. At the same time, they have utilized a hand-oriented objective which undergo sequential optimization by taking hard decisions. It restricts the usage in wide applicability. In this paper, a Submodular Convex Optimization (SCX) and dynamic support vector machine (DSVM) based VS model called Submodular Dynamical Video Summarization (SDVS) model is introduced. SCX is used for subset selection and DSVM is applied to classify the video summary. At the initial level, video sequence is given as input to the SDVS model. The transformation of input videos takes place to a set of frames. Next, extraction of key frames is carried out form the entire frame count for the generation of the video summary. For measuring the goodness of the SDVS model, a set of 8 videos are gathered from the Internet sources. The simulation outcome pointed out that the presented model achieved a maximum precision of 88.54, recall of 89.32 and accuracy of 88.91 respectively.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131974984","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 : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987864
J. Sahu, S. Sahu, J. P. Patra, S. K. Maharana, B. Panda
Generally, two devices are responsible for generation of time variant power. They are alternator and inverter. Harmonics are the unwanted signals generally created on the output of the inverter. In this paper hysteresis current control inverters are described. Here the HCC Inverters are connected with grid and without grid and integrated with a photo voltaic panel. The HCC inverters are connected to grid by the help of phase lock loop. Finally total harmonics distortion is calculated of this model and compares their results based on total harmonics distortion.
{"title":"Harmonics analysis of a PV integrated Hysteresis current control inverter connected with grid and without grid","authors":"J. Sahu, S. Sahu, J. P. Patra, S. K. Maharana, B. Panda","doi":"10.1109/ICSSIT46314.2019.8987864","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987864","url":null,"abstract":"Generally, two devices are responsible for generation of time variant power. They are alternator and inverter. Harmonics are the unwanted signals generally created on the output of the inverter. In this paper hysteresis current control inverters are described. Here the HCC Inverters are connected with grid and without grid and integrated with a photo voltaic panel. The HCC inverters are connected to grid by the help of phase lock loop. Finally total harmonics distortion is calculated of this model and compares their results based on total harmonics distortion.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"356 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134376414","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 : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987793
L. Nanda, S. V
In this paper, a literature review on SETI signal spectrogram image classification is presented. Since there has been an abundance of astronomical data, automation seems to be the easier solution for classification and this brings in machine learning into the picture. In this paper, we have discussed both traditional methods and automated methods and also made an analysis of which algorithm comparatively has better performance. We cover classical machine vision along with machine deep learning approach to prototype signal classifiers for extraterrestrial intelligence. Our novel approach uses two-dimensional spectrograms of regular and assumed radio signals taking the establishment of a technological source. The research are executed by applying archived narrow-band signal data taken from real-time SETI observations along the Allen Telescope Array and a set of digitally assumed signals created to mimic real noticed signals. By considering the 2D spectrogram as an image, we exhibit that high quality parametric as well as nonparametric classifiers established on automatic visual analysis can attain high levels of intolerance and efficiency, along with low false-positive rates.
{"title":"SETI (Search for Extra Terrestrial Intelligence) Signal Classification using Machine Learning","authors":"L. Nanda, S. V","doi":"10.1109/ICSSIT46314.2019.8987793","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987793","url":null,"abstract":"In this paper, a literature review on SETI signal spectrogram image classification is presented. Since there has been an abundance of astronomical data, automation seems to be the easier solution for classification and this brings in machine learning into the picture. In this paper, we have discussed both traditional methods and automated methods and also made an analysis of which algorithm comparatively has better performance. We cover classical machine vision along with machine deep learning approach to prototype signal classifiers for extraterrestrial intelligence. Our novel approach uses two-dimensional spectrograms of regular and assumed radio signals taking the establishment of a technological source. The research are executed by applying archived narrow-band signal data taken from real-time SETI observations along the Allen Telescope Array and a set of digitally assumed signals created to mimic real noticed signals. By considering the 2D spectrogram as an image, we exhibit that high quality parametric as well as nonparametric classifiers established on automatic visual analysis can attain high levels of intolerance and efficiency, along with low false-positive rates.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134629443","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 : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987794
S. Routray, A. Javali, Laxmi Sharma, Aritri Ghosh, Anindita Sahoo
Precision agriculture (PA) is associated with the engineering of exact needs of plants and their productivities. In the modern times, PA uses a large number of sensors in a networked architecture to collect the information on the exact needs of the plants and their productivities. With the arrival of Internet of things (IoT), now PA can be implemented quite systematically. Undoubtedly, agriculture is one of the most important economic sectors of the world. For the developing countries, it is an essential sector. Agriculture is directly associated with the daily needs of human being such as food, clothing, and shelter. In the recent years, developing countries are facing a lot of difficulties in the agriculture related aspects such as lack of water for irrigation, desertification of fertile land, and reduction in harvests. PA can ease these problems through the use of IoT based applications. In this paper, we provide the recent frameworks of PA using IoT. We show how it can help the agricultural sectors of the developing countries in the long term.
{"title":"Internet of Things Based Precision Agriculture for Developing Countries","authors":"S. Routray, A. Javali, Laxmi Sharma, Aritri Ghosh, Anindita Sahoo","doi":"10.1109/ICSSIT46314.2019.8987794","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987794","url":null,"abstract":"Precision agriculture (PA) is associated with the engineering of exact needs of plants and their productivities. In the modern times, PA uses a large number of sensors in a networked architecture to collect the information on the exact needs of the plants and their productivities. With the arrival of Internet of things (IoT), now PA can be implemented quite systematically. Undoubtedly, agriculture is one of the most important economic sectors of the world. For the developing countries, it is an essential sector. Agriculture is directly associated with the daily needs of human being such as food, clothing, and shelter. In the recent years, developing countries are facing a lot of difficulties in the agriculture related aspects such as lack of water for irrigation, desertification of fertile land, and reduction in harvests. PA can ease these problems through the use of IoT based applications. In this paper, we provide the recent frameworks of PA using IoT. We show how it can help the agricultural sectors of the developing countries in the long term.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121794303","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 : 2019-11-01DOI: 10.1109/ICSSIT46314.2019.8987844
S. Sree, S. Vyshnavi, N. Jayapandian
The world today is running on the latest computer technologies and one of those is machine learning. The real life example that most of us know is speech recognition. Google Assistant is the common example for this Speech recognition. This google assistant is not only limited till ‘Ok Google’, but it responds to all your questions in a smart way. It can manage all your calls or can book appointments. Imagine you fell down while de-boarding a bus. So, Next time you take care so that you don't fall that is something that your brain has interpreted from your past experience. This is what exactly deep learning is, it imitates human brain works. Deep learning is sub-branch of machine learning. It is able to build all new things based on its previous experiences. Many of us have heard about driverless cars and medical diagnosis. Recently google has developed a new technology where all your cardiovascular events can be predicted by eye scan so, that doctors can get a clear view of what is inside the body of a patient. These all are developed using machine learning. It has a capability to change the human world into a complete robotic world. Anyways, it also has its own disadvantages. This article discusses about those, Scope of machine learning, its Market potential, financial growth and Current applications of machine learning.
{"title":"Real-World Application of Machine Learning and Deep Learning","authors":"S. Sree, S. Vyshnavi, N. Jayapandian","doi":"10.1109/ICSSIT46314.2019.8987844","DOIUrl":"https://doi.org/10.1109/ICSSIT46314.2019.8987844","url":null,"abstract":"The world today is running on the latest computer technologies and one of those is machine learning. The real life example that most of us know is speech recognition. Google Assistant is the common example for this Speech recognition. This google assistant is not only limited till ‘Ok Google’, but it responds to all your questions in a smart way. It can manage all your calls or can book appointments. Imagine you fell down while de-boarding a bus. So, Next time you take care so that you don't fall that is something that your brain has interpreted from your past experience. This is what exactly deep learning is, it imitates human brain works. Deep learning is sub-branch of machine learning. It is able to build all new things based on its previous experiences. Many of us have heard about driverless cars and medical diagnosis. Recently google has developed a new technology where all your cardiovascular events can be predicted by eye scan so, that doctors can get a clear view of what is inside the body of a patient. These all are developed using machine learning. It has a capability to change the human world into a complete robotic world. Anyways, it also has its own disadvantages. This article discusses about those, Scope of machine learning, its Market potential, financial growth and Current applications of machine learning.","PeriodicalId":330309,"journal":{"name":"2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123572143","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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