Pub Date : 2023-05-11DOI: 10.1109/ICDT57929.2023.10150644
Prashant Kaushik, V. Saxena
With the new and emerging usages of faster video classification and identifications of new classes has pushed the research in this direction. Be it like similar video detection, percentage of similarity, anomaly detection or finding something trending in the current videos. Use of identification of objects in frames and features in surrounding has proven its advantages for video classifications specially for short video similarity detection. Use of temporally important objects and actions has also proved advantages for video classifications. However existing methods takes huge computation to train the model and does not detect the possibility of new classes. To address this scenario for faster video classification and reducing the training time and computation cost, we propose one directional temporal difference of frames and selectively selecting the spatial information with custom loss function. This allows faster training of the models and has a capability of detecting the new classes in the production videos. This new class detection will provide us new ways looking at video data and thus new kinds of platform conceptualization. Experiments were conducted in UCF and MSVD datasets. Validations were done using statistical methods like f-test etc. Validation for being faster in training are done using comparison of state of the art methods. The novelty of the work lies in the processing of video data for similarity detection in short video and new kinds of intelligence extraction. Which is generated from regression values for possible new classes of video.
{"title":"Fast Video Classification based on unidirectional temporal differences based dynamic spatial selection with custom loss function and new class suggestion","authors":"Prashant Kaushik, V. Saxena","doi":"10.1109/ICDT57929.2023.10150644","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10150644","url":null,"abstract":"With the new and emerging usages of faster video classification and identifications of new classes has pushed the research in this direction. Be it like similar video detection, percentage of similarity, anomaly detection or finding something trending in the current videos. Use of identification of objects in frames and features in surrounding has proven its advantages for video classifications specially for short video similarity detection. Use of temporally important objects and actions has also proved advantages for video classifications. However existing methods takes huge computation to train the model and does not detect the possibility of new classes. To address this scenario for faster video classification and reducing the training time and computation cost, we propose one directional temporal difference of frames and selectively selecting the spatial information with custom loss function. This allows faster training of the models and has a capability of detecting the new classes in the production videos. This new class detection will provide us new ways looking at video data and thus new kinds of platform conceptualization. Experiments were conducted in UCF and MSVD datasets. Validations were done using statistical methods like f-test etc. Validation for being faster in training are done using comparison of state of the art methods. The novelty of the work lies in the processing of video data for similarity detection in short video and new kinds of intelligence extraction. Which is generated from regression values for possible new classes of video.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129814578","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 : 2023-05-11DOI: 10.1109/ICDT57929.2023.10151115
B. Laxmaiah, Balamurugan Easwaran, H. P. Sultana, D. Praveenadevi, Likitha Sai Katragadda
The existing resource allocation mechanism in fog computing environment fails to allocate optimal resources in the network environment. Since, these mechanism fails to allocate increasing user data from the internet of things devices. It is hence necessary to model a system that enables processing of task based on the resource available. The paper explains an internet of things based fog computing for allocation of resources using deep learning computations. The deep learning model is trained, tested and validated in an efficient manner to allocate the task in fog environment when user IoT data is sent for storage and processing. The experimental validation shows increased network throughput and reduced losses while a task is allocated in the user computing environment.
{"title":"Iot Enabled Fog Based Computing with Deep Learning Models to Increase The Allocation of Resource","authors":"B. Laxmaiah, Balamurugan Easwaran, H. P. Sultana, D. Praveenadevi, Likitha Sai Katragadda","doi":"10.1109/ICDT57929.2023.10151115","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10151115","url":null,"abstract":"The existing resource allocation mechanism in fog computing environment fails to allocate optimal resources in the network environment. Since, these mechanism fails to allocate increasing user data from the internet of things devices. It is hence necessary to model a system that enables processing of task based on the resource available. The paper explains an internet of things based fog computing for allocation of resources using deep learning computations. The deep learning model is trained, tested and validated in an efficient manner to allocate the task in fog environment when user IoT data is sent for storage and processing. The experimental validation shows increased network throughput and reduced losses while a task is allocated in the user computing environment.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133252551","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}
Human Posture estimation is a field which gathers huge researchers interest due to its variations in different machine learning (ML) & deep learning (DL) architectures to estimate human postures This work includes tweaking of layers with varying neurons in Convolutional Neural Network Architecture to test which pair of neurons and layers gives the best accuracy, also visualizing each of the pair with help of graphs. The results of this work provide great results with high accuracy.
{"title":"Using Convolutional Neural Network for Human Posture Estimation: A study of the effects of number of layers and number of neurons on accuracy","authors":"Nalin Kashyap, Satnam Singh, Viswajeet Kumar, Kanika Singla","doi":"10.1109/ICDT57929.2023.10150730","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10150730","url":null,"abstract":"Human Posture estimation is a field which gathers huge researchers interest due to its variations in different machine learning (ML) & deep learning (DL) architectures to estimate human postures This work includes tweaking of layers with varying neurons in Convolutional Neural Network Architecture to test which pair of neurons and layers gives the best accuracy, also visualizing each of the pair with help of graphs. The results of this work provide great results with high accuracy.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132201375","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 : 2023-05-11DOI: 10.1109/ICDT57929.2023.10151422
Dr. Rashmi Sharma, Vishal Mishra, Suryansh Srivastava
Agriculture has a significant impact on the development of agricultural nations. One-third of India's GDP, and over 70% of its population, are dependent on agriculture. The nation's development has frequently been impeded by agricultural problems. The only solution to this problem is smart agriculture, which modernises the traditional farming techniques now in use. The Internet of Things (IoT) has many advantages for smart agriculture. Smart farming is a newly emerging concept because to IoT devices that may supply information about agricultural areas. In agricultural fields, various IoT sensors can be utilised to track the important factors that determine productivity. Based on a machine learning model's analysis of the soil's NPK value, the paper seeks to suggest the best crops for the particular field. The entire handling is centred on gathering data for usage by farmers and other collaborators. Farmers in the agriculture industry and IoT devices are increasingly bridging the digital divide. Intelligent greenhouses, which can have hydroponic and micro aquaponic systems, are another application for the Internet of Things. Intelligent greenhouses are becoming more prevalent in cities as they allow for the tracking of many components of fertiliser solutions and enhance plant growth, productivity, and quality. Future food production that is more environmentally friendly will increase output, and the environment will be safeguarded by using water wisely and maximising inputs and treatments. Remote monitoring, decision-support tools, automatic irrigation systems, frost prevention, fertilising, and other methods are all part of smart agriculture. IoT technology, which consists of hardware, intelligent software, integration platforms, monitoring strategies, operating systems, and cloud computing, enables these procedures.
{"title":"Enhancing Crop Yields through IoT-Enabled Precision Agriculture","authors":"Dr. Rashmi Sharma, Vishal Mishra, Suryansh Srivastava","doi":"10.1109/ICDT57929.2023.10151422","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10151422","url":null,"abstract":"Agriculture has a significant impact on the development of agricultural nations. One-third of India's GDP, and over 70% of its population, are dependent on agriculture. The nation's development has frequently been impeded by agricultural problems. The only solution to this problem is smart agriculture, which modernises the traditional farming techniques now in use. The Internet of Things (IoT) has many advantages for smart agriculture. Smart farming is a newly emerging concept because to IoT devices that may supply information about agricultural areas. In agricultural fields, various IoT sensors can be utilised to track the important factors that determine productivity. Based on a machine learning model's analysis of the soil's NPK value, the paper seeks to suggest the best crops for the particular field. The entire handling is centred on gathering data for usage by farmers and other collaborators. Farmers in the agriculture industry and IoT devices are increasingly bridging the digital divide. Intelligent greenhouses, which can have hydroponic and micro aquaponic systems, are another application for the Internet of Things. Intelligent greenhouses are becoming more prevalent in cities as they allow for the tracking of many components of fertiliser solutions and enhance plant growth, productivity, and quality. Future food production that is more environmentally friendly will increase output, and the environment will be safeguarded by using water wisely and maximising inputs and treatments. Remote monitoring, decision-support tools, automatic irrigation systems, frost prevention, fertilising, and other methods are all part of smart agriculture. IoT technology, which consists of hardware, intelligent software, integration platforms, monitoring strategies, operating systems, and cloud computing, enables these procedures.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128532589","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 : 2023-05-11DOI: 10.1109/ICDT57929.2023.10150832
Ramesh Babu P, P. Anitha, Wakgari Dibaba, R. Boddu
All throughout the world, the outdated cloud is being rapidly upgraded to the modern cloud that is currently being installed. A cloud comes with a number of potential benefits, yet it is not devoid of any potential downsides. The protection of the cloud from malicious cyber activity is an extremely important subject. The most challenging aspect is managing such a huge network because millions of sensors are constantly sending and receiving data packets over it. A convolutional neural network is incorporated into the model so that it can recognize phishing and application-layer DDoS attacks. The findings of the research provide evidence that the proposed model is effective in determining whether phishing attempts are being made. The findings make it abundantly evident that the strategy that was suggested can be utilized to identify attacks in a decentralized manner. The proposed methods achieve more amount of accuracy than the existing methods like LSTM and SAE.
{"title":"Mitigation of Attacks Using Cybersecurity Deep Models in Cloud Servers","authors":"Ramesh Babu P, P. Anitha, Wakgari Dibaba, R. Boddu","doi":"10.1109/ICDT57929.2023.10150832","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10150832","url":null,"abstract":"All throughout the world, the outdated cloud is being rapidly upgraded to the modern cloud that is currently being installed. A cloud comes with a number of potential benefits, yet it is not devoid of any potential downsides. The protection of the cloud from malicious cyber activity is an extremely important subject. The most challenging aspect is managing such a huge network because millions of sensors are constantly sending and receiving data packets over it. A convolutional neural network is incorporated into the model so that it can recognize phishing and application-layer DDoS attacks. The findings of the research provide evidence that the proposed model is effective in determining whether phishing attempts are being made. The findings make it abundantly evident that the strategy that was suggested can be utilized to identify attacks in a decentralized manner. The proposed methods achieve more amount of accuracy than the existing methods like LSTM and SAE.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132755534","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 : 2023-05-11DOI: 10.1109/ICDT57929.2023.10151188
B. Devi, M. P. Kumar, L. Maguluri, P. Tamilselvan
The only way to get better crop yields is to find and treat crop diseases quickly. Deep learning models diagnoses the plant diseases by looking at the leaves. A residual neural network is developed for the detection of disease in maize leaf. The leaves are collected from the available dataset, where the detection architecture is decentralized using blockchain architecture. The residual neural network with decentralized blockchain enables an optimal classification of instances. The model is implemented with improved disease detection accuracy with reduced training time in a python simulator with keras library. The results of simulation show an improved rate of classification accuracy, precision, recall land f-measure in detecting the leaf disease than the existing convolutional neural network models.
{"title":"Resnet Based Blockchain Architecture for The Detection of Plant Leaf Disease in Agriculture Field","authors":"B. Devi, M. P. Kumar, L. Maguluri, P. Tamilselvan","doi":"10.1109/ICDT57929.2023.10151188","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10151188","url":null,"abstract":"The only way to get better crop yields is to find and treat crop diseases quickly. Deep learning models diagnoses the plant diseases by looking at the leaves. A residual neural network is developed for the detection of disease in maize leaf. The leaves are collected from the available dataset, where the detection architecture is decentralized using blockchain architecture. The residual neural network with decentralized blockchain enables an optimal classification of instances. The model is implemented with improved disease detection accuracy with reduced training time in a python simulator with keras library. The results of simulation show an improved rate of classification accuracy, precision, recall land f-measure in detecting the leaf disease than the existing convolutional neural network models.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134120398","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 : 2023-05-11DOI: 10.1109/ICDT57929.2023.10151239
Deepak Parashar, Om Mishra, Kanhaiya Sharma, Shilpa Choudhary
Glaucoma is a severe condition that causes eyesight loss. The ability to recognize glaucoma in its early stages is critical in preventing long-term vision loss. This paper presents a two-dimensional empirical Littlewood—Paley (LP) wavelet transform (2D-EWT)-based method for glaucoma detection using retinal fundus pictures. For the decay of the preanalyzed photographs into different sub-bands, EWT is used in this investigation. High-frequency sub-band images are then used to compute the features. The ReliefF method chose the valuable descriptors from the extricated include set. Finally, selected descriptors are classified using the random forest (RF) classifier. We use the RIM-ONE public online glaucoma database for performance evaluation of the proposed framework.
{"title":"2-D Empirical LP Wavelet Transform based Automated Framework for Glaucoma Screening","authors":"Deepak Parashar, Om Mishra, Kanhaiya Sharma, Shilpa Choudhary","doi":"10.1109/ICDT57929.2023.10151239","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10151239","url":null,"abstract":"Glaucoma is a severe condition that causes eyesight loss. The ability to recognize glaucoma in its early stages is critical in preventing long-term vision loss. This paper presents a two-dimensional empirical Littlewood—Paley (LP) wavelet transform (2D-EWT)-based method for glaucoma detection using retinal fundus pictures. For the decay of the preanalyzed photographs into different sub-bands, EWT is used in this investigation. High-frequency sub-band images are then used to compute the features. The ReliefF method chose the valuable descriptors from the extricated include set. Finally, selected descriptors are classified using the random forest (RF) classifier. We use the RIM-ONE public online glaucoma database for performance evaluation of the proposed framework.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122143308","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 : 2023-05-11DOI: 10.1109/ICDT57929.2023.10150690
Ritambhara, S. Singh
Innovation i.e., the process of new ideas that are useful or effective in different types of domains. Innovation should be taught in schools, homes, and other extra places. Innovative will be increased or improved with the help of Education Data Mining (EDM), which will improve the quality of Information. By employing BERT- type, objectives are to train representation from sequence process data, then fine-tunes these representations on subsequent prediction tasks, by WEKA and machine learning algorithms. In addition, we investigated students’ performance in exams using machine learning and symmetry-based learning algorithms. This article highly predicts female students pass more than boys students.
{"title":"Creativity: Mining of Innovative Thinking Using Educational Data","authors":"Ritambhara, S. Singh","doi":"10.1109/ICDT57929.2023.10150690","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10150690","url":null,"abstract":"Innovation i.e., the process of new ideas that are useful or effective in different types of domains. Innovation should be taught in schools, homes, and other extra places. Innovative will be increased or improved with the help of Education Data Mining (EDM), which will improve the quality of Information. By employing BERT- type, objectives are to train representation from sequence process data, then fine-tunes these representations on subsequent prediction tasks, by WEKA and machine learning algorithms. In addition, we investigated students’ performance in exams using machine learning and symmetry-based learning algorithms. This article highly predicts female students pass more than boys students.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126036201","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 : 2023-05-11DOI: 10.1109/ICDT57929.2023.10150715
Jay Singh, Priyanka Datta, Nagendra Kumar, Kailash Sharma, Abhinav Saxena, A.M. Gupta, A. Ambikapathy
This paper provide overview of the model which describe how to minimize the road accident on the curve roads by proposing a model which uses IR sensors as sensing elements for the vehicles coming from either side of the road IR sensor is connected with Arduino Uno software to alert drivers about the vehicles coming from either side of the road also Author have used 16* 2 counter to count the vehicles at the turning points to enhance the accuracy at the mountain roads the Arduino sense the signal from the IR sensors which commands the buzzer to start alarming the driver along with RGB LED present on either side of the road we have also use the LDR sensors for a street lighting system at the curve point which get activated at night automatically, in this paper for the energy-generating process we have used piezoelectric sensors in the speed breakers on both the sides through which energy is stored and utilized.
{"title":"IR Sensor Based Accident Prevention System for Hilly Areas","authors":"Jay Singh, Priyanka Datta, Nagendra Kumar, Kailash Sharma, Abhinav Saxena, A.M. Gupta, A. Ambikapathy","doi":"10.1109/ICDT57929.2023.10150715","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10150715","url":null,"abstract":"This paper provide overview of the model which describe how to minimize the road accident on the curve roads by proposing a model which uses IR sensors as sensing elements for the vehicles coming from either side of the road IR sensor is connected with Arduino Uno software to alert drivers about the vehicles coming from either side of the road also Author have used 16* 2 counter to count the vehicles at the turning points to enhance the accuracy at the mountain roads the Arduino sense the signal from the IR sensors which commands the buzzer to start alarming the driver along with RGB LED present on either side of the road we have also use the LDR sensors for a street lighting system at the curve point which get activated at night automatically, in this paper for the energy-generating process we have used piezoelectric sensors in the speed breakers on both the sides through which energy is stored and utilized.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125147863","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 : 2023-05-11DOI: 10.1109/ICDT57929.2023.10150450
Jay Singh, Priyanka Datta, Nagendra Kumar, Kailash Sharma, Abhinav Saxena, Aditya Verma, A. Ambika Pathy
Nowadays most well Grounded and Slashed source of Energy is wind energy and it is easily within reach, convenient and easy to employ. So, as we are growing day by day with Technology, it’s our responsibility to protect our nature for these Engineers and scientist are unfailingly working on different technologies to make human Life reliable and easy to access energy. So, we are also giving a little contribution to our society to make environment pollution free and help for humanities. This research paper is tiny contributions to our society in this confounding field so authors trust that in future this wondrous innovation could assist us with vanquishing all Reliable energy issues so that forthcoming Age could utilize that innovation. So here authors come with innovative solution Power Saving and Power Generating in Automobile using Wind Energy.
{"title":"Power Saving and Power Generating in Automobile (Self-Charging Kit)","authors":"Jay Singh, Priyanka Datta, Nagendra Kumar, Kailash Sharma, Abhinav Saxena, Aditya Verma, A. Ambika Pathy","doi":"10.1109/ICDT57929.2023.10150450","DOIUrl":"https://doi.org/10.1109/ICDT57929.2023.10150450","url":null,"abstract":"Nowadays most well Grounded and Slashed source of Energy is wind energy and it is easily within reach, convenient and easy to employ. So, as we are growing day by day with Technology, it’s our responsibility to protect our nature for these Engineers and scientist are unfailingly working on different technologies to make human Life reliable and easy to access energy. So, we are also giving a little contribution to our society to make environment pollution free and help for humanities. This research paper is tiny contributions to our society in this confounding field so authors trust that in future this wondrous innovation could assist us with vanquishing all Reliable energy issues so that forthcoming Age could utilize that innovation. So here authors come with innovative solution Power Saving and Power Generating in Automobile using Wind Energy.","PeriodicalId":266681,"journal":{"name":"2023 International Conference on Disruptive Technologies (ICDT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126196826","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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