Pub Date : 2023-03-01DOI: 10.1109/ESCI56872.2023.10100144
Ameya Ghadge, Ayush Juvekar, M. Wakode, Geetangali Kale
As urbanization continues to accelerate at a break-neck pace, the need for smart cities has become increasingly pressing. This need is particularly evident in developing countries, such as India, where the rapid pace of growth has led to significant problems, including the issue of air pollution. Inhaling pollutants over extended periods of time can be harmful to human health, and can even be life-threatening. Carbon monox-ide (CO) is one such pollutant, and its detection and control in residential and industrial environments is critical to avoid potential health problems. To address this issue, sensor networks can be deployed in affected areas to measure the concentrations of different gases and to take necessary action to reduce their levels in the air. Wireless Sensor Networks (WSNs) are currently a popular research area due to their potential applications, and this paper discusses the implementation of WSNs for monitoring CO concentration in order to automate the filtration process using the Zigbee Protocol for communication. By deploying sensor networks and leveraging the power of the Zigbee Protocol, we can help to mitigate the damaging effects of air pollution and improve the quality of air in the cities.
{"title":"Carbon Monoxide Concentration Monitoring System for Automating Air Filters","authors":"Ameya Ghadge, Ayush Juvekar, M. Wakode, Geetangali Kale","doi":"10.1109/ESCI56872.2023.10100144","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10100144","url":null,"abstract":"As urbanization continues to accelerate at a break-neck pace, the need for smart cities has become increasingly pressing. This need is particularly evident in developing countries, such as India, where the rapid pace of growth has led to significant problems, including the issue of air pollution. Inhaling pollutants over extended periods of time can be harmful to human health, and can even be life-threatening. Carbon monox-ide (CO) is one such pollutant, and its detection and control in residential and industrial environments is critical to avoid potential health problems. To address this issue, sensor networks can be deployed in affected areas to measure the concentrations of different gases and to take necessary action to reduce their levels in the air. Wireless Sensor Networks (WSNs) are currently a popular research area due to their potential applications, and this paper discusses the implementation of WSNs for monitoring CO concentration in order to automate the filtration process using the Zigbee Protocol for communication. By deploying sensor networks and leveraging the power of the Zigbee Protocol, we can help to mitigate the damaging effects of air pollution and improve the quality of air in the cities.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116601519","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 : 2023-03-01DOI: 10.1109/ESCI56872.2023.10099625
Nilesh P. Sable, P. Shelke, Ninad Deogaonkar, Nachiket Joshi, Rudra Kabadi, Tushar Joshi
Physical documents may easily be converted into digital versions in the modern digital era by employing scanning software and the internet. The day when this activity needed printers and scanners is long gone. Nowadays, even our smartphones and cameras may be used to quickly convert paper documents into digital ones. This is especially useful in the wake of the COVID-19 pandemic, where the ability to share and access documents online is more important than ever. This study proposes an application for illiterate people to quickly translate scanned papers or photos into their native language and save them in a digital format. The Application makes use of image processing methods and has capabilities including PDF conversion, image colour adjustment, cropping, and Optical Character Recognition (OCR). A user-friendly application, developed using the Flutter Framework and programmed in Python and Dart, serves as the interface for the system. The proposed application is cross-platform and works with a variety of gadgets. This method intends to increase accessibility and productivity for illiterate people in the digital age by integrating image processing with language translation.
{"title":"Doc-Handler: Document Scanner, Manipulator, and Translator based on Image and Natural language processing","authors":"Nilesh P. Sable, P. Shelke, Ninad Deogaonkar, Nachiket Joshi, Rudra Kabadi, Tushar Joshi","doi":"10.1109/ESCI56872.2023.10099625","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099625","url":null,"abstract":"Physical documents may easily be converted into digital versions in the modern digital era by employing scanning software and the internet. The day when this activity needed printers and scanners is long gone. Nowadays, even our smartphones and cameras may be used to quickly convert paper documents into digital ones. This is especially useful in the wake of the COVID-19 pandemic, where the ability to share and access documents online is more important than ever. This study proposes an application for illiterate people to quickly translate scanned papers or photos into their native language and save them in a digital format. The Application makes use of image processing methods and has capabilities including PDF conversion, image colour adjustment, cropping, and Optical Character Recognition (OCR). A user-friendly application, developed using the Flutter Framework and programmed in Python and Dart, serves as the interface for the system. The proposed application is cross-platform and works with a variety of gadgets. This method intends to increase accessibility and productivity for illiterate people in the digital age by integrating image processing with language translation.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116602212","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 : 2023-03-01DOI: 10.1109/ESCI56872.2023.10099738
Cendra Devayana Putra, Hei-Chia Wang
Hate speech is a phenomenon which presents offensive content that people may find on social networking sites. Recognizing and reducing inappropriate content is critical for preventing and reducing hate speech. This article highlights the diversity of possible hate speech datasets and developed challenges in four domains by investigating 27 related papers in several trusted databases. The findings point to future system development directions to trace objectionable content transformations over time on various online social platforms and domains.
{"title":"Automate Lifelong Hate Speech Detection: Current Challenge In Cross-Domain Adaption","authors":"Cendra Devayana Putra, Hei-Chia Wang","doi":"10.1109/ESCI56872.2023.10099738","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099738","url":null,"abstract":"Hate speech is a phenomenon which presents offensive content that people may find on social networking sites. Recognizing and reducing inappropriate content is critical for preventing and reducing hate speech. This article highlights the diversity of possible hate speech datasets and developed challenges in four domains by investigating 27 related papers in several trusted databases. The findings point to future system development directions to trace objectionable content transformations over time on various online social platforms and domains.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122464297","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 : 2023-03-01DOI: 10.1109/ESCI56872.2023.10100245
Garima Chopra
With the exponential growth in demand by sub-scribers, ultra-dense networks (UDN) has shown to be effective in providing a high data rate. However, this excessive and random deployment of base stations (BSs) has escalated energy consumption and inter-cell interference. Base Station Sleeping (BSS) can significantly scale down the energy consumption by BSs during the underutilized period. To tackle this, a BSS configuration is proposed by keeping account of the UDN deployment scenario and users present per small cell BS (SBS). The proposed configuration is compared in terms of the overall downlink rate with the random configuration of BSS in UDN. Through extensive simulations, a trade-off is observed among downlink rate, Fairness index, and Energy saved.
{"title":"An Efficient Base Station Sleeping Configuration for Ultra-dense Networks","authors":"Garima Chopra","doi":"10.1109/ESCI56872.2023.10100245","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10100245","url":null,"abstract":"With the exponential growth in demand by sub-scribers, ultra-dense networks (UDN) has shown to be effective in providing a high data rate. However, this excessive and random deployment of base stations (BSs) has escalated energy consumption and inter-cell interference. Base Station Sleeping (BSS) can significantly scale down the energy consumption by BSs during the underutilized period. To tackle this, a BSS configuration is proposed by keeping account of the UDN deployment scenario and users present per small cell BS (SBS). The proposed configuration is compared in terms of the overall downlink rate with the random configuration of BSS in UDN. Through extensive simulations, a trade-off is observed among downlink rate, Fairness index, and Energy saved.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128976878","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 : 2023-03-01DOI: 10.1109/ESCI56872.2023.10099839
Prajwal Gujarkar, Sarthak Lonkar, T. Jain, Shubham Nigal, Pramod Patil, Pallavi Deshpande, Ketki P. Kshirsagar, Shraddha K. Habbu, Gauri Ghule, A. Ratnaparkhi
Nowadays, as attendance is taken using the tra-ditional pen and paper method, it increases the workload for employees and employers. This increases the cost of maintaining records and will also increase the manipulation in the system. So, there is a dire need of proper attendance management system. As it will help in Accurate tracking, increase productivity and reduces time for marking attendance. As the world around us becomes more modern, organizations are adopting more advanced methods for managing attendance and recording. But there are still some organizations that are using traditional methods for maintaining attendance records. A smart loT-based attendance system can improve the effectiveness of work in the industry. The purpose of this study is to design a system that would be used for fingerprint attendance. This system consists of ESP 8266, R307 Fingerprint Sensor and OLED Display. The ESP8266 WiFi module will collect fingerprint data from multiple users and send it over the internet. The experimental study showed the designed system has a high level of efficiency and 99.9% accuracy. The designed system completed attendance in 7.86 seconds on average, which is quicker than many other systems in use. The outcome also demonstrates a trustworthy, well-secured system that can prevent impersonation. Novelty In our system is that we have allow access to attendance records from anywhere, and provide real-time data to the management. We have also used biometric technology which allows for a more accurate and secure way to track attendance, as it uses unique physical characteristics of an individual to identify them.
{"title":"IoT based Smart Attendance System","authors":"Prajwal Gujarkar, Sarthak Lonkar, T. Jain, Shubham Nigal, Pramod Patil, Pallavi Deshpande, Ketki P. Kshirsagar, Shraddha K. Habbu, Gauri Ghule, A. Ratnaparkhi","doi":"10.1109/ESCI56872.2023.10099839","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099839","url":null,"abstract":"Nowadays, as attendance is taken using the tra-ditional pen and paper method, it increases the workload for employees and employers. This increases the cost of maintaining records and will also increase the manipulation in the system. So, there is a dire need of proper attendance management system. As it will help in Accurate tracking, increase productivity and reduces time for marking attendance. As the world around us becomes more modern, organizations are adopting more advanced methods for managing attendance and recording. But there are still some organizations that are using traditional methods for maintaining attendance records. A smart loT-based attendance system can improve the effectiveness of work in the industry. The purpose of this study is to design a system that would be used for fingerprint attendance. This system consists of ESP 8266, R307 Fingerprint Sensor and OLED Display. The ESP8266 WiFi module will collect fingerprint data from multiple users and send it over the internet. The experimental study showed the designed system has a high level of efficiency and 99.9% accuracy. The designed system completed attendance in 7.86 seconds on average, which is quicker than many other systems in use. The outcome also demonstrates a trustworthy, well-secured system that can prevent impersonation. Novelty In our system is that we have allow access to attendance records from anywhere, and provide real-time data to the management. We have also used biometric technology which allows for a more accurate and secure way to track attendance, as it uses unique physical characteristics of an individual to identify them.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129612159","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 : 2023-03-01DOI: 10.1109/ESCI56872.2023.10100135
Akshat Ajay Das, V. Mayya, Manohara M M Pai
An event or an observation that is statistically different from the others is termed an anomaly. Anomaly detection is the process of identifying such anomalies. Anomaly detection is an effective tool for risk mitigation, fraud detection, and improving the system's robustness. It is also an active research area, with numerous algorithms being proposed. In this paper, we compare the performance of various anomaly detection algorithms on mul-tivariate as well as univariate datasets. The assessment measures generated are important and can be beneficial for predicting anomalies in a timely and accurate manner. Experimental results demonstrate that on a univariate dataset, the auto-regressive moving average (ARMA), performs better than the local outlier factor (LOF), while on a multivariate dataset, the LOF model performs better. The prototype developed has been extensively tested on publicly available datasets and can be evaluated on larger, more comprehensive datasets for deployment in the real-time anomaly detection setup.
{"title":"Anomaly Detection for Highly Imbalanced Data–an Empirical Analysis","authors":"Akshat Ajay Das, V. Mayya, Manohara M M Pai","doi":"10.1109/ESCI56872.2023.10100135","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10100135","url":null,"abstract":"An event or an observation that is statistically different from the others is termed an anomaly. Anomaly detection is the process of identifying such anomalies. Anomaly detection is an effective tool for risk mitigation, fraud detection, and improving the system's robustness. It is also an active research area, with numerous algorithms being proposed. In this paper, we compare the performance of various anomaly detection algorithms on mul-tivariate as well as univariate datasets. The assessment measures generated are important and can be beneficial for predicting anomalies in a timely and accurate manner. Experimental results demonstrate that on a univariate dataset, the auto-regressive moving average (ARMA), performs better than the local outlier factor (LOF), while on a multivariate dataset, the LOF model performs better. The prototype developed has been extensively tested on publicly available datasets and can be evaluated on larger, more comprehensive datasets for deployment in the real-time anomaly detection setup.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127718540","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 : 2023-03-01DOI: 10.1109/ESCI56872.2023.10100231
V. Tanwar, Shweta Lamba, Bhanu Sharma
Conventional rice crop disease prediction models show some drawbacks, such as the expensive cost of acquiring the input data necessary to run the model, the absence of spatial information, or the shortage of high-quality datasets. These problems are discussed in this work, which also develops a yield prediction fusion model. Convolutional neural networks (CNN) and support vector machines make up the prediction model (SVM). In this work, Leaf smut infection of rice health is discussed. The infected plant's pictures are first collected through secondary sources. The deep learning method's best characteristic is the feature extraction and classification of the different levels of blight infection severity is done using CNN and SVM. Mild, Average, Severe, and Profound are the four severity projection levels used in the study. Kaggle etc. are the data repositories that were utilized, and the total size of the dataset was 272. The suggested approach produces four severity-level predictions with 98% accuracy.
{"title":"Deep Learning-Based Hybrid Model For Severity Prediction of Leaf Smut Rice Infection","authors":"V. Tanwar, Shweta Lamba, Bhanu Sharma","doi":"10.1109/ESCI56872.2023.10100231","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10100231","url":null,"abstract":"Conventional rice crop disease prediction models show some drawbacks, such as the expensive cost of acquiring the input data necessary to run the model, the absence of spatial information, or the shortage of high-quality datasets. These problems are discussed in this work, which also develops a yield prediction fusion model. Convolutional neural networks (CNN) and support vector machines make up the prediction model (SVM). In this work, Leaf smut infection of rice health is discussed. The infected plant's pictures are first collected through secondary sources. The deep learning method's best characteristic is the feature extraction and classification of the different levels of blight infection severity is done using CNN and SVM. Mild, Average, Severe, and Profound are the four severity projection levels used in the study. Kaggle etc. are the data repositories that were utilized, and the total size of the dataset was 272. The suggested approach produces four severity-level predictions with 98% accuracy.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126463635","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 : 2023-03-01DOI: 10.1109/ESCI56872.2023.10099691
Meet Kumari
Nowadays, visible light communication (VLC) is an attractive scheme for intelligent transportation systems. In this paper, a red-green-blue light emitting diodes (RGB LEDs) based VLC consisting orthogonal frequency division multiplexing (OFDM) modulation at 10Gbps data rate is purposed. The results show that red LED shows better performance than green and blue LEDs. Also, the maximum VLC transmission range in the proposed system using avalanche photo-detector (APD) is 3200m. Moreover, the comparative performance of proposed work is better as compared to other recent work.
{"title":"Performance analysis of VLC based Intelligent Transportation System","authors":"Meet Kumari","doi":"10.1109/ESCI56872.2023.10099691","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099691","url":null,"abstract":"Nowadays, visible light communication (VLC) is an attractive scheme for intelligent transportation systems. In this paper, a red-green-blue light emitting diodes (RGB LEDs) based VLC consisting orthogonal frequency division multiplexing (OFDM) modulation at 10Gbps data rate is purposed. The results show that red LED shows better performance than green and blue LEDs. Also, the maximum VLC transmission range in the proposed system using avalanche photo-detector (APD) is 3200m. Moreover, the comparative performance of proposed work is better as compared to other recent work.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"217 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134178232","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 : 2023-03-01DOI: 10.1109/ESCI56872.2023.10099543
S. T. Ahmed, D. V. Ratnamb, K. Swamy
Global Positioning System of Americans, GLONASS of Russians, Galileo of Europeans and BeiDou of Chinese have been continuously transmitting radio signals on various frequencies for the applications of PVT. In addition to them other countries constellations like NavIC of India and QZSS of Japan are providing service in limited area. The multiple constellations can improve the signal quality which helps to the robustness and stability for measuring position and navigation. The main intention for this investigation is for tracking the accuracy and capability of the GPS receivers in addition to the status of PVT for the total number of constellations available at the setup location. This will help in developing various navigation parameters like latitude, longitude, velocity and also studying TEC values related to time. Locality of user will defers depending on the DOP (dilution of precision) values in this receiver. Elevation and azimuthal angles along with SNR of the signal can be observed. Through the help of PolaRx5 receiver, a Real-time observations data were collected from which was setup at our institute located in Kurnool (15o.47'N, 78o.04E). Overall results shows that this Septentrio model of Rx5 can have the capability of receiving minimum of 64 constellation signals along with azimuth and elevation angles, having more accuracy and can study the impact of different ionization effect on different constellations and can be helpful for the future applications on navigation and satellite positions.
{"title":"A Study on Real-Time Signal Observations Acquired by Multi-Frequency Multi-GNSS Septentrio PolaRx5 Receiver","authors":"S. T. Ahmed, D. V. Ratnamb, K. Swamy","doi":"10.1109/ESCI56872.2023.10099543","DOIUrl":"https://doi.org/10.1109/ESCI56872.2023.10099543","url":null,"abstract":"Global Positioning System of Americans, GLONASS of Russians, Galileo of Europeans and BeiDou of Chinese have been continuously transmitting radio signals on various frequencies for the applications of PVT. In addition to them other countries constellations like NavIC of India and QZSS of Japan are providing service in limited area. The multiple constellations can improve the signal quality which helps to the robustness and stability for measuring position and navigation. The main intention for this investigation is for tracking the accuracy and capability of the GPS receivers in addition to the status of PVT for the total number of constellations available at the setup location. This will help in developing various navigation parameters like latitude, longitude, velocity and also studying TEC values related to time. Locality of user will defers depending on the DOP (dilution of precision) values in this receiver. Elevation and azimuthal angles along with SNR of the signal can be observed. Through the help of PolaRx5 receiver, a Real-time observations data were collected from which was setup at our institute located in Kurnool (15o.47'N, 78o.04E). Overall results shows that this Septentrio model of Rx5 can have the capability of receiving minimum of 64 constellation signals along with azimuth and elevation angles, having more accuracy and can study the impact of different ionization effect on different constellations and can be helpful for the future applications on navigation and satellite positions.","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131086044","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 : 2023-03-01DOI: 10.1109/esci56872.2023.10099515
{"title":"ESCI 2023 Schedule","authors":"","doi":"10.1109/esci56872.2023.10099515","DOIUrl":"https://doi.org/10.1109/esci56872.2023.10099515","url":null,"abstract":"","PeriodicalId":441215,"journal":{"name":"2023 International Conference on Emerging Smart Computing and Informatics (ESCI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133044957","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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