Pub Date : 2022-06-24DOI: 10.1109/CONIT55038.2022.9848402
R. Mapari, K. Bhangale, Pranjal Patil, H. Tiwari, Shivani Khot, Sanjana J. Rane
As the world is moving at a very fast pace in aspects like technology and science, farming methods are also changing. Soil erosion and infertility is a very big issue in traditional farming and so to evade this a soilless farming also known as hydroponics is becoming very popular. Hydroponics is a technique for growing plants without the use of soil in a controlled manner by providing necessary nutrients to the crop. The existing systems of farming require regular ploughing and weeding of land, use of large area and an enormous amount of water. All these problems can be eradicated by using the hydroponics system of farming, and reduce the work of the farmer by automating the watering processes. The idea of proposed hydroponic style vertical farming is to use the Internet of Things (IoT) for sensing and monitoring important factors such as pH, TDS, temperature, and humidity to automate the system. The novelty of the project lies in its feature of automating the irrigation process, displaying all-important factors on an app and notifies the user through email in abnormal conditions.
{"title":"An IoT based Automated Hydroponics Farming and Real Time Crop Monitoring","authors":"R. Mapari, K. Bhangale, Pranjal Patil, H. Tiwari, Shivani Khot, Sanjana J. Rane","doi":"10.1109/CONIT55038.2022.9848402","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848402","url":null,"abstract":"As the world is moving at a very fast pace in aspects like technology and science, farming methods are also changing. Soil erosion and infertility is a very big issue in traditional farming and so to evade this a soilless farming also known as hydroponics is becoming very popular. Hydroponics is a technique for growing plants without the use of soil in a controlled manner by providing necessary nutrients to the crop. The existing systems of farming require regular ploughing and weeding of land, use of large area and an enormous amount of water. All these problems can be eradicated by using the hydroponics system of farming, and reduce the work of the farmer by automating the watering processes. The idea of proposed hydroponic style vertical farming is to use the Internet of Things (IoT) for sensing and monitoring important factors such as pH, TDS, temperature, and humidity to automate the system. The novelty of the project lies in its feature of automating the irrigation process, displaying all-important factors on an app and notifies the user through email in abnormal conditions.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114600481","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}
In this paper, a novel CMOS inverter with the same n-channel and same gate work function has been proposed. This new structure is composed of junctionless (JL) n-FinFET and inversion-mode (IM) p-FinFET. Compared with the conventional CMOS inverter, the novel CMOS device can be fabricated on the same SOI substrates with the same gate material, which simplifies the fabrication process and reduces fabrication costs. The logic performance of CMOS inverters is evaluated using 3D numerical simulation at sub-5 nm technology nodes.The ION/ IOFF ratio of the JL n-FinFET improved up to 3.8%, the intrinsic gain improved up to 4.8% as compared to the IM n-FinFET. The rise time, fall time and RO frequency of the novel CMOS inverter are improved up to 1.8%, 8.5% and 7.6% respectively, compared with the traditional CMOS inverter.
{"title":"A Novel CMOS Structure Composed of Junctionless n-FinFET with the Same n-Channel and Common Gate","authors":"Xinlong Shi, Huiyong Hu, Ying Wang, Liming Wang, Bin Wang, Ningning Zhang","doi":"10.1109/CONIT55038.2022.9847724","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847724","url":null,"abstract":"In this paper, a novel CMOS inverter with the same n-channel and same gate work function has been proposed. This new structure is composed of junctionless (JL) n-FinFET and inversion-mode (IM) p-FinFET. Compared with the conventional CMOS inverter, the novel CMOS device can be fabricated on the same SOI substrates with the same gate material, which simplifies the fabrication process and reduces fabrication costs. The logic performance of CMOS inverters is evaluated using 3D numerical simulation at sub-5 nm technology nodes.The ION/ IOFF ratio of the JL n-FinFET improved up to 3.8%, the intrinsic gain improved up to 4.8% as compared to the IM n-FinFET. The rise time, fall time and RO frequency of the novel CMOS inverter are improved up to 1.8%, 8.5% and 7.6% respectively, compared with the traditional CMOS inverter.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122084124","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 : 2022-06-24DOI: 10.1109/CONIT55038.2022.9848120
B. Sharma, N. Karthick, Durgesh Prasad Bagarty
This paper presents an evaluation of multi string multi-level inverter for a nine-level output. This multi-level inverter has the better comparative results in the form of THD, Losses and number of used devices The multi-string multi-level inverter comprises with eight power switches and 3 asymmetrical DC voltage for a nine-level output, this topologies has lower number of devices as compared with existing topology. Level-shifted pulse width modulation for triangular carriers is employed and compared in this study. The results of the comparative harmonic analysis are presented in the paper. Asymmetric DC voltages are used to get a higher number of levels, which is responsible for lower the THD profile. The multi-level inverter topology investigated is tested in steady-state and dynamic situations, as well as the findings are given. The simulation in the MATLAB® Simulink environment is used to carry out the analysis and verify its results.
{"title":"A Circuit Analysis on Multilevel-Inverter Using Multi string Topology for Minimize THD Profile","authors":"B. Sharma, N. Karthick, Durgesh Prasad Bagarty","doi":"10.1109/CONIT55038.2022.9848120","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848120","url":null,"abstract":"This paper presents an evaluation of multi string multi-level inverter for a nine-level output. This multi-level inverter has the better comparative results in the form of THD, Losses and number of used devices The multi-string multi-level inverter comprises with eight power switches and 3 asymmetrical DC voltage for a nine-level output, this topologies has lower number of devices as compared with existing topology. Level-shifted pulse width modulation for triangular carriers is employed and compared in this study. The results of the comparative harmonic analysis are presented in the paper. Asymmetric DC voltages are used to get a higher number of levels, which is responsible for lower the THD profile. The multi-level inverter topology investigated is tested in steady-state and dynamic situations, as well as the findings are given. The simulation in the MATLAB® Simulink environment is used to carry out the analysis and verify its results.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117288621","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}
Quantum computing functions on qubits, different from the classical bits. These qubits follow the properties of quantum physics such as superposition, interference and entanglement. Our aim is to use this quantum technology in the prediction of earthquakes, a natural disaster resulting in a large number of deaths and destruction every year. Earthquakes are one of the most catastrophic natural hazards, and they frequently turn into disasters that cause utter devastation and loss of life. We first implement the prediction on a classical machine learning algorithm and then compare the results with quantum machine learning. Since the processing power of quantum computers is significantly higher than classical computers, it is expected to predict earthquakes accurately and give an early warning to alert the locals residing in that area.
{"title":"Exploring Quantum Machine Learning (QML) for Earthquake Prediction","authors":"Saloni Dhotre, Karan Doshi, Sneha Satish, Kalpita Wagaskar","doi":"10.1109/CONIT55038.2022.9848250","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848250","url":null,"abstract":"Quantum computing functions on qubits, different from the classical bits. These qubits follow the properties of quantum physics such as superposition, interference and entanglement. Our aim is to use this quantum technology in the prediction of earthquakes, a natural disaster resulting in a large number of deaths and destruction every year. Earthquakes are one of the most catastrophic natural hazards, and they frequently turn into disasters that cause utter devastation and loss of life. We first implement the prediction on a classical machine learning algorithm and then compare the results with quantum machine learning. Since the processing power of quantum computers is significantly higher than classical computers, it is expected to predict earthquakes accurately and give an early warning to alert the locals residing in that area.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129727175","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 : 2022-06-24DOI: 10.1109/CONIT55038.2022.9847825
J. K, Namdev Parth Deendayal, Gurnehmat Kaur Dhindsa, Agrim Nagrani, Vinay Bali
The early diagnosis and treatment of lung diseases is a very critical procedure and it requires the use of Computed Tomography (CT) imaging for the segmentation of lungs. Segmentation of the lung helps in the analysis of the lesions. The project proposes a CT lung and vessel segmentation model without any labels which is based on medical image processing using Python. This would assist the medical practitioners and scientists who are working in the field of CT intensity segmentation of lungs. It would make the diagnosis process easier and more convenient for patients, especially in pandemic situations like COVID.
{"title":"CT Intensity Segmentation of Lungs","authors":"J. K, Namdev Parth Deendayal, Gurnehmat Kaur Dhindsa, Agrim Nagrani, Vinay Bali","doi":"10.1109/CONIT55038.2022.9847825","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847825","url":null,"abstract":"The early diagnosis and treatment of lung diseases is a very critical procedure and it requires the use of Computed Tomography (CT) imaging for the segmentation of lungs. Segmentation of the lung helps in the analysis of the lesions. The project proposes a CT lung and vessel segmentation model without any labels which is based on medical image processing using Python. This would assist the medical practitioners and scientists who are working in the field of CT intensity segmentation of lungs. It would make the diagnosis process easier and more convenient for patients, especially in pandemic situations like COVID.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129947460","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 : 2022-06-24DOI: 10.1109/CONIT55038.2022.9847875
Vukyam Sri Sravya, Sachin Kumar S, K. Soman
The era of digitization has generated huge amounts of data in every field in the range of petabytes, and the news is one of them. To adopt a classification technique using only human intervention is impossible and also like many other Indian languages, the Telugu language is belonging to the Dravidian family which is rich in morphological content. While Natural Language Processing deals with the textual format of data, different types of word embedding features are considered and passed to the models. Existing work on this problem statement is accomplished only with count-based algorithm word embeddings. In this study, several methods were performed to obtain the best model for categorization of the newspaper articles. These methods include building custom-based Machine Learning and Deep Learning models with both count and prediction based word embeddings.
{"title":"Text Categorization of Telugu News Headlines","authors":"Vukyam Sri Sravya, Sachin Kumar S, K. Soman","doi":"10.1109/CONIT55038.2022.9847875","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847875","url":null,"abstract":"The era of digitization has generated huge amounts of data in every field in the range of petabytes, and the news is one of them. To adopt a classification technique using only human intervention is impossible and also like many other Indian languages, the Telugu language is belonging to the Dravidian family which is rich in morphological content. While Natural Language Processing deals with the textual format of data, different types of word embedding features are considered and passed to the models. Existing work on this problem statement is accomplished only with count-based algorithm word embeddings. In this study, several methods were performed to obtain the best model for categorization of the newspaper articles. These methods include building custom-based Machine Learning and Deep Learning models with both count and prediction based word embeddings.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128575335","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 : 2022-06-24DOI: 10.1109/CONIT55038.2022.9848303
V. Vidya, K. Saly, C. Balan
Due to the onset of the Covid-19 pandemic, people are compelled to maintain social distance in all spheres of life, forcing people to adopt virtual mode of activity. Usage of social media and other internet activity has shot up in this period, and consequently, cybercrimes have also increased. If cybercrimes are reported, computer forensics analysts will examine the concerned website, online forum, or social media to find meticulous details about the cybercrime. But webpage content seen on the day may not be available on the next day. The contents of the webpage, which is the subject of crime, will be deleted or withdrawn, or deactivated to destroy evidence to escape from legal proceedings. The victims usually produce a screenshot of the webpage or image or video as a piece of evidence. But there is a distinct possibility of manipulating the offensive materials and it may not be considered a valid piece of evidence before the court of law. Such a scenario requires a forensic technique that should acquire the content of the webpage before it is removed from web site to maintain the authenticity of captured data. So, we are proposing an automated system for the forensic acquisition of a website that will effectively capture all content from the live website and make it useful for forensic investigation and may be produced before the court as valid evidence of cybercrime.
{"title":"Forensic Acquisition and Analysis of Webpage","authors":"V. Vidya, K. Saly, C. Balan","doi":"10.1109/CONIT55038.2022.9848303","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848303","url":null,"abstract":"Due to the onset of the Covid-19 pandemic, people are compelled to maintain social distance in all spheres of life, forcing people to adopt virtual mode of activity. Usage of social media and other internet activity has shot up in this period, and consequently, cybercrimes have also increased. If cybercrimes are reported, computer forensics analysts will examine the concerned website, online forum, or social media to find meticulous details about the cybercrime. But webpage content seen on the day may not be available on the next day. The contents of the webpage, which is the subject of crime, will be deleted or withdrawn, or deactivated to destroy evidence to escape from legal proceedings. The victims usually produce a screenshot of the webpage or image or video as a piece of evidence. But there is a distinct possibility of manipulating the offensive materials and it may not be considered a valid piece of evidence before the court of law. Such a scenario requires a forensic technique that should acquire the content of the webpage before it is removed from web site to maintain the authenticity of captured data. So, we are proposing an automated system for the forensic acquisition of a website that will effectively capture all content from the live website and make it useful for forensic investigation and may be produced before the court as valid evidence of cybercrime.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129484269","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 : 2022-06-24DOI: 10.1109/CONIT55038.2022.9848045
S. Kinger, B. V. Reddy, Sanket Jadhao, Kaustubh Hambarde, Aamir Hullur
The number of malware samples intercepted and analyzed by antivirus providers has increased considerably in recent years. However, much of this software is essentially a repackaged version of malware that has already been identified. Consequently, assessing whether a piece of malware belongs to a known family or exhibits previously identified behavior that requires additional examination has become crucial. Random forest and Decision tree algorithms, as well as hybrid models of both algorithms, have been employed in past studies and research papers. We attempted to introduce an additional prediction technique known as SGD, which delivers good results when a dataset has over 100k variables (In our case 130k). As a result, SGD is one of our study paper's distinguishing characteristics. Our approach has also been tested on both packed and obfuscated malware samples, ensuring that it is both reliable and scalable.
{"title":"Malware Analysis Using Machine Learning Techniques","authors":"S. Kinger, B. V. Reddy, Sanket Jadhao, Kaustubh Hambarde, Aamir Hullur","doi":"10.1109/CONIT55038.2022.9848045","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848045","url":null,"abstract":"The number of malware samples intercepted and analyzed by antivirus providers has increased considerably in recent years. However, much of this software is essentially a repackaged version of malware that has already been identified. Consequently, assessing whether a piece of malware belongs to a known family or exhibits previously identified behavior that requires additional examination has become crucial. Random forest and Decision tree algorithms, as well as hybrid models of both algorithms, have been employed in past studies and research papers. We attempted to introduce an additional prediction technique known as SGD, which delivers good results when a dataset has over 100k variables (In our case 130k). As a result, SGD is one of our study paper's distinguishing characteristics. Our approach has also been tested on both packed and obfuscated malware samples, ensuring that it is both reliable and scalable.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129078944","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 : 2022-06-24DOI: 10.1109/CONIT55038.2022.9848298
S. Bhatlawande, Ishan Girgaonkar
Technological advancements in medical field have caused increase in life expectancy of humankind. Recent societal changes and other conditions cause most of the elder population to live alone. Health and safety of such elders have become a burning issue nowadays. Growth in Computer vision and sensor technology has presented a prominent solution for this problem. In this paper, a study on elderly monitoring system is presented with a proposed posture monitoring model. Proposed model takes video frames as input. Model works on the concept of Bag of Visual Words (BoVW). Model uses Oriented FAST and rotated BRIEF (ORB) to obtain features from input images. Subsequently, K means method is deployed for feature reduction. Reduced dimension vectors are used to classify various posture of person in frame. In this study provides major emphasis on posture recognition of sitting, standing and transitional postures. this non-intrusive, efficient monitoring system is tested on various datasets which have yielded good results.
{"title":"Elderly Care System for Classification and Recognition of Sitting Posture","authors":"S. Bhatlawande, Ishan Girgaonkar","doi":"10.1109/CONIT55038.2022.9848298","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848298","url":null,"abstract":"Technological advancements in medical field have caused increase in life expectancy of humankind. Recent societal changes and other conditions cause most of the elder population to live alone. Health and safety of such elders have become a burning issue nowadays. Growth in Computer vision and sensor technology has presented a prominent solution for this problem. In this paper, a study on elderly monitoring system is presented with a proposed posture monitoring model. Proposed model takes video frames as input. Model works on the concept of Bag of Visual Words (BoVW). Model uses Oriented FAST and rotated BRIEF (ORB) to obtain features from input images. Subsequently, K means method is deployed for feature reduction. Reduced dimension vectors are used to classify various posture of person in frame. In this study provides major emphasis on posture recognition of sitting, standing and transitional postures. this non-intrusive, efficient monitoring system is tested on various datasets which have yielded good results.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129181962","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}
Highly automated vehicles are expected to become commonplace shortly. Driving authority is switched between the automated driving system and the human driver for highly automated vehicles. The appropriate level of drivers' trust in highly automated vehicles (THAV) plays an essential role in the safety of the switching process. Hence, the assessment of THAV and the investigation of its influencing factors are necessary for highly automated vehicles. In this paper, a second-order measurement model for THAV was established based on exploratory factor analysis and confirmatory factor analysis. Then, the affecting factors of THAV were systematically explored based on structural equation modeling. The results indicated that the proposed measurement model could effectively measure THAV. In addition, education, age, and driving experience had significant effects on THAV, while gender and accident experience showed insignificant effects on THAV. This study contributes to a systematic understanding of drivers' trust in highly automated vehicles, the development of human-centered automated driving systems, and enhancing the acceptance of highly automated vehicles.
{"title":"Understanding Human Drivers' Trust in Highly Automated Vehicles via Structural Equation Modeling","authors":"Qingkun Li, Zhenyuan Wang, Weimin Liu, Wenjun Wang, Chao Zeng, Bo Cheng","doi":"10.1109/CONIT55038.2022.9847690","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847690","url":null,"abstract":"Highly automated vehicles are expected to become commonplace shortly. Driving authority is switched between the automated driving system and the human driver for highly automated vehicles. The appropriate level of drivers' trust in highly automated vehicles (THAV) plays an essential role in the safety of the switching process. Hence, the assessment of THAV and the investigation of its influencing factors are necessary for highly automated vehicles. In this paper, a second-order measurement model for THAV was established based on exploratory factor analysis and confirmatory factor analysis. Then, the affecting factors of THAV were systematically explored based on structural equation modeling. The results indicated that the proposed measurement model could effectively measure THAV. In addition, education, age, and driving experience had significant effects on THAV, while gender and accident experience showed insignificant effects on THAV. This study contributes to a systematic understanding of drivers' trust in highly automated vehicles, the development of human-centered automated driving systems, and enhancing the acceptance of highly automated vehicles.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121159298","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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