Computer usage is increasing rapidly day by day but the input devices are limited and to access them, we need to be near the screen. To overcome this problem and control the screen, we can use hand gestures. For every operation, we used different hand gestures. We proposed a python program to control the media player through hand gestures. In this method, we used libraries like OpenCV, Media Pipe, PyAuto GUI, and other libraries to capture the video, provide ready-to-use ML solutions and automate your GUI and programmatically control your keyboard and mouse. Hand gestures will be used as the input for providing natural interaction by reducing external hardware interaction. The whole process is divided into two steps. Firstly, gesture recognition through the camera is done by OpenCV and media Pipe helps to identify the gesture b its position, and the respective command is executed. Secondly, PyAuto GUI is used to automate the keyboard and controls the media player.
计算机的使用日益迅速，但输入设备是有限的，我们需要靠近屏幕才能访问它们。为了克服这个问题并控制屏幕，我们可以使用手势。对于每个操作，我们使用不同的手势。我们提出了一个python程序来通过手势控制媒体播放器。在这种方法中，我们使用像OpenCV, Media Pipe, PyAuto GUI和其他库来捕获视频，提供现成的ML解决方案，自动化GUI并以编程方式控制键盘和鼠标。手势将被用作输入，通过减少外部硬件交互来提供自然交互。整个过程分为两个步骤。首先，通过摄像头进行手势识别是由OpenCV和media Pipe帮助识别手势的位置，并执行相应的命令。其次，使用PyAuto GUI实现键盘的自动化和媒体播放器的控制。
{"title":"Controlling Media Player Using Hand Gestures","authors":"K. Chakradhar, Prasanna Rejinthala Lakshmi, salla chowdary Sree Rama Brunda, Bharath Pola, Bhargava Petlu","doi":"10.46632/eae/2/1/7","DOIUrl":"https://doi.org/10.46632/eae/2/1/7","url":null,"abstract":"Computer usage is increasing rapidly day by day but the input devices are limited and to access them, we need to be near the screen. To overcome this problem and control the screen, we can use hand gestures. For every operation, we used different hand gestures. We proposed a python program to control the media player through hand gestures. In this method, we used libraries like OpenCV, Media Pipe, PyAuto GUI, and other libraries to capture the video, provide ready-to-use ML solutions and automate your GUI and programmatically control your keyboard and mouse. Hand gestures will be used as the input for providing natural interaction by reducing external hardware interaction. The whole process is divided into two steps. Firstly, gesture recognition through the camera is done by OpenCV and media Pipe helps to identify the gesture b its position, and the respective command is executed. Secondly, PyAuto GUI is used to automate the keyboard and controls the media player.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122179913","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}
Effective fault detection and isolation technologies are very necessary for uninterrupted power supply and for making a flexible protection scheme. Almost all protection schemes in the power system are based on data exchange among protection units through a strong communication structure. Thus, it is important to deal with a large amount of data. Artificial Intelligence (AI) is one of the key factors in this regard. AI has several sections and Artificial Neural Network (ANN) is one of them. It is suggested to implement the ANN-based models while working with big data. The existing protection models are facing difficulties while trying to deal with big data. Thus ANN-based approaches have come into the front line in advanced power system networks. The performance of the ANN model is depending on the training of the data set. Hence in this work, we are focusing on preparing the data to provide input in the ANN model. The principal component analysis (PCA) method is applied here for reduced the dimension of a large number of data sets. The new data set is used to run the k-means clustering algorithm. It is shown that the clustering is more accurate with the processed data set by PCA. Therefore, the prepared data set is used to run the ANN model that has a smaller size with higher information and minimum computational time. This study shows the data preparation part to train the ANN model.
{"title":"Data Processing Method for Artificial Neural Network ANN Based Microgrid Protection Model","authors":"Baidya Sanghita, Nandi Champa","doi":"10.46632/ese/2/1/8","DOIUrl":"https://doi.org/10.46632/ese/2/1/8","url":null,"abstract":"Effective fault detection and isolation technologies are very necessary for uninterrupted power supply and for making a flexible protection scheme. Almost all protection schemes in the power system are based on data exchange among protection units through a strong communication structure. Thus, it is important to deal with a large amount of data. Artificial Intelligence (AI) is one of the key factors in this regard. AI has several sections and Artificial Neural Network (ANN) is one of them. It is suggested to implement the ANN-based models while working with big data. The existing protection models are facing difficulties while trying to deal with big data. Thus ANN-based approaches have come into the front line in advanced power system networks. The performance of the ANN model is depending on the training of the data set. Hence in this work, we are focusing on preparing the data to provide input in the ANN model. The principal component analysis (PCA) method is applied here for reduced the dimension of a large number of data sets. The new data set is used to run the k-means clustering algorithm. It is shown that the clustering is more accurate with the processed data set by PCA. Therefore, the prepared data set is used to run the ANN model that has a smaller size with higher information and minimum computational time. This study shows the data preparation part to train the ANN model.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115515901","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}
A. Suneel Kumar, R. Lakshmi Swarna Prasanna, V. Nandini, T. Dharma Teja, S. Sai
This paper examines a dual-band, low-cost microstrip patch antenna for Ku and K applications through simulation study. Ansys High Frequency Structure Simulator (HFSS) software is used to do the simulation analysis of the suggested antenna. Using Ansys High Frequency Structure Simulator (HFSS) software, the suggested antenna is constructed and simulated to evaluate several characteristics including reflection coefficient (S11), radiation pattern, gain, and bandwidth. The substrate for the antenna is made of FR-4, which has a relative permittivity of 4.4 and a dielectric loss tangent of 0.02. Using the microstrip feed line technology, the planned millimeter wave dual band antenna is examined at operating frequencies of 13 and 22 GHz. At frequencies of 13 and 22, respectively, the antenna's maximum gain values are 4.81 dB and 4.82 dB in the x-y plane. The suggested material might be a decent substitute.
{"title":"A Low-Cost and Dual band Microstrip Patch Antenna for Ku \u0000and K Band Applications","authors":"A. Suneel Kumar, R. Lakshmi Swarna Prasanna, V. Nandini, T. Dharma Teja, S. Sai","doi":"10.46632/eae/2/1/6","DOIUrl":"https://doi.org/10.46632/eae/2/1/6","url":null,"abstract":"This paper examines a dual-band, low-cost microstrip patch antenna for Ku and K applications through simulation study. Ansys High Frequency Structure Simulator (HFSS) software is used to do the simulation analysis of the suggested antenna. Using Ansys High Frequency Structure Simulator (HFSS) software, the suggested antenna is constructed and simulated to evaluate several characteristics including reflection coefficient (S11), radiation pattern, gain, and bandwidth. The substrate for the antenna is made of FR-4, which has a relative permittivity of 4.4 and a dielectric loss tangent of 0.02. Using the microstrip feed line technology, the planned millimeter wave dual band antenna is examined at operating frequencies of 13 and 22 GHz. At frequencies of 13 and 22, respectively, the antenna's maximum gain values are 4.81 dB and\u00004.82 dB in the x-y plane. The suggested material might be a decent substitute.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127706761","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}
Vutukuru Keerthi Reddy, Vanmalli Varshini, N. Gireesh, M. Venkata Naresh
Crop recommendation is among the most crucial components of the field known as precision agriculture. The crop recommendations were formulated after considering a wide range of distinct considerations. The term "precision agriculture" refers to a method of contemporary farming that makes use of information on soil features, soil kinds, and other factors, such as crop yields, and weather conditions to provide farmers with recommendations regarding the types of crops that would be most beneficial to grow on their farms to achieve the highest possible levels of both yield and profit. The crop recommendation system is currently being built with the use of machine learning methods including Random Forest, Gradient Boosting, XG Boost, Light GBM, SVM, and decision tree. The process of identifying the best crop to produce is aided by the information that consists of qualities such as potassium (K), phosphorous (P), and nitrogen (N) as well as temperature, humidity, pH, and rainfall. This application will be of assistance to farmers in enhancing agricultural output, minimizing the deterioration of soil on the cultivated ground, reducing the number of chemicals used in agricultural production, and increasing the productivity of cultivated land with available water resources. Also, this application recommends the top 5 prioritized crops to farmers. XG Boost achieved the best accuracy of 99.500 out of all these classifiers that were utilized in this paper. It also achieved the highest recall score of 99.545455, a precision score of 99.564935, and an F1 score of 99.545669.
{"title":"A Comprehensive Study on Crop Recommendation System for Precision Agriculture Using Machine Learning\u0000Algorithms","authors":"Vutukuru Keerthi Reddy, Vanmalli Varshini, N. Gireesh, M. Venkata Naresh","doi":"10.46632/eae/2/1/5","DOIUrl":"https://doi.org/10.46632/eae/2/1/5","url":null,"abstract":"Crop recommendation is among the most crucial components of the field known as precision agriculture. The crop recommendations were formulated after considering a wide range of distinct considerations. The term \"precision agriculture\" refers to a method of contemporary farming that makes use of information on soil features, soil kinds, and other factors, such as crop yields, and weather conditions to provide farmers with recommendations regarding the types of crops that would be most beneficial to grow on their farms to achieve the highest possible levels of both yield and profit. The crop recommendation system is currently being built with the use of machine learning methods including Random Forest, Gradient Boosting, XG Boost, Light GBM, SVM, and decision tree. The process of identifying the best crop to produce is aided by the information that consists of qualities such as potassium (K), phosphorous (P), and nitrogen (N) as well as temperature, humidity, pH, and rainfall. This application will be of assistance to farmers in enhancing agricultural output, minimizing the deterioration of soil on the cultivated ground, reducing the number of chemicals used in agricultural production, and increasing the productivity of cultivated land with available water resources. Also, this application recommends the top 5 prioritized crops to farmers. XG Boost achieved the best accuracy of 99.500 out of all these classifiers that were utilized in this paper. It also achieved the highest recall score of 99.545455, a precision score of 99.564935, and an F1 score of 99.545669.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127722915","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}
K. Sujeeth Kumara, J. Sathwikab, B. Sruthic, R. Pravachand, B. Vijay kumare
As the world's population continues to grow, the demand for electricity is also increasing rapidly. Ensuring the quality of power supply, voltage stability, unity power factor, and minimizing power losses is essential for delivering power to every user end. In order to achieve this, compensation techniques are needed. This project focuses on Serial controllable Flexible AC Transmission Systems (FACTS) devices, such as Controllable Series Compensator (CSC) and Static Synchronous Series Compensator (SSSC), which have a significant impact on the voltage and power stability of an electric power system (EPS). The mathematical derivation of the voltage dependency of CSC and SSSC is extracted for the single-load infinitive-bus model (SLIB). New analytical equations are developed to compare the impact of CSC and SSSC on voltage stability in a five-bus system. The results of the analysis are expected to reveal that CSC has a crucial role to play in enhancing voltage stability, and its impact is greater than that of SSSC when considering equal CSC and SSSC MVA ratings. When it comes to voltage controllability, SSSC (Static synchronous series compensator) is superior to CSC (Controllable Series Compensator), especially in situations where there are having low voltages or having low loads.
{"title":"The Impact of Serial Controllable Facts Devices on Voltage Stability","authors":"K. Sujeeth Kumara, J. Sathwikab, B. Sruthic, R. Pravachand, B. Vijay kumare","doi":"10.46632/eae/2/1/3","DOIUrl":"https://doi.org/10.46632/eae/2/1/3","url":null,"abstract":"As the world's population continues to grow, the demand for electricity is also increasing rapidly. Ensuring the quality of power supply, voltage stability, unity power factor, and minimizing power losses is essential for delivering power to every user end. In order to achieve this, compensation techniques are needed. This project focuses on Serial controllable Flexible AC Transmission Systems (FACTS) devices, such as Controllable Series Compensator (CSC) and Static Synchronous Series Compensator (SSSC), which have a significant impact on the voltage and power stability of an electric power system (EPS). The mathematical derivation of the voltage dependency of CSC and SSSC is extracted for the single-load infinitive-bus model (SLIB). New analytical equations are developed to compare the impact of CSC and SSSC on voltage stability in a five-bus system. The results of the analysis are expected to reveal that CSC has a crucial role to play in enhancing voltage stability, and its impact is greater than that of SSSC when considering equal CSC and SSSC MVA ratings. When it comes to voltage controllability, SSSC (Static synchronous series compensator) is superior to CSC (Controllable Series Compensator), especially in situations where there are having low voltages or having low loads.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134191385","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}
An electrical device called a heartbeat sensor is used to detect a person's heart rate, or heartbeat pace. The fundamental things we do to keep ourselves healthy are to monitor our body temperature, heart rate, and blood pressure. We utilise thermometers and a sphygmomanometer to check the blood pressure and arterial pressure in addition to measuring body temperature. A heartbeat sensor can be used to monitor heart rate in addition to manually checking the pulse at the wrists or neck. In this experiment, the heartbeat is found using fingertip pulse oximetry. The amount of blood in the fingertip increases during diastole and decreases during systole of the heart. If you could somehow count the number of pulses in one minute, that would be the heart rate in beats per minute. The subsequent pulsing of blood volume inside the fingertip is precisely proportional to heart rate (bpm).
{"title":"Pulse Monitoring System","authors":"M. Jyothirmai, M. Jyothi","doi":"10.46632/eae/2/1/4","DOIUrl":"https://doi.org/10.46632/eae/2/1/4","url":null,"abstract":"An electrical device called a heartbeat sensor is used to detect a person's heart rate, or heartbeat pace. The fundamental things we do to keep ourselves healthy are to monitor our body temperature, heart rate, and blood pressure. We utilise thermometers and a sphygmomanometer to check the blood pressure and arterial pressure in addition to measuring body temperature. A heartbeat sensor can be used to monitor heart rate in addition to manually checking the pulse at the wrists or neck. In this experiment, the heartbeat is found using fingertip pulse oximetry. The amount of blood in the fingertip increases during diastole and decreases during systole of the heart. If you could somehow count the number of pulses in one minute, that would be the heart rate in beats per minute. The subsequent pulsing of blood volume inside the fingertip is precisely proportional to heart rate (bpm).","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"207 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131590075","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}
The process of creating an image's emulsion is selecting the crucial details from numerous images and combining them into smaller images, often one bone. In the areas of satellite imaging, remote seeing, target shadowing, medical imaging, and many other areas, image emulsion is quite useful. This design tries to illustrate how Empirical Wavelet transfigures work when used with the Simple Average Emulsion Rule to emulsify multi-focus images. The suggested approach has been tested using common datasets for merging images with various focal points. Empirical Wavelet Transform is primarily a method that uses an adaptive approach to produce a Multi-Resolution Analysis of the signal. The effectiveness of the suggested approach is calculated in a variety of ways. Visual perception and the evaluation of common quality metrics, such as Root Mean Squared Error, Entropy, and Peak Signal to Noise ratio, are used to compare the performance of the proposed system. The proposed fashion based on the Empirical Wavelet Transform (EWT) outperforms the existing methods, according to the study of the experimental results. According to the suggested criteria, the fused image's entropy should be higher than the component images' because the emulsion's efficiency decreases as entropy increases. This technique takes MRI and CT scans into account.
{"title":"Empirical Wavelet Transform Method for Enhancement of Medical Image Fusion","authors":"Nagendra Reddy Nelaturi, Jayalakshmi Bitra, Rao Goli Srinivasa","doi":"10.46632/ese/2/1/10","DOIUrl":"https://doi.org/10.46632/ese/2/1/10","url":null,"abstract":"The process of creating an image's emulsion is selecting the crucial details from numerous images and combining them into smaller images, often one bone. In the areas of satellite imaging, remote seeing, target shadowing, medical imaging, and many other areas, image emulsion is quite useful. This design tries to illustrate how Empirical Wavelet transfigures work when used with the Simple Average Emulsion Rule to emulsify multi-focus images. The suggested approach has been tested using common datasets for merging images with various focal points. Empirical Wavelet Transform is primarily a method that uses an adaptive approach to produce a Multi-Resolution Analysis of the signal. The effectiveness of the suggested approach is calculated in a variety of ways. Visual perception and the evaluation of common quality metrics, such as Root Mean Squared Error, Entropy, and Peak Signal to Noise ratio, are used to compare the performance of the proposed system. The proposed fashion based on the Empirical Wavelet Transform (EWT) outperforms the existing methods, according to the study of the experimental results. According to the suggested criteria, the fused image's entropy should be higher than the component images' because the emulsion's efficiency decreases as entropy increases. This technique takes MRI and CT scans into account.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"13 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132382958","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}
Effective fault detection and isolation technologies are very necessary for uninterrupted power supply and for making a flexible protection scheme. Almost all protection schemes in the power system are based on data exchange among protection units through a strong communication structure. Thus, it is important to deal with a large amount of data. Artificial Intelligence (AI) is one of the key factors in this regard. AI has several sections and Artificial Neural Network (ANN) is one of them. It is suggested to implement the ANN-based models while working with big data. The existing protection models are facing difficulties while trying to deal with big data. Thus ANN-based approaches have come into the front line in advanced power system networks. The performance of the ANN model is depending on the training of the data set. Hence in this work, we are focusing on preparing the data to provide input in the ANN model. The principal component analysis (PCA) method is applied here for reduced the dimension of a large number of data sets. The new data set is used to run the k-means clustering algorithm. It is shown that the clustering is more accurate with the processed data set by PCA. Therefore, the prepared data set is used to run the ANN model that has a smaller size with higher information and minimum computational time. This study shows the data preparation part to train the ANN model.
{"title":"Data Processing Method for Artificial Neural Network ANN Based Micro grid Protection Model","authors":"Baidya Sanghita, Nandi Champa","doi":"10.46632/ese/2/1/18","DOIUrl":"https://doi.org/10.46632/ese/2/1/18","url":null,"abstract":"Effective fault detection and isolation technologies are very necessary for uninterrupted power supply and for making a flexible protection scheme. Almost all protection schemes in the power system are based on data exchange among protection units through a strong communication structure. Thus, it is important to deal with a large amount of data. Artificial Intelligence (AI) is one of the key factors in this regard. AI has several sections and Artificial Neural Network (ANN) is one of them. It is suggested to implement the ANN-based models while working with big data. The existing protection models are facing difficulties while trying to deal with big data. Thus ANN-based approaches have come into the front line in advanced power system networks. The performance of the ANN model is depending on the training of the data set. Hence in this work, we are focusing on preparing the data to provide input in the ANN model. The principal component analysis (PCA) method is applied here for reduced the dimension of a large number of data sets. The new data set is used to run the k-means clustering algorithm. It is shown that the clustering is more accurate with the processed data set by PCA. Therefore, the prepared data set is used to run the ANN model that has a smaller size with higher information and minimum computational time. This study shows the data preparation part to train the ANN model.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115781839","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}
Nowadays we can see a lot of accidents occurring on the road. And nearly 78.4% of road accidents are occurring due to the drowsiness of drivers riding the vehicles. To avoid road accidents, there is a need for a driver assistance system for monitoring the activities of drivers. The proposed technique monitors the driver's eye movements using an eye blink sensor located in the device, in case of driver closes the eye frequently or other abnormal moments occurred, the eye blink sensors produce the alarm sound for altering the driver to stop the vehicle with an IR sensor attached to it. Also, an alcohol sensor is attached to it which detects the alcohol consumed by the driver and in case of alcohol is detected, it buzzes an alarm which in order avoids the road accidents.
{"title":"Implementation of Driver Drowsiness Detection and Accident Prevention System Using Wireless Sensors","authors":"","doi":"10.46632/eae/2/1/1","DOIUrl":"https://doi.org/10.46632/eae/2/1/1","url":null,"abstract":"Nowadays we can see a lot of accidents occurring on the road. And nearly 78.4% of road accidents are occurring due to the drowsiness of drivers riding the vehicles. To avoid road accidents, there is a need for a driver assistance system for monitoring the activities of drivers. The proposed technique monitors the driver's eye movements using an eye blink sensor located in the device, in case of driver closes the eye frequently or other abnormal moments occurred, the eye blink sensors produce the alarm sound for altering the driver to stop the vehicle with an IR sensor attached to it. Also, an alcohol sensor is attached to it which detects the alcohol consumed by the driver and in case of alcohol is detected, it buzzes an alarm which in order avoids the road accidents.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","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":"131057727","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}
This paper describes a smart Wi-Fi door lock system developed using the esp32 cam and BLYNK app. the system aims to enhance home security by providing real-time notifications and visual verification of visitors. When the doorbell rings, the homeowner receives a notification on their smartphone along with a captured image of the person at the door. This allows the homeowner to remotely verify the individual's identity before granting access by unlocking the door through the door security system application. by bridging traditional door locks with advanced technology, this solution offers convenience and control to homeowners, ensuring the safety of their homes even when they are not present.
{"title":"Wi-Fi Door Lock Using Esp32 Cam and Blynk","authors":"P. Divya, V. Devaraj, V. Aswin","doi":"10.46632/eae/2/1/18","DOIUrl":"https://doi.org/10.46632/eae/2/1/18","url":null,"abstract":"This paper describes a smart Wi-Fi door lock system developed using the esp32 cam and BLYNK app. the system aims to enhance home security by providing real-time notifications and visual verification of visitors. When the doorbell rings, the homeowner receives a notification on their smartphone along with a captured image of the person at the door. This allows the homeowner to remotely verify the individual's identity before granting access by unlocking the door through the door security system application. by bridging traditional door locks with advanced technology, this solution offers convenience and control to homeowners, ensuring the safety of their homes even when they are not present.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"78 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":"133552504","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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