Pub Date : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193264
Mr. S. Vimalkumar, Dr.R. Latha
Maize is a main global food crop and is the most productive grain crop. It is also an optimum feed for the progress of animal husbandry and crucial raw material for the chemical industry, light industry, health medicine, and. Diseases are the significant factor limiting the high and stable yield of maize. For classifying diseases based on that damages the plants, the leaves of affected plants can be studied utilizing pixel-wise approaches. The Convolutional Neural Network (CNN) is the most effectual Deep Learning (DL) algorithm utilized in classification of an image to correctly diagnose plant ailments. Therefore, this study introduces an automated Maize Leaf Disease Detection using Biogeography-based Optimization with Deep Learning (MLDDBBODL) algorithm. The presented MLDD-BBODL method aims to identify and classify the occurrence of maize disease accurately. To achieve this, the presented MLDD-BBODL method employs contrast enhancement as an initial preprocessing stage. Besides, the SqueezeNet model is exploited for the derivation of feature vectors. Meanwhile, a Backpropagation Neural Network (BPNN) classifier is utilized for the recognition of maize leaf ailments. Furthermore, the BBO technique is implemented for the parameter tuning of the BPNN model which in turn enhances the classification results. The performance evaluation of the MLDD-BBODL technique is carried out on the leaf disease dataset. An extensive comparison study stated that the MLDD-BBODL technique reaches outperformed results over other recent approaches in terms of different measures.
{"title":"Heuristic Optimization with Deep Learning based Maize Leaf Disease Detection Model","authors":"Mr. S. Vimalkumar, Dr.R. Latha","doi":"10.1109/ICESC57686.2023.10193264","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193264","url":null,"abstract":"Maize is a main global food crop and is the most productive grain crop. It is also an optimum feed for the progress of animal husbandry and crucial raw material for the chemical industry, light industry, health medicine, and. Diseases are the significant factor limiting the high and stable yield of maize. For classifying diseases based on that damages the plants, the leaves of affected plants can be studied utilizing pixel-wise approaches. The Convolutional Neural Network (CNN) is the most effectual Deep Learning (DL) algorithm utilized in classification of an image to correctly diagnose plant ailments. Therefore, this study introduces an automated Maize Leaf Disease Detection using Biogeography-based Optimization with Deep Learning (MLDDBBODL) algorithm. The presented MLDD-BBODL method aims to identify and classify the occurrence of maize disease accurately. To achieve this, the presented MLDD-BBODL method employs contrast enhancement as an initial preprocessing stage. Besides, the SqueezeNet model is exploited for the derivation of feature vectors. Meanwhile, a Backpropagation Neural Network (BPNN) classifier is utilized for the recognition of maize leaf ailments. Furthermore, the BBO technique is implemented for the parameter tuning of the BPNN model which in turn enhances the classification results. The performance evaluation of the MLDD-BBODL technique is carried out on the leaf disease dataset. An extensive comparison study stated that the MLDD-BBODL technique reaches outperformed results over other recent approaches in terms of different measures.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131577207","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193491
R. Devi, S. Deepthi Shree, K. S. Harita, L. Keerthika
Cardiac arrest claims the lives of many people among us. Recent years have seen an increase in cases of cardiac arrest while driving. This is a result of their diet, advanced age, lack of exercise, and numerous other factors. Cardiovascular arrest is the main cause of death in today’s world. A serious medical emergency like cardiac arrest needs to be attended to right away. Cardiac arrest is difficult to recognize, and male and female cardiac arrest symptoms differ. This study develops a novel system to combat and defend our society against heart diseases and attacks. Utilizing this system requires riding a motorbike. It tracks the user’s heart rate using a heart rate sensor, and in the event of a cardiac arrest, it alerts the user’s family and emergency contacts. Additionally, it averts potential tragedies. As the cause is identified earlier by this system, the victim may also be spared from a potentially fatal accident.
{"title":"Sensor based Cardiac Arrest Monitoring using Internet of Things (IoT)","authors":"R. Devi, S. Deepthi Shree, K. S. Harita, L. Keerthika","doi":"10.1109/ICESC57686.2023.10193491","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193491","url":null,"abstract":"Cardiac arrest claims the lives of many people among us. Recent years have seen an increase in cases of cardiac arrest while driving. This is a result of their diet, advanced age, lack of exercise, and numerous other factors. Cardiovascular arrest is the main cause of death in today’s world. A serious medical emergency like cardiac arrest needs to be attended to right away. Cardiac arrest is difficult to recognize, and male and female cardiac arrest symptoms differ. This study develops a novel system to combat and defend our society against heart diseases and attacks. Utilizing this system requires riding a motorbike. It tracks the user’s heart rate using a heart rate sensor, and in the event of a cardiac arrest, it alerts the user’s family and emergency contacts. Additionally, it averts potential tragedies. As the cause is identified earlier by this system, the victim may also be spared from a potentially fatal accident.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131857901","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 many nations, school buses are viewed as effortless options for parents to send their children to their schools. However, nowadays, parents are distressed regarding their wards because of more incidents of students going missing. In certain situations, for the school bus to arrive, pupils may have to wait for a prolonged period. Waiting for school buses to drop off/pick up the children in the morning and then in the afternoon is a waste of time, even for parents, peculiarly with the congestion at peak hours. Certain technologies are available that are employed to guarantee the security of the students, yet they fall short of providing parents with efficient services. The proposed work describes the design of a Bus Boarding-Deboarding and Location Notifying System, capable of yielding effective services by providing the amenity to track the bus location using cutting-edge technologies like Global Positioning System (GPS) tracking and Radio Frequency Identification (RFID). The suggested system uses RFID, GPS, and GSM technologies to track pupils within a school bus. Through short messaging services, parents may stay updated on their child’s boarding/deboarding status, as well as monitor the bus route and estimate its arrival time. Safe and convenient school buses can cut back on the usage of private cars and eventually alleviate traffic congestion in cities, particularly during school hours. The suggested intelligent and secured tracking system for school buses allows parents to keep track of all buses.
{"title":"GPS/GSM based School Bus Boarding-Deboarding and Location Notifying System","authors":"Ashwini Sawant, Pooja Narayanan, Omkar Mourya, Sarthak Adhangale, Gaurang Kedare","doi":"10.1109/ICESC57686.2023.10193226","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193226","url":null,"abstract":"In many nations, school buses are viewed as effortless options for parents to send their children to their schools. However, nowadays, parents are distressed regarding their wards because of more incidents of students going missing. In certain situations, for the school bus to arrive, pupils may have to wait for a prolonged period. Waiting for school buses to drop off/pick up the children in the morning and then in the afternoon is a waste of time, even for parents, peculiarly with the congestion at peak hours. Certain technologies are available that are employed to guarantee the security of the students, yet they fall short of providing parents with efficient services. The proposed work describes the design of a Bus Boarding-Deboarding and Location Notifying System, capable of yielding effective services by providing the amenity to track the bus location using cutting-edge technologies like Global Positioning System (GPS) tracking and Radio Frequency Identification (RFID). The suggested system uses RFID, GPS, and GSM technologies to track pupils within a school bus. Through short messaging services, parents may stay updated on their child’s boarding/deboarding status, as well as monitor the bus route and estimate its arrival time. Safe and convenient school buses can cut back on the usage of private cars and eventually alleviate traffic congestion in cities, particularly during school hours. The suggested intelligent and secured tracking system for school buses allows parents to keep track of all buses.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132280252","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193272
E. Indhuja, J. Angelina, S. Subhashini, B.Ajay Kumar, L. Amulya, G. Gopi
This hospital management system aims to develop a user-friendly and efficient system using PHP as the front-end interface and MySQL as the database. The system enables the management of patient information, doctor information, prescription details, and appointment details. The system provides a centralized platform for the management of these aspects, enabling healthcare providers to access and manage the data in real-time from anywhere. The system allows authorized users to add or remove doctor details, manage patient appointments and claims securely. The system has been designed to ensure the protection of personal data to speed up data processing. The system provides various features such as appointment scheduling, patient record management, doctor record management, prescription management, and billing management. Overall, the hospital management system is a reliable and efficient solution that streamlines the management of healthcare facilities.
{"title":"E-Health Records Stored Over the Cloud with Automated Medication Reminders for Enhanced Patient Care","authors":"E. Indhuja, J. Angelina, S. Subhashini, B.Ajay Kumar, L. Amulya, G. Gopi","doi":"10.1109/ICESC57686.2023.10193272","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193272","url":null,"abstract":"This hospital management system aims to develop a user-friendly and efficient system using PHP as the front-end interface and MySQL as the database. The system enables the management of patient information, doctor information, prescription details, and appointment details. The system provides a centralized platform for the management of these aspects, enabling healthcare providers to access and manage the data in real-time from anywhere. The system allows authorized users to add or remove doctor details, manage patient appointments and claims securely. The system has been designed to ensure the protection of personal data to speed up data processing. The system provides various features such as appointment scheduling, patient record management, doctor record management, prescription management, and billing management. Overall, the hospital management system is a reliable and efficient solution that streamlines the management of healthcare facilities.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133808479","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193098
C. Jamunadevi, J. Bharanitharan, S. Deepa, T. J. P. Antony
Brain tumors are a type of cancerous growth that occurs in the brain tissue. It can develop in any part of the brain and can be either malignant or benign. Brain tumors can cause a range of symptoms such as headaches. seizures. difficulty speaking, vision problems, and cognitive impairment [1]. An early and precise diagnosis of a brain tumor is crucial for the effective administration of the remedy. Brain tumors can start outside the brain and spread there, or it can start inside the brain and grow there. Headaches, nausea, and balance issues are some of the indications and symptoms that the tumor can produce as it spreads because it puts pressure on the surrounding brain tissue and alters how it functions. Early tumor detection minimizes the need for surgery and other forms of treatment, improving the prognosis for many patients. The development of new technologies that improve neurosurgery’s success rate and avoid problems is still ongoing today. Magnetic resonance imaging (MRr) is one of the most often utilized procedures for analyzing pictures of brain tumors [6]. EEG signal is used in the suggested method to forecast brain tumors. SVM is used by this system to forecast brain tumors. When compared to other methods, the accuracy rate of the SVM (support vector machine) approach was shown to be higher.
{"title":"Brain Tumor Prediction from EEG Signal using Machine Learning Algorithm","authors":"C. Jamunadevi, J. Bharanitharan, S. Deepa, T. J. P. Antony","doi":"10.1109/ICESC57686.2023.10193098","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193098","url":null,"abstract":"Brain tumors are a type of cancerous growth that occurs in the brain tissue. It can develop in any part of the brain and can be either malignant or benign. Brain tumors can cause a range of symptoms such as headaches. seizures. difficulty speaking, vision problems, and cognitive impairment [1]. An early and precise diagnosis of a brain tumor is crucial for the effective administration of the remedy. Brain tumors can start outside the brain and spread there, or it can start inside the brain and grow there. Headaches, nausea, and balance issues are some of the indications and symptoms that the tumor can produce as it spreads because it puts pressure on the surrounding brain tissue and alters how it functions. Early tumor detection minimizes the need for surgery and other forms of treatment, improving the prognosis for many patients. The development of new technologies that improve neurosurgery’s success rate and avoid problems is still ongoing today. Magnetic resonance imaging (MRr) is one of the most often utilized procedures for analyzing pictures of brain tumors [6]. EEG signal is used in the suggested method to forecast brain tumors. SVM is used by this system to forecast brain tumors. When compared to other methods, the accuracy rate of the SVM (support vector machine) approach was shown to be higher.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117345919","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193402
R. Sathya, V. Bharathi, S. Ananthi, K. Vaidehi, S. Sangeetha
The creation of an automated security system aims to protect residences and workplaces by automating visitor entrance and enabling more flexibility in visitor record maintenance. Among all biometric authentications, face recognition is very secure because of unique facial features. There are two phases in authentication, face mask detection and face recognition. In first phase, Grassmann algorithm is used for face mask detection. If any mask is discovered, an alarm will sound for the user to remove the mask and in second phase face recognition is done through CNN. The CNN method is utilized to compare facial traits, and if an outsider is found, a warning message is then displayed to the user. Real time datasets are collected for training and testing the CNN model. The executed result gives 98.02% higher accuracy compared to existing method.
{"title":"Intelligent Home Surveillance System using Convolution Neural Network Algorithms","authors":"R. Sathya, V. Bharathi, S. Ananthi, K. Vaidehi, S. Sangeetha","doi":"10.1109/ICESC57686.2023.10193402","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193402","url":null,"abstract":"The creation of an automated security system aims to protect residences and workplaces by automating visitor entrance and enabling more flexibility in visitor record maintenance. Among all biometric authentications, face recognition is very secure because of unique facial features. There are two phases in authentication, face mask detection and face recognition. In first phase, Grassmann algorithm is used for face mask detection. If any mask is discovered, an alarm will sound for the user to remove the mask and in second phase face recognition is done through CNN. The CNN method is utilized to compare facial traits, and if an outsider is found, a warning message is then displayed to the user. Real time datasets are collected for training and testing the CNN model. The executed result gives 98.02% higher accuracy compared to existing method.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116886125","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193064
G. Jenulin Makros, J. Ancy Jenifer., B. V. Adithya, R. Rohan Samuel, M. Giribalan
Parking spots for people with disabilities help to create an environment that is accessible to everyone. Abusing these parking spots by parking when you don’t have a disability or when you don’t have a valid accessible parking permit prevents persons with disabilities from accessing resources, which is both unlawful and immoral. Through the use of a mobile application, this project allows authorized users to secure a parking place. To determine if the reserved vehicle has parked or not, this system employs RFID readers that can help recognizing the disabled vehicle. Each handicapped parking area has an IR sensor to detect the presence of a car. To warn non-disabled drivers who try to park in places reserved for the disabled, this system also uses an alarm system. The goal of this research is to make clear how various of the smart parking approaches under investigation may be utilized to administer parking for handicapped individuals and improved by validating disability parking authorization.
{"title":"Disabled Smart Parking Management using RFID Technology","authors":"G. Jenulin Makros, J. Ancy Jenifer., B. V. Adithya, R. Rohan Samuel, M. Giribalan","doi":"10.1109/ICESC57686.2023.10193064","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193064","url":null,"abstract":"Parking spots for people with disabilities help to create an environment that is accessible to everyone. Abusing these parking spots by parking when you don’t have a disability or when you don’t have a valid accessible parking permit prevents persons with disabilities from accessing resources, which is both unlawful and immoral. Through the use of a mobile application, this project allows authorized users to secure a parking place. To determine if the reserved vehicle has parked or not, this system employs RFID readers that can help recognizing the disabled vehicle. Each handicapped parking area has an IR sensor to detect the presence of a car. To warn non-disabled drivers who try to park in places reserved for the disabled, this system also uses an alarm system. The goal of this research is to make clear how various of the smart parking approaches under investigation may be utilized to administer parking for handicapped individuals and improved by validating disability parking authorization.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116272752","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193389
Dr.M.Jagadeeswari, P.Naveen Karthi, S.Lokith, S. Ram, V.A.Nitish Kumar
In the digital era, organizations, especially financial institutions, place an increasing emphasis on data security and privacy. To maintain data confidentiality, availability, and integrity, financial auditing organizations need secure file sharing and audit trail tracking technologies. Financial auditing firms demand a cloud-based audit trail monitoring platform as well as a secure file exchange platform with high encryption standards. Users may submit and download data using a secure online interface. An administrative dashboard simplifies user registration and deactivation. The audit trail function allows the administrator to know who requested a file, when they requested it, and when the file was downloaded. This audit trail monitoring technology raises compliance responsibilities. The platform uses Advanced Encryption Standard (AES) encryption to secure data. The platform encrypts submitted files using a random key. The file owner gets a download request, which he or she may accept or deny. If the request is granted, the owner sends the user the AES key required to decode and download the file. On the platform, Amazon Web Services and Relational Database Service (RDS) hold massive files (RDS). The Amazon database is protected by login and DoS alarms. Login notifications for Amazon root and IAM users notify the administrator of the browser, IP address, date, and number of attempted logins. The administrator receives DoS attack notifications and database traffic statistics from a variety of sources. Administrators may use alerts to prevent security breaches. The solution facilitates secure and timely communication between financial auditing firms. Data is protected by AES encryption and Amazon S3 storage, while audit trail monitoring and alerts prevent data breaches.
在数字时代，组织，特别是金融机构，越来越重视数据安全和隐私。为了维护数据的机密性、可用性和完整性，财务审计组织需要安全的文件共享和审计跟踪跟踪技术。金融审计公司需要基于云的审计跟踪监控平台，以及具有高加密标准的安全文件交换平台。用户可以使用安全的在线界面提交和下载数据。管理指示板简化了用户注册和停用。审计跟踪功能允许管理员知道谁请求了文件，何时请求，以及文件何时被下载。这种审计跟踪监视技术提高了遵从性责任。该平台采用高级加密标准AES (Advanced Encryption Standard)加密来保护数据。该平台使用随机密钥加密提交的文件。文件所有者收到下载请求，他或她可以接受或拒绝。如果请求被批准，所有者向用户发送解码和下载文件所需的AES密钥。在该平台上，Amazon Web Services和关系数据库服务(RDS)保存大量文件(RDS)。Amazon数据库有登录和DoS告警保护。Amazon root和IAM用户的登录通知通知管理员浏览器、IP地址、登录日期和尝试登录次数。管理员可以从不同的来源接收DoS攻击通知和数据库流量统计信息。管理员可以使用警报来防止安全漏洞。该解决方案促进了财务审计事务所之间安全、及时的沟通。数据由AES加密和Amazon S3存储保护，而审计跟踪监控和警报可防止数据泄露。
{"title":"A Secure File Sharing and Audit Trail Tracking Platform with Advanced Encryption Standard for Cloud-Based Environments","authors":"Dr.M.Jagadeeswari, P.Naveen Karthi, S.Lokith, S. Ram, V.A.Nitish Kumar","doi":"10.1109/ICESC57686.2023.10193389","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193389","url":null,"abstract":"In the digital era, organizations, especially financial institutions, place an increasing emphasis on data security and privacy. To maintain data confidentiality, availability, and integrity, financial auditing organizations need secure file sharing and audit trail tracking technologies. Financial auditing firms demand a cloud-based audit trail monitoring platform as well as a secure file exchange platform with high encryption standards. Users may submit and download data using a secure online interface. An administrative dashboard simplifies user registration and deactivation. The audit trail function allows the administrator to know who requested a file, when they requested it, and when the file was downloaded. This audit trail monitoring technology raises compliance responsibilities. The platform uses Advanced Encryption Standard (AES) encryption to secure data. The platform encrypts submitted files using a random key. The file owner gets a download request, which he or she may accept or deny. If the request is granted, the owner sends the user the AES key required to decode and download the file. On the platform, Amazon Web Services and Relational Database Service (RDS) hold massive files (RDS). The Amazon database is protected by login and DoS alarms. Login notifications for Amazon root and IAM users notify the administrator of the browser, IP address, date, and number of attempted logins. The administrator receives DoS attack notifications and database traffic statistics from a variety of sources. Administrators may use alerts to prevent security breaches. The solution facilitates secure and timely communication between financial auditing firms. Data is protected by AES encryption and Amazon S3 storage, while audit trail monitoring and alerts prevent data breaches.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116178999","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193597
S.Saravanan, B. Prakash, Navya Guntuku, D. Kumar, C. Akshaya, P. Chinna, D. Goud
As drinking water becomes more and more contaminated and polluted; it poses one of the greatest risks today. The diseases that could be transmitted by the contaminated water to humans and animals have an effect on the ecosystem’s life cycle. Early detection of water contamination enables proper action to be taken and harmful situations to be avoided. To guarantee the provision of pure water, real-time monitoring of the water’s quality is required. The need for intelligent solutions for monitoring water contamination is growing as sensors, connectivity, and Internet of Things (IoT) technology develop. This research study deals with an in-depth examination of current advancements in the field of intelligent water pollution monitoring systems. An IoT-based smart water quality monitoring system that continuously monitors the quality parameters is recommended by the research as being both affordable and efficient. The built-in model is tested using water samples, and the parameters are transferred to the cloud server to be processed further.
{"title":"A Novel Sensor based Water Quality Monitoring System using Internet of Things (IoT)","authors":"S.Saravanan, B. Prakash, Navya Guntuku, D. Kumar, C. Akshaya, P. Chinna, D. Goud","doi":"10.1109/ICESC57686.2023.10193597","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193597","url":null,"abstract":"As drinking water becomes more and more contaminated and polluted; it poses one of the greatest risks today. The diseases that could be transmitted by the contaminated water to humans and animals have an effect on the ecosystem’s life cycle. Early detection of water contamination enables proper action to be taken and harmful situations to be avoided. To guarantee the provision of pure water, real-time monitoring of the water’s quality is required. The need for intelligent solutions for monitoring water contamination is growing as sensors, connectivity, and Internet of Things (IoT) technology develop. This research study deals with an in-depth examination of current advancements in the field of intelligent water pollution monitoring systems. An IoT-based smart water quality monitoring system that continuously monitors the quality parameters is recommended by the research as being both affordable and efficient. The built-in model is tested using water samples, and the parameters are transferred to the cloud server to be processed further.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":"56 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116572303","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 : 2023-07-06DOI: 10.1109/ICESC57686.2023.10193180
K. Bhaskar, T. Kumanan, S. Sree Southry., Vetrimani Elangovan
Wireless Sensor Network (WSN) is distinguished by size, dynamism, and decentralization. These complicated properties give rise to various problems, one of which is the impact of wireless communications on the efficiency of networks and the protocols used for routing. The prediction methods of link reliability can boost the efficiency of the routing algorithms used in WSNs while preventing weak connections. This approach introduces a Deep neural network algorithm to improve link reliability (DILR) in WSN. A Deep neural network (DNN) algorithm is used to evaluate the input parameters like node Received Signal Strength, available bandwidth, delay, and packet received rate parameters for calculating the link reliability output. The available bandwidth parameter recognizes the efficient data transmitting path. The experimental outcomes illustrate that the DILR mechanism improves the link reliability among nodes and reduces routing overhead compared to the conventional mechanism.
无线传感器网络(WSN)的特点是规模、动态性和分散性。这些复杂的特性引起了各种各样的问题，其中之一就是无线通信对网络效率和用于路由的协议的影响。链路可靠性预测方法可以在防止弱连接的同时提高无线传感器网络路由算法的效率。该方法引入了一种深度神经网络算法来提高无线传感器网络的链路可靠性。采用深度神经网络(Deep neural network, DNN)算法对节点接收信号强度(Received Signal Strength)、可用带宽(available bandwidth)、时延(delay)、接收包速率(packet Received rate)等输入参数进行评估，计算链路可靠性输出。可用带宽参数用于识别有效的数据传输路径。实验结果表明，与传统机制相比，DILR机制提高了节点间链路的可靠性，降低了路由开销。
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