2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)最新文献_第8页

Internet of Things Assisted Road Traffic and Safety Monitoring Scheme using Sensitive Alcohol Detectors with Speed Analyzing Protocol 物联网辅助道路交通和安全监测方案使用敏感酒精探测器与速度分析协议

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Pub Date : 2023-05-25 DOI: 10.1109/ACCAI58221.2023.10199292

Judy Simon, N. Kapileswar, K. G, J. Venu Gopal Reddy., V. Narendra Reddy., J. Naga Lakshmi.

引用次数: 0

A Novel Method for Detecting and Predicting Emerging Disease in Poultry Chickens Based on MobileNet Model 基于MobileNet模型的家禽鸡新发疾病检测与预测方法

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Pub Date : 2023-05-25 DOI: 10.1109/ACCAI58221.2023.10200749

T. Joel, B. S. Dharshini, D. D., Gangaaraam, Poojitha, Nandha Kumar

{"title":"A Novel Method for Detecting and Predicting Emerging Disease in Poultry Chickens Based on MobileNet Model","authors":"T. Joel, B. S. Dharshini, D. D., Gangaaraam, Poojitha, Nandha Kumar","doi":"10.1109/ACCAI58221.2023.10200749","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10200749","url":null,"abstract":"The chicken business has a significant impact on the food manufacturing sector. Concerns over poultry birds’ quality have increased globally as demand has risen. Chicken eggs and chicken meat are both helped along by the industry’s commitment to quality control. The industry’s players are worried about the welfare of the birds because of the rising demand for poultry meat. The poultry sector is able to keep better tabs on the well-being of its chickens thanks to recent technology breakthroughs. With the use of Internet of Things (IoT)-based wearable sensing devices like accelerometers and gyro devices, avian diseases and chicken health may now be diagnosed via video surveillance, voice observations, and feces inspections. Placed atop a chicken, these motion detectors send the hen’s daily movements to the internet for examination. It’s a difficult problem to analyze such data and provide more precise forecasts regarding chicken health. In this research, we present a framework for an Internet of Things-based prediction service that can identify illnesses in chicken flocks at an early stage. The MobileNet approach has been shown to reach a 97% accuracy in both theoretical analysis and experimental findings. In addition, the suggested research compares the efficacy of several classification models to provide a more precise and top-performing classification strategy. The primary goal of the research is to provide predictive service architecture based on Industrial IoT that can more precisely categorize poultry hens in real time.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129161285","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}

引用次数: 1

Adaptive Neuro Fuzzy Data Aggregation Model for Developing and Planning for Aquaculture Farming Practices 水产养殖养殖方式开发与规划的自适应神经模糊数据聚合模型

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Pub Date : 2023-05-25 DOI: 10.1109/ACCAI58221.2023.10200854

G. Shahana, P. Ezhilarasi, S. Kannan

{"title":"Adaptive Neuro Fuzzy Data Aggregation Model for Developing and Planning for Aquaculture Farming Practices","authors":"G. Shahana, P. Ezhilarasi, S. Kannan","doi":"10.1109/ACCAI58221.2023.10200854","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10200854","url":null,"abstract":"The dynamic nature of environmental elements limits the power and information flow of sensor-based network systems, which are critical to the performance of real-time systems, particularly in the fisheries/aquaculture sector. There is a need for a techniquewhich will improve the network information flow. As a result, a data aggregation process utilising advanced artificial intelligence methods such as Sugeno and mamdanifuzzy system, Adaptive Neuro (or Network based) -Fuzzy Inference System, deep learning, neural networks, and others to reduce the communication activity that creates a single data by aggregating information from a group of various source data in the cluster head. In this backdrop, sugeno fuzzy based adaptive neuro fuzzy data aggregation model/system was developed and validated in aquaculture systems to minimise traffic, improve sensor network efficiency, and create a cost-effective system for the predicted output. It will also be valuable for creating and planning aquaculture farming practises. Results obtained from the models were validated using four statistical parameters. In this model, 70 training dataset and 30 testing dataset were used for validation. The aggregation provides accurate result and has Rootmean square error (0.01936), Coefficient of determination (0.999999245), Mean relative percent error (0.1936)and Variance Account For (99.9837 %). the results of the developed ANFIS model and its tool reveals that will be useful for developing and planning aquaculture farming practices.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128639451","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}

引用次数: 0

Fuzzy and ANN based model for Test case prioritization for Regression testing 基于模糊神经网络的回归测试用例优先级模型

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Pub Date : 2023-05-25 DOI: 10.1109/ACCAI58221.2023.10199547

Dr B Nithya, Dr. B. G. Prasanthi

{"title":"Fuzzy and ANN based model for Test case prioritization for Regression testing","authors":"Dr B Nithya, Dr. B. G. Prasanthi","doi":"10.1109/ACCAI58221.2023.10199547","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10199547","url":null,"abstract":"This research article performs the prioritization of the test case to test the software system after the occurrence of changes for Regression testing. The test expert here will categorize the sets as Optimistic test cases and Pessimistic test cases as formatted data for preprocessing by the Fuzzy rules. The optimistic test cases ensure that they are considered for regression testing by the tester. They are allowed to go into the next phase for deciding the prioritization. The test case is expected to have the details of case_id, case_name, case_details, predicted_result, obtained_result, seconds_time, and status. The ANN model deployed, gives the ranking to only Optimistic test cases by ensuring its capability to a dynamic environment. The efficiency of the regression testing on the proposed ANN model is evaluated by representing the faults, statements, and paths using the average percentage. The results provide a superior value above 95% when compared to the other methods taken in literature survey. The future scope of this ANN-based model can be used for prioritizing, selecting, and categorizing every cycle using reinforcement learning methods.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115820962","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}

引用次数: 1

Breast Cancer Tissue Identification Using Deep Learning in Mammogram Images 乳房x光图像中使用深度学习的乳腺癌组织识别

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Pub Date : 2023-05-25 DOI: 10.1109/ACCAI58221.2023.10199234

Sathish Kumar, Praveen Kumar

引用次数: 1

Dynamic Healthcare System using Cloud Computing 使用云计算的动态医疗保健系统

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Pub Date : 2023-05-25 DOI: 10.1109/ACCAI58221.2023.10200152

C. A. Subasini, Sarah Swetha Peter N, Sneha Ravishankar, A. Sheeba

引用次数: 0

Sensor Information Transmission System Using LORA based Communication in a Nanosatellite 基于LORA通信的纳米卫星传感器信息传输系统

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Pub Date : 2023-05-25 DOI: 10.1109/ACCAI58221.2023.10199424

Syed Owais Hussain, Zaib Unnisa Nayeem, K. Vasanth, S. Tejaswi, L. Murali, A. Praveen Martin

引用次数: 0

Record Framework Utilization for the Collection of Wireless Device Static Users 无线设备静态用户采集的记录框架利用

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Pub Date : 2023-05-25 DOI: 10.1109/ACCAI58221.2023.10200577

Maganti Syamala, Annaji Kuthe, V. Selvakumar, Alankrita Joshi, K. Baranidharan, J. Dhanraj

{"title":"Record Framework Utilization for the Collection of Wireless Device Static Users","authors":"Maganti Syamala, Annaji Kuthe, V. Selvakumar, Alankrita Joshi, K. Baranidharan, J. Dhanraj","doi":"10.1109/ACCAI58221.2023.10200577","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10200577","url":null,"abstract":"The cell of today is a typical instrument. It has become a significant \"social item,\" as opposed to only a minor \"specialized object,\" in the regular daily existences of its users. In this article, we look at a few ongoing improvements in the examination of mobile phone data. With the developing openness of enormous, anonymised datasets, this field of concentrate previously seemed decade prior and has since formed into an independent subject. The estimating investigation of record framework utilization for a gathering of mobile gadget users in different spots is introduced in this work. The purpose of this research is to refute the notion that mobile system behaviour can be modelled as being uniform across different environments. The research demonstrates that when participants travel between places, they obtain statistically substantially diverse sets of data. These findings call into question how mobile computing systems are normally evaluated, which often models a user's behaviour as being comparable to her behaviour at a single place over a longer length of time.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114575460","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}

引用次数: 0

Early Detection of Breast Cancer with IoT: A Promising Solution 物联网早期检测乳腺癌:一个有前途的解决方案

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Pub Date : 2023-05-25 DOI: 10.1109/ACCAI58221.2023.10199910

H. D, Alex David S, Almas Begum, Potti Hemanth

{"title":"Early Detection of Breast Cancer with IoT: A Promising Solution","authors":"H. D, Alex David S, Almas Begum, Potti Hemanth","doi":"10.1109/ACCAI58221.2023.10199910","DOIUrl":"https://doi.org/10.1109/ACCAI58221.2023.10199910","url":null,"abstract":"Breast cancer is a serious health concern that affects millions of women worldwide. Early detection is crucial for effective management and increasing the chances of survival. However, traditional methods of breast cancer detection can be time-consuming, expensive, and inaccessible to many women. In recent years, the Internet of Things (IoT) has emerged as a promising solution for healthcare providers to monitor and manage patients remotely. By leveraging IoT devices such as wearables and sensors, healthcare providers can collect data on patients' health and track changes over time. This paper explores the use of IoT in breast cancer detection and management. Breast Cancer Detection System using IoT presented in this work that combines wearable devices and sensors to monitor changes in breast tissue and collect data on a patient's health. The collected data is analysed using machine learning algorithms to identify potential abnormalities and provide early warning signs of breast cancer. The system is designed to be affordable and accessible, making it particularly suitable for use in low-income or rural areas where traditional methods of breast cancer detection may not be available.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115308023","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}

引用次数: 2

A Multi Layered Model for Polystic Syndrome Perception using CNMP 基于CNMP的多囊综合征多层感知模型

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) Pub Date : 2023-05-25 DOI: 10.1109/ACCAI58221.2023.10200936

Mithun P, Balamurali A, D. A., Sundarababu Maddu, Teena D, Swetha Ss

引用次数: 0