2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)最新文献_第5页

Design of a Novel Priority Mux Based Indoor Autonomous Surveillance Robot 一种新型优先复用室内自主监控机器人的设计

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193057

S. Mythri, Nanditha G Bharadwaj, Nanditha Pai, Ashwini, Netra S Soraganvi, B. N. Krupa

{"title":"Design of a Novel Priority Mux Based Indoor Autonomous Surveillance Robot","authors":"S. Mythri, Nanditha G Bharadwaj, Nanditha Pai, Ashwini, Netra S Soraganvi, B. N. Krupa","doi":"10.1109/I2CACIS57635.2023.10193057","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193057","url":null,"abstract":"Bank robberies have exacerbated with time. It is a daunting task to monitor the banks for human-based security, considering long hours. Autonomous surveillance robots, in such situations, are beneficial to patrol a particular environment by collecting data with an electronic payload. DRISHTI, the proposed robot model designed using Robot Operating System (ROS), includes facial recognition to raise an alert if any suspect is detected, and human tracking is implemented during night patrolling. An Intrusion Alarm Panel (IAP) is employed using external sensors to detect any unethical breaking of the vault in addition to the anti-theft feature. The robot surveillance is aided by autonomous patrolling using Cartographer-based Simultaneous Localization and Mapping (SLAM). The accuracy of the generated map of the prototype is found to be 95.31% with respect to the corresponding ground truth. The design of a novel priority mux is proposed to integrate the surveillance functionalities with the navigation node. The alert velocity command node is made to override the navigation velocity commands with a 10 times priority ratio using the novel priority mux with a latency of less than one millisecond.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132625693","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

Simulation of Real-Time Frontier Exploration in Confined & Cluttered Environment 受限与杂乱环境下的实时前沿探索仿真

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193051

I. Saleh, Nuradlin Borhan, Azan Yunus, W. Rahiman, D. Novaliendry, Risfendra

引用次数: 0

Design of a Simple Real-time Data Acquisition System for Healthcare Monitoring 一种简单的医疗监测实时数据采集系统的设计

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193260

L. Lee, Maryam Khalid, Mohd Abdalla

引用次数: 0

Performance Comparison of Machine Learning Classifiers for DDOS Detection and Mitigation on Software Defined Networks 软件定义网络中DDOS检测和缓解机器学习分类器的性能比较

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193601

Babangida Isyaku, K. A. Bakar, Muhammad Salisu Ali, Muhammed Nura Yusuf

{"title":"Performance Comparison of Machine Learning Classifiers for DDOS Detection and Mitigation on Software Defined Networks","authors":"Babangida Isyaku, K. A. Bakar, Muhammad Salisu Ali, Muhammed Nura Yusuf","doi":"10.1109/I2CACIS57635.2023.10193601","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193601","url":null,"abstract":"Software Defined Networks (SDN) is an emerging network with better network management through the separation of Control logic and data forwarding elements. Several emerging networks, including the Internet of Things, Wireless Body Area Networks, and Blockchain, are incorporating SDN technology to improve resource management, thereby speeding up network innovation. The increasing number of internet-connected devices and the growing number of online applications pose various security concerns. SDN suffered various security threats due to centralized network architecture and limited memory space in the switch Flowtable. Distributed Denial of Service (DDOS) attacks is among the severe security threats that flood the precious switch Flowtable with massive flows to hijack the network. Several machine-learning DDOS attack detection has been proposed to mitigate such threats. However, the choice of effective machine learning algorithms with high accuracy and short prediction and learning time is paramount. This study analyses the performance of eight machine-learning algorithms for DDOS detection and mitigation in SDN. On average, Decision Tree (DT) and Random Forest have the highest accuracy with 99.86%, respectively. Naive Bayes has a minimal prediction time of 144.511 seconds, while DT has the shortest learning time of 22229 seconds.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127548805","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

Agarwood Distillation Pot Via PID and Self-tuning Fuzzy Control 沉香蒸馏罐的PID和自整定模糊控制

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193175

Nurul Nadia Mohammad, Muhammad Danial Bin Ahmad Hilmie, N. Hambali, M. Rahiman

{"title":"Agarwood Distillation Pot Via PID and Self-tuning Fuzzy Control","authors":"Nurul Nadia Mohammad, Muhammad Danial Bin Ahmad Hilmie, N. Hambali, M. Rahiman","doi":"10.1109/I2CACIS57635.2023.10193175","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193175","url":null,"abstract":"Maintaining good control over water temperature is important to ensure the best quality of Agarwood product is obtained. Proportional-Integral-Derivative (PID) controller and Fuzzy Logic Controller (FLC) are widely used in this industry to control the plant’s water temperature at its optimum. In this research, the study objective is to estimate the transfer function of water temperature of small-scaled Agarwood distillation pot through Pseudo-Random Binary Sequence (PRBS) and Random Gaussian Signal (RGS) perturbation input signal, evaluate the efficiency of the estimated transfer function, and to design the controller using PID and FLC tuning method then comparing its control performance. Then, the comparative study between PID and FLC is demonstrated based on the PRBS and RGS perturbation input signal. Furthermore, model linearization and estimation are applied based on the input-output data during the modelling of the dynamic system. Both perturbation input signals’ transfer function were evaluated based on the value of FIT, MSE, and FPE. Then, performance comparison between PID and FLC was evaluated based on their rise time (Tr), settling time (Ts), and percentage of overshoot (%OS). The result obtained shows that the FLC with PRBS input signal provided the best overall performance with the rise time, Tr was 2149s, settling time, Ts was 2695s, and the percentage of overshoot, %OS was 1.965%.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123035215","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

Effect of Tag-to-Anchor and Multiple Tag Interference on UWB Sensors Accuracy for Dynamic Real-time Position Tracking of Mobile Robot in Indoor Environment 标签-锚和多标签干扰对超宽带传感器精度的影响，用于室内环境下移动机器人动态实时位置跟踪

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193553

Harun Dzulquornain Idris, A. N. Ibrahim

引用次数: 0

Confused vs Non-Confused Electroencephalography Signal Classification Using Deep Learning Algorithm 使用深度学习算法的混淆与非混淆脑电图信号分类

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193048

Z. Lim, Yong Li Neo

{"title":"Confused vs Non-Confused Electroencephalography Signal Classification Using Deep Learning Algorithm","authors":"Z. Lim, Yong Li Neo","doi":"10.1109/I2CACIS57635.2023.10193048","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193048","url":null,"abstract":"When students are doubtful or uncertain about a certain subject, they frequently face confusion. If students did not pose questions, it would be difficult for the teacher to see this circumstance. Eventually, this will slow down the pupils’ learning development and impact their academic performance. While confusion is a mental state, it is proposed to utilise the electroencephalogram (EEG) signal to evaluate if a pupil is confused or not. Unfortunately, it is challenging to distinguish between a confused and non-confused EEG signal based on basic characteristics like as frequency domain and power spectral density. As technology progresses, deep learning in artificial intelligence is currently a prevalent technique. Thus, this research aimed to run a series of experiments to determine which deep learning model is the best at classifying EEG signals as confused or not confused. The results indicate that the hybrid CNN-biLSTM deep learning model is superior to the six other deep learning models included in this study. In identifying the EEG signals of confused and non-confused pupils, it obtains an AUC of 82%, 76.7% accuracy, 76.9% recall rate (76.9%), 71.4% precision, and 76.5% specificity. The dependability of the hybrid CNN-biLSTM deep neural network indicates that it has the potential to be utilised in the classroom in the future to identify whether a student is confused or has fully grasped the curriculum that the teacher has taught. This can guarantee that the teacher efficiently transferred knowledge to the pupil.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131978728","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

Performance Evaluation of Optimum Number of Stages for ADPLL Ring Oscillator ADPLL环形振荡器最佳级数的性能评价

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193135

Syaza Norfilsha Ishak, Mohammad Faseehuddin, J. Sampe, N. Nayan, N. M. Yunus

{"title":"Performance Evaluation of Optimum Number of Stages for ADPLL Ring Oscillator","authors":"Syaza Norfilsha Ishak, Mohammad Faseehuddin, J. Sampe, N. Nayan, N. M. Yunus","doi":"10.1109/I2CACIS57635.2023.10193135","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193135","url":null,"abstract":"An all-digital phase-locked loop (ADPLL) has been demanded among academics and industries due to its advantages in the complementary-metal-oxide semiconductor (CMOS) technology process. In the ADPLL, one of the crucial blocks is the digital-controlled oscillator (DCO), which is a combination of the digital-to-analog converter (DAC) and the voltage-controlled oscillator (VCO). In this work, the approach of the CMOS inverter ring oscillator is designed using Cadence OrCad Capture with CMOS 90 nm technology process. The ring oscillator is designed with different stages, which are 3-stage, 5-stage, and 7-stage configurations. At the output of every stage, a 0.001pF capacitor is connected as a capacitance load. The result shows that the oscillation period started for the 7-stage is 0.1 ns, which is faster than the 5-stage and the 3-stage of the ring oscillator, which are 0.6 ns and 0.15, ns respectively. For the power consumption performance, the 3-stage recorded $52.47 mu mathrm{W}$ which is the lowest power dissipated compared to others.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"8 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128251189","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

Automation of Airport Baggage Handling System Using Factory I/O and Control by WinSPS-S7 PLC 基于工厂I/O和WinSPS-S7 PLC控制的机场行李处理系统自动化

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193273

R. Sam, M. Masrie, Z. Janin

引用次数: 0

Gas Sensor-Based Nondestructive Testing for Jackfruit Ripeness Level 基于气体传感器的菠萝蜜成熟度无损检测

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193593

Merrylle A. Gonzales, Jeanel Fiel M. Datingaling, Lennon A. Herman, Engr. Helcy D. Alon

{"title":"Gas Sensor-Based Nondestructive Testing for Jackfruit Ripeness Level","authors":"Merrylle A. Gonzales, Jeanel Fiel M. Datingaling, Lennon A. Herman, Engr. Helcy D. Alon","doi":"10.1109/I2CACIS57635.2023.10193593","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193593","url":null,"abstract":"Jackfruit is a fruit native to South and Southeast Asia that is now cultivated all over the world due to its adaptability, as it can be eaten both ripe and unripe. This study was conducted to accurately identify the Jackfruit’s ripeness. Four MQ families have been identified as the most effective for classifying the ripeness of Jackfruit based on the sensitivity of the sensors. MQ Gas Sensors such as MQ3, MQ5, MQ7, and MQ135 are used to determine the ripeness of the Jackfruit without cutting it open. Jackfruit emits an aroma, which can be used to determine the ripeness of the fruit. The data is collected using 36 Jackfruits, of which 12 Jackfruits each classification. This study evaluates the performance of a device designed to classify Jackfruits into three categories based solely on the gas concentration in their aroma: unripe, ripe, and forcibly ripe. As a result, the system can determine the level of ripeness of the jackfruit. Unripe jackfruit received a score of 1 for precision, recall, F1-Score, and accuracy. Meanwhile, ripe jackfruit received precision, recall, F1-score, and accuracy scores of 0.83333, 1, 0.9091, and 0.9444, respectively. Precision was given a score of 1 for forcibly ripe, while recall and F1-score were 0.8571 and 0.9231, respectively. Similarly, the precision score for forcibly ripe was 0.9444. The device’s overall accuracy rate was 96%, indicating that it distinguished the ripeness level of the jackfruit with high precision. The results of the study provide producers and consumers with a good course of action, allowing them to produce and consume fruit more efficiently and effectively. This not only minimizes food waste, but also ensures that the fruit is consumed at its optimal ripeness, leading to greater consumer satisfaction.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131567950","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