2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)最新文献_第6页

Design of an Automated System for Cattle-Feed Dispensing in Cattle-Cows 牛-奶牛饲料自动分配系统的设计

2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2021-12-01 DOI: 10.1109/UEMCON53757.2021.9666491

Iraiz Lucero Quintanilla Mosquera, Jesus Eduardo Rosales Fierro, Jhon Rodrigo Ortiz Zacarias, Jhamir Beltran Montero, Sario Angel Chamorro Quijano, Deyby Huamanchahua

引用次数: 16

Intelligent Cyber Safe Framework for Children 儿童智能网络安全框架

2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2021-12-01 DOI: 10.1109/UEMCON53757.2021.9666696

Mohomed Harfath, Rahal Amrith, Navindu Dulanaka, Praveen Perera, Lakmal Rupersinga, C. Liyanapathirana

{"title":"Intelligent Cyber Safe Framework for Children","authors":"Mohomed Harfath, Rahal Amrith, Navindu Dulanaka, Praveen Perera, Lakmal Rupersinga, C. Liyanapathirana","doi":"10.1109/UEMCON53757.2021.9666696","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666696","url":null,"abstract":"Technology-wise, children are much ahead of their parents. Due to hectic schedules and daily struggles, time is limited for parents. For that reason, the AI-powered child protection system helps protect children from modern cyber-attacks while offering parents more control over their children. Keyloggers, keystroke and mouse movement loggers help to collect data and can record user behaviour and find patterns. Furthermore, the use of those records is able to detect children’s improper behaviour and reveal children’s emotional states. Behavioral Data Extractor and Risk Analysis systems can analyze huge numbers of URLs and web content recorded by proxy, as well as application usage and screen times collected by background service. The Smart Resource Restricter is designed to help parents and children navigate the web safely and appropriately. The research can identify and prevent child predators. Indeed, cyberbullying and phishing attacks cross many boundaries, causing great harm to the community. It blocks outside threats and notifies parents of sexual and other online predators that often target children. The PandaGuardian successfully achieved its goal with the assistance of different algorithms and the respective outcomes. The model evaluation report, which compares all the methods, is a guardian companion. Parents could get assistance in order to safeguard their children from the day-to-day evolving cyber threats.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130439034","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

Buffer-Aided Collision Resolution for UHF RFID 超高频射频识别的缓冲辅助碰撞分辨率

2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2021-12-01 DOI: 10.1109/uemcon53757.2021.9666570

Gan Luan, N. Beaulieu, Xianpeng Wang, Mengxing Huang

引用次数: 0

Joint Disaster Classification and Victim Detection using Multi-Task Learning 基于多任务学习的联合灾害分类与受害者检测

2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2021-12-01 DOI: 10.1109/uemcon53757.2021.9666576

Mau-Luen Tham, Y. Wong, Ban-Hoe Kwan, Y. Owada, M. Sein, Yoong Choon Chang

{"title":"Joint Disaster Classification and Victim Detection using Multi-Task Learning","authors":"Mau-Luen Tham, Y. Wong, Ban-Hoe Kwan, Y. Owada, M. Sein, Yoong Choon Chang","doi":"10.1109/uemcon53757.2021.9666576","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666576","url":null,"abstract":"Recent advances in deep learning and computer vision have transformed surveillance into an important application for smart disaster monitoring systems. Based on the detected number of victims and activity of disasters, emergency response unit can dispatch manpower more efficiently, which could save more lives. However, most of existing disaster detection methods fall into the class of single-task learning, which can either detect victim or classify disaster. In contrast, this paper proposes a YOLO-based multi-task model which performs the aforementioned tasks simultaneously. This is accomplished by attaching a disaster classification head model to the backbone of a victim detection model. The head model is inherited from the MobileNetv2 architecture, and we precisely select the backbone feature map layer to which the head model is attached. For the victim detection, results reveal that the solution achieves up to 0.6938 and 20.31 in terms of average precision and frame per second, respectively. Whereas for the disaster classification, the algorithm is comparable with most deep learning models that are specifically trained for single task. This shows that our solution is flexible and robust enough to handle both victim detection and disaster classification.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128259220","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: 3

Development of Web Based Online One Stop Platform to Fight Covid-19 基于Web的新型冠状病毒肺炎在线一站式平台开发

2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2021-12-01 DOI: 10.1109/uemcon53757.2021.9666655

Ihfaz Tahmid Morshed, Mohammad Monirujjaman Khan, Saife Shuhaib Md. Enan, Fahim Tanzil Takin

引用次数: 0

An IOT Based Nurse Calling System for Real-time Emergency Alert Using Local Wireless Network 基于物联网的护士呼叫系统，利用本地无线网络实现实时紧急警报

2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2021-12-01 DOI: 10.1109/uemcon53757.2021.9666705

Omar Faruk Riyad, Ahraf Sharif, Arif-ur-Rahman Chowdhury Suhan, Mohammad Monirujjaman Khan

引用次数: 1

Visual Pollution Detection Using Google Street View and YOLO 使用谷歌街景和YOLO进行视觉污染检测

2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2021-12-01 DOI: 10.1109/uemcon53757.2021.9666654

Md. Yearat Hossain, Ifran Rahman Nijhum, Abu Adnan Sadi, Md. Tazin Morshed Shad, Rashedur M. Rahman

{"title":"Visual Pollution Detection Using Google Street View and YOLO","authors":"Md. Yearat Hossain, Ifran Rahman Nijhum, Abu Adnan Sadi, Md. Tazin Morshed Shad, Rashedur M. Rahman","doi":"10.1109/uemcon53757.2021.9666654","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666654","url":null,"abstract":"In recent years, visual pollution has become a major concern in rapidly rising cities. This research deals with detecting visual pollutants from the street images collected using Google Street View. For this experiment, we chose the streets of Dhaka, the capital city of Bangladesh, to build our image dataset, mainly because Dhaka was ranked recently as one the most polluted cities in the world. However, the methods shown in this study can be applied to images of any city around the world and would produce close to a similar output. Throughout this study, we tried to portray the possible utilisation of Google Street View in building datasets and how this data can be used to solve environmental pollution with the help of deep learning. The image dataset was created manually by taking screenshots from various angles of every street view with visual pollutants in the frame. The images were then manually annotated using CVAT and were fed into the model for training. For the detection, we have used the object detection model YOLOv5 to detect all the visual pollutants present in the image. Finally, we evaluated the results achieved from this study and gave direction of using the outcome from this study in different domains.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124176832","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: 3

[UEMCON 2021 Front cover] [UEMCON 2021封面]

2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2021-12-01 DOI: 10.1109/uemcon53757.2021.9666711

引用次数: 0

Extraction of Respiration Rate from Wrist ECG Signals 从腕部心电信号中提取呼吸频率

2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2021-12-01 DOI: 10.1109/uemcon53757.2021.9666489

Mahfuzur Rahman, B. Morshed

{"title":"Extraction of Respiration Rate from Wrist ECG Signals","authors":"Mahfuzur Rahman, B. Morshed","doi":"10.1109/uemcon53757.2021.9666489","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666489","url":null,"abstract":"Respiratory behavior is one of the important parameters that indicate any physiological changes in human body. However, using a respiration sensor device for continuous monitoring is inconvenient and expensive. In this paper, an approach to acquire the respiration signal from the wrist electrocardiogram (ECG) is proposed. An analog front end (AFE) sampled at 100 Hz is used to collect ECG signals from the wrist to compute and verify the corresponding heart rate (HR) with a commercial ECG device. Signal processing mechanisms are applied on the raw data to denoise the ECG signal. The captured ECG signal is further processed to extract a breathing pattern to calculate a respiration rate (RR) in breath per minute (BPM). The extracted BPMs are compared with a commercial respiration monitor to validate the data by following a protocol at 5 different BPMs (12, 15, 20, 24 and 30). For each BPM, commercial respiration monitor is validated at first. Then, data are taken simultaneously wearing wrist electrodes and commercial respiratory device to validate the performance of our proposed method at different BPMs. The results indicate high accuracy of the proposed system which is low-cost, simpler to implement, can be integrated with a wearable device and remove the demand of any dedicated sensor for RR measurements.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116670977","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 Novel Partitioning Scheme for Partial Transmit Sequence Method 一种新的部分传输序列分划方案

2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) Pub Date : 2021-12-01 DOI: 10.1109/UEMCON53757.2021.9666686

Hassan Musafer, M. Faezipour

{"title":"A Novel Partitioning Scheme for Partial Transmit Sequence Method","authors":"Hassan Musafer, M. Faezipour","doi":"10.1109/UEMCON53757.2021.9666686","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666686","url":null,"abstract":"An efficient and distortionless partitioning scheme for the Partial Transmit Sequence (PTS) method is proposed to control the nonlinear property producing other peaks in the Orthogonal Frequency Division Multiplexing (OFDM) transmit signal. The approach is flexible and works with a limited and controlled number of subcarriers and can significantly improve peak power statistics of the optimized transmit signal. The traditional partitioning strategy of the PTS method allows all subchannels/subcarriers to contribute in the reduction of the peak-to-average power ratio (PAPR). Therefore, the traditional scheme is ineffective for controlling the nonlinear property, which may produce other peaks by rotating all subchannels of the OFDM signal. Although the PTS method can optimize the value of PAPR, the effect of the nonlinear property of the PTS method has not been properly addressed in the literature. In this paper, we examine the number of actual parameters/rotations used in the PTS method by suitably testing the nonlinear property on the rotated partial sequences. In contrast to the traditional partitioning strategy, the proposed strategy involves rotating half of the separated subcarriers to eliminate the effect of producing other peaks. The traditional and proposed schemes are compared through simulation results with respect to the required system complexity and the minimum PAPR of the OFDM transmit signal. Finally, it is shown that the controlled partitioning scheme is closer to the theoretical limit of PAPR optimization, and it also requires less system complexity than the traditional scheme.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122049913","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