2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET)最新文献_第2页

Design a Power Converter to Charge a Hybrid Electric Vehicle 设计一种为混合动力汽车充电的电源转换器

2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) Pub Date : 2021-10-11 DOI: 10.1109/HONET53078.2021.9615492

Afshin Balal, Miguel Herrera

引用次数: 4

Void Handling in Routing Protocols for Underwater Wireless Sensor Networks: A Quantitative Analysis 水下无线传感器网络路由协议中的空洞处理:定量分析

2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) Pub Date : 2021-10-11 DOI: 10.1109/HONET53078.2021.9615468

Sarang Karim, F. Shaikh, B. S. Chowdhry

{"title":"Void Handling in Routing Protocols for Underwater Wireless Sensor Networks: A Quantitative Analysis","authors":"Sarang Karim, F. Shaikh, B. S. Chowdhry","doi":"10.1109/HONET53078.2021.9615468","DOIUrl":"https://doi.org/10.1109/HONET53078.2021.9615468","url":null,"abstract":"Underwater Wireless Sensor Networks (UWSNs) is a promising technology with several open issues and challenges. UWSN communication has dependencies on acoustics instead of radio. The route maintenance is one of the difficult tasks in UWSNs due to the random behavior of water tides. The dynamic nature of water waves also poses void-holes in the network region due to which the routing path is severely affected. Meanwhile, numerous research work has been carried out to handle such void-hole problem. In this article, we perform a quantitative analysis on four void handling based routing protocols for UWSN, namely, Vector-Based Void Avoidance (VBVA), Void Aware Pressure Routing (VAPR), GEographic and opportunistic routing with Depth Adjustment-based topology control for communication Recovery (GEDAR), and Void Handling technique in Anchor Nodes assisted Cluster-based Routing Protocol (VH-ANCRP) to assess the performance. The performance metrics for quantitative analysis are data transfer rate, latency, energy cost, network lifespan, and number of redundant packets. NS3 is used for the simulation results. Simulation results expel that VH-ANCRP and GEDAR perform better than VAPR and VBVA in all aforementioned performance metrics.","PeriodicalId":177268,"journal":{"name":"2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130049439","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

Integrating DGNSS/RTK Positioning with IoT and Smart City Applications 集成DGNSS/RTK定位与物联网和智慧城市应用

2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) Pub Date : 2021-10-11 DOI: 10.1109/HONET53078.2021.9615482

R. Xiao, Zhanwei Wu, O. Buruk, Juho Hamari

引用次数: 1

Novel Approach for Concealing Penetration Testing Payloads Using Data Privacy Obfuscation Techniques 利用数据隐私混淆技术隐藏渗透测试有效载荷的新方法

2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) Pub Date : 2021-10-11 DOI: 10.1109/HONET53078.2021.9615485

Abdul Basit Ajmal, A. Anjum, Adnan Anjum, M. Khan

引用次数: 2

From 5G to 6G: key drivers, applications and research directions 从5G到6G:关键驱动因素、应用和研究方向

2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) Pub Date : 2021-10-11 DOI: 10.1109/HONET53078.2021.9615484

̇uhammad Zeeshan Asghar, Jyri Hämäläinen

{"title":"From 5G to 6G: key drivers, applications and research directions","authors":"̇uhammad Zeeshan Asghar, Jyri Hämäläinen","doi":"10.1109/HONET53078.2021.9615484","DOIUrl":"https://doi.org/10.1109/HONET53078.2021.9615484","url":null,"abstract":"The world is on the cusp of experiencing beyond 5G and it will surely reshape our lives in the most effective way. The fourth industrial revolution has been laid upon the pillars of 5G, cloud computing, and machine learning. We are on the verge of a merger of the physical world with the digital world. This article aims to peek into the future, in an era beyond 5G. To see a wireless world, 5G has to evolve to 6G. This article highlights the challenges posed by the dynamically disruptive emerging technologies, highly sophisticated applications, and unlimited data handling in an era of 5G, which will drift towards 6G in near future. The article presents the vision for 6G, key enabling technologies for 6G, and finally the bottleneck constraints and future research directions for beyond 5G. We foresee that 6G will be the key technology for sustainable development in highly populated developing countries and far-flung areas with sparsely spread populations. We stress upon 5G and beyond research to have an inbuilt societal awareness of the users about the social impacts and the use of the advanced technologies.","PeriodicalId":177268,"journal":{"name":"2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126188718","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

MQTT Pub-Sub Service for Connected Vehicles 面向互联汽车的MQTT收发服务

2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) Pub Date : 2021-10-11 DOI: 10.1109/HONET53078.2021.9615393

M. Jaseemuddin, A. Alam, Nuzhat Gawhar

引用次数: 0

Faster RCNN based Vehicle Detection and Counting Framework for Undisciplined Traffic Conditions 基于RCNN的无序交通状况车辆检测与计数框架

2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) Pub Date : 2021-10-11 DOI: 10.1109/HONET53078.2021.9615466

Syeda Hafsa Ahmed, Mehwish Raza, Syeda Shajeeha Mehdi, Inshal Rehman, M. Kazmi, S. A. Qazi

{"title":"Faster RCNN based Vehicle Detection and Counting Framework for Undisciplined Traffic Conditions","authors":"Syeda Hafsa Ahmed, Mehwish Raza, Syeda Shajeeha Mehdi, Inshal Rehman, M. Kazmi, S. A. Qazi","doi":"10.1109/HONET53078.2021.9615466","DOIUrl":"https://doi.org/10.1109/HONET53078.2021.9615466","url":null,"abstract":"With recent development in deep learning and computer vision techniques, Intelligent Transportation System (ITS) has emerged as a useful tool for traffic management, congestion control and building a sound traffic infrastructure. For effective monitoring of traffic conditions, there is a need to detect and count moving vehicles. Previously, several computer vision techniques have been proposed for vehicle recognition. However, majority of the techniques were not able to cover undisciplined traffic conditions. Moreover, these frameworks do not include the local vehicles of South Asian nations like Pakistan, Bangladesh and India. Keeping in view the limitations of existing frameworks, this paper presents an efficient vehicle detection and counting model for undisciplined traffic to enhance the efficiency of ITS. A dataset of more than 1200 images of vehicles has been collected comprising of 6 categories of local vehicles considering undisciplined traffic conditions to ensure robustness in vehicle detection and counting system. Faster RCNN algorithm has been used to detect moving vehicles. The experimental results show precision of 82.14% in terms of mAP.","PeriodicalId":177268,"journal":{"name":"2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131051208","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

An EKF, Accelerometer, Gravity Based Wheel Odometry Method 一种基于EKF、加速度计、重力的车轮里程计方法

2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) Pub Date : 2021-10-11 DOI: 10.1109/HONET53078.2021.9615473

Jacob Morgan, J. Conrad

{"title":"An EKF, Accelerometer, Gravity Based Wheel Odometry Method","authors":"Jacob Morgan, J. Conrad","doi":"10.1109/HONET53078.2021.9615473","DOIUrl":"https://doi.org/10.1109/HONET53078.2021.9615473","url":null,"abstract":"Gathering information on robot motion is critical in determining its trajectory in an environment. The information about a robot's motion, called odometry, can be collected by tracking the wheels for ground based robots. Wheel encoders are common for monitoring kinematic information of a wheel. Wheel encoders generally split the circumference of the wheel into equally discrete distances to track the distance traveled along the wheel's circumference. The proposal of this research is to dismiss the use of the above discrete based wheel encoders and use an accelerometer as a wheel encoder for a more continuous reading of the wheel's position. Accelerometers are typically difficult to use for precise data collection because of noisy outputs causing inaccurate odometry information. This is overcome by comparing sensor data to modeled behavior and with some filtering. The filter analyzed in this paper is the Extended Kalman Filter and proved to provide accurate wheel tracking with low error, even with disturbances. The maximum error was observed at start up and dropped below 1 % in each environment.","PeriodicalId":177268,"journal":{"name":"2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET)","volume":"252 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133143559","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

Cassava Leaf Disease Classification using Deep Neural Networks 基于深度神经网络的木薯叶病分类

2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) Pub Date : 2021-10-11 DOI: 10.1109/HONET53078.2021.9615488

Alina Maryum, M. Akram, A. A. Salam

{"title":"Cassava Leaf Disease Classification using Deep Neural Networks","authors":"Alina Maryum, M. Akram, A. A. Salam","doi":"10.1109/HONET53078.2021.9615488","DOIUrl":"https://doi.org/10.1109/HONET53078.2021.9615488","url":null,"abstract":"In recent years, deep learning has gained much popularity over traditional machine learning techniques in terms of accuracy and precision when trained on substantial amount of data. In this work, a state-of-the-art deep learning technique has been employed for classification and prediction of cassava leaf diseases. Being the second largest producer of carbohydrates in the world, cassava plant has become an important source of calories for people in tropical regions, but it is highly susceptible to viral, bacterial, and fungal attacks resulting in stunted plant growth and hence the yield. So, the aim of the research is to help the farmers quickly identify diseased leaves before they cause any severe damage. The dataset that is used in this work is taken from Kaggle competition 2020 containing 21,397 images of cassava plant leaves belonging to 5 classes: Cassava Bacterial Blight, Cassava Brown Streak Disease, Cassava Green Mottle, Cassava Mosaic Disease and Healthy leaves. In this work, EfficientNet model B4 was trained using transfer learning approach. Further, to remove background noise, Segmentation was performed using U-Net to extract only the leaves from images. Our system provided reasonable performance when validation data was provided to trained model yielding 81.43% and 89.09% accuracy on original and segmented datasets, respectively.","PeriodicalId":177268,"journal":{"name":"2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125362556","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: 10

Designing Crowdsourcing Software to Inform Municipalities About Infrastructure Condition 设计众包软件告知市政当局基础设施状况

2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) Pub Date : 2021-10-11 DOI: 10.1109/HONET53078.2021.9615483

Eric Shoemaker, Harrison T. Randolph, James Bryce, Husnu S. Narman

{"title":"Designing Crowdsourcing Software to Inform Municipalities About Infrastructure Condition","authors":"Eric Shoemaker, Harrison T. Randolph, James Bryce, Husnu S. Narman","doi":"10.1109/HONET53078.2021.9615483","DOIUrl":"https://doi.org/10.1109/HONET53078.2021.9615483","url":null,"abstract":"Determining how to utilize and allocate budgets for public infrastructure is an essential issue that local governments face. For a beneficial budgeting plan to be made for civil engineering infrastructure maintenance and projects, a local government needs first to know the condition of its infrastructure. Without such information, it is not possible to create a plan that will use funds effectively and address the needs and desires of the community members. For larger bodies, like state governments or populous cities, collecting this information is achievable through the dedication of workforce and surveyors. However, smaller municipalities can often lack the funds and the resources. Consequently, this will foster reactive management of public infrastructure such that information is collected after an issue occurs and becomes major rather than minor, so repairs can be more expensive if the damage is significant. This only applies more strain to the limited budgets. To solve this issue, crowdsourcing information about the condition of public infrastructure from the community in the municipality can be used. Therefore, we developed a crowdsourcing based system to address this issue. The data will be collected through the use of public software that will seek to collect data and encourage users to report about all issues-, not just severe or significant damages. By receiving reports about all issues, regardless of severity, municipalities will have the information not only to react to and fix the damage, but also they may proactively predict, repair, and prevent severe damages based on timelines of reports about more minor issues. Moreover, upon the adaptation of this method proves to be helpful, this research aims to produce and deploy such software to benefit smaller municipalities.","PeriodicalId":177268,"journal":{"name":"2021 IEEE 18th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116486647","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