2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)最新文献_第2页

Conception of a Generic IoT Device Life Cycle Model 通用物联网设备生命周期模型的概念

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2021-11-23 DOI: 10.1109/IoTaIS53735.2021.9628736

Steffen Späthe

{"title":"Conception of a Generic IoT Device Life Cycle Model","authors":"Steffen Späthe","doi":"10.1109/IoTaIS53735.2021.9628736","DOIUrl":"https://doi.org/10.1109/IoTaIS53735.2021.9628736","url":null,"abstract":"The ideas of the Internet of Things are widespread, and connected devices are used in a broader range of application domains. Many specific aspects of IoT applications have been analyzed and applied from a technical perspective, such as the product life cycle. This paper presents the concept of a generally applicable life cycle model focused on IoT devices. While many product life cycle models have been made, the handling and interaction with the device itself were rarely in focus. In reference to the IoT device life cycle model to be presented, the main activities of the device existence are presented, as well as the active actors and the resulting impact on the connected services are highlighted. To align with existing life cycle models based on the generic beginning, middle, and end of life phases, these phases are also used for the life cycle model of IoT devices and structured in more detail. Distinctions and interactions between the product life cycle and the device life cycle are pointed out. Since the application scenarios and business models in the IoT environment differ significantly, the model must be able to reflect these differences to be universally applicable. The presented IoT device life cycle model is applicable in many scenarios, primarily due to its differentiation of generic roles and specific actors. Overall, the model provides a general and clear basis for a structured and device-oriented analysis of activities and responsibility distribution along the IoT device life cycle.","PeriodicalId":183547,"journal":{"name":"2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124942081","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

Experimental Analysis of WSN based Solution for Early Forest Fire Detection 基于WSN的森林火灾早期检测方案实验分析

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2021-11-23 DOI: 10.1109/IoTaIS53735.2021.9628482

Sayantani Bhattacharya, A. SherinM., P. Poonguzhali, R. Vasudevan, S. Lokeshwar, M. Vaibhav, S. Sridevi

{"title":"Experimental Analysis of WSN based Solution for Early Forest Fire Detection","authors":"Sayantani Bhattacharya, A. SherinM., P. Poonguzhali, R. Vasudevan, S. Lokeshwar, M. Vaibhav, S. Sridevi","doi":"10.1109/IoTaIS53735.2021.9628482","DOIUrl":"https://doi.org/10.1109/IoTaIS53735.2021.9628482","url":null,"abstract":"Forest fire is a burning issue worldwide. It destroys the green belt, increases air pollution, damages the natural habitat for trees and animals, and even sometimes it causes death to the forest fire fighters. Economically and environmentally it is responsible for huge losses to the country. The satellite-based classical system lags continuous monitoring, requires complex processing and the information does not reach the ground in real-time. Hence, there is a need for a 24/7 forest fire monitoring system that will generate alerts in near real-time. In this paper, we discuss a WSN based solution with visualization and alert generation schemes. The system has been developed and field-tested. The sensors in the system monitor environmental parameters during an outbreak of a forest fire. Sensor data gets processed and upon detection of the outbreak of a fire, alerts are issued to the concerned forest officials. Experimental analysis of sensor node behaviour during a fire in a test set-up has been discussed in detail. Near real-time alerting and prompt response to the alerts might help to mitigate the impact of forest fires such as loss of human lives, loss of large green belts, areas of vegetation, economic loss, and environmental pollution.","PeriodicalId":183547,"journal":{"name":"2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129184469","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

Narrow Band Digital Filtering Approach for CR-IoT Node with Carrier Aggregation Using Zero/Pole Placement 基于零极点放置载波聚合的CR-IoT节点窄带数字滤波方法

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2021-11-23 DOI: 10.1109/IoTaIS53735.2021.9628733

Modar Shbat

引用次数: 0

Comparison and Evaluation of LwM2M and MQTT in Low-Power Wide-Area Networks 低功耗广域网中LwM2M与MQTT的比较与评价

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2021-11-23 DOI: 10.1109/IoTaIS53735.2021.9628463

Alessandro Parmigiani, U. Dettmar

引用次数: 0

AI-based Models for Resource Allocation and Resource Demand Forecasting Systems in Aviation: A Survey and Analytical Study 基于人工智能的航空资源配置与需求预测系统模型:调查与分析研究

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2021-11-23 DOI: 10.1109/IoTaIS53735.2021.9628555

D. Hejji, M. A. Talib, A. B. Nassif, Q. Nasir, A. Bouridane

引用次数: 2

Analysis of ONOS Clustering Performance on Software Defined Network 软件定义网络上ONOS聚类性能分析

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2021-11-23 DOI: 10.1109/IoTaIS53735.2021.9628659

Kinanthi Audina Septian, Istikmal, Ishak Ginting

{"title":"Analysis of ONOS Clustering Performance on Software Defined Network","authors":"Kinanthi Audina Septian, Istikmal, Ishak Ginting","doi":"10.1109/IoTaIS53735.2021.9628659","DOIUrl":"https://doi.org/10.1109/IoTaIS53735.2021.9628659","url":null,"abstract":"The increasing need for service providers makes the performance of network management must also be improved. In this study, the author builds a clustering controller using the Open Network Operating System (ONOS) controller on an Software Defined Network (SDN) network. ONOS has a cluster feature that allows it to distribute traffic loads to other controllers to increase performance. The performance of clustering controller is compared with single controller and multi controller without clustering by measuring Quality of Service (QoS) on delay, jitter, and throughput parameters for data, voice, and video services. The test is done by adding background traffic. After being tested and analyzed, the performance of the clustering controller has the most superior QoS with an average delay in data services of 0.047026667 ms, jitter of 0.015414943 ms, throughput of 37.56360736 kbit/s. In the voice service, the delay value is 0.03909 ms, the jitter is 0.01828 ms, the throughput is 72.79049 kbit/s. In the video service, the delay value is 0,12072 ms, the jitter is 0,042013 ms, and the throughput is 5314,059 kbit/s. While in single and multi controller the average value obtained is not much different from the clustering controller. This is due to the single controller architecture, the network control center is only centered on 1 controller, as well as multi controllers, so that it affects the performance of service distribution.","PeriodicalId":183547,"journal":{"name":"2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124364042","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

Threats and Attacks to Modern Vehicles 对现代车辆的威胁和攻击

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2021-11-23 DOI: 10.1109/IoTaIS53735.2021.9628576

Simon Grønfeldt Philipsen, Birger Andersen, Bhupjit Singh

引用次数: 4

Performance Analysis on Artificial Neural Network Based State of Charge Estimation for Electric Vehicles 基于人工神经网络的电动汽车充电状态估计性能分析

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2021-11-23 DOI: 10.1109/IoTaIS53735.2021.9628725

Manoharan Aaruththiran, K. M. Begam, V. R. Aparow, Denesh Sooriamoorthy

{"title":"Performance Analysis on Artificial Neural Network Based State of Charge Estimation for Electric Vehicles","authors":"Manoharan Aaruththiran, K. M. Begam, V. R. Aparow, Denesh Sooriamoorthy","doi":"10.1109/IoTaIS53735.2021.9628725","DOIUrl":"https://doi.org/10.1109/IoTaIS53735.2021.9628725","url":null,"abstract":"In the recent years, Artificial Neural Networks (ANNs) have gained wider interest in estimating the State of charge (SOC) of Li-ion batteries used in electric vehicles. As the ANN configurations proposed in recent literature were trained under different training parameters and datasets, a fair comparison cannot be made by directly referring to the prediction errors reported. Thus, the SOC prediction performance of the ANNs proposed in the recent years were investigated, by training with same training parameters and dataset (US06 vehicle dynamic profile from the Centre of Advanced Life Cycle Engineering). Results show that the testing dataset Mean Squared Error (MSE) for using only Convolutional Neural Network (CNN) is 3.140%, whereas combining CNN with Long Short-Term Memory Networks (LSTM-RNN) is 1.820%, and CNN with Gate Recurrent Unit (GRU-RNN) is 1.819% MSE. Therefore, it is evident that in-cooperation of any form of recurrent architecture in an ANN configuration contributes to better SOC prediction. The results also highlight that inclusion of a bidirectional recurrent architecture such as Bidirectional LSTM-RNN (MSE: 0.927%) and attention mechanism such as the combination of LSTM-RNN with attention (MSE: 0.004%) contribute to better SOC prediction. Overall, the performance analysis conducted shows that there is a need in further research investigation on integrating different types of bidirectional recurrent architecture and attention mechanism with other ANNs and evaluate the SOC prediction performance as compared to previously proposed ANN configurations. Successful testing and implementation would contribute to increased battery life span and reduced maintenance costs, leading to increased usage of EVs.","PeriodicalId":183547,"journal":{"name":"2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123670846","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

Budgeting System In Event Management Application Using Web-Based Genetic Algorithms 基于web遗传算法的事件管理预算系统应用

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2021-11-23 DOI: 10.1109/IoTaIS53735.2021.9628830

Surya Muhammad, Roswan Latuconsina, C. Setianingsih

{"title":"Budgeting System In Event Management Application Using Web-Based Genetic Algorithms","authors":"Surya Muhammad, Roswan Latuconsina, C. Setianingsih","doi":"10.1109/IoTaIS53735.2021.9628830","DOIUrl":"https://doi.org/10.1109/IoTaIS53735.2021.9628830","url":null,"abstract":"The increasing number of events usually formed a committee in small to large fields involving event organizers. In this study, the survey results were used to Telkom University students in Roadshow, Try Out and other committees. However, there are often problems in the implementation process caused by poor planning and supervision processes to have less clear financial statements. To anticipate this problem and create a web application-based event management application that provides appropriate budget recommendations. So, by using Genetics Algorithm is an optimization algorithm that can provide optimal results. This application is expected to help financial management reduce errors in the budgeting creation process and provide recommendations to users. Based on the test results, three experiments were carried out to see the optimal fitness value. In the first test, the densest optimal fitness value is between the ± 18 th generation out of a total of 50 generations. In the second experiment, the optimal fitness value is between the 20th generation to the 30th generation. In the last experiment, the optimal fitness value is between the 2nd generation to the 10th generation. This difference occurs because the random values used in each experiment are different. In this study, the genetic algorithm succeeded in recommending goods that match the maximum budget parameters of the division, indoor or outdoor category.","PeriodicalId":183547,"journal":{"name":"2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125321271","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

Power Factor Correction Control Based on Internet of Things Using Lumped Compensation Capacitor Bank 基于集总补偿电容器组的物联网功率因数校正控制

2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2021-11-23 DOI: 10.1109/IoTaIS53735.2021.9628423

Arin Juan Sari, M. A. Murti, I. P. Wibawa

{"title":"Power Factor Correction Control Based on Internet of Things Using Lumped Compensation Capacitor Bank","authors":"Arin Juan Sari, M. A. Murti, I. P. Wibawa","doi":"10.1109/IoTaIS53735.2021.9628423","DOIUrl":"https://doi.org/10.1109/IoTaIS53735.2021.9628423","url":null,"abstract":"Power factor is often used as an indicator of a good or bad power supply in a system Electrical power in household and industrial needs for inductively reactive loads can cause a decrease in power factor The decrease in power factor is a problem that must be minimized because it can make the quality of electrical power not optimal which is detrimental to consumers and a decrease in the ability to supply electrical power to electrical energy suppliers. Capacitive reactive power can reduce this loss by installing capacitors. Therefore, we need a tool that can improve power factor value and increase efficiency for distribution systems under inductive loads. The tool that will be made using a lumped compensation capacitor bank uses the reactive power compensator calculation method to get the required capacitor capacitance. In this research, a power factor repair tool has been made using the NodeMCU ESP8266. Microcontroller and also an android application as a connection tool with the Internet of Things server. MQTT protocol was chosen as IoT protocol after comparing speed and energy consumption with HTTP protocol. Also in this research, added recommendation features to calculate the value of capacitance capacitors that are installed in the devices to make them easier to use during installation. The system is implemented in a house with a power rating of 900 Watt and uses 4 capacitors with each size in micro Farad $(mu F)$ units of 2.5, 3, 5, and 5. The result takes 1 minute 45 seconds to reach a set point of 0.95 Power Factor with an average error of 0.8%.","PeriodicalId":183547,"journal":{"name":"2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126654810","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