Pub Date : 2023-05-18DOI: 10.1109/eIT57321.2023.10187349
D. Möller, H. Vakilzadian
Cybersecurity is a computing-based discipline dealing with cyber-attacks that harm organizations. It spans many areas of an organization, including but not limited to data security, cryptography, software and hardware security, network and systems security, and others. Thus, cybersecurity is fundamental to protecting confidential data, business assets, and operations. Therefore, any organization must defend against any unauthorized access by cyber-attackers. Hence, implementing cybersecurity is to ensure a security posture for computers, servers, networks, mobile devices, and the data stored on these devices to protect against potential cyber-attackers' malicious intentions. In this regard, cybersecurity risk is critical for all organizations, requiring awareness for employees, specialists, managers, and others that work with sensitive data, business assets, and operations. Cybersecurity training is essential to provide a certain level of cybersecurity awareness l to support organization staff with a comprehensive perspective on potential cyber-attack risks and skills for risk defense. This requires developing a program in cybersecurity awareness training that empowers individuals and organizations to seize opportunities and tackle cybersecurity challenges with the necessary knowledge, skills, and practices described in the curriculum example for training. This paper focus on training on respective knowledge skills and topics for a cybersecurity program to develop effective and efficient skills for participating personnel, enabling them to identify and defend against malicious cyber-attacks [1].
{"title":"Cybersecurity Awareness Training: A Use Case Model","authors":"D. Möller, H. Vakilzadian","doi":"10.1109/eIT57321.2023.10187349","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187349","url":null,"abstract":"Cybersecurity is a computing-based discipline dealing with cyber-attacks that harm organizations. It spans many areas of an organization, including but not limited to data security, cryptography, software and hardware security, network and systems security, and others. Thus, cybersecurity is fundamental to protecting confidential data, business assets, and operations. Therefore, any organization must defend against any unauthorized access by cyber-attackers. Hence, implementing cybersecurity is to ensure a security posture for computers, servers, networks, mobile devices, and the data stored on these devices to protect against potential cyber-attackers' malicious intentions. In this regard, cybersecurity risk is critical for all organizations, requiring awareness for employees, specialists, managers, and others that work with sensitive data, business assets, and operations. Cybersecurity training is essential to provide a certain level of cybersecurity awareness l to support organization staff with a comprehensive perspective on potential cyber-attack risks and skills for risk defense. This requires developing a program in cybersecurity awareness training that empowers individuals and organizations to seize opportunities and tackle cybersecurity challenges with the necessary knowledge, skills, and practices described in the curriculum example for training. This paper focus on training on respective knowledge skills and topics for a cybersecurity program to develop effective and efficient skills for participating personnel, enabling them to identify and defend against malicious cyber-attacks [1].","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117258508","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}
Pub Date : 2023-05-18DOI: 10.1109/eIT57321.2023.10187331
R. J. Nowling, Samuel H. Keyser, Alex R. Moran, John G. Peters, Daniel Leskiewicz
Large, polymorphic inversions can contribute to population structure and enable mutually-exclusive adaptations to survive in the same population. Current methods for detecting inversions from single-nucleotide polymorphisms (SNPs) called from population genomics data require an experienced, human user to prepare the data and interpret the results. Ideally, these methods would be completely automated yet robust to allow usage by inexperienced users. Towards this goal, automated approaches for segmentation of inversions and inference of sample genotypes are introduced and evaluated on chromosomes from flies, mosquitoes, and prairie sunflowers.
{"title":"Segmenting and Genotyping Large, Polymorphic Inversions","authors":"R. J. Nowling, Samuel H. Keyser, Alex R. Moran, John G. Peters, Daniel Leskiewicz","doi":"10.1109/eIT57321.2023.10187331","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187331","url":null,"abstract":"Large, polymorphic inversions can contribute to population structure and enable mutually-exclusive adaptations to survive in the same population. Current methods for detecting inversions from single-nucleotide polymorphisms (SNPs) called from population genomics data require an experienced, human user to prepare the data and interpret the results. Ideally, these methods would be completely automated yet robust to allow usage by inexperienced users. Towards this goal, automated approaches for segmentation of inversions and inference of sample genotypes are introduced and evaluated on chromosomes from flies, mosquitoes, and prairie sunflowers.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"5 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120862281","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}
Pub Date : 2023-05-18DOI: 10.1109/eIT57321.2023.10187307
Yang Chen, Jun Chen, Chen-Zhe Liu, Guodong Liu, Maximiliano F. Ferrari, Aditya Sundararajan
Focusing on remote, isolated, and underserved communities, a multi-energy system is designed in this research which is capable of utilizing different energy sources in a more coordinated and energy-efficient way to support various demands, such as fresh water, electricity, hydrogen, thermal demand, etc. The energy sources considered are renewables (wind, solar, marine) and natural gas. The energy conversion process includes water desalination, gas combustion, water electrolyzation, and different types of storage (hydrogen tank, electricity, thermal, etc.) are designed to serve as buffers in supply-demand balancing. Sets of experiments are designed to demonstrate the effectiveness of the proposed operating model and investigate the impact of uncertainties from renewable generations and demands.
{"title":"Integrated Modeling and Optimal Operation of Multi-Energy System for Coastal Community","authors":"Yang Chen, Jun Chen, Chen-Zhe Liu, Guodong Liu, Maximiliano F. Ferrari, Aditya Sundararajan","doi":"10.1109/eIT57321.2023.10187307","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187307","url":null,"abstract":"Focusing on remote, isolated, and underserved communities, a multi-energy system is designed in this research which is capable of utilizing different energy sources in a more coordinated and energy-efficient way to support various demands, such as fresh water, electricity, hydrogen, thermal demand, etc. The energy sources considered are renewables (wind, solar, marine) and natural gas. The energy conversion process includes water desalination, gas combustion, water electrolyzation, and different types of storage (hydrogen tank, electricity, thermal, etc.) are designed to serve as buffers in supply-demand balancing. Sets of experiments are designed to demonstrate the effectiveness of the proposed operating model and investigate the impact of uncertainties from renewable generations and demands.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125146796","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}
Pub Date : 2023-05-18DOI: 10.1109/eIT57321.2023.10187264
Samuel Kalenowski, David Arnold, M. Gromov, J. Saniie
Due to the rapid adoption of Internet of Things (IoT) technologies, many networks are composed of a patchwork of devices designed by different software and hardware developers. In addition to the heterogeneity of IoT networks, the general rush-to-market produced products with poor adherence to core cybersecurity principles. Coupled together, these weaknesses leave organizations vulnerable to attack by botnets, such as Mirai and Gafgyt. Infected devices pose a threat to both internal and external devices as they attempt to add new devices to the collective or to perpetrate targeted attacks within the network or against third parties. Artificial Intelligence (AI) tools for intrusion detection are popular platforms for detecting indicators of botnet infiltration. However, when training AI tools, the heterogeneity of the network hampers detection and classification accuracy due to the differences in device architecture and network layout. To investigate this challenge, we explored the application of a Neural Network (NN) to the N-BaIoT dataset. The NN achieved 94% classification accuracy when trained using data from all devices in the network. Further, we examined the model's transferability by training on a single device and applying it to data from all devices. This resulted in a noticeable decline in classification accuracy. However, when considering cyberattack detection the model retained a very high true positive rate of 99.6%.
{"title":"Heterogeneity Tolerance in IoT Botnet Attack Classification","authors":"Samuel Kalenowski, David Arnold, M. Gromov, J. Saniie","doi":"10.1109/eIT57321.2023.10187264","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187264","url":null,"abstract":"Due to the rapid adoption of Internet of Things (IoT) technologies, many networks are composed of a patchwork of devices designed by different software and hardware developers. In addition to the heterogeneity of IoT networks, the general rush-to-market produced products with poor adherence to core cybersecurity principles. Coupled together, these weaknesses leave organizations vulnerable to attack by botnets, such as Mirai and Gafgyt. Infected devices pose a threat to both internal and external devices as they attempt to add new devices to the collective or to perpetrate targeted attacks within the network or against third parties. Artificial Intelligence (AI) tools for intrusion detection are popular platforms for detecting indicators of botnet infiltration. However, when training AI tools, the heterogeneity of the network hampers detection and classification accuracy due to the differences in device architecture and network layout. To investigate this challenge, we explored the application of a Neural Network (NN) to the N-BaIoT dataset. The NN achieved 94% classification accuracy when trained using data from all devices in the network. Further, we examined the model's transferability by training on a single device and applying it to data from all devices. This resulted in a noticeable decline in classification accuracy. However, when considering cyberattack detection the model retained a very high true positive rate of 99.6%.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126720354","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}
Pub Date : 2023-05-18DOI: 10.1109/eIT57321.2023.10187362
Tianyang Fang, J. Saniie, S. Bakhtiari, A. Heifetz
This paper investigates optimization of parameters to enhance performance of a microwave resonant cavity transducer for high temperature fluid flow sensing in advanced reactors. The cylindrical microwave cavity flowmeter is a novel sensor that measures fluid flow velocity through deflection of the cavity wall due to dynamic fluid pressure. This sensor is designed to operate in harsh environments of a nuclear reactor because sensor material is resilient to high temperatures, ionizing radiation, and corrosion. Parameters that determine performance characteristics of the transducer include dimensions of the microwave cavity, cavity electromagnetic excitation method, and cavity material. We investigate transducer design through computer simulations, with the objective of maximizing cavity Q-factor.
{"title":"Optimization of Microwave Resonant Cavity Flowmeter Design for High Temperature Fluid Sensing Applications","authors":"Tianyang Fang, J. Saniie, S. Bakhtiari, A. Heifetz","doi":"10.1109/eIT57321.2023.10187362","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187362","url":null,"abstract":"This paper investigates optimization of parameters to enhance performance of a microwave resonant cavity transducer for high temperature fluid flow sensing in advanced reactors. The cylindrical microwave cavity flowmeter is a novel sensor that measures fluid flow velocity through deflection of the cavity wall due to dynamic fluid pressure. This sensor is designed to operate in harsh environments of a nuclear reactor because sensor material is resilient to high temperatures, ionizing radiation, and corrosion. Parameters that determine performance characteristics of the transducer include dimensions of the microwave cavity, cavity electromagnetic excitation method, and cavity material. We investigate transducer design through computer simulations, with the objective of maximizing cavity Q-factor.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"369 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122763368","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}
Pub Date : 2023-05-18DOI: 10.1109/eIT57321.2023.10187299
Jacob Solus, Maureen Rakotondraibe, Xinrui Yu, Won-Jae Yi, M. Gromov, J. Saniie
This paper presents a system design for a smart bike helmet with multiple safety features that are intended to empower bicycle riders to proactively avoid potential sources of danger or injury. A Smart Sensor/Actuator Node (SSAN), driven by an Arduino Uno single-board microcontroller, contains input sensors and actuators to provide riders the ability to send and receive warnings promptly on their helmet. A Vision Node, driven by an NVIDIA Jetson Nano and a cable pin-connected camera, executes AI object detection algorithms for any dangerous objects that are out of sight of the rider and sends alerts to the SSAN as needed. By combining safety features of the SSAN and Vision Node while continuously sending data to an IoT-enabled backend web server, the safety operation of a typical bike ride can be substantially improved.
{"title":"IoT-Enabled Smart Bike Helmet with an AI-Driven Collision Avoidance System","authors":"Jacob Solus, Maureen Rakotondraibe, Xinrui Yu, Won-Jae Yi, M. Gromov, J. Saniie","doi":"10.1109/eIT57321.2023.10187299","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187299","url":null,"abstract":"This paper presents a system design for a smart bike helmet with multiple safety features that are intended to empower bicycle riders to proactively avoid potential sources of danger or injury. A Smart Sensor/Actuator Node (SSAN), driven by an Arduino Uno single-board microcontroller, contains input sensors and actuators to provide riders the ability to send and receive warnings promptly on their helmet. A Vision Node, driven by an NVIDIA Jetson Nano and a cable pin-connected camera, executes AI object detection algorithms for any dangerous objects that are out of sight of the rider and sends alerts to the SSAN as needed. By combining safety features of the SSAN and Vision Node while continuously sending data to an IoT-enabled backend web server, the safety operation of a typical bike ride can be substantially improved.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122935639","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}
Pub Date : 2023-05-18DOI: 10.1109/eIT57321.2023.10187330
A. Fite, M. Gromov, Tianyang Fang, J. Saniie
In ultrasonic nondestructive evaluation (NDE) of materials an essential step in characterizing an ultrasonic signal is decomposing the patterns of multiple interfering echoes. The Chirplet Transform (CT) is a powerful method to analyze the echoes in an ultrasonic signal. However, CT analysis is computationally heavy and impractical. Motivated by achieving real-time execution of the CT this research presents a speed-optimized implementation of the chirplet functions on FPGA. Chirplet echo generation used in Fast Chirplet Decomposition (FCD) Algorithm for ultrasonic signal analysis necessitates the frequent generation of chirplet functions with a 6-degree of freedom associated with chirplet parameters including the amplitude scaler; the time of arrival; the Gaussian envelope scaler; the phase of the chirplet; the center frequency and the frequency sweep. By minimizing the processing time of the chirplet generation, the FCD algorithm can be implemented efficiently on FPGA System-on-Chip (SoC). This study presents the hardware realization of the chirplet function on FPGA which is 37 times faster compared to using a Teensy 4.0 microcontroller, and 146 times faster than a highly popular Raspberry Pi 4.0 single board computer.
{"title":"Speed-Optimized Implementation of Fast Chirplet Decomposition Algorithm on FPGA-SoC","authors":"A. Fite, M. Gromov, Tianyang Fang, J. Saniie","doi":"10.1109/eIT57321.2023.10187330","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187330","url":null,"abstract":"In ultrasonic nondestructive evaluation (NDE) of materials an essential step in characterizing an ultrasonic signal is decomposing the patterns of multiple interfering echoes. The Chirplet Transform (CT) is a powerful method to analyze the echoes in an ultrasonic signal. However, CT analysis is computationally heavy and impractical. Motivated by achieving real-time execution of the CT this research presents a speed-optimized implementation of the chirplet functions on FPGA. Chirplet echo generation used in Fast Chirplet Decomposition (FCD) Algorithm for ultrasonic signal analysis necessitates the frequent generation of chirplet functions with a 6-degree of freedom associated with chirplet parameters including the amplitude scaler; the time of arrival; the Gaussian envelope scaler; the phase of the chirplet; the center frequency and the frequency sweep. By minimizing the processing time of the chirplet generation, the FCD algorithm can be implemented efficiently on FPGA System-on-Chip (SoC). This study presents the hardware realization of the chirplet function on FPGA which is 37 times faster compared to using a Teensy 4.0 microcontroller, and 146 times faster than a highly popular Raspberry Pi 4.0 single board computer.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117039878","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}
Pub Date : 2023-05-18DOI: 10.1109/eIT57321.2023.10187273
Jesse Holwerda, B. Dunne, Paul W. Keenlance
Traditional animal tracking radio collars employ a low-duty cycle VHF radio beacon for directional antenna-based tracking and collar retrieval. With the advent of compact GPS receivers, an efficient method to transmit GPS coordinates while minimizing weight, power consumption and cost is desired. A protocol is described based on the modulation of the existing VHF beacon to achieve the GPS coordinate communication while meeting the desired metrics. The implementation utilizes the LimeSDR mini interfaced to a Raspberry PI. Discussed within are the communication protocol, algorithm implementation and device field application.
{"title":"Low-rate GPS Coordinate Communication Protocol Embedded into VHF Beacon for Animal Tracking","authors":"Jesse Holwerda, B. Dunne, Paul W. Keenlance","doi":"10.1109/eIT57321.2023.10187273","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187273","url":null,"abstract":"Traditional animal tracking radio collars employ a low-duty cycle VHF radio beacon for directional antenna-based tracking and collar retrieval. With the advent of compact GPS receivers, an efficient method to transmit GPS coordinates while minimizing weight, power consumption and cost is desired. A protocol is described based on the modulation of the existing VHF beacon to achieve the GPS coordinate communication while meeting the desired metrics. The implementation utilizes the LimeSDR mini interfaced to a Raspberry PI. Discussed within are the communication protocol, algorithm implementation and device field application.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126818362","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}
Pub Date : 2023-05-18DOI: 10.1109/eIT57321.2023.10187236
Susana Rodriguez Fuerte, Xinrui Yu, J. Saniie
This paper presents the current use of the Internet of Things (IoT) in fire evacuation and extinction. It examines the different approaches to the problem and technologies like Building Information Modeling (BIM) and mathematical algorithms that can be used to determine the optimal evacuation route. It also evaluates existing fire security solutions such as smoke, flame, motion, and gas sensors, LED lights, buzzers, and SMS modules. Entities that specialize in Residential and Commercial Security Systems and Home Automation are also discussed, along with the services they offer. The main objective of this study is to understand current systems and resources regarding fire evacuation and extinction systems and to analyze different developments in smart buildings to create an efficient system for fire detection and evacuation.
{"title":"Fire Security Systems Analysis and Internet of Things Implications","authors":"Susana Rodriguez Fuerte, Xinrui Yu, J. Saniie","doi":"10.1109/eIT57321.2023.10187236","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187236","url":null,"abstract":"This paper presents the current use of the Internet of Things (IoT) in fire evacuation and extinction. It examines the different approaches to the problem and technologies like Building Information Modeling (BIM) and mathematical algorithms that can be used to determine the optimal evacuation route. It also evaluates existing fire security solutions such as smoke, flame, motion, and gas sensors, LED lights, buzzers, and SMS modules. Entities that specialize in Residential and Commercial Security Systems and Home Automation are also discussed, along with the services they offer. The main objective of this study is to understand current systems and resources regarding fire evacuation and extinction systems and to analyze different developments in smart buildings to create an efficient system for fire detection and evacuation.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130963347","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}
Pub Date : 2023-05-18DOI: 10.1109/eIT57321.2023.10187384
Seth Wolfgang, Xiang Cao
Nowadays, in Internet of Things (IoT) applications, IoT devices generate and gather data. These data can be handled in different ways. They can be processed by IoT devices directly, by the Cloud, or by the edge servers. In recent years, Raspberry Pi has been developed as a small IoT device for many applications. In this paper, we design and implement various computing models, i.e., Cloud Computing, Edge Computing, and computing on IoT devices, using Raspberry Pis as prototypes. We deploy multiple applications, run hands-on experiments, and analyze the results accordingly. We also compare the performances of these different computing paradigms, and take advantage of the parallel processing capability of Raspberry Pi devices to demonstrate the effectiveness of improving the prototype performance.
{"title":"Raspberry Pi Based Computing Prototypes: Design, Implementation and Performance Analysis","authors":"Seth Wolfgang, Xiang Cao","doi":"10.1109/eIT57321.2023.10187384","DOIUrl":"https://doi.org/10.1109/eIT57321.2023.10187384","url":null,"abstract":"Nowadays, in Internet of Things (IoT) applications, IoT devices generate and gather data. These data can be handled in different ways. They can be processed by IoT devices directly, by the Cloud, or by the edge servers. In recent years, Raspberry Pi has been developed as a small IoT device for many applications. In this paper, we design and implement various computing models, i.e., Cloud Computing, Edge Computing, and computing on IoT devices, using Raspberry Pis as prototypes. We deploy multiple applications, run hands-on experiments, and analyze the results accordingly. We also compare the performances of these different computing paradigms, and take advantage of the parallel processing capability of Raspberry Pi devices to demonstrate the effectiveness of improving the prototype performance.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115366748","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}
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