Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10155046
Arta Misini, A. Kadriu, Ercan Canhasi
Authorship attribution (AA) is a subfield of NLP that analyzes the author's prior works to determine who wrote a text based on its features. Each natural language has its characteristics, just like every author's unique writing style. This study aims to conduct an in-depth comparison of several AA machine-learning techniques. The specially created Albanian corpus (A3C) and the English dataset (Reuters C50) have been used in the experiments. Using n-grams, we perform character-level and word-level analyses of the text to represent the author's writing style. We use five different classification algorithms to train the AA models. The TF-IDF feature vector is used as input to the models. Various experiments were conducted on the corpora. The most accurate results were obtained using word n-grams after stopword removal. The SVM algorithm performed best on the A3C dataset (Albanian). We get a 95% F1 score using SVM. On the C50 dataset (English), the SVM classifier achieved an 83% F1 score. Experiments have provided evidence of the models' robust performance on the AA corpora.
{"title":"Albanian Authorship Attribution Model","authors":"Arta Misini, A. Kadriu, Ercan Canhasi","doi":"10.1109/MECO58584.2023.10155046","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155046","url":null,"abstract":"Authorship attribution (AA) is a subfield of NLP that analyzes the author's prior works to determine who wrote a text based on its features. Each natural language has its characteristics, just like every author's unique writing style. This study aims to conduct an in-depth comparison of several AA machine-learning techniques. The specially created Albanian corpus (A3C) and the English dataset (Reuters C50) have been used in the experiments. Using n-grams, we perform character-level and word-level analyses of the text to represent the author's writing style. We use five different classification algorithms to train the AA models. The TF-IDF feature vector is used as input to the models. Various experiments were conducted on the corpora. The most accurate results were obtained using word n-grams after stopword removal. The SVM algorithm performed best on the A3C dataset (Albanian). We get a 95% F1 score using SVM. On the C50 dataset (English), the SVM classifier achieved an 83% F1 score. Experiments have provided evidence of the models' robust performance on the AA corpora.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115151280","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 : 2023-06-06DOI: 10.1109/MECO58584.2023.10155001
Yiming Tan, Aditya Diwakar, Ja Jagielo, V. Mooney
Malicious attackers are constantly attacking software compilers and attempting to exploit various security vulnerabili-ties. By executing carefully chosen machine instructions already present in the program, an attacker can perform harmful actions arbitrarily. In this paper, we propose hardware/software codesign techniques to perform software compilation steps in hardware, specifically the register allocation step on a Field Programmable Gate Array (FPGA). Our experiment incorporates two key features: 1) Advanced RISC Machine (ARM) instruction set architecture (ISA)-based register allocation algorithms to calculate variable liveness as well as map virtual registers to physical registers and 2) the feasibility of executing the register allocation algorithms on a Cyclone V FPGA. Our experimental results show the timing efficiency and resource efficiency - while diminishing security risks - when performing register allocation of the gcd program on the FPGA.
恶意攻击者不断攻击软件编译器并试图利用各种安全漏洞。通过执行程序中已经存在的精心选择的机器指令，攻击者可以任意地执行有害的操作。在本文中，我们提出了硬件/软件协同设计技术来执行硬件中的软件编译步骤，特别是在现场可编程门阵列(FPGA)上的寄存器分配步骤。我们的实验包含两个关键特征:1)基于高级RISC机器(ARM)指令集架构(ISA)的寄存器分配算法，用于计算可变活度以及将虚拟寄存器映射到物理寄存器;2)在Cyclone V FPGA上执行寄存器分配算法的可行性。我们的实验结果表明，在FPGA上执行gcd程序的寄存器分配时，时序效率和资源效率-同时降低了安全风险。
{"title":"Software Compilation Using FPGA Hardware: Register Allocation","authors":"Yiming Tan, Aditya Diwakar, Ja Jagielo, V. Mooney","doi":"10.1109/MECO58584.2023.10155001","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155001","url":null,"abstract":"Malicious attackers are constantly attacking software compilers and attempting to exploit various security vulnerabili-ties. By executing carefully chosen machine instructions already present in the program, an attacker can perform harmful actions arbitrarily. In this paper, we propose hardware/software codesign techniques to perform software compilation steps in hardware, specifically the register allocation step on a Field Programmable Gate Array (FPGA). Our experiment incorporates two key features: 1) Advanced RISC Machine (ARM) instruction set architecture (ISA)-based register allocation algorithms to calculate variable liveness as well as map virtual registers to physical registers and 2) the feasibility of executing the register allocation algorithms on a Cyclone V FPGA. Our experimental results show the timing efficiency and resource efficiency - while diminishing security risks - when performing register allocation of the gcd program on the FPGA.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133083402","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 : 2023-06-06DOI: 10.1109/MECO58584.2023.10154909
M. Stork
A frequency synthesizer is an electronic circuit that generates a desired frequency from a single reference frequency or several reference frequencies. In this paper, a new simple frequency synthesizer is described, which will make it possible to generate a signal at the output whose frequency is the sum of the frequencies of the input signals divided by a constant. The results of the synthesizer simulation are presented in this paper. The synthesizer was not only simulated, but actually implemented by a microcontroller, and the measurement results are also presented. The main advantage is that the synthesizer can be created by programming in any microcontroller.
{"title":"Software Implementation of a Simple All-Digital Frequency Synthesizer","authors":"M. Stork","doi":"10.1109/MECO58584.2023.10154909","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154909","url":null,"abstract":"A frequency synthesizer is an electronic circuit that generates a desired frequency from a single reference frequency or several reference frequencies. In this paper, a new simple frequency synthesizer is described, which will make it possible to generate a signal at the output whose frequency is the sum of the frequencies of the input signals divided by a constant. The results of the synthesizer simulation are presented in this paper. The synthesizer was not only simulated, but actually implemented by a microcontroller, and the measurement results are also presented. The main advantage is that the synthesizer can be created by programming in any microcontroller.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133327491","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 : 2023-06-06DOI: 10.1109/MECO58584.2023.10155019
D. Spirjakin, A. Baranov, I. Ivanov, H. Karami, G. Gharehpetian
Prevention of emergencies associated with flammable gases explosions remains an urgent task. A ranking place in solving of this task plays environment monitoring for combustible gases presence. The environmental explosiveness level can also be assessed overall, without measuring separate gases concentrations. The assessment of environmental explosiveness level can be performed using catalytic gas sensors based on combustion heat measurements of flammable gases combustion in the sensors. Modern data processing methods application, such as machine learning, allows to increase the measurements accuracy. However, machine learning needs a Iot of data. To collect that data enough measurements for different gases should be performed. At the same time, the question remains of whether it is possible to apply the machine learning models to gases, which have not been used while training. In this work, the results of the research are presented, where the possibility of successful models training using limited gases set and the ability of such models to assess the explosiveness level of other gases and mixtures were examined.
{"title":"Gases and mixtures explosiveness estimation using a model trained by limited sets of gases","authors":"D. Spirjakin, A. Baranov, I. Ivanov, H. Karami, G. Gharehpetian","doi":"10.1109/MECO58584.2023.10155019","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155019","url":null,"abstract":"Prevention of emergencies associated with flammable gases explosions remains an urgent task. A ranking place in solving of this task plays environment monitoring for combustible gases presence. The environmental explosiveness level can also be assessed overall, without measuring separate gases concentrations. The assessment of environmental explosiveness level can be performed using catalytic gas sensors based on combustion heat measurements of flammable gases combustion in the sensors. Modern data processing methods application, such as machine learning, allows to increase the measurements accuracy. However, machine learning needs a Iot of data. To collect that data enough measurements for different gases should be performed. At the same time, the question remains of whether it is possible to apply the machine learning models to gases, which have not been used while training. In this work, the results of the research are presented, where the possibility of successful models training using limited gases set and the ability of such models to assess the explosiveness level of other gases and mixtures were examined.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115627193","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 : 2023-06-06DOI: 10.1109/MECO58584.2023.10154994
R. Ristov, S. Koceski
With Internet of Things (IoT) becoming increasingly popular and widespread, the somewhat secure devices could potentially become completely insecure with the emergence of quantum computers. The problem is that a lot of IoT devices in crucial places are not secured and use unencrypted communication or use the current recommended encryption algorithms. This paper explores public key encryption (PKE) with post quantum cryptography (PQC) algorithm Kyber, despite it being usually used as key-encapsulation mechanism (KEM). The proposed approach has been evaluated experimentally. The conducted experiment encrypts the data on one scenario on the IoT device itself and in the other scenario the data is encrypted on a fog node. Obtained results are promising and suggest that quantum resilient public key cryptography is applicable in internet of things.
{"title":"Quantum Resilient Public Key Cryptography in Internet of Things","authors":"R. Ristov, S. Koceski","doi":"10.1109/MECO58584.2023.10154994","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154994","url":null,"abstract":"With Internet of Things (IoT) becoming increasingly popular and widespread, the somewhat secure devices could potentially become completely insecure with the emergence of quantum computers. The problem is that a lot of IoT devices in crucial places are not secured and use unencrypted communication or use the current recommended encryption algorithms. This paper explores public key encryption (PKE) with post quantum cryptography (PQC) algorithm Kyber, despite it being usually used as key-encapsulation mechanism (KEM). The proposed approach has been evaluated experimentally. The conducted experiment encrypts the data on one scenario on the IoT device itself and in the other scenario the data is encrypted on a fog node. Obtained results are promising and suggest that quantum resilient public key cryptography is applicable in internet of things.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114292252","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 : 2023-06-06DOI: 10.1109/MECO58584.2023.10154919
Faton Kabashi, Vehbi Neziri, Halil Snopçe, A. Luma, Azir Aliu, Lamir Shkurti
Blockchain technology has the potential to revolutionize the way Higher Education operates. Blockchain is a decentralized and secure database that can store and manage digital information without the need for a centralized authority. This technology can be applied in Higher Education to improve the security, transparency, and efficiency of academic and administrative processes such as student records, credentials verification, and payment processing. Additionally, blockchainbased platforms can provide new opportunities for collaboration and credentialing that could enhance the learning experience for students. While there are still some challenges to be overcome, such as regulatory issues and the need for interoperability, the potential benefits of blockchain in Higher Education are significant and worth exploring. The purpose of this paper is to investigate the possible applications of blockchain technology in Higher Education institutions and to provide a proposal/scheme of a blockchain-based academic and career record system in Higher Education. The system being proposed is composed of three layers, which are the data, blockchain, and application layers. It is distinguished by decentralized control, secure transactions, and privacy protection.
{"title":"The possibility of blockchain application in Higher Education","authors":"Faton Kabashi, Vehbi Neziri, Halil Snopçe, A. Luma, Azir Aliu, Lamir Shkurti","doi":"10.1109/MECO58584.2023.10154919","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154919","url":null,"abstract":"Blockchain technology has the potential to revolutionize the way Higher Education operates. Blockchain is a decentralized and secure database that can store and manage digital information without the need for a centralized authority. This technology can be applied in Higher Education to improve the security, transparency, and efficiency of academic and administrative processes such as student records, credentials verification, and payment processing. Additionally, blockchainbased platforms can provide new opportunities for collaboration and credentialing that could enhance the learning experience for students. While there are still some challenges to be overcome, such as regulatory issues and the need for interoperability, the potential benefits of blockchain in Higher Education are significant and worth exploring. The purpose of this paper is to investigate the possible applications of blockchain technology in Higher Education institutions and to provide a proposal/scheme of a blockchain-based academic and career record system in Higher Education. The system being proposed is composed of three layers, which are the data, blockchain, and application layers. It is distinguished by decentralized control, secure transactions, and privacy protection.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123209140","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 : 2023-06-06DOI: 10.1109/MECO58584.2023.10154984
O. Druzhina, Oleg Isakov, A. Karimov, Georgii Y. Kolev, Timur I. Karimov
Sensors based on chaotic oscillators comprise a promising direction in the field of nonlinear dynamics. Hypothetically, such sensors have improved sensitivity, selectivity, and rate. In this paper, we research and develop an inductive sensor based on the Sprott Case B chaotic oscillator, which features a double-scroll attractor. We propose a circuit implementation with inductive coil, and compare the results of the computer simulation with experimental study. We conclude that the proposed circuit is suitable for use as a limit switch to determine the position of a steel plate, as its dynamics is switching from chaotic to periodic regime at a certain adjustable distance between a coil and the plate. The performance obtained in the study is comparable with sensors of conventional design, but has the potential for improvement.
基于混沌振子的传感器是非线性动力学领域中一个很有前途的方向。理论上，这种传感器可以提高灵敏度、选择性和速率。本文研究并开发了一种基于Sprott Case B混沌振荡器的电感传感器，该传感器具有双涡旋吸引子。我们提出了一种电感线圈的电路实现，并将计算机仿真结果与实验研究结果进行了比较。我们得出的结论是，所提出的电路适合用作限位开关来确定钢板的位置，因为它的动力学在线圈和钢板之间的一定可调距离上从混沌状态切换到周期性状态。在研究中获得的性能与传统设计的传感器相当，但有改进的潜力。
{"title":"Inductive Limit Switch Based on Chaotic Circuit with Double-Scroll Attractor","authors":"O. Druzhina, Oleg Isakov, A. Karimov, Georgii Y. Kolev, Timur I. Karimov","doi":"10.1109/MECO58584.2023.10154984","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154984","url":null,"abstract":"Sensors based on chaotic oscillators comprise a promising direction in the field of nonlinear dynamics. Hypothetically, such sensors have improved sensitivity, selectivity, and rate. In this paper, we research and develop an inductive sensor based on the Sprott Case B chaotic oscillator, which features a double-scroll attractor. We propose a circuit implementation with inductive coil, and compare the results of the computer simulation with experimental study. We conclude that the proposed circuit is suitable for use as a limit switch to determine the position of a steel plate, as its dynamics is switching from chaotic to periodic regime at a certain adjustable distance between a coil and the plate. The performance obtained in the study is comparable with sensors of conventional design, but has the potential for improvement.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123678388","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 : 2023-06-06DOI: 10.1109/MECO58584.2023.10154986
F. Kempf, J. Becker
Nowadays, embedded systems are ubiquitous and their functionality is becoming increasingly intertwined with various critical demands. Integrating functionality with different criticality demands has led to the emergence of mixed-criticality systems (MCS), which require adaptive fault tolerance to ensure the correctness of critical tasks. In this paper, we propose a hardware-based adaptive redundancy approach for multi-core systems, which aims to enhance the reliability and safety of MCS. Our approach involves the reconfiguration of two physical processor cores into a single logical core that executes the same program on demand. The logical core provides adaptive redundancy to detect and mask faults. However, this reconfiguration can potentially result in deadlocks. To address this issue, we identify the scenarios where deadlocks may occur and provide a countermeasure to prevent their emergence. By adopting this runtime adaptive and hardware-based adaptive redundancy method, we can improve the reliability and safety of mixed-criticality systems. At the same time we utilize the processor architecture to abstract the reconfiguration process.
{"title":"Leveraging Adaptive Redundancy in Multi-Core Processors for Realizing Adaptive Fault Tolerance in Mixed-Criticality Systems","authors":"F. Kempf, J. Becker","doi":"10.1109/MECO58584.2023.10154986","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154986","url":null,"abstract":"Nowadays, embedded systems are ubiquitous and their functionality is becoming increasingly intertwined with various critical demands. Integrating functionality with different criticality demands has led to the emergence of mixed-criticality systems (MCS), which require adaptive fault tolerance to ensure the correctness of critical tasks. In this paper, we propose a hardware-based adaptive redundancy approach for multi-core systems, which aims to enhance the reliability and safety of MCS. Our approach involves the reconfiguration of two physical processor cores into a single logical core that executes the same program on demand. The logical core provides adaptive redundancy to detect and mask faults. However, this reconfiguration can potentially result in deadlocks. To address this issue, we identify the scenarios where deadlocks may occur and provide a countermeasure to prevent their emergence. By adopting this runtime adaptive and hardware-based adaptive redundancy method, we can improve the reliability and safety of mixed-criticality systems. At the same time we utilize the processor architecture to abstract the reconfiguration process.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121884237","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 : 2023-06-06DOI: 10.1109/MECO58584.2023.10155012
S. Gartner, M. Krasna
In the last few months we see the increased use of AI system in all aspects of live, including the education. Changes are seen in the IT business, ordinary business and introduce a plethora of problems into education. The AI can be absolute personal assistance if used correctly or a hell for learners and teachers if misused. On the other way it is so easy to misuse it and too time consuming to prevent these activities. The previous thought: Who will teach the teachers, is more and more important as the AI literacy of all involved in education must also incorporate the ethical consideration of application of AI in the education. We are trying to present the ethical codes that include AI and four basic building blocks of the ethical attitude of AI in education (autonomy, privacy, trust, and responsibility). Understanding the concepts of AI and their ethical considerations is a condition for acting in accordance with them and for introduction them in education.
{"title":"Artificial Intelligence in Education - Ethical framework","authors":"S. Gartner, M. Krasna","doi":"10.1109/MECO58584.2023.10155012","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155012","url":null,"abstract":"In the last few months we see the increased use of AI system in all aspects of live, including the education. Changes are seen in the IT business, ordinary business and introduce a plethora of problems into education. The AI can be absolute personal assistance if used correctly or a hell for learners and teachers if misused. On the other way it is so easy to misuse it and too time consuming to prevent these activities. The previous thought: Who will teach the teachers, is more and more important as the AI literacy of all involved in education must also incorporate the ethical consideration of application of AI in the education. We are trying to present the ethical codes that include AI and four basic building blocks of the ethical attitude of AI in education (autonomy, privacy, trust, and responsibility). Understanding the concepts of AI and their ethical considerations is a condition for acting in accordance with them and for introduction them in education.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125240212","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 : 2023-06-06DOI: 10.1109/MECO58584.2023.10154954
Omid Jafari, Stanislav Kolosov, Nhan Vo, Asmita Thapa Magar, J. Heikkonen, R. Kanth
This research aims to develop a smart traffic light system that can improve traffic flow in urban areas. The proposed system uses sensors, cameras, and software to adjust the timing of traffic signals based on real-time traffic conditions. In this study, a Raspberry Pi 4 and MATLAB software was used to build the smart traffic controller. The detection part of the system involves several steps, including removing noise and retrieving information to calculate the number of cars detected. The system then switches traffic lights based on the detected car count. The MATLAB Image Acquisition and Computer Vision toolboxes were used to obtain and analyze the video frames received from the connected cameras. The detector uses the Gaussian Mixture Model to suppress frequently occurring features and to detect abnormal features, which are then used to detect changes caused by moving objects. Morphological operations are used to remove noise from the output. Finally, the system counts the cars detected by the Foreground Detector and switches the traffic lights accordingly. The proposed approach can help reduce traffic congestion and improve the overall flow of traffic in urban areas.
{"title":"Intelligent Traffic Light Solution for Green and Sustainable Smart City","authors":"Omid Jafari, Stanislav Kolosov, Nhan Vo, Asmita Thapa Magar, J. Heikkonen, R. Kanth","doi":"10.1109/MECO58584.2023.10154954","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154954","url":null,"abstract":"This research aims to develop a smart traffic light system that can improve traffic flow in urban areas. The proposed system uses sensors, cameras, and software to adjust the timing of traffic signals based on real-time traffic conditions. In this study, a Raspberry Pi 4 and MATLAB software was used to build the smart traffic controller. The detection part of the system involves several steps, including removing noise and retrieving information to calculate the number of cars detected. The system then switches traffic lights based on the detected car count. The MATLAB Image Acquisition and Computer Vision toolboxes were used to obtain and analyze the video frames received from the connected cameras. The detector uses the Gaussian Mixture Model to suppress frequently occurring features and to detect abnormal features, which are then used to detect changes caused by moving objects. Morphological operations are used to remove noise from the output. Finally, the system counts the cars detected by the Foreground Detector and switches the traffic lights accordingly. The proposed approach can help reduce traffic congestion and improve the overall flow of traffic in urban areas.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129989690","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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