2023 12th Mediterranean Conference on Embedded Computing (MECO)最新文献

A Multicore Implementation of an AUTOSAR-based XCP Module 基于autosar的XCP模块的多核实现

2023 12th Mediterranean Conference on Embedded Computing (MECO) Pub Date : 2023-06-06 DOI: 10.1109/MECO58584.2023.10154903

Mahmoud Osama, S. Hammad, Nancy E. ElHady, M. El-Kharashi

引用次数: 0

Parallelizing Non-Neural ML Algorithm for Edge-based Face Recognition on Parallel Ultra-Low Power (PULP) Cluster 基于并行超低功耗(PULP)聚类的边缘人脸识别并行非神经机器学习算法

2023 12th Mediterranean Conference on Embedded Computing (MECO) Pub Date : 2023-06-06 DOI: 10.1109/MECO58584.2023.10154955

M. S. Nagar, Rahul Kumar, Pinalkumar Engineer

{"title":"Parallelizing Non-Neural ML Algorithm for Edge-based Face Recognition on Parallel Ultra-Low Power (PULP) Cluster","authors":"M. S. Nagar, Rahul Kumar, Pinalkumar Engineer","doi":"10.1109/MECO58584.2023.10154955","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154955","url":null,"abstract":"The multi-core parallel ultra-low power (PULP) cluster architecture allows the IoT edge node to shift toward near-sensor computing. In this paper, non-neural Eigenfaces-based face recognition (FR) is examined on an octa-core PULP cluster. It is possible to achieve high accuracy in the Eigenfaces-based algorithm without using a large data model. It is observed that the Eigenfaces-based face recognition algorithm achieved 93% accuracy on the PULP platform with a $4.55times$ lesser model size compared to the state-of-the-art SqueezeNet1.1-based FR algorithm on GAP8 platform. Parallelization of Eigenfaces-based face recognition is done to achieve maximum speed-up on multi-core, reducing recognition time. Furthermore, DMA-based communication between the fabric controller and multi-core cluster reduces the recognition time by $50times$ at the cost of a little degradation in speed-up on the multi-core. By adopting this technique, 165 faces per second are recognized with 93% accuracy on octa-core PULP cluster, which is $7.85times$ faster than a single core RISC-V with DMA. Compared to the ARM Cortex-M7 architecture, the multi-core PULP cluster reduces recognition time by 89.89%. These results make the multi-core PULP cluster an efficient choice for Eigenfaces-based face recognition on the edge.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"73 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":"116646043","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

Enhancing Cyber Security in Industrial Internet of Things Systems: An Experimental Assessment 加强工业物联网系统的网络安全:一项实验评估

2023 12th Mediterranean Conference on Embedded Computing (MECO) Pub Date : 2023-06-06 DOI: 10.1109/MECO58584.2023.10155100

A. Buja, M. Apostolova, A. Luma

{"title":"Enhancing Cyber Security in Industrial Internet of Things Systems: An Experimental Assessment","authors":"A. Buja, M. Apostolova, A. Luma","doi":"10.1109/MECO58584.2023.10155100","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155100","url":null,"abstract":"In the digital age, Industry Control Systems (ICS) and the Industrial Internet of Things (IIoT) are having an impact on the operations of industry sectors. Although, with the development of technology even cyber-attacks have advanced in methods and techniques. The systems, which manage and control critical infrastructures such as power plants, manufacturing facilities, and transportation networks, are exposed to cyber-attacks. Nevertheless, security breaches can come from various cyber-attacks that target industrial systems, and in some cases, an infected device can affect the entire infrastructure in more disastrous attacks. This article digs into the existing models of ICS where we compare in terms of cyber-attacks, timely response, and impact control in the system is presented. This investigative work helps identify differences and create a proactive approach to security response. Finally, we will make an experimental assessment of the impact of security on existing models, in terms of recommendations for the advancement of cyber security in ICS and IIoT systems. Furthermore, we will present the different approaches that are now used to protect ICS and IIoT systems from cyber-attacks. In conclusion, the test found that the IIoT sensor and system are vulnerable to attacks used against it but not from malicious code injection.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"81 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":"124802124","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: 1

A Comparative Study of Automated Asset Declaration Systems in Selected European Countries 欧洲部分国家自动资产申报制度的比较研究

2023 12th Mediterranean Conference on Embedded Computing (MECO) Pub Date : 2023-06-06 DOI: 10.1109/MECO58584.2023.10155029

Besnik Dragusha, Azir Aliu, A. Luma, Kadri Sylejmani

引用次数: 0

The Role of SOC in Ensuring the Security of IoT Devices: A Review of Current Challenges and Future Directions SOC在确保物联网设备安全中的作用:当前挑战和未来方向的回顾

2023 12th Mediterranean Conference on Embedded Computing (MECO) Pub Date : 2023-06-06 DOI: 10.1109/MECO58584.2023.10155021

Hajar Bennouri, A. Abdi, Iqbal Hossain, Alexandre Pujol

引用次数: 0

Crop yield forecasting with climate data using PCA and Machine Learning 利用PCA和机器学习的气候数据预测作物产量

2023 12th Mediterranean Conference on Embedded Computing (MECO) Pub Date : 2023-06-06 DOI: 10.1109/MECO58584.2023.10155083

E. Vasileska, V. Gečevska, O. Čukaliev

{"title":"Crop yield forecasting with climate data using PCA and Machine Learning","authors":"E. Vasileska, V. Gečevska, O. Čukaliev","doi":"10.1109/MECO58584.2023.10155083","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155083","url":null,"abstract":"Accurately forecasting annual crop production is crucial for countries as it enables them to formulate import and export policies and estimate the economic benefits of their agricultural planning. The crop growth is significantly influenced by weather conditions throughout the year, and climate conditions during different stages of plant development can greatly affect crop yield. The availability of historical climate data has greatly benefited the agricultural sciences and food sector, particularly with the application of Artificial Intelligence methods in big data analysis, enabling the extraction of practical information and actions. The objective of this research is to develop a predictive Machine Learning (ML) model that utilizes climate data from a specific time frame to forecast the wheat yield in the Pelagonia valley, a crucial region for wheat cultivation in North Macedonia. Principal Component Analysis (PCA) was employed as a dimensionality-reduction method to reduce the input data set's dimensionality. A least-squares boosting regression model was implemented as the ML method to estimate wheat yield from climate data. The results indicate a high accuracy of wheat yield prediction, even with limited dataset, on both the training and testing datasets. The study demonstrates the feasibility of utilizing ML methods as complementary to existing models for accurate wheat yield forecasting, offering significant advantages due to the ease of calibrating the ML model parameters.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"89 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":"114443428","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

Curve Reconstruction from Inclinometer Sensor Array for Aligning a Long Crane Rail 用倾角传感器阵列重建长起重机轨道对准曲线

2023 12th Mediterranean Conference on Embedded Computing (MECO) Pub Date : 2023-06-06 DOI: 10.1109/MECO58584.2023.10154941

G. Rath, Gerold Probst, A. Lamprecht, Armin Hoffellner

引用次数: 0

On Verifying Temporal Properties of Configurable Software 论可组态软件时间特性的验证

2023 12th Mediterranean Conference on Embedded Computing (MECO) Pub Date : 2023-06-06 DOI: 10.1109/MECO58584.2023.10155049

Aleksandar S. Dimovski, B. Fetaji

引用次数: 0

An overview of reinforcement learning techniques 强化学习技术概述

2023 12th Mediterranean Conference on Embedded Computing (MECO) Pub Date : 2023-06-06 DOI: 10.1109/MECO58584.2023.10155066

Damjan Pecioski, V. Gavriloski, Simona Domazetovska, Anastasija Ignjatovska

{"title":"An overview of reinforcement learning techniques","authors":"Damjan Pecioski, V. Gavriloski, Simona Domazetovska, Anastasija Ignjatovska","doi":"10.1109/MECO58584.2023.10155066","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155066","url":null,"abstract":"Writing control code for a system where the optimal solution is not known in advance can be a very time-consuming process. The Artificial Intelligence (AI) methods typically involve designing a set of rules which can be effective in situations where the problem is precisely defined and well understood. As in real world problems the optimal solution is rarely known, the reinforcement learning framework which incorporates trial and error attempts can be used. Reinforcement learning (RL) is a machine learning technique that involves training an agent to make decisions which are based on the feedback it receives from the environment. One important decision to make when designing an RL system is whether to use a single or multiple agents. This decision depends on the type of problem that needs to be solved as well the environment complexity. Having a goal that can be achieved by a single agent (one player) it is recommended to use single-agent RL while if there is a need for coordination between multiple agents (players) then a multi-agent approach is recommended. In this article, the differences between single agent RL and multi agent RL techniques, as well as their advantages and disadvantages have been presented, and insights are provided into when one approach may be more appropriate than the other.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"18 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":"126704304","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

Exploring the Energy Metaverse: Potential Benefits and Challenges 探索能源元宇宙:潜在的利益和挑战

2023 12th Mediterranean Conference on Embedded Computing (MECO) Pub Date : 2023-06-06 DOI: 10.1109/MECO58584.2023.10154906

M. Maksimovic, Marko Č. Bošković, T. Šekara, B. Lutovac

引用次数: 1