Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10154903
Mahmoud Osama, S. Hammad, Nancy E. ElHady, M. El-Kharashi
The automotive industry depends on computers to control and monitor vehicles behaviour. The Universal Measurement and Calibration Protocol (XCP) connects calibration systems to electronic control units (ECUs). Nowadays, AUTOSAR-based XCP for single core ECUs is widely used in automotive industry. As the demand for computing power is rapidly increasing in the automotive domain, car manufacturers are gradually introducing multi-core ECUs in their electronic architectures. Multi-core ECUs provide high level of parallelism. This research work aims to deliver a multi-core implementation of an AUTOSAR-based XCP module, as it is important to have an efficient process of measurement and calibration on multi-core targets. The paper results are ensuring data consistency on the application level, avoiding race conditions between writer core and reader core which might result in processing rubbish data, and decreasing data dependency between cores.
{"title":"A Multicore Implementation of an AUTOSAR-based XCP Module","authors":"Mahmoud Osama, S. Hammad, Nancy E. ElHady, M. El-Kharashi","doi":"10.1109/MECO58584.2023.10154903","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154903","url":null,"abstract":"The automotive industry depends on computers to control and monitor vehicles behaviour. The Universal Measurement and Calibration Protocol (XCP) connects calibration systems to electronic control units (ECUs). Nowadays, AUTOSAR-based XCP for single core ECUs is widely used in automotive industry. As the demand for computing power is rapidly increasing in the automotive domain, car manufacturers are gradually introducing multi-core ECUs in their electronic architectures. Multi-core ECUs provide high level of parallelism. This research work aims to deliver a multi-core implementation of an AUTOSAR-based XCP module, as it is important to have an efficient process of measurement and calibration on multi-core targets. The paper results are ensuring data consistency on the application level, avoiding race conditions between writer core and reader core which might result in processing rubbish data, and decreasing data dependency between cores.","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":"123094715","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/MECO58584.2023.10154955
M. S. Nagar, Rahul Kumar, Pinalkumar Engineer
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.
{"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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10155100
A. Buja, M. Apostolova, A. Luma
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.
{"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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10155029
Besnik Dragusha, Azir Aliu, A. Luma, Kadri Sylejmani
Senior public officials are required to periodically declare their assets to the national anti-corruption agency that manages and verifies the assets. Each anti-corruption agency currently has its own asset declaration system to identify any unusual asset growth or unjustified enrichment. Although most of these systems have digitized their declaration and submission processes, the preliminary control and full verification still require manual intervention. Our study analyzes and compares asset declaration systems of nine European countries, including four from the Western Balkans and five from other regions. We present a comparative analysis of their asset declaration processes, key features of the declaration form for full verification of declared assets, and indicators for identifying suspicious senior public officials' declarations. The study aims to identify key processes of asset declaration systems that can be automated for more effective decision-making, resulting in a more transparent and accountable system for public officials' asset declaration and management.
{"title":"A Comparative Study of Automated Asset Declaration Systems in Selected European Countries","authors":"Besnik Dragusha, Azir Aliu, A. Luma, Kadri Sylejmani","doi":"10.1109/MECO58584.2023.10155029","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155029","url":null,"abstract":"Senior public officials are required to periodically declare their assets to the national anti-corruption agency that manages and verifies the assets. Each anti-corruption agency currently has its own asset declaration system to identify any unusual asset growth or unjustified enrichment. Although most of these systems have digitized their declaration and submission processes, the preliminary control and full verification still require manual intervention. Our study analyzes and compares asset declaration systems of nine European countries, including four from the Western Balkans and five from other regions. We present a comparative analysis of their asset declaration processes, key features of the declaration form for full verification of declared assets, and indicators for identifying suspicious senior public officials' declarations. The study aims to identify key processes of asset declaration systems that can be automated for more effective decision-making, resulting in a more transparent and accountable system for public officials' asset declaration and management.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"111 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":"124888336","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/MECO58584.2023.10155021
Hajar Bennouri, A. Abdi, Iqbal Hossain, Alexandre Pujol
The growing popularity and deployment of Internet of Things (IoT) devices has led to serious security concerns. The integration of a security operations center (SOC) becomes increasingly important in this situation to ensure the security of IoT devices. In this article, we will present a summary of IoT device security issues, their vulnerabilities, a review of current challenges to keep these devices secure, and discuss the role that SOC can bring in protecting IoT devices while considering the challenges encountered and the directions to consider when implementing a reliable SOC for IoT monitoring.
{"title":"The Role of SOC in Ensuring the Security of IoT Devices: A Review of Current Challenges and Future Directions","authors":"Hajar Bennouri, A. Abdi, Iqbal Hossain, Alexandre Pujol","doi":"10.1109/MECO58584.2023.10155021","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155021","url":null,"abstract":"The growing popularity and deployment of Internet of Things (IoT) devices has led to serious security concerns. The integration of a security operations center (SOC) becomes increasingly important in this situation to ensure the security of IoT devices. In this article, we will present a summary of IoT device security issues, their vulnerabilities, a review of current challenges to keep these devices secure, and discuss the role that SOC can bring in protecting IoT devices while considering the challenges encountered and the directions to consider when implementing a reliable SOC for IoT monitoring.","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":"122708230","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/MECO58584.2023.10155083
E. Vasileska, V. Gečevska, O. Čukaliev
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.
{"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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10154941
G. Rath, Gerold Probst, A. Lamprecht, Armin Hoffellner
A measurement device was developed that evaluates and displays the bending deformation of a crane with long horizontal extension used for construction work in a railway tunnel. The purpose is to adjust the crane rail vertically so that the trolley can move on a straight and smooth path. An array of inclinometer sensors measures the tilt angles along the machine. Piecewise interpolation with polynomials of third and second order is used to reconstruct the bending curve of the crane rail. The computer language Python with its library packages provides a good platform for the implementation of the algorithms, the user interface and the communication task. Evaluation is not done with the machine control hardware, but with a separate, rugged Rasperry Pi running under Linux operating system. With the optical display of the interpolated curve on a touch screen the operator is able to adjust the crane for the construction work.
{"title":"Curve Reconstruction from Inclinometer Sensor Array for Aligning a Long Crane Rail","authors":"G. Rath, Gerold Probst, A. Lamprecht, Armin Hoffellner","doi":"10.1109/MECO58584.2023.10154941","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154941","url":null,"abstract":"A measurement device was developed that evaluates and displays the bending deformation of a crane with long horizontal extension used for construction work in a railway tunnel. The purpose is to adjust the crane rail vertically so that the trolley can move on a straight and smooth path. An array of inclinometer sensors measures the tilt angles along the machine. Piecewise interpolation with polynomials of third and second order is used to reconstruct the bending curve of the crane rail. The computer language Python with its library packages provides a good platform for the implementation of the algorithms, the user interface and the communication task. Evaluation is not done with the machine control hardware, but with a separate, rugged Rasperry Pi running under Linux operating system. With the optical display of the interpolated curve on a touch screen the operator is able to adjust the crane for the construction work.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"159 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":"128345255","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/MECO58584.2023.10155049
Aleksandar S. Dimovski, B. Fetaji
Configurable software systems today are becoming very popular. They can produce a set of related programs by choosing preferable features (configuration options) at compile-time. Many configurable programs are applied in safety-critical areas, so their formal verification is of primary importance. In this paper, we introduce a new, interesting approach for verifying temporal properties of configurable programs that contain numerical features. We extend an abstract interpretation-based static analysis framework for proving temporal properties of single programs that uses a decision tree abstract domain. In particular, we define a novel lifted decision tree domain for proving temporal properties of configurable programs. We have developed a lifted static analyzer for proving temporal properties of #if-enriched C configurable programs. The evaluation on a range of loop benchmarks from SV-COMP confirms the effectiveness of our approach.
{"title":"On Verifying Temporal Properties of Configurable Software","authors":"Aleksandar S. Dimovski, B. Fetaji","doi":"10.1109/MECO58584.2023.10155049","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155049","url":null,"abstract":"Configurable software systems today are becoming very popular. They can produce a set of related programs by choosing preferable features (configuration options) at compile-time. Many configurable programs are applied in safety-critical areas, so their formal verification is of primary importance. In this paper, we introduce a new, interesting approach for verifying temporal properties of configurable programs that contain numerical features. We extend an abstract interpretation-based static analysis framework for proving temporal properties of single programs that uses a decision tree abstract domain. In particular, we define a novel lifted decision tree domain for proving temporal properties of configurable programs. We have developed a lifted static analyzer for proving temporal properties of #if-enriched C configurable programs. The evaluation on a range of loop benchmarks from SV-COMP confirms the effectiveness of our approach.","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":"129646657","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/MECO58584.2023.10155066
Damjan Pecioski, V. Gavriloski, Simona Domazetovska, Anastasija Ignjatovska
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.
{"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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10154906
M. Maksimovic, Marko Č. Bošković, T. Šekara, B. Lutovac
Technology advancements have a huge impact on conventional methods and practices, which causes the energy sector to undergo significant change. The digitalization of energy systems is what will undoubtedly shape the energy sector's future. The Metaverse may be the next phase of digitalization that will make the energy sector vastly different from what it does now, by providing exceptional chances to reorganize workflows, increase productivity, and reduce costs. Although the use of the Metaverse in the energy sector is still in its early stages, the popularity of the Energy Metaverse is rising as a result of its numerous advantages. Nevertheless, a number of challenges must be carefully considered for Metaverse to be widely adopted in the energy sector. This paper aims to provide a thorough overview of the Energy Metaverse in order to stimulate further research and hasten the adoption of this ground-breaking idea in the energy sector, which is currently lacking in research studies.
{"title":"Exploring the Energy Metaverse: Potential Benefits and Challenges","authors":"M. Maksimovic, Marko Č. Bošković, T. Šekara, B. Lutovac","doi":"10.1109/MECO58584.2023.10154906","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154906","url":null,"abstract":"Technology advancements have a huge impact on conventional methods and practices, which causes the energy sector to undergo significant change. The digitalization of energy systems is what will undoubtedly shape the energy sector's future. The Metaverse may be the next phase of digitalization that will make the energy sector vastly different from what it does now, by providing exceptional chances to reorganize workflows, increase productivity, and reduce costs. Although the use of the Metaverse in the energy sector is still in its early stages, the popularity of the Energy Metaverse is rising as a result of its numerous advantages. Nevertheless, a number of challenges must be carefully considered for Metaverse to be widely adopted in the energy sector. This paper aims to provide a thorough overview of the Energy Metaverse in order to stimulate further research and hasten the adoption of this ground-breaking idea in the energy sector, which is currently lacking in research studies.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"32 7 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":"123227255","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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