List of Articles اینترنت اشیا

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  1 - Identifying and ranking factors affecting the digital transformation strategy in Iran's road freight transportation industry focusing on the Internet of Things and data analytics
  Mehran Ehteshami Mohammad Hasan Cheraghali Bita Tabrizian Maryam Teimourian sefidehkhan
  This research has been done with the aim of identifying and ranking the factors affecting the digital transformation strategy in Iran's road freight transportation industry, focusing on the Internet of Things and data analytics. After reviewing the literature, semi-stru More

  This research has been done with the aim of identifying and ranking the factors affecting the digital transformation strategy in Iran's road freight transportation industry, focusing on the Internet of Things and data analytics. After reviewing the literature, semi-structured interviews were conducted with 20 academic and road freight transportation industry experts in Iran, who were selected using the purposive sampling method and saturation principle. In the quantitative part, the opinions of 170 employees of this industry, who were selected based on Cochran's formula and stratified sampling method, were collected using a researcher-made questionnaire. Delphi technique, literature review and coding were used to analyze the data in the qualitative part. In the quantitative part, inferential statistics and SPSS and smartPLS software were used. Finally, 40 indicators were extracted in the form of 8 factors and ranking of indicators and affecting factors was done using factor analysis. The result of this research shows that the internal factors have the highest rank and software infrastructure, hardware infrastructure, economic, external factors, legal, cultural and penetration factor are in the next ranks respectively. Therefore, it is suggested that organizations consider their human resource empowerment program in line with the use of technology and digital tools. Manuscript profile
• Open Access Article
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  2 - Priority based Deployment of IoT Applications in Fog
  Masomeh Azimzadeh Ali Rezaee Somayyeh  Jafarali Jassbi MohammadMahdi Esnaashari
  Fog computing technology has emerged to respond to the need for modern IoT applications for low latency, high security, etc. On the other hand, the limitations of fog computing such as heterogeneity, distribution, and resource constraints make service management in this More

  Fog computing technology has emerged to respond to the need for modern IoT applications for low latency, high security, etc. On the other hand, the limitations of fog computing such as heterogeneity, distribution, and resource constraints make service management in this environment challenging. Intelligent service placement means placing application services on fog nodes to ensure their QoS and effective use of resources. Using communities to organize nodes for service placement is one of the approaches in this area, where communities are mainly created based on the connection density of nodes, and applications are placed based on a single-criteria prioritization approach. This leads to the creation of unbalanced communities and inefficient placement of applications. This paper presents a priority-based method for deploying applications in the fog environment. To this end, balanced communities are created and applications are placed in balanced communities based on a multi-criteria prioritization approach. This leads to optimal use of network capacities and increases in QoS. The simulation results show that the proposed method improves deadline by up to 22%, increases availability by about 12%, and increases resource utilization by up to 10%. Manuscript profile
• Open Access Article
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  3 - Modeling and evaluation of RPL routing protocol by colored Petri nets
  Mohammad Pishdar Younes Seifi
  20.1001.1.27170411.1401.14.53.2.2
  The Internet of Things (IoT) is a novel and widely used idea aimed at connecting objects through communication technologies. The problem of the prior technology adaptation has always been one of the most challenging issues in this area over the years. The Recognition of More

  The Internet of Things (IoT) is a novel and widely used idea aimed at connecting objects through communication technologies. The problem of the prior technology adaptation has always been one of the most challenging issues in this area over the years. The Recognition of Prior Learning (RPL) protocol has been proposed by scientists since 2012 as a solution for IoT routing. This protocol has been utilized by many researchers and hardware companies in the field of the mentioned technology. The present study evaluates RPL behavior from the perspective of the existence of stopping conditions, crossing multiple routes from a special route (loop conditions), and how it reacts to different inputs, while presenting a modular and readable model of this protocol. Manuscript profile
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  4 - The effect of Internet of Things (IOT) implementation on the Rail Freight Industry; A futures study approach
  Noureddin Taraz Monfared علی شایان ali rajabzadeh ghotri
  20.1001.1.27170411.1402.15.55.10.1
  The rail freight industry in Iran has been faced several challenges which affected its performance. Notwithstanding that Internet of Things leverage is rapidly increasing in railway industries-as an experienced solution in other countries-, Iran’s rail freight industry More

  The rail freight industry in Iran has been faced several challenges which affected its performance. Notwithstanding that Internet of Things leverage is rapidly increasing in railway industries-as an experienced solution in other countries-, Iran’s rail freight industry has not been involved in, yet. Related research and experiment has not been identified in Iran, as well. The aim of this survey is to identify the effects of the implementation of Internet of Things in the Rail Freight Industry in Iran. To gather the data, the Delphi method was selected, and the Snowball technique was used for organizing a Panel including twenty experts. To evaluate the outcomes, IQR, Binomial tests, and Mean were calculated. Several statements were identified and there was broad consensus on most of them, which approved that their implementation affects the Iranian rail freight industry, but in different ranks. Finally, the results formed in the Balanced Scorecard’s format. The internal business process has been affected more than the other aspects by the approved statements. Eleven recognized elements are affected in different ranks, including Internal Business Process, Financial, Learning, and Growth, Customers. The Financial perspective remarked as least consensus and the Internal Business Process has received the extreme consensus. The research outcomes can be used to improve the strategic planning of the Iranian rail freight industry by applying the achievements of information technology in practice. Manuscript profile
• Open Access Article
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  5 - Improvement of intrusion detection system on Industrial Internet of Things based on deep learning using metaheuristic algorithms
  mohammadreza zeraatkarmoghaddam majid ghayori
  20.1001.1.27170411.1402.15.57.12.7
  Due to the increasing use of industrial Internet of Things (IIoT) systems, one of the most widely used security mechanisms is intrusion detection system (IDS) in the IIoT. In these systems, deep learning techniques are increasingly used to detect attacks, anomalies or i More

  Due to the increasing use of industrial Internet of Things (IIoT) systems, one of the most widely used security mechanisms is intrusion detection system (IDS) in the IIoT. In these systems, deep learning techniques are increasingly used to detect attacks, anomalies or intrusions. In deep learning, the most important challenge for training neural networks is determining the hyperparameters in these networks. To overcome this challenge, we have presented a hybrid approach to automate hyperparameter tuning in deep learning architecture by eliminating the human factor. In this article, an IDS in IIoT based on convolutional neural networks (CNN) and recurrent neural network based on short-term memory (LSTM) using metaheuristic algorithms of particle swarm optimization (PSO) and Whale (WOA) is used. This system uses a hybrid method based on neural networks and metaheuristic algorithms to improve neural network performance and increase detection rate and reduce neural network training time. In our method, considering the PSO-WOA algorithm, the hyperparameters of the neural network are determined automatically without the intervention of human agent. In this paper, UNSW-NB15 dataset is used for training and testing. In this research, the PSO-WOA algorithm has use optimized the hyperparameters of the neural network by limiting the search space, and the CNN-LSTM neural network has been trained with this the determined hyperparameters. The results of the implementation indicate that in addition to automating the determination of hyperparameters of the neural network, the detection rate of are method improve 98.5, which is a good improvement compared to other methods. Manuscript profile
• Open Access Article
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  6 - Community-Based Multi-Criteria Placement of Applications in the Fog Environment
  Masomeh Azimzadeh Ali Rezaee Somayyeh  Jafarali Jassbi MohammadMahdi Esnaashari
  Fog computing technology has emerged to respond to the need for modern IoT applications for low latency, high security, etc. On the other hand, the limitations of fog computing such as heterogeneity, distribution, and resource constraints make service management in this More

  Fog computing technology has emerged to respond to the need for modern IoT applications for low latency, high security, etc. On the other hand, the limitations of fog computing such as heterogeneity, distribution, and resource constraints make service management in this environment challenging. Intelligent service placement means placing application services on fog nodes to ensure their QoS and effective use of resources. Using communities to organize nodes for service placement is one of the approaches in this area, where communities are mainly created based on the connection density of nodes, and applications are placed based on a single-criteria prioritization approach. This leads to the creation of unbalanced communities and inefficient placement of applications. This paper presents a priority-based method for deploying applications in the fog environment. To this end, balanced communities are created and applications are placed in balanced communities based on a multi-criteria prioritization approach. This leads to optimal use of network capacities and increases in QoS. The simulation results show that the proposed method improves deadline by up to 22%, increases availability by about 12%, and increases resource utilization by up to 10%. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  7 - Identifying and Ranking Factors Affecting the Digital Transformation Strategy in Iran's Road Freight Transportation Industry Focusing on the Internet of Things and Data Analytics
  Mehran Ehteshami Mohammad Hasan Cheraghali Bita Tabrizian Maryam Teimourian sefidehkhan
  This research has been done with the aim of identifying and ranking the factors affecting the digital transformation strategy in Iran's road freight transportation industry, focusing on the Internet of Things and data analytics. After reviewing the literature, semi-stru More

  This research has been done with the aim of identifying and ranking the factors affecting the digital transformation strategy in Iran's road freight transportation industry, focusing on the Internet of Things and data analytics. After reviewing the literature, semi-structured interviews were conducted with 20 academic and road freight transportation industry experts in Iran, who were selected using the purposive sampling method and saturation principle. In the quantitative part, the opinions of 170 employees of this industry, who were selected based on Cochran's formula and stratified sampling method, were collected using a researcher-made questionnaire. Delphi technique, literature review and coding were used to analyze the data in the qualitative part. In the quantitative part, inferential statistics and SPSS and smartPLS software were used. Finally, 40 indicators were extracted in the form of 8 factors and ranking of indicators and affecting factors was done using factor analysis. The result of this research shows that the internal factors have the highest rank and software infrastructure, hardware infrastructure, economic, external factors, legal, cultural and penetration factor are in the next ranks respectively. Therefore, it is suggested that organizations consider their human resource empowerment program in line with the use of technology and digital tools. Manuscript profile