Pub Date : 2021-09-01DOI: 10.1109/ICAIoT53762.2021.00011
Bülent Bilgehan, Omid Mirzaei
There are several network protocols available to enable efficient data transmission between the source and the destination. Mobile ad-hoc networks (MANETs) are usually small, battery-operated mobile devices or nodes. The communication between the nodes does not have a fixed infrastructure. This work aims to use the available resources at the maximum level at the minimum executable period. This work uses an improved algorithm for the Mobile Ad hoc Networks (MANETs) routing protocol to optimize the number of hop count without considering the usual parameters such as the energy involved in the process. The performance has further increased by combining the scheduling and the optimal route selection algorithms. The success of the overall routing process relies on a combinational work of balanced minimum execution time scheduling and the optimum route selecting algorithms. The introduced balanced-minimum execution time provides two advantages. It increases the scheduling performance and provides load balance on the network. The combined optimum route selection algorithm uses varying network parameters of the link quality, mobility, and end-to-end delay at the optimization process. The superiority of the method presented has been proven by the results obtained in the simulation.
{"title":"Enhanced Hybrid Combiner Scheme for Wireless Network Communication","authors":"Bülent Bilgehan, Omid Mirzaei","doi":"10.1109/ICAIoT53762.2021.00011","DOIUrl":"https://doi.org/10.1109/ICAIoT53762.2021.00011","url":null,"abstract":"There are several network protocols available to enable efficient data transmission between the source and the destination. Mobile ad-hoc networks (MANETs) are usually small, battery-operated mobile devices or nodes. The communication between the nodes does not have a fixed infrastructure. This work aims to use the available resources at the maximum level at the minimum executable period. This work uses an improved algorithm for the Mobile Ad hoc Networks (MANETs) routing protocol to optimize the number of hop count without considering the usual parameters such as the energy involved in the process. The performance has further increased by combining the scheduling and the optimal route selection algorithms. The success of the overall routing process relies on a combinational work of balanced minimum execution time scheduling and the optimum route selecting algorithms. The introduced balanced-minimum execution time provides two advantages. It increases the scheduling performance and provides load balance on the network. The combined optimum route selection algorithm uses varying network parameters of the link quality, mobility, and end-to-end delay at the optimization process. The superiority of the method presented has been proven by the results obtained in the simulation.","PeriodicalId":344613,"journal":{"name":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123044826","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 : 2021-09-01DOI: 10.1109/ICAIoT53762.2021.00009
M. Hasan, Tarfa Hamed, F. Al-turjman
While it is well understood that the emerging Social Internet of Things (SIoT) offers a description of a new world of billions of humans which are intelligently communicate and interact with each other. SIoT presents new challenges for suggesting useful objects with certain services for people. This is due to the limitation of social networks between human and objects, such as the evaluation of the various patterns inherent in human walk in cities. In this study we focus services on the problem of recommendation on SIoT which is very important for many applications such as urban computing, smart cities, and health care. The optimized results of swarm of certain infected people COViD-19 introduced in this paper aims at finding a given region of interest. Guided by a fitness function, the particle swarm optimization (PSO) algorithm has proved its efficiency to explore the search space and find the optimal solution. However, in real world scenarios in which the peoples are simulated as particles, there are practical constraints that should be taken into considerations. The most two significant constraints are (1) given the social-distance, the measurement of input variable fluctuations and their possibility of occurring via probability distribution function over the whole particles. (2) given the limited the communication range of particle/people/users, therefore, the spread of the diseases are simulated and evaluated using neighborhood particle swarm optimization (NPSO).
{"title":"Particle Swarm Optimization for Adaptive Social-distance of Neighborhood in the IoT and COVID-19 Era","authors":"M. Hasan, Tarfa Hamed, F. Al-turjman","doi":"10.1109/ICAIoT53762.2021.00009","DOIUrl":"https://doi.org/10.1109/ICAIoT53762.2021.00009","url":null,"abstract":"While it is well understood that the emerging Social Internet of Things (SIoT) offers a description of a new world of billions of humans which are intelligently communicate and interact with each other. SIoT presents new challenges for suggesting useful objects with certain services for people. This is due to the limitation of social networks between human and objects, such as the evaluation of the various patterns inherent in human walk in cities. In this study we focus services on the problem of recommendation on SIoT which is very important for many applications such as urban computing, smart cities, and health care. The optimized results of swarm of certain infected people COViD-19 introduced in this paper aims at finding a given region of interest. Guided by a fitness function, the particle swarm optimization (PSO) algorithm has proved its efficiency to explore the search space and find the optimal solution. However, in real world scenarios in which the peoples are simulated as particles, there are practical constraints that should be taken into considerations. The most two significant constraints are (1) given the social-distance, the measurement of input variable fluctuations and their possibility of occurring via probability distribution function over the whole particles. (2) given the limited the communication range of particle/people/users, therefore, the spread of the diseases are simulated and evaluated using neighborhood particle swarm optimization (NPSO).","PeriodicalId":344613,"journal":{"name":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116500351","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 : 2021-09-01DOI: 10.1109/ICAIoT53762.2021.00013
P. Esmaili, P. Esmaili, F. Cavedo, M. Norgia
To achieve desired level of accuracy in piezoresistive pressure sensors based on silicon, calibration should be performed frequently. In this paper, an Intelligent auto-calibration approach is proposed to update characterization curve in differential pressure-based level sensor. This intelligent method is based on particle swarm optimization method. To achieve optimum results, different factors such as self-knowledge and social knowledge coefficients in addition to inertia weight have been considered in this intelligent auto-calibration method. The compensation process is the last part of the system. It leads to achieve the up bounded measurement error becomes limited to 0.25 mm.
{"title":"PSO-based autocalibration for differential pressure level sensor","authors":"P. Esmaili, P. Esmaili, F. Cavedo, M. Norgia","doi":"10.1109/ICAIoT53762.2021.00013","DOIUrl":"https://doi.org/10.1109/ICAIoT53762.2021.00013","url":null,"abstract":"To achieve desired level of accuracy in piezoresistive pressure sensors based on silicon, calibration should be performed frequently. In this paper, an Intelligent auto-calibration approach is proposed to update characterization curve in differential pressure-based level sensor. This intelligent method is based on particle swarm optimization method. To achieve optimum results, different factors such as self-knowledge and social knowledge coefficients in addition to inertia weight have been considered in this intelligent auto-calibration method. The compensation process is the last part of the system. It leads to achieve the up bounded measurement error becomes limited to 0.25 mm.","PeriodicalId":344613,"journal":{"name":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130392633","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 : 2021-09-01DOI: 10.1109/icaiot53762.2021.00007
in Africa provides new scholarly perspectives on the relations between Portugal and its former African colonies. The conference addresses connections and borrowings between Portugal and Lusophone Africa and is designed to generate a book co-edited by Isabel Ferreira Gould and Pedro Schacht Pereira. The initiative pursues two main lines of inquiry. First, it debates the roles played by the Portuguese-speaking African countries in the continuous elaboration of a new postcolonial Portuguese culture, as well as the roles played by Portugal in the formation and transformation of the cultures of the Lusophone African nations. Second, it examines the ways in which the ongoing critical and theoretical debate in Lusophone African studies can have a positive impact upon the broader discussions of African studies and postcolonial studies, that is, how a regional discipline can contribute to shaping and enriching concepts that are to be used by scholars working in diverse fields and disciplines.
{"title":"Conference Organizers","authors":"","doi":"10.1109/icaiot53762.2021.00007","DOIUrl":"https://doi.org/10.1109/icaiot53762.2021.00007","url":null,"abstract":"in Africa provides new scholarly perspectives on the relations between Portugal and its former African colonies. The conference addresses connections and borrowings between Portugal and Lusophone Africa and is designed to generate a book co-edited by Isabel Ferreira Gould and Pedro Schacht Pereira. The initiative pursues two main lines of inquiry. First, it debates the roles played by the Portuguese-speaking African countries in the continuous elaboration of a new postcolonial Portuguese culture, as well as the roles played by Portugal in the formation and transformation of the cultures of the Lusophone African nations. Second, it examines the ways in which the ongoing critical and theoretical debate in Lusophone African studies can have a positive impact upon the broader discussions of African studies and postcolonial studies, that is, how a regional discipline can contribute to shaping and enriching concepts that are to be used by scholars working in diverse fields and disciplines.","PeriodicalId":344613,"journal":{"name":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130007848","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 : 2021-09-01DOI: 10.1109/ICAIoT53762.2021.00014
Şükrü Mustafa Kaya, Ali Güneş, Atakan Erdem
The internet of things (IoT) is a technology that allows many objects used in daily life to produce a variety of data and transfer those data to other objects or systems. The application domain of this system is increasing day by day, and the technologies used for its infrastructure are also varied. However, to process the huge amount of sensor data effectively, smart and fast filtering solutions are required. As a data pre-processing task, smart data filtering improves not only the data processing speed but also the quality of data as well. In other words, big data management is facilitated by getting more effective results with little noise and meaningful data. In this study, we examined big IoT data stored on IoT edges to detect anomalies in temperature, age, gender, weight, height, and time data. In this context, the Logistic Regression algorithm was applied at both sensing and network layers for anomaly detection purposes. Furthermore, the performance of the classification algorithm in terms of speed and accuracy was reported as the output of the study.
{"title":"A Smart Data Pre-Processing Approach by Using ML Algorithms on IoT Edges: A Case Study","authors":"Şükrü Mustafa Kaya, Ali Güneş, Atakan Erdem","doi":"10.1109/ICAIoT53762.2021.00014","DOIUrl":"https://doi.org/10.1109/ICAIoT53762.2021.00014","url":null,"abstract":"The internet of things (IoT) is a technology that allows many objects used in daily life to produce a variety of data and transfer those data to other objects or systems. The application domain of this system is increasing day by day, and the technologies used for its infrastructure are also varied. However, to process the huge amount of sensor data effectively, smart and fast filtering solutions are required. As a data pre-processing task, smart data filtering improves not only the data processing speed but also the quality of data as well. In other words, big data management is facilitated by getting more effective results with little noise and meaningful data. In this study, we examined big IoT data stored on IoT edges to detect anomalies in temperature, age, gender, weight, height, and time data. In this context, the Logistic Regression algorithm was applied at both sensing and network layers for anomaly detection purposes. Furthermore, the performance of the classification algorithm in terms of speed and accuracy was reported as the output of the study.","PeriodicalId":344613,"journal":{"name":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128366961","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 : 2021-09-01DOI: 10.1109/ICAIoT53762.2021.00016
Auwaku Saleh Mubarak, Zubaida Sa’id Ameen, P. Tonga, F. Al-turjman
Smart tourism is one of the booming industries, several countries are trying to have smart cities in which technologies will be used to ease life and connect almost everything. Several objects detectors were developed by many researchers, but there is a need to have lightweight models so that they can fit smartphones and other edge devices. In this study, the aim is to prove the concept of using a mobile application for smart tourism. The mobile application which has EfficientDet-d2 as a backbone will detect several statues belonging to the Cyprus Museum of Modern Arts and provide relevant information about each statue.
{"title":"Smart Tourism: A Proof of Concept For Cyprus Museum of Modern Arts In The IoT Era","authors":"Auwaku Saleh Mubarak, Zubaida Sa’id Ameen, P. Tonga, F. Al-turjman","doi":"10.1109/ICAIoT53762.2021.00016","DOIUrl":"https://doi.org/10.1109/ICAIoT53762.2021.00016","url":null,"abstract":"Smart tourism is one of the booming industries, several countries are trying to have smart cities in which technologies will be used to ease life and connect almost everything. Several objects detectors were developed by many researchers, but there is a need to have lightweight models so that they can fit smartphones and other edge devices. In this study, the aim is to prove the concept of using a mobile application for smart tourism. The mobile application which has EfficientDet-d2 as a backbone will detect several statues belonging to the Cyprus Museum of Modern Arts and provide relevant information about each statue.","PeriodicalId":344613,"journal":{"name":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123914657","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 : 2021-09-01DOI: 10.1109/ICAIoT53762.2021.00015
Muhammad Haseeb Rasool, Syed Mohammad Meesam Raza, M. Musadiq, Ahmed Zarrar
Renewable energy systems are gaining enormous importance worldwide due to their techno-economic feasibility with decreased carbon emissions. However, they are unreliable as they depend on varying resources, hence need energy storage system to increase reliability. The article analyzes the Internet of Things (IoT) based techno-economic feasibility of a Photovoltaic-Battery system for a house in Güzelyurt, Northern Cyprus. Moreover, integrating the renewable energy system with IoT increases the system's economic benefits and technical feasibility. IoT decreases the electricity cost of the system by 0.001 $/kWh in IoT enabled scenario for increasing the economic benefit (Scenario 2) with a 17.71% decrease in demand-supply fraction. In comparison, the demand-supply fraction increases by 8.14% with an increase in electricity cost by 0.004 $/kWh in the IoT-enabled scenario hence increasing the technical feasibility (Scenario 3). Scenario 3 also increases the minimum average state of charge, enhancing the battery life in a real-time application, making Scenario 3 best suited for a household in Northern Cyprus.
{"title":"IoT Based Enhanced Techno-Economic Feasibility of Photovoltaic-Battery System for a Household in Northern Cyprus","authors":"Muhammad Haseeb Rasool, Syed Mohammad Meesam Raza, M. Musadiq, Ahmed Zarrar","doi":"10.1109/ICAIoT53762.2021.00015","DOIUrl":"https://doi.org/10.1109/ICAIoT53762.2021.00015","url":null,"abstract":"Renewable energy systems are gaining enormous importance worldwide due to their techno-economic feasibility with decreased carbon emissions. However, they are unreliable as they depend on varying resources, hence need energy storage system to increase reliability. The article analyzes the Internet of Things (IoT) based techno-economic feasibility of a Photovoltaic-Battery system for a house in Güzelyurt, Northern Cyprus. Moreover, integrating the renewable energy system with IoT increases the system's economic benefits and technical feasibility. IoT decreases the electricity cost of the system by 0.001 $/kWh in IoT enabled scenario for increasing the economic benefit (Scenario 2) with a 17.71% decrease in demand-supply fraction. In comparison, the demand-supply fraction increases by 8.14% with an increase in electricity cost by 0.004 $/kWh in the IoT-enabled scenario hence increasing the technical feasibility (Scenario 3). Scenario 3 also increases the minimum average state of charge, enhancing the battery life in a real-time application, making Scenario 3 best suited for a household in Northern Cyprus.","PeriodicalId":344613,"journal":{"name":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129130794","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 : 2021-09-01DOI: 10.1109/ICAIoT53762.2021.00008
Jawad Rasheed
Seafood being one of the major source of omega-3 fatty acid, is widely consumed around the world, thus at the same time affects baby-growth due to high mercury. Therefore, an automatic and intelligent seafood classification system is demanded greatly. This study proposed a shallow but effective deep learning based computationally intelligent system that can classify nine different fish species. The model is trained with publicly available data set, called A Large Scale Fish Dataset. 35% of data is used for testing while rest is reserved for training and validation. Experimental results shows that proposed model achieved an overall accuracy of 94%, thus surpasses many previously proposed models. Detail analysis shows that the model secured better F1-score (98%) on Red Mullet fish.
海鲜是omega-3脂肪酸的主要来源之一，在世界各地被广泛食用，同时由于高汞含量影响婴儿的生长。因此，对自动化、智能化的海产品分类系统提出了更高的要求。本研究提出了一个浅层但有效的基于深度学习的计算智能系统，可以对9种不同的鱼类进行分类。该模型使用公开可用的数据集(称为A Large Scale Fish Dataset)进行训练，其中35%的数据用于测试，其余的用于训练和验证。实验结果表明，该模型的总体准确率达到了94%，超过了之前提出的许多模型。详细分析表明，该模型在红鲻鱼上获得了更好的f1评分(98%)。
{"title":"A Sustainable Deep Learning based Computationally Intelligent Seafood Monitoring System for Fish Species Screening","authors":"Jawad Rasheed","doi":"10.1109/ICAIoT53762.2021.00008","DOIUrl":"https://doi.org/10.1109/ICAIoT53762.2021.00008","url":null,"abstract":"Seafood being one of the major source of omega-3 fatty acid, is widely consumed around the world, thus at the same time affects baby-growth due to high mercury. Therefore, an automatic and intelligent seafood classification system is demanded greatly. This study proposed a shallow but effective deep learning based computationally intelligent system that can classify nine different fish species. The model is trained with publicly available data set, called A Large Scale Fish Dataset. 35% of data is used for testing while rest is reserved for training and validation. Experimental results shows that proposed model achieved an overall accuracy of 94%, thus surpasses many previously proposed models. Detail analysis shows that the model secured better F1-score (98%) on Red Mullet fish.","PeriodicalId":344613,"journal":{"name":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126966275","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 : 2021-09-01DOI: 10.1109/ICAIoT53762.2021.00010
Ahmed Zarrar, Muhammad Haseeb Rasool, Syed Mohammad Raza, Ahmad Rasheed
In the current era, manufacturing industries are entering an extremely competitive environment that harbors new challenges and solutions to overcome those problems. Manufacturers around the globe are finding new ways to operate to maximize operational efficiency, improve sustainability and productivity while decreasing the net overhead cost. Lean production is often seen as one of the most robust framework used by the tycoons of the industries to achieve these goals. With the recent evolution of digitized production technologies in industry 4.0, such as the Internet of things (IoT); Scientists, Manufacturers and Researchers are finding new ways to improve the traditional Lean framework. This research paper aims to examine the link present between Lean manufacturing and IoT. With extensive literature review, it was identified that IoT technology can act as a support tool for lean manufacturing, it not only improves productivity during planning and execution but also streamlines the maintenance stage.
{"title":"IoT-Enabled Lean Manufacturing: Use of IoT as a Support Tool for Lean Manufacturing","authors":"Ahmed Zarrar, Muhammad Haseeb Rasool, Syed Mohammad Raza, Ahmad Rasheed","doi":"10.1109/ICAIoT53762.2021.00010","DOIUrl":"https://doi.org/10.1109/ICAIoT53762.2021.00010","url":null,"abstract":"In the current era, manufacturing industries are entering an extremely competitive environment that harbors new challenges and solutions to overcome those problems. Manufacturers around the globe are finding new ways to operate to maximize operational efficiency, improve sustainability and productivity while decreasing the net overhead cost. Lean production is often seen as one of the most robust framework used by the tycoons of the industries to achieve these goals. With the recent evolution of digitized production technologies in industry 4.0, such as the Internet of things (IoT); Scientists, Manufacturers and Researchers are finding new ways to improve the traditional Lean framework. This research paper aims to examine the link present between Lean manufacturing and IoT. With extensive literature review, it was identified that IoT technology can act as a support tool for lean manufacturing, it not only improves productivity during planning and execution but also streamlines the maintenance stage.","PeriodicalId":344613,"journal":{"name":"2021 International Conference on Artificial Intelligence of Things (ICAIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134641801","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 : 2021-09-01DOI: 10.1109/icaiot53762.2021.00001
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