Pub Date : 2022-03-01DOI: 10.1177/15501329221088740
Yan-Xin Lin, Hongliang Zhu, Guoai Xu, Guosheng Xu
Wireless sensor network is a key technology in the sensing layer of the Internet of Things. Data security in wireless sensor network is directly related to the authenticity and validity of data transmitted in the Internet of Things. Due to the large number and different types of nodes in wireless sensor networks, layered secret key sharing technology is increasingly used in wireless sensor networks. In a hierarchical secret sharing scheme, participants are divided into sections with different permissions for each team, but the same permissions for participants in the same team. In this article, we follow the approach of the hierarchical secret sharing scheme derived from the linear homogeneous recurrence relations. We design a hierarchical multi-secret sharing scheme for wireless sensor networks on the basis of the elliptic curve public key cryptosystem combined with the linear homogeneous recurrence relations. In the proposed scheme, we do not make sure that the participants are half-truthful. In addition, the participants’ shadows can be reused. Our scheme is computational security. Only one share from each member is required in our hierarchical multi-secret sharing scheme. It is more suitable for wireless sensor networks compared to the up-to-date schemes.
{"title":"Hierarchical secret sharing scheme for WSN based on linear homogeneous recurrence relations","authors":"Yan-Xin Lin, Hongliang Zhu, Guoai Xu, Guosheng Xu","doi":"10.1177/15501329221088740","DOIUrl":"https://doi.org/10.1177/15501329221088740","url":null,"abstract":"Wireless sensor network is a key technology in the sensing layer of the Internet of Things. Data security in wireless sensor network is directly related to the authenticity and validity of data transmitted in the Internet of Things. Due to the large number and different types of nodes in wireless sensor networks, layered secret key sharing technology is increasingly used in wireless sensor networks. In a hierarchical secret sharing scheme, participants are divided into sections with different permissions for each team, but the same permissions for participants in the same team. In this article, we follow the approach of the hierarchical secret sharing scheme derived from the linear homogeneous recurrence relations. We design a hierarchical multi-secret sharing scheme for wireless sensor networks on the basis of the elliptic curve public key cryptosystem combined with the linear homogeneous recurrence relations. In the proposed scheme, we do not make sure that the participants are half-truthful. In addition, the participants’ shadows can be reused. Our scheme is computational security. Only one share from each member is required in our hierarchical multi-secret sharing scheme. It is more suitable for wireless sensor networks compared to the up-to-date schemes.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44948378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501477211049910
Li Duan, Jingxian Zhou, You Wu, Wenyao Xu
In smart systems, attackers can use botnets to launch different cyber attack activities against the Internet of Things. The traditional methods of detecting botnets commonly used machine learning algorithms, and it is difficult to detect and control botnets in a network because of unbalanced traffic data. In this article, we present a novel and highly efficient botnet detection method based on an autoencoder neural network in cooperation with decision trees on a given network. The deep flow inspection method and statistical analysis are first applied as a feature selection technique to select relevant features, which are used to characterize the communication-related behavior between network nodes. Then, the autoencoder neural network for feature selection is used to improve the efficiency of model construction. Finally, Tomek-Recursion Borderline Synthetic Minority Oversampling Technique generates additional minority samples to achieve class balance, and an improved gradient boosting decision tree algorithm is used to train and establish an abnormal traffic detection model to improve the detection of unbalanced botnet data. The results of experiments on the ISCX-botnet traffic dataset show that the proposed method achieved better botnet detection performance with 99.10% recall, 99.20% accuracy, 99.1% F1 score, and 99.0% area under the curve.
{"title":"A novel and highly efficient botnet detection algorithm based on network traffic analysis of smart systems","authors":"Li Duan, Jingxian Zhou, You Wu, Wenyao Xu","doi":"10.1177/15501477211049910","DOIUrl":"https://doi.org/10.1177/15501477211049910","url":null,"abstract":"In smart systems, attackers can use botnets to launch different cyber attack activities against the Internet of Things. The traditional methods of detecting botnets commonly used machine learning algorithms, and it is difficult to detect and control botnets in a network because of unbalanced traffic data. In this article, we present a novel and highly efficient botnet detection method based on an autoencoder neural network in cooperation with decision trees on a given network. The deep flow inspection method and statistical analysis are first applied as a feature selection technique to select relevant features, which are used to characterize the communication-related behavior between network nodes. Then, the autoencoder neural network for feature selection is used to improve the efficiency of model construction. Finally, Tomek-Recursion Borderline Synthetic Minority Oversampling Technique generates additional minority samples to achieve class balance, and an improved gradient boosting decision tree algorithm is used to train and establish an abnormal traffic detection model to improve the detection of unbalanced botnet data. The results of experiments on the ISCX-botnet traffic dataset show that the proposed method achieved better botnet detection performance with 99.10% recall, 99.20% accuracy, 99.1% F1 score, and 99.0% area under the curve.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44095249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221077165
Xinmiao Lu, Yanwen Su, Qiong Wu, Yuhan Wei, Jiaxu Wang
Aiming at the problems of low data reconstruction accuracy in wireless sensor networks and users unable to receive accurate original signals, improvements are made on the basis of the stagewise orthogonal matching pursuit algorithm, combined with sparseness adaptation and the pre-selection strategy, which proposes a sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm. In the framework of the stagewise orthogonal matching pursuit algorithm, the algorithm in this article uses a combination of a fixed-value strategy and a threshold strategy to screen the candidate atom sets in two rounds to improve the accuracy of atom selection, and then according to the sparsity adaptive principle, the sparse approximation and accurate signal reconstruction are realized by the variable step size method. The simulation results show that the algorithm proposed in this article is compared with the orthogonal matching pursuit algorithm, regularized orthogonal matching pursuit algorithm, and stagewise orthogonal matching pursuit algorithm. When the sparsity is 35 < K < 45, regardless of the size of the perception matrix and the length of the signal, M = 128, N = 256 or M = 128, N = 512 are improved, and the reconstruction time is when the sparsity is 10, the fastest time between 25 and 25, that is, less than 4.5 s. It can be seen that the sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm has better adaptive characteristics to the sparsity of the signal, which is beneficial for users to receive more accurate original signals.
{"title":"An improved algorithm of segmented orthogonal matching pursuit based on wireless sensor networks","authors":"Xinmiao Lu, Yanwen Su, Qiong Wu, Yuhan Wei, Jiaxu Wang","doi":"10.1177/15501329221077165","DOIUrl":"https://doi.org/10.1177/15501329221077165","url":null,"abstract":"Aiming at the problems of low data reconstruction accuracy in wireless sensor networks and users unable to receive accurate original signals, improvements are made on the basis of the stagewise orthogonal matching pursuit algorithm, combined with sparseness adaptation and the pre-selection strategy, which proposes a sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm. In the framework of the stagewise orthogonal matching pursuit algorithm, the algorithm in this article uses a combination of a fixed-value strategy and a threshold strategy to screen the candidate atom sets in two rounds to improve the accuracy of atom selection, and then according to the sparsity adaptive principle, the sparse approximation and accurate signal reconstruction are realized by the variable step size method. The simulation results show that the algorithm proposed in this article is compared with the orthogonal matching pursuit algorithm, regularized orthogonal matching pursuit algorithm, and stagewise orthogonal matching pursuit algorithm. When the sparsity is 35 < K < 45, regardless of the size of the perception matrix and the length of the signal, M = 128, N = 256 or M = 128, N = 512 are improved, and the reconstruction time is when the sparsity is 10, the fastest time between 25 and 25, that is, less than 4.5 s. It can be seen that the sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm has better adaptive characteristics to the sparsity of the signal, which is beneficial for users to receive more accurate original signals.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49226254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221085495
Li-yong Yuan, Feilong Lin
Routing optimization in wireless sensor networks facilitates to reduce the overhead of the maintaining of wireless sensor networks and extend the lifetime of wireless sensor networks. Collection tree-based routing protocol, which does not require route discovery, has been widely used for low overheads of calculation and storage. However, with collection tree-based routing protocol, some nodes easily become the bottleneck points and quickly run out of the energy. To deal with this drawback, this article proposes a collection tree-oriented mesh routing strategy with cooperatively consuming the residual energy among the neighboring sensor nodes. The collection tree-oriented mesh routing is formulated into a linear programming problem with the purpose to maximize the network lifetime. By solving the optimization problem, the optimal mesh routing and data forwarding scheme is derived. Experimental simulations show that the proposed collection tree-oriented mesh routing optimization strategy can extend the network lifetime by more than 20%.
{"title":"Collection tree-oriented mesh routing optimization for extending the lifetime of wireless sensor networks","authors":"Li-yong Yuan, Feilong Lin","doi":"10.1177/15501329221085495","DOIUrl":"https://doi.org/10.1177/15501329221085495","url":null,"abstract":"Routing optimization in wireless sensor networks facilitates to reduce the overhead of the maintaining of wireless sensor networks and extend the lifetime of wireless sensor networks. Collection tree-based routing protocol, which does not require route discovery, has been widely used for low overheads of calculation and storage. However, with collection tree-based routing protocol, some nodes easily become the bottleneck points and quickly run out of the energy. To deal with this drawback, this article proposes a collection tree-oriented mesh routing strategy with cooperatively consuming the residual energy among the neighboring sensor nodes. The collection tree-oriented mesh routing is formulated into a linear programming problem with the purpose to maximize the network lifetime. By solving the optimization problem, the optimal mesh routing and data forwarding scheme is derived. Experimental simulations show that the proposed collection tree-oriented mesh routing optimization strategy can extend the network lifetime by more than 20%.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42988941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501477211067740
Gerald K. Ijemaru, Kenneth Li-Minn Ang, Jasmine KP Seng
Distributed sensor networks have emerged as part of the advancements in sensing and wireless technologies and currently support several applications, including continuous environmental monitoring, surveillance, tracking, and so on which are running in wireless sensor network environments, and large-scale wireless sensor network multimedia applications that require large amounts of data transmission to an access point. However, these applications are often hampered because sensor nodes are energy-constrained, low-powered, with limited operational lifetime and low processing and limited power-storage capabilities. Current research shows that sensors deployed for distributed sensor network applications are low-power and low-cost devices characterized with multifunctional abilities. This contributes to their quick battery drainage, if they are to operate for long time durations. Owing to the associated cost implications and mode of deployments of the sensor nodes, battery recharging/replacements have significant disadvantages. Energy harvesting and wireless power transfer have therefore become very critical for applications running for longer time durations. This survey focuses on presenting a comprehensive review of the current literature on several wireless power transfer and energy harvesting technologies and highlights their opportunities and challenges in distributed sensor networks. This review highlights updated studies which are specific to wireless power transfer and energy harvesting technologies, including their opportunities, potential applications, limitations and challenges, classifications and comparisons. The final section presents some practical considerations and real-time implementation of a radio frequency–based energy harvesting wireless power transfer technique using Powercast™ power harvesters, and performance analysis of the two radio frequency–based power harvesters is discussed. Experimental results show both short-range and long-range applications of the two radio frequency–based energy harvesters with high power transfer efficiency.
{"title":"Wireless power transfer and energy harvesting in distributed sensor networks: Survey, opportunities, and challenges","authors":"Gerald K. Ijemaru, Kenneth Li-Minn Ang, Jasmine KP Seng","doi":"10.1177/15501477211067740","DOIUrl":"https://doi.org/10.1177/15501477211067740","url":null,"abstract":"Distributed sensor networks have emerged as part of the advancements in sensing and wireless technologies and currently support several applications, including continuous environmental monitoring, surveillance, tracking, and so on which are running in wireless sensor network environments, and large-scale wireless sensor network multimedia applications that require large amounts of data transmission to an access point. However, these applications are often hampered because sensor nodes are energy-constrained, low-powered, with limited operational lifetime and low processing and limited power-storage capabilities. Current research shows that sensors deployed for distributed sensor network applications are low-power and low-cost devices characterized with multifunctional abilities. This contributes to their quick battery drainage, if they are to operate for long time durations. Owing to the associated cost implications and mode of deployments of the sensor nodes, battery recharging/replacements have significant disadvantages. Energy harvesting and wireless power transfer have therefore become very critical for applications running for longer time durations. This survey focuses on presenting a comprehensive review of the current literature on several wireless power transfer and energy harvesting technologies and highlights their opportunities and challenges in distributed sensor networks. This review highlights updated studies which are specific to wireless power transfer and energy harvesting technologies, including their opportunities, potential applications, limitations and challenges, classifications and comparisons. The final section presents some practical considerations and real-time implementation of a radio frequency–based energy harvesting wireless power transfer technique using Powercast™ power harvesters, and performance analysis of the two radio frequency–based power harvesters is discussed. Experimental results show both short-range and long-range applications of the two radio frequency–based energy harvesters with high power transfer efficiency.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44676727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221080666
Shanshan Wan, Zhuo Chen, Cheng Lyu, Ruofan Li, Yuntao Yue, Y. Liu
Sudden disaster events are usually unpredictable and uncontrollable, and how to achieve efficient and accurate disaster information dissemination is an important topic for society security. At present, social sensor networks which integrate human mobile sensors and traditional physical sensors are widely used in dealing with emergencies. Previous studies mainly focused on the impact of human mobility patterns on social sensor networks. In this article, based on the inherent autonomy property of human individuals, we propose a social sensor information dissemination model, which mainly focuses on the impact of the individual characteristics, social characteristics, and group information dissemination mode on social sensor networks. Specifically, the human sensor model is first constructed based on the inherent social and psychological attributes of human autonomy. Then, various information dissemination models such as one-to-one, one-to-many, and peer-to-peer are proposed by considering different transmission media and human interaction preferences. We simulate the environment of information dissemination in disaster events based on the NetLogo platform. Evaluation matrix is applied to test the performance of social sensor information dissemination model, such as event dissemination coverage, event delivery time, and event delivery rate. With the comparisons to epidemic model, social sensor information dissemination model shows excellent performance in improving the efficiency and accuracy of information transmission in disaster events.
{"title":"Research on disaster information dissemination based on social sensor networks","authors":"Shanshan Wan, Zhuo Chen, Cheng Lyu, Ruofan Li, Yuntao Yue, Y. Liu","doi":"10.1177/15501329221080666","DOIUrl":"https://doi.org/10.1177/15501329221080666","url":null,"abstract":"Sudden disaster events are usually unpredictable and uncontrollable, and how to achieve efficient and accurate disaster information dissemination is an important topic for society security. At present, social sensor networks which integrate human mobile sensors and traditional physical sensors are widely used in dealing with emergencies. Previous studies mainly focused on the impact of human mobility patterns on social sensor networks. In this article, based on the inherent autonomy property of human individuals, we propose a social sensor information dissemination model, which mainly focuses on the impact of the individual characteristics, social characteristics, and group information dissemination mode on social sensor networks. Specifically, the human sensor model is first constructed based on the inherent social and psychological attributes of human autonomy. Then, various information dissemination models such as one-to-one, one-to-many, and peer-to-peer are proposed by considering different transmission media and human interaction preferences. We simulate the environment of information dissemination in disaster events based on the NetLogo platform. Evaluation matrix is applied to test the performance of social sensor information dissemination model, such as event dissemination coverage, event delivery time, and event delivery rate. With the comparisons to epidemic model, social sensor information dissemination model shows excellent performance in improving the efficiency and accuracy of information transmission in disaster events.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47478869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221083168
A. Rajput, Jianqiang Li, F. Akhtar, Zahid Hussain Khand, Jason C. Hung, Yan Pei, A. Börner
The idea of applying integer Reversible Colour Transform to increase compression ratios in lossless image compression is a well-established and widely used practice. Although various colour transformations have been introduced and investigated in the past two decades, the process of determining the best colour scheme in a reasonable time remains an open challenge. For instance, the overhead time (i.e. to determine a suitable colour transformation) of the traditional colour selector mechanism can take up to 50% of the actual compression time. To avoid such high overhead, usually, one pre-specified transformation is applied regardless of the nature of the image and/or correlation of the colour components. We propose a robust selection mechanism capable of reducing the overhead time to 20% of the actual compression time. It is postulated that implementing the proposed selection mechanism within the actual compression scheme such as JPEG-LS can further reduce the overhead time to 10%. In addition, the proposed scheme can also be extended to facilitate network-based compression–decompression mechanism over distributed systems.
{"title":"A content awareness module for predictive lossless image compression to achieve high throughput data sharing over the network storage","authors":"A. Rajput, Jianqiang Li, F. Akhtar, Zahid Hussain Khand, Jason C. Hung, Yan Pei, A. Börner","doi":"10.1177/15501329221083168","DOIUrl":"https://doi.org/10.1177/15501329221083168","url":null,"abstract":"The idea of applying integer Reversible Colour Transform to increase compression ratios in lossless image compression is a well-established and widely used practice. Although various colour transformations have been introduced and investigated in the past two decades, the process of determining the best colour scheme in a reasonable time remains an open challenge. For instance, the overhead time (i.e. to determine a suitable colour transformation) of the traditional colour selector mechanism can take up to 50% of the actual compression time. To avoid such high overhead, usually, one pre-specified transformation is applied regardless of the nature of the image and/or correlation of the colour components. We propose a robust selection mechanism capable of reducing the overhead time to 20% of the actual compression time. It is postulated that implementing the proposed selection mechanism within the actual compression scheme such as JPEG-LS can further reduce the overhead time to 10%. In addition, the proposed scheme can also be extended to facilitate network-based compression–decompression mechanism over distributed systems.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65535113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501477211062835
K. Seng, L. Ang, Ericmoore Ngharamike
The advances and convergence in sensor, information processing, and communication technologies have shaped the Internet of Things of today. The rapid increase of data and service requirements brings new challenges for Internet of Thing. Emerging technologies and intelligent techniques can play a compelling role in prompting the development of intelligent architectures and services in Internet of Things to form the artificial intelligence Internet of Things. In this article, we give an introduction and review recent developments of artificial intelligence Internet of Things, the various artificial intelligence Internet of Things computational frameworks and highlight the challenges and opportunities for effective deployment of artificial intelligence Internet of Things technology to address complex problems for various applications. This article surveys the recent developments and discusses the convergence of artificial intelligence and Internet of Things from four aspects: (1) architectures, techniques, and hardware platforms for artificial intelligence Internet of Things; (2) sensors, devices, and energy approaches for artificial intelligence Internet of Things; (3) communication and networking for artificial intelligence Internet of Things; and (4) applications for artificial intelligence Internet of Things. The article also discusses the combination of smart sensors, edge computing, and software-defined networks as enabling technologies for the artificial intelligence Internet of Things.
{"title":"Artificial intelligence Internet of Things: A new paradigm of distributed sensor networks","authors":"K. Seng, L. Ang, Ericmoore Ngharamike","doi":"10.1177/15501477211062835","DOIUrl":"https://doi.org/10.1177/15501477211062835","url":null,"abstract":"The advances and convergence in sensor, information processing, and communication technologies have shaped the Internet of Things of today. The rapid increase of data and service requirements brings new challenges for Internet of Thing. Emerging technologies and intelligent techniques can play a compelling role in prompting the development of intelligent architectures and services in Internet of Things to form the artificial intelligence Internet of Things. In this article, we give an introduction and review recent developments of artificial intelligence Internet of Things, the various artificial intelligence Internet of Things computational frameworks and highlight the challenges and opportunities for effective deployment of artificial intelligence Internet of Things technology to address complex problems for various applications. This article surveys the recent developments and discusses the convergence of artificial intelligence and Internet of Things from four aspects: (1) architectures, techniques, and hardware platforms for artificial intelligence Internet of Things; (2) sensors, devices, and energy approaches for artificial intelligence Internet of Things; (3) communication and networking for artificial intelligence Internet of Things; and (4) applications for artificial intelligence Internet of Things. The article also discusses the combination of smart sensors, edge computing, and software-defined networks as enabling technologies for the artificial intelligence Internet of Things.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46530420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221082030
Minbo Li, Yu Wu
In recent years, the rapid development of Internet of Things smart hardware has increased the demand for intelligent control of devices, mainly in the smart home industry. The framework to solve the problem of equipment intelligent control is studied. The advantages and disadvantages of existing context modeling strategies are analyzed. According to the characteristics of household context activities, combined with the design principles of graph databases, a new context modeling method based on object and attribute graph is proposed, which is suitable for Internet of Things scenarios with limited resources. Rule control, mode control, and voice control approaches of smart home interaction are designed. An inference engine is used to map the data of context awareness to the Internet of Things control services that executed automatic control of the system, and a framework of smart control system based on context awareness of Internet of Things is proposed. Considering the behavior habits of users, the concept of user preference is introduced to provide more personalized services. Performance tests with simulated data show that the new context modeling method has a faster system response time than the ontology modeling control mode.
{"title":"Intelligent control system of smart home for context awareness","authors":"Minbo Li, Yu Wu","doi":"10.1177/15501329221082030","DOIUrl":"https://doi.org/10.1177/15501329221082030","url":null,"abstract":"In recent years, the rapid development of Internet of Things smart hardware has increased the demand for intelligent control of devices, mainly in the smart home industry. The framework to solve the problem of equipment intelligent control is studied. The advantages and disadvantages of existing context modeling strategies are analyzed. According to the characteristics of household context activities, combined with the design principles of graph databases, a new context modeling method based on object and attribute graph is proposed, which is suitable for Internet of Things scenarios with limited resources. Rule control, mode control, and voice control approaches of smart home interaction are designed. An inference engine is used to map the data of context awareness to the Internet of Things control services that executed automatic control of the system, and a framework of smart control system based on context awareness of Internet of Things is proposed. Considering the behavior habits of users, the concept of user preference is introduced to provide more personalized services. Performance tests with simulated data show that the new context modeling method has a faster system response time than the ontology modeling control mode.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46887648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-01DOI: 10.1177/15501329221087183
Ben Wu, Wei Liu, P. Shi, Xiangyang Xu, Yingjing Liu
Due to the continuous expansion of congested urban areas, many new tunnels are inevitable to over-cross the existing subway lines and may even affect the operation of existing lines. It is vital to investigate the response of existing tunnel caused by over-crossing tunneling. In this study, a case history of closely spaced twin tunnels excavated above the existing tunnels in soft soil stratum was presented. The deformation of the existing tunnels induced by the excavation of the new tunnels was automatically monitored. In-situ monitoring results showed that the vertical displacement of the existing tunnels was mainly uplift and its development showed obvious phase characteristics. The increase rate of the vertical displacement in Phase I and II induced by the second over-crossing was smaller than that of the first over-crossing. A superposition method was employed to describe the uplift section characteristics of the existing tunnels. The influence ranges of tunnel excavation on the left and right lines of the existing tunnels were approximately 5.5D and 4.5D, respectively. The torsional deformation of the rail bed and the convergence of the existing tunnels are explored, and the reasons for the changes of the over-crossing sections are analyzed at the same time.
{"title":"A case study of newly tunnels over-crossing the existing subway tunnels","authors":"Ben Wu, Wei Liu, P. Shi, Xiangyang Xu, Yingjing Liu","doi":"10.1177/15501329221087183","DOIUrl":"https://doi.org/10.1177/15501329221087183","url":null,"abstract":"Due to the continuous expansion of congested urban areas, many new tunnels are inevitable to over-cross the existing subway lines and may even affect the operation of existing lines. It is vital to investigate the response of existing tunnel caused by over-crossing tunneling. In this study, a case history of closely spaced twin tunnels excavated above the existing tunnels in soft soil stratum was presented. The deformation of the existing tunnels induced by the excavation of the new tunnels was automatically monitored. In-situ monitoring results showed that the vertical displacement of the existing tunnels was mainly uplift and its development showed obvious phase characteristics. The increase rate of the vertical displacement in Phase I and II induced by the second over-crossing was smaller than that of the first over-crossing. A superposition method was employed to describe the uplift section characteristics of the existing tunnels. The influence ranges of tunnel excavation on the left and right lines of the existing tunnels were approximately 5.5D and 4.5D, respectively. The torsional deformation of the rail bed and the convergence of the existing tunnels are explored, and the reasons for the changes of the over-crossing sections are analyzed at the same time.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48727531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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