The dynamic landscape of the Internet of Things(IoT)is set to revolutionize the pace of interaction among entities,ushering in a proliferation of applications characterized by heightened quality and diversity.Among th...The dynamic landscape of the Internet of Things(IoT)is set to revolutionize the pace of interaction among entities,ushering in a proliferation of applications characterized by heightened quality and diversity.Among the pivotal applications within the realm of IoT,as a significant example,the Smart Grid(SG)evolves into intricate networks of energy deployment marked by data integration.This evolution concurrently entails data interchange with other IoT entities.However,there are also several challenges including data-sharing overheads and the intricate establishment of trusted centers in the IoT ecosystem.In this paper,we introduce a hierarchical secure data-sharing platform empowered by cloud-fog integration.Furthermore,we propose a novel non-interactive zero-knowledge proof-based group authentication and key agreement protocol that supports one-to-many sharing sets of IoT data,especially SG data.The security formal verification tool shows that the proposed scheme can achieve mutual authentication and secure data sharing while protecting the privacy of data providers.Compared with previous IoT data sharing schemes,the proposed scheme has advantages in both computational and transmission efficiency,and has more superiority with the increasing volume of shared data or increasing number of participants.展开更多
Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespre...Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespread adoption, have to meet the expectations of different players in the IoT ecosystem, including devices [1]. Low cost devices are easily able to connect wirelessly to the Internet, from handhelds to coffee machines, also known as Internet of Things (IoT). This research describes the methodology and the development process of creating an IoT platform. This paper also presents the architecture and implementation for the IoT platform. The goal of this research is to develop an analytics engine which can gather sensor data from different devices and provide the ability to gain meaningful information from IoT data and act on it using machine learning algorithms. The proposed system is introducing the use of a messaging system to improve the overall system performance as well as provide easy scalability.展开更多
为提高铁路供配电系统故障检测的及时性和精准性,基于窄带物联网(Narrow Band Internet of Things,NB-IoT)通信技术,提出了铁路供配电系统故障数据识别技术,并构建了完整的数据采集、传输和识别模型系统。研究结果表明,该技术在故障识...为提高铁路供配电系统故障检测的及时性和精准性,基于窄带物联网(Narrow Band Internet of Things,NB-IoT)通信技术,提出了铁路供配电系统故障数据识别技术,并构建了完整的数据采集、传输和识别模型系统。研究结果表明,该技术在故障识别准确性和响应速度上表现突出,为复杂环境下铁路供配电系统的稳定运行提供了有效支持。展开更多
As the ubiquitous electric power internet of things(UEPIoT)evolves and IoT data increases,traditional scheduling modes for load dispatch centers have yielded a variety of chal-lenges such as calculation of real-time o...As the ubiquitous electric power internet of things(UEPIoT)evolves and IoT data increases,traditional scheduling modes for load dispatch centers have yielded a variety of chal-lenges such as calculation of real-time optimization,extraction of time-varying characteristics and formulation of coordinated scheduling strategy for capacity optimization of electric heating and cooling loads.In this paper,a deep neural network coor-dination model for electric heating and cooling loads based on the situation awareness(SA)of thermostatically controlled loads(TCLs)is proposed.First,a sliding window is used to adaptively preprocess the IoT node data with uncertainty.According to personal thermal comfort(PTC)and peak shaving contribution(PSC),a dynamic model for loads is proposed;meanwhile,personalized behavior and consumer psychology are integrated into a flexible regulation model of TCLs.Then,a deep Q-network(DQN)-based approach,using the thermal comfort and electricity cost as the comprehensive reward function,is proposed to solve the sequential decision problem.Finally,the simulation model is designed to support the validity of the deep neural network coordination model for electric heating and cooling loads,by using UEPIoT intelligent dispatching system data.The case study demonstrates that the proposed method can efficiently manage coordination with large-scale electric heating and cooling loads.展开更多
With the wide application of the Internet of Things(IoT),storing large amounts of IoT data and protecting data privacy has become a meaningful issue.In general,the access control mechanism is used to prevent illegal u...With the wide application of the Internet of Things(IoT),storing large amounts of IoT data and protecting data privacy has become a meaningful issue.In general,the access control mechanism is used to prevent illegal users from accessing private data.However,traditional data access control schemes face some non-ignorable problems,such as only supporting coarse-grained access control,the risk of centralization,and high trust issues.In this paper,an attribute-based data access control scheme using blockchain technology is proposed.To address these problems,attribute-based encryption(ABE)has become a promising solution for encrypted data access control.Firstly,we utilize blockchain technology to construct a decentralized access control scheme,which can grant data access with transparency and traceability.Furthermore,our scheme also guarantees the privacy of policies and attributes on the blockchain network.Secondly,we optimize an ABE scheme,which makes the size of system parameters smaller and improves the efficiency of algorithms.These optimizations enable our proposed scheme supports large attribute universe requirements in IoT environments.Thirdly,to prohibit attribute impersonation and attribute replay attacks,we design a challenge-response mechanism to verify the ownership of attributes.Finally,we evaluate the security and performance of the scheme.And comparisons with other related schemes show the advantages of our proposed scheme.Compared to existing schemes,our scheme has more comprehensive advantages,such as supporting a large universe,full security,expressive policy,and policy hiding.展开更多
The growth of the Internet of Things(IoT)equipment business encourages the collection of large sizes of data.IoT data is being regarded as a new digital asset which contains valuable information.As a result,IoT data t...The growth of the Internet of Things(IoT)equipment business encourages the collection of large sizes of data.IoT data is being regarded as a new digital asset which contains valuable information.As a result,IoT data transactions are gaining in popularity,and data markets are starting to emerge.To support the smooth flow of data transactions,several academics offer market models and pricing techniques from various perspectives.However,the factors considered in the pricing model are still not comprehensive enough,and the willingness to sell of data providers has been ignored.Therefore,this paper investigates the pricing and profit maximization problems for the IoT data market who considers the willingness of data providers as well as data quality when purchasing data.Firstly,we analyze the factors that impact data providers’willingness to sell and give a definition of the willingness function.Secondly,we propose a data quality evaluation method and define a joint utility function based on data size and data quality.In addition,we build the profit function model of data market and give theoretical analysis.Finally,numerical experiments demonstrate that the suggested pricing mechanism can benefit the data market participants the most.展开更多
Blockchain is a viable solution to provide data integrity for the enormous volume of 5G IoT social data, while we need to break through the throughput bottleneck of blockchain. Sharding is a promising technology to so...Blockchain is a viable solution to provide data integrity for the enormous volume of 5G IoT social data, while we need to break through the throughput bottleneck of blockchain. Sharding is a promising technology to solve the problem of low throughput in blockchains. However, cross-shard communication hinders the effective improvement of blockchain throughput. Therefore, it is critical to reasonably allocate transactions to different shards to improve blockchain throughput. Existing research on blockchain sharding mainly focuses on shards formation, configuration, and consensus, while ignoring the negative impact of cross-shard communication on blockchain throughput. Aiming to maximize the throughput of transaction processing, we study how to allocate blockchain transactions to shards in this paper. We propose an Associated Transaction assignment algorithm based on Closest Fit (ATCF). ATCF classifies associated transactions into transaction groups which are then assigned to different shards in the non-ascending order of transaction group sizes periodically. Within each epoch, ATCF tries to select a shard that can handle all the transactions for each transaction group. If there are multiple such shards, ATCF selects the shard with the remaining processing capacity closest to the number of transactions in the transaction group. When no such shard exists, ATCF chooses the shard with the largest remaining processing capacity for the transaction group. The transaction groups that cannot be completely processed within the current epoch will be allocated in the subsequent epochs. We prove that ATCF is a 2-approximation algorithm for the associated transaction assignment problem. Simulation results show that ATCF can effectively improve the blockchain throughput and reduce the number of cross-shard transactions.展开更多
Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offer...Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offers opportunities but may also bear risks. A hitherto neglected aspect is the possible increase in power consumption as smart devices in IoT applications are expected to be reachable by other devices at all times. This implies that the device is consuming electrical energy even when it is not in use for its primary function. Many researchers’ communities have started addressing storage ability like cache memory of smart devices using the concept called—Named Data Networking (NDN) to achieve better energy efficient communication model. In NDN, memory or buffer overflow is the common challenge especially when internal memory of node exceeds its limit and data with highest degree of freshness may not be accommodated and entire scenarios behaves like a traditional network. In such case, Data Caching is not performed by intermediate nodes to guarantee highest degree of freshness. On the periodical updates sent from data producers, it is exceedingly demanded that data consumers must get up to date information at cost of lease energy. Consequently, there is challenge in maintaining tradeoff between freshness energy consumption during Publisher-Subscriber interaction. In our work, we proposed the architecture to overcome cache strategy issue by Smart Caching Algorithm for improvement in memory management and data freshness. The smart caching strategy updates the data at precise interval by keeping garbage data into consideration. It is also observed from experiment that data redundancy can be easily obtained by ignoring/dropping data packets for the information which is not of interest by other participating nodes in network, ultimately leading to optimizing tradeoff between freshness and energy required.展开更多
One of the most indispensable needs of life is food and its worldwide availability endorsement has made agriculture an essential sector in recent years. As the technology evolved, the need to maintain a good and suita...One of the most indispensable needs of life is food and its worldwide availability endorsement has made agriculture an essential sector in recent years. As the technology evolved, the need to maintain a good and suitable climate in the greenhouse became imperative to ensure that the indoor plants are more productive hence the agriculture sector was not left behind. That notwithstanding, the introduction and deployment of IoT technology in agriculture solves many problems and increases crop production. This paper focuses mainly on the deployment of the Internet of Things (IoT) in acquiring real- time data of environmental parameters in the greenhouse. Various IoT technologies that can be applicable in greenhouse monitoring system was presented and in the proposed model, a method is developed to send the air temperature and humidity data obtained by the DHT11 sensor to the cloud using an ESP8266-based NodeMCU and firstly to the cloud platform Thing- Speak, and then to Adafruit.IO in which MQTT protocol was used for the reception of sensor data to the application layer referred as Human-Machine Interface. The system has been completely implemented in an actual prototype, allowing the acquiring of data and the publisher/subscriber concept used for communication. The data is published with a broker’s aid, which is responsible for transferring messages to the intended clients based on topic choice. Lastly, the functionality testing of MQTT was carried out and the results showed that the messages are successfully published.展开更多
This paper presents a state of the art machine learning-based approach for automation of a varied class of Internet of things(Io T) analytics problems targeted on 1-dimensional(1-D) sensor data. As feature recommendat...This paper presents a state of the art machine learning-based approach for automation of a varied class of Internet of things(Io T) analytics problems targeted on 1-dimensional(1-D) sensor data. As feature recommendation is a major bottleneck for general Io Tbased applications, this paper shows how this step can be successfully automated based on a Wide Learning architecture without sacrificing the decision-making accuracy, and thereby reducing the development time and the cost of hiring expensive resources for specific problems. Interpretation of meaningful features is another contribution of this research. Several data sets from different real-world applications are considered to realize the proof-of-concept. Results show that the interpretable feature recommendation techniques are quite effective for the problems at hand in terms of performance and drastic reduction in development time.展开更多
Under industry 4.0, internet of things(IoT), especially radio frequency identification(RFID) technology, has been widely applied in manufacturing environment. This technology can bring convenience to production contro...Under industry 4.0, internet of things(IoT), especially radio frequency identification(RFID) technology, has been widely applied in manufacturing environment. This technology can bring convenience to production control and production transparency. Meanwhile, it generates increasing production data that are sometimes discrete, uncorrelated, and hard-to-use. Thus,an efficient analysis method is needed to utilize the invaluable data. This work provides an RFID-based production data analysis method for production control in Io T-enabled smart job-shops.The physical configuration and operation logic of Io T-enabled smart job-shop production are firstly described. Based on that,an RFID-based production data model is built to formalize and correlate the heterogeneous production data. Then, an eventdriven RFID-based production data analysis method is proposed to construct the RFID events and judge the process command execution. Furthermore, a near big data approach is used to excavate hidden information and knowledge from the historical production data. A demonstrative case is studied to verify the feasibility of the proposed model and methods. It is expected that our work will provide a different insight into the RFIDbased production data analysis.展开更多
The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after a...The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after another and created strong interdependence among one another. For example, IoT applications that generate small data with large volume and fast velocity will need 5G with characteristics of high data rate and low latency to transmit such data faster and cheaper. On the other hand, those data also need Cloud to process and to store and furthermore, SDN to provide scalable network infrastructure to transport this large volume of data in an optimal way. This article explores the technical relationships among the development of IoT, Big Data, Cloud, and SDN in the coming 5G era and illustrates several ongoing programs and applications at National Chiao Tung University that are based on the converging of those technologies.展开更多
为解决智慧城市中传感器数据传输的安全与效率问题,聚焦基于窄带物联网(Narrow Band Internet of Things,NB-IoT)技术的轻量级加密传输系统设计,探索资源受限环境下的数据保护方法。研究分析NB-IoT技术特性和轻量级加密算法优势,以Spec...为解决智慧城市中传感器数据传输的安全与效率问题,聚焦基于窄带物联网(Narrow Band Internet of Things,NB-IoT)技术的轻量级加密传输系统设计,探索资源受限环境下的数据保护方法。研究分析NB-IoT技术特性和轻量级加密算法优势,以Speck为基础,结合低带宽与低功耗特点进行优化,提出动态轮数调整和密钥更新策略,设计分层架构与高效传输流程。研究成果表明,该系统在复杂城市环境中传输成功率高、延迟低,且降低了设备能耗,为智慧城市传感器网络安全运行提供了可行方案。展开更多
为提升窄带物联网(Narrow Band Internet of Things,NB-IoT)在配电工程数据传输中的安全性,研究分析该技术在实际应用中的安全风险,提出针对性的防护方案。通过优化加密算法、动态身份认证、数据完整性校验以及入侵检测机制,有效提升系...为提升窄带物联网(Narrow Band Internet of Things,NB-IoT)在配电工程数据传输中的安全性,研究分析该技术在实际应用中的安全风险,提出针对性的防护方案。通过优化加密算法、动态身份认证、数据完整性校验以及入侵检测机制,有效提升系统的安全性与效率。实验结果表明,所提方案在保障配电数据安全的同时,显著降低资源开销,并在攻击仿真中表现出较强的防护能力,证实该方案在实际部署中具有可行性与优势。展开更多
基金supported by the National Key R&D Program of China(No.2022YFB3103400)the National Natural Science Foundation of China under Grants 61932015 and 62172317.
文摘The dynamic landscape of the Internet of Things(IoT)is set to revolutionize the pace of interaction among entities,ushering in a proliferation of applications characterized by heightened quality and diversity.Among the pivotal applications within the realm of IoT,as a significant example,the Smart Grid(SG)evolves into intricate networks of energy deployment marked by data integration.This evolution concurrently entails data interchange with other IoT entities.However,there are also several challenges including data-sharing overheads and the intricate establishment of trusted centers in the IoT ecosystem.In this paper,we introduce a hierarchical secure data-sharing platform empowered by cloud-fog integration.Furthermore,we propose a novel non-interactive zero-knowledge proof-based group authentication and key agreement protocol that supports one-to-many sharing sets of IoT data,especially SG data.The security formal verification tool shows that the proposed scheme can achieve mutual authentication and secure data sharing while protecting the privacy of data providers.Compared with previous IoT data sharing schemes,the proposed scheme has advantages in both computational and transmission efficiency,and has more superiority with the increasing volume of shared data or increasing number of participants.
文摘Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespread adoption, have to meet the expectations of different players in the IoT ecosystem, including devices [1]. Low cost devices are easily able to connect wirelessly to the Internet, from handhelds to coffee machines, also known as Internet of Things (IoT). This research describes the methodology and the development process of creating an IoT platform. This paper also presents the architecture and implementation for the IoT platform. The goal of this research is to develop an analytics engine which can gather sensor data from different devices and provide the ability to gain meaningful information from IoT data and act on it using machine learning algorithms. The proposed system is introducing the use of a messaging system to improve the overall system performance as well as provide easy scalability.
文摘为提高铁路供配电系统故障检测的及时性和精准性,基于窄带物联网(Narrow Band Internet of Things,NB-IoT)通信技术,提出了铁路供配电系统故障数据识别技术,并构建了完整的数据采集、传输和识别模型系统。研究结果表明,该技术在故障识别准确性和响应速度上表现突出,为复杂环境下铁路供配电系统的稳定运行提供了有效支持。
基金This project was supported by National Key Research and Development Plan(2017YFB0902100)Key Project of Liaoning Natural Science Foundation under Grant(20170520292).
文摘As the ubiquitous electric power internet of things(UEPIoT)evolves and IoT data increases,traditional scheduling modes for load dispatch centers have yielded a variety of chal-lenges such as calculation of real-time optimization,extraction of time-varying characteristics and formulation of coordinated scheduling strategy for capacity optimization of electric heating and cooling loads.In this paper,a deep neural network coor-dination model for electric heating and cooling loads based on the situation awareness(SA)of thermostatically controlled loads(TCLs)is proposed.First,a sliding window is used to adaptively preprocess the IoT node data with uncertainty.According to personal thermal comfort(PTC)and peak shaving contribution(PSC),a dynamic model for loads is proposed;meanwhile,personalized behavior and consumer psychology are integrated into a flexible regulation model of TCLs.Then,a deep Q-network(DQN)-based approach,using the thermal comfort and electricity cost as the comprehensive reward function,is proposed to solve the sequential decision problem.Finally,the simulation model is designed to support the validity of the deep neural network coordination model for electric heating and cooling loads,by using UEPIoT intelligent dispatching system data.The case study demonstrates that the proposed method can efficiently manage coordination with large-scale electric heating and cooling loads.
基金supported by the Defense Industrial Technology Development Program,China(JCKY2021208B036).
文摘With the wide application of the Internet of Things(IoT),storing large amounts of IoT data and protecting data privacy has become a meaningful issue.In general,the access control mechanism is used to prevent illegal users from accessing private data.However,traditional data access control schemes face some non-ignorable problems,such as only supporting coarse-grained access control,the risk of centralization,and high trust issues.In this paper,an attribute-based data access control scheme using blockchain technology is proposed.To address these problems,attribute-based encryption(ABE)has become a promising solution for encrypted data access control.Firstly,we utilize blockchain technology to construct a decentralized access control scheme,which can grant data access with transparency and traceability.Furthermore,our scheme also guarantees the privacy of policies and attributes on the blockchain network.Secondly,we optimize an ABE scheme,which makes the size of system parameters smaller and improves the efficiency of algorithms.These optimizations enable our proposed scheme supports large attribute universe requirements in IoT environments.Thirdly,to prohibit attribute impersonation and attribute replay attacks,we design a challenge-response mechanism to verify the ownership of attributes.Finally,we evaluate the security and performance of the scheme.And comparisons with other related schemes show the advantages of our proposed scheme.Compared to existing schemes,our scheme has more comprehensive advantages,such as supporting a large universe,full security,expressive policy,and policy hiding.
基金Supported by the Humanities and Social Science Fund of Ministry of Education of China(21YJCZH197)the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(2020L0252)。
文摘The growth of the Internet of Things(IoT)equipment business encourages the collection of large sizes of data.IoT data is being regarded as a new digital asset which contains valuable information.As a result,IoT data transactions are gaining in popularity,and data markets are starting to emerge.To support the smooth flow of data transactions,several academics offer market models and pricing techniques from various perspectives.However,the factors considered in the pricing model are still not comprehensive enough,and the willingness to sell of data providers has been ignored.Therefore,this paper investigates the pricing and profit maximization problems for the IoT data market who considers the willingness of data providers as well as data quality when purchasing data.Firstly,we analyze the factors that impact data providers’willingness to sell and give a definition of the willingness function.Secondly,we propose a data quality evaluation method and define a joint utility function based on data size and data quality.In addition,we build the profit function model of data market and give theoretical analysis.Finally,numerical experiments demonstrate that the suggested pricing mechanism can benefit the data market participants the most.
基金supported by Anhui Provincial Key R&D Program of China(202004a05020040),the open project of State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System in China(CEMEE2018Z0102B)the open fund of Intelligent Interconnected Systems Laboratory of Anhui Province(PA2021AKSK0114),Hefei University of Technology.
文摘Blockchain is a viable solution to provide data integrity for the enormous volume of 5G IoT social data, while we need to break through the throughput bottleneck of blockchain. Sharding is a promising technology to solve the problem of low throughput in blockchains. However, cross-shard communication hinders the effective improvement of blockchain throughput. Therefore, it is critical to reasonably allocate transactions to different shards to improve blockchain throughput. Existing research on blockchain sharding mainly focuses on shards formation, configuration, and consensus, while ignoring the negative impact of cross-shard communication on blockchain throughput. Aiming to maximize the throughput of transaction processing, we study how to allocate blockchain transactions to shards in this paper. We propose an Associated Transaction assignment algorithm based on Closest Fit (ATCF). ATCF classifies associated transactions into transaction groups which are then assigned to different shards in the non-ascending order of transaction group sizes periodically. Within each epoch, ATCF tries to select a shard that can handle all the transactions for each transaction group. If there are multiple such shards, ATCF selects the shard with the remaining processing capacity closest to the number of transactions in the transaction group. When no such shard exists, ATCF chooses the shard with the largest remaining processing capacity for the transaction group. The transaction groups that cannot be completely processed within the current epoch will be allocated in the subsequent epochs. We prove that ATCF is a 2-approximation algorithm for the associated transaction assignment problem. Simulation results show that ATCF can effectively improve the blockchain throughput and reduce the number of cross-shard transactions.
文摘Over the last few years, the Internet of Things (IoT) has become an omnipresent term. The IoT expands the existing common concepts, anytime and anyplace to the connectivity for anything. The proliferation in IoT offers opportunities but may also bear risks. A hitherto neglected aspect is the possible increase in power consumption as smart devices in IoT applications are expected to be reachable by other devices at all times. This implies that the device is consuming electrical energy even when it is not in use for its primary function. Many researchers’ communities have started addressing storage ability like cache memory of smart devices using the concept called—Named Data Networking (NDN) to achieve better energy efficient communication model. In NDN, memory or buffer overflow is the common challenge especially when internal memory of node exceeds its limit and data with highest degree of freshness may not be accommodated and entire scenarios behaves like a traditional network. In such case, Data Caching is not performed by intermediate nodes to guarantee highest degree of freshness. On the periodical updates sent from data producers, it is exceedingly demanded that data consumers must get up to date information at cost of lease energy. Consequently, there is challenge in maintaining tradeoff between freshness energy consumption during Publisher-Subscriber interaction. In our work, we proposed the architecture to overcome cache strategy issue by Smart Caching Algorithm for improvement in memory management and data freshness. The smart caching strategy updates the data at precise interval by keeping garbage data into consideration. It is also observed from experiment that data redundancy can be easily obtained by ignoring/dropping data packets for the information which is not of interest by other participating nodes in network, ultimately leading to optimizing tradeoff between freshness and energy required.
文摘One of the most indispensable needs of life is food and its worldwide availability endorsement has made agriculture an essential sector in recent years. As the technology evolved, the need to maintain a good and suitable climate in the greenhouse became imperative to ensure that the indoor plants are more productive hence the agriculture sector was not left behind. That notwithstanding, the introduction and deployment of IoT technology in agriculture solves many problems and increases crop production. This paper focuses mainly on the deployment of the Internet of Things (IoT) in acquiring real- time data of environmental parameters in the greenhouse. Various IoT technologies that can be applicable in greenhouse monitoring system was presented and in the proposed model, a method is developed to send the air temperature and humidity data obtained by the DHT11 sensor to the cloud using an ESP8266-based NodeMCU and firstly to the cloud platform Thing- Speak, and then to Adafruit.IO in which MQTT protocol was used for the reception of sensor data to the application layer referred as Human-Machine Interface. The system has been completely implemented in an actual prototype, allowing the acquiring of data and the publisher/subscriber concept used for communication. The data is published with a broker’s aid, which is responsible for transferring messages to the intended clients based on topic choice. Lastly, the functionality testing of MQTT was carried out and the results showed that the messages are successfully published.
文摘This paper presents a state of the art machine learning-based approach for automation of a varied class of Internet of things(Io T) analytics problems targeted on 1-dimensional(1-D) sensor data. As feature recommendation is a major bottleneck for general Io Tbased applications, this paper shows how this step can be successfully automated based on a Wide Learning architecture without sacrificing the decision-making accuracy, and thereby reducing the development time and the cost of hiring expensive resources for specific problems. Interpretation of meaningful features is another contribution of this research. Several data sets from different real-world applications are considered to realize the proof-of-concept. Results show that the interpretable feature recommendation techniques are quite effective for the problems at hand in terms of performance and drastic reduction in development time.
基金supported by the National Natural Science Foundation of China(71571142,51275396)
文摘Under industry 4.0, internet of things(IoT), especially radio frequency identification(RFID) technology, has been widely applied in manufacturing environment. This technology can bring convenience to production control and production transparency. Meanwhile, it generates increasing production data that are sometimes discrete, uncorrelated, and hard-to-use. Thus,an efficient analysis method is needed to utilize the invaluable data. This work provides an RFID-based production data analysis method for production control in Io T-enabled smart job-shops.The physical configuration and operation logic of Io T-enabled smart job-shop production are firstly described. Based on that,an RFID-based production data model is built to formalize and correlate the heterogeneous production data. Then, an eventdriven RFID-based production data analysis method is proposed to construct the RFID events and judge the process command execution. Furthermore, a near big data approach is used to excavate hidden information and knowledge from the historical production data. A demonstrative case is studied to verify the feasibility of the proposed model and methods. It is expected that our work will provide a different insight into the RFIDbased production data analysis.
文摘The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after another and created strong interdependence among one another. For example, IoT applications that generate small data with large volume and fast velocity will need 5G with characteristics of high data rate and low latency to transmit such data faster and cheaper. On the other hand, those data also need Cloud to process and to store and furthermore, SDN to provide scalable network infrastructure to transport this large volume of data in an optimal way. This article explores the technical relationships among the development of IoT, Big Data, Cloud, and SDN in the coming 5G era and illustrates several ongoing programs and applications at National Chiao Tung University that are based on the converging of those technologies.
文摘为解决智慧城市中传感器数据传输的安全与效率问题,聚焦基于窄带物联网(Narrow Band Internet of Things,NB-IoT)技术的轻量级加密传输系统设计,探索资源受限环境下的数据保护方法。研究分析NB-IoT技术特性和轻量级加密算法优势,以Speck为基础,结合低带宽与低功耗特点进行优化,提出动态轮数调整和密钥更新策略,设计分层架构与高效传输流程。研究成果表明,该系统在复杂城市环境中传输成功率高、延迟低,且降低了设备能耗,为智慧城市传感器网络安全运行提供了可行方案。
文摘为提升窄带物联网(Narrow Band Internet of Things,NB-IoT)在配电工程数据传输中的安全性,研究分析该技术在实际应用中的安全风险,提出针对性的防护方案。通过优化加密算法、动态身份认证、数据完整性校验以及入侵检测机制,有效提升系统的安全性与效率。实验结果表明,所提方案在保障配电数据安全的同时,显著降低资源开销,并在攻击仿真中表现出较强的防护能力,证实该方案在实际部署中具有可行性与优势。
