Road transport is been used for moving people and all kinds of goods throughout the world. However, it is one mode of transportation that is prone to accidents and it faces a plethora of never-ending challenges, such ...Road transport is been used for moving people and all kinds of goods throughout the world. However, it is one mode of transportation that is prone to accidents and it faces a plethora of never-ending challenges, such as the frequent loss of lives and valuables when accident occurs. The best course of action to handle these issues is to set up an autonomous incident detection system using wireless communication, 5G technologies and the Internet of Things. IoT is a seamless technology that increases the connectivity between humans and machines. It is web-based, and improves communication between vehicle to vehicle, vehicle to infrastructures, transfer of data and information to predict incident occurrences through various networks and frameworks such as eCall, OneM2M and integration of mobile broadband. Additionally, internet of things is being adopted for public safety;for instance, it can speed up first responders’ response times to situations by displaying the best routes to a scene of an accident. The rapid development of 5G is happening in parallel with developments of internet of things (IoT), artificial intelligence (AI), and smart platforms for novel applications such as mission-critical communications. 5G is a new generation technology that operates on the Ultra High Spectrum Band UHSB. It is an innovation that uses the pedestrians-vehicle-road-cloud, and the communication between vehicle locations and temperature of high-quality connection. It is essential for intelligent transport systems because it allows for information sharing, prediction of incidences as safety is the primary concern of road transport. This review examines accident detection through 5G technology, integrated mobile broadband, and multiple inputs multiple outputs (MIMO) wireless system. Finally, we conclude by examining recent technology, challenges, present and future research trends.展开更多
The Internet of Things (IoT) is a large-scale network of devices capable of sensing, data processing, and communicating with each other through different communication protocols. In today's technology ecosystem, I...The Internet of Things (IoT) is a large-scale network of devices capable of sensing, data processing, and communicating with each other through different communication protocols. In today's technology ecosystem, IoT interacts with many application areas such as smart city, smart building, security, traffic, remote monitoring, health, energy, disaster, agriculture, industry. The IoT network in these scenarios comprises tiny devices, gateways, and cloud platforms. An IoT network is able to keep these fundamental components in transmission under many conditions with lightweight communication protocols taking into account the limited hardware features (memory, processor, energy, etc.) of tiny devices. These lightweight communication protocols affect the network traffic, reliability, bandwidth, and energy consumption of the IoT application. Therefore, determining the most proper communication protocol for application developers emerges as an important engineering problem. This paper presents a straightforward overview of the lightweight communication protocols, technological advancements in application layer for the IoT ecosystem. The survey then analyzes various recent lightweight communication protocols and reviews their strengths and limitations. In addition, the paper explains the experimental comparison of Constrained Applications Protocol (CoAP), Message Queuing Telemetry (MQTT), and WebSocket protocols, more convenient for tiny IoT devices. Finally, we discuss future research directions of communication protocols for IoT.展开更多
Rapid advancement in science and technology has seen computer network technology being upgraded constantly, and computer technology, in particular, has been applied more and more extensively, which has brought conveni...Rapid advancement in science and technology has seen computer network technology being upgraded constantly, and computer technology, in particular, has been applied more and more extensively, which has brought convenience to people’s lives. The number of people using the internet around the globe has also increased significantly, exerting a profound influence on artificial intelligence. Further, the constant upgrading and development of artificial intelligence has led to the continuous innovation and improvement of computer technology. Countries around the world have also registered an increase in investment, paying more attention to artificial intelligence. Through an analysis of the current development situation and the existing applications of artificial intelligence, this paper explicates the role of artificial intelligence in the face of the unceasing expansion of computer network technology.展开更多
Driven by the visions of the Internet of Things(IoT),Artificial Intelligence(AI),and 5G communications,the Internet of Cultural Things(IoCT)realize the comprehensive interconnection among cultural products,cultural se...Driven by the visions of the Internet of Things(IoT),Artificial Intelligence(AI),and 5G communications,the Internet of Cultural Things(IoCT)realize the comprehensive interconnection among cultural products,cultural services,cultural resources,and cultural platforms,bringing individuals with richer humanistic experience,increasing economic benefits for the cultural sector,and promoting the development of cultural heritage protection and education.At present,IoCT has received widespread attention in both industry and academia.To explore new research opportunities and assist users in constructing suitable IoCT systems for specific applications,this survey provides a comprehensive overview of the IoCT components and key technologies.A comparison study of representative IoCT systems is presented according to their applicability.A general platform architecture of IoCT is proposed to link cultural objects with the internet and human.Finally,open issues for research challenges and future opportunities of IoCT are also studied in this paper.展开更多
为解决物联网通信技术目前存在的传输距离受限、成本高昂和信号易受干扰等问题,对PLC-IoT(power line communication internet of things)技术在智能物联网领域的应用架构开展了相关研究。在ZigBee无线通信技术、Konnex(KNX)总线技术的...为解决物联网通信技术目前存在的传输距离受限、成本高昂和信号易受干扰等问题,对PLC-IoT(power line communication internet of things)技术在智能物联网领域的应用架构开展了相关研究。在ZigBee无线通信技术、Konnex(KNX)总线技术的基础上,依据PLC-IoT技术的免布专用通信线、通信带宽高、通信时延低等技术特性及优势,设计了PLC-IoT技术在配电物联网、智慧道路、智能充电桩等智慧物联网领域的应用架构,并验证了PLC-IoT技术应用于智能家居系统的可行性。结果表明:应用PLC-IoT技术的家居系统实现了ZigBee技术家居系统无法做到的长距离稳定通信,较使用KNX技术降低了约30%的成本,提升了系统整体的抗干扰性。PLC-IoT技术相较于ZigBee技术和KNX技术更适合实现智能家居、楼宇自动化等智慧物联,可提升系统的安全性与稳定性,满足新兴业务对可靠性和效率的需求。展开更多
In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data traffic.Meanwhile,with the...In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data traffic.Meanwhile,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication paradigm.However,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic information.With the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to increase.In contrast,the Pulse Coupled Neural Network(PCNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image transmission.However,the parameters of PCNN are determined by trial and error,which limits its application.To overcome this limitation,an Improved Pulse Coupled Neural Networks(IPCNN)model is proposed in this work.The IPCNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of images.Experimental segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPCNN on the gray images and natural images from the Matlab and Berkeley Segmentation Datasets.The IPCNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.展开更多
Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada...Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.展开更多
士兵训练是培养士兵战术素养和提高实际战斗力的摇篮。为士兵提供实时可靠的无线终端系统,是有效完成士兵训练的前提和基础。作为一种近几年新发展起来的物联网技术,窄带物联网(Narrow Band Internet of Things,NB-IoT)具有功耗和速率...士兵训练是培养士兵战术素养和提高实际战斗力的摇篮。为士兵提供实时可靠的无线终端系统,是有效完成士兵训练的前提和基础。作为一种近几年新发展起来的物联网技术,窄带物联网(Narrow Band Internet of Things,NB-IoT)具有功耗和速率低、覆盖广、容量高、大连接和成本低等特点。结合NB-IoT技术设计了一种士兵训练无线终端系统,给出了总体设计方案,并完成了主要模块的设计和实现,包括控制器、北斗定位模块、NB-IoT模块和报警模块。实践表明,此系统应用在实际训练中可以大大提高训练质量,具有重要的实际应用价值。展开更多
文摘Road transport is been used for moving people and all kinds of goods throughout the world. However, it is one mode of transportation that is prone to accidents and it faces a plethora of never-ending challenges, such as the frequent loss of lives and valuables when accident occurs. The best course of action to handle these issues is to set up an autonomous incident detection system using wireless communication, 5G technologies and the Internet of Things. IoT is a seamless technology that increases the connectivity between humans and machines. It is web-based, and improves communication between vehicle to vehicle, vehicle to infrastructures, transfer of data and information to predict incident occurrences through various networks and frameworks such as eCall, OneM2M and integration of mobile broadband. Additionally, internet of things is being adopted for public safety;for instance, it can speed up first responders’ response times to situations by displaying the best routes to a scene of an accident. The rapid development of 5G is happening in parallel with developments of internet of things (IoT), artificial intelligence (AI), and smart platforms for novel applications such as mission-critical communications. 5G is a new generation technology that operates on the Ultra High Spectrum Band UHSB. It is an innovation that uses the pedestrians-vehicle-road-cloud, and the communication between vehicle locations and temperature of high-quality connection. It is essential for intelligent transport systems because it allows for information sharing, prediction of incidences as safety is the primary concern of road transport. This review examines accident detection through 5G technology, integrated mobile broadband, and multiple inputs multiple outputs (MIMO) wireless system. Finally, we conclude by examining recent technology, challenges, present and future research trends.
文摘The Internet of Things (IoT) is a large-scale network of devices capable of sensing, data processing, and communicating with each other through different communication protocols. In today's technology ecosystem, IoT interacts with many application areas such as smart city, smart building, security, traffic, remote monitoring, health, energy, disaster, agriculture, industry. The IoT network in these scenarios comprises tiny devices, gateways, and cloud platforms. An IoT network is able to keep these fundamental components in transmission under many conditions with lightweight communication protocols taking into account the limited hardware features (memory, processor, energy, etc.) of tiny devices. These lightweight communication protocols affect the network traffic, reliability, bandwidth, and energy consumption of the IoT application. Therefore, determining the most proper communication protocol for application developers emerges as an important engineering problem. This paper presents a straightforward overview of the lightweight communication protocols, technological advancements in application layer for the IoT ecosystem. The survey then analyzes various recent lightweight communication protocols and reviews their strengths and limitations. In addition, the paper explains the experimental comparison of Constrained Applications Protocol (CoAP), Message Queuing Telemetry (MQTT), and WebSocket protocols, more convenient for tiny IoT devices. Finally, we discuss future research directions of communication protocols for IoT.
文摘Rapid advancement in science and technology has seen computer network technology being upgraded constantly, and computer technology, in particular, has been applied more and more extensively, which has brought convenience to people’s lives. The number of people using the internet around the globe has also increased significantly, exerting a profound influence on artificial intelligence. Further, the constant upgrading and development of artificial intelligence has led to the continuous innovation and improvement of computer technology. Countries around the world have also registered an increase in investment, paying more attention to artificial intelligence. Through an analysis of the current development situation and the existing applications of artificial intelligence, this paper explicates the role of artificial intelligence in the face of the unceasing expansion of computer network technology.
基金supported by National Natural Science Foundation of China(62172155)The National Key Research and Development Program of China(2019YFB1405702)。
文摘Driven by the visions of the Internet of Things(IoT),Artificial Intelligence(AI),and 5G communications,the Internet of Cultural Things(IoCT)realize the comprehensive interconnection among cultural products,cultural services,cultural resources,and cultural platforms,bringing individuals with richer humanistic experience,increasing economic benefits for the cultural sector,and promoting the development of cultural heritage protection and education.At present,IoCT has received widespread attention in both industry and academia.To explore new research opportunities and assist users in constructing suitable IoCT systems for specific applications,this survey provides a comprehensive overview of the IoCT components and key technologies.A comparison study of representative IoCT systems is presented according to their applicability.A general platform architecture of IoCT is proposed to link cultural objects with the internet and human.Finally,open issues for research challenges and future opportunities of IoCT are also studied in this paper.
文摘为解决物联网通信技术目前存在的传输距离受限、成本高昂和信号易受干扰等问题,对PLC-IoT(power line communication internet of things)技术在智能物联网领域的应用架构开展了相关研究。在ZigBee无线通信技术、Konnex(KNX)总线技术的基础上,依据PLC-IoT技术的免布专用通信线、通信带宽高、通信时延低等技术特性及优势,设计了PLC-IoT技术在配电物联网、智慧道路、智能充电桩等智慧物联网领域的应用架构,并验证了PLC-IoT技术应用于智能家居系统的可行性。结果表明:应用PLC-IoT技术的家居系统实现了ZigBee技术家居系统无法做到的长距离稳定通信,较使用KNX技术降低了约30%的成本,提升了系统整体的抗干扰性。PLC-IoT技术相较于ZigBee技术和KNX技术更适合实现智能家居、楼宇自动化等智慧物联,可提升系统的安全性与稳定性,满足新兴业务对可靠性和效率的需求。
基金supported in part by the National Key Research and Development Program of China(Grant No.2019YFA0706200).
文摘In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data traffic.Meanwhile,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication paradigm.However,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic information.With the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to increase.In contrast,the Pulse Coupled Neural Network(PCNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image transmission.However,the parameters of PCNN are determined by trial and error,which limits its application.To overcome this limitation,an Improved Pulse Coupled Neural Networks(IPCNN)model is proposed in this work.The IPCNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of images.Experimental segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPCNN on the gray images and natural images from the Matlab and Berkeley Segmentation Datasets.The IPCNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.
文摘Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.
文摘士兵训练是培养士兵战术素养和提高实际战斗力的摇篮。为士兵提供实时可靠的无线终端系统,是有效完成士兵训练的前提和基础。作为一种近几年新发展起来的物联网技术,窄带物联网(Narrow Band Internet of Things,NB-IoT)具有功耗和速率低、覆盖广、容量高、大连接和成本低等特点。结合NB-IoT技术设计了一种士兵训练无线终端系统,给出了总体设计方案,并完成了主要模块的设计和实现,包括控制器、北斗定位模块、NB-IoT模块和报警模块。实践表明,此系统应用在实际训练中可以大大提高训练质量,具有重要的实际应用价值。
