WO2016086831A1 - 基于物联网和通信网络的神经元系统及其神经元装置 - Google Patents

基于物联网和通信网络的神经元系统及其神经元装置 Download PDF

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Publication number
WO2016086831A1
WO2016086831A1 PCT/CN2015/096103 CN2015096103W WO2016086831A1 WO 2016086831 A1 WO2016086831 A1 WO 2016086831A1 CN 2015096103 W CN2015096103 W CN 2015096103W WO 2016086831 A1 WO2016086831 A1 WO 2016086831A1
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Prior art keywords
neuron
information
actuator
neuron device
cloud server
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PCT/CN2015/096103
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English (en)
French (fr)
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马正方
马颐宁
马也驰
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马正方
马颐宁
马也驰
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Priority to US15/531,391 priority Critical patent/US20170317891A1/en
Publication of WO2016086831A1 publication Critical patent/WO2016086831A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/16—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/38—Transceivers, i.e. devices in which transmitter and receiver form a structural unit and in which at least one part is used for functions of transmitting and receiving
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L65/00—Network arrangements, protocols or services for supporting real-time applications in data packet communication
    • H04L65/40—Support for services or applications
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]

Definitions

  • the present invention relates to a neuron system, and more particularly to a neuron system comprising a sensor actuator in an Internet of Things and a neuron device of a communication network (including the Internet and a wireless network) and a cloud server.
  • the sensor network or RFID network is equivalent to the Internet of Things.
  • sensor technology and RFID technology are just one of the information acquisition technologies.
  • GPS, video recognition, infrared, laser, scanning and other technologies that can realize automatic identification and object communication can become the information collection technology of the Internet of Things.
  • Sensor networks or RFID networks are just one application of the Internet of Things, but they are by no means all of the Internet of Things.
  • the internet has undergone a long process of development, and each device has a separate IP address.
  • the machine-to-machine (M2M) communication is also upgraded, without the need for human intervention, and information exchange and processing can be performed between devices.
  • One of the terminals of the Internet of Things is the appliance that we use every day. These “things” are interconnected by a communication standard such as a ZigBee, Sub-GHz, Wi-Fi or PLC connected infrastructure or backbone network. However, the main connection in the Internet of Things is the so-called “last inch” node in the network. These nodes contain microcontrollers (MCUs), wireless devices, sensors, and actuators, which are the brain, eyes, and fingers of the Internet of Things.
  • MCUs microcontrollers
  • the goal of the Internet of Things is not the connection between the user and the device. After all, the user does not want to monitor the sensors everywhere in the home and the sensors that are distributed throughout the production process.
  • the goal of the Internet of Things is to not only collect important information, but also to communicate with each other and make important decisions.
  • the software must be able to bridge devices, aggregate sensor data, and display information to the user through the display in an intuitive manner, or via the network to a user's computer, tablet or mobile phone.
  • Smart meters are a typical example of IoT applications. In addition to simply measuring power consumption, smart meters enable power companies to communicate instantly with customers, actively shutting down high-load appliances at peak usage levels, saving electricity bills for users, and mitigating load for power companies. In fact, smart meters are just one of the applications of the Internet of Things in smart homes. The Internet of Things can not only benefit industrial automation, lighting control, smart home, security and surveillance, health and wellness, but also agricultural applications. The emerging Internet of wearable applications can also see the Internet of Things.
  • the object of the present invention is to solve the above problems, and provide a neuron system and a neuron device based on the Internet of Things and a communication network, integrate resources of the Internet of Things and the communication network, improve the utilization degree of the data collected by the sensor, and reduce the degree of use.
  • the manufacturing cost of the mobile terminal improves the resource utilization efficiency.
  • the technical solution of the present invention is: a neuron system based on the Internet of Things and a communication network, characterized in that the system comprises a sensor actuator, an internet of things, a communication network, a cloud server and a neuron device, wherein:
  • Sensing actuator for collecting information of the sensing object
  • a neuron device that performs direct data communication with the sensing actuator and acts as a dynamic in the communication network State mobile node, interacting with information through the communication network and the cloud server;
  • the cloud server communicates with each neuron device in the communication network to uniformly store and process the information uploaded by the neuron device.
  • the sensor actuator includes a sensor and a plurality of switch modules.
  • the neuron device comprises a microprocessor, a receiving module, a transmitting module, an input interface, an output interface, and a storage module, wherein the input interface and the output interface are nerves a channel for data transmission between the meta device and the cloud server, and between the neuron device and the external input device, the receiving module and the transmitting module are channels for transmitting information between the neuron device and the cloud server and the sensing actuator, and the storage module
  • the microprocessor is respectively connected to the receiving module, the transmitting module, the input interface, the output interface and the storage module through the system bus, and the modules and interfaces are respectively connected Take control.
  • the sensing actuator is further provided with a wireless transceiver module for transmitting the read information to the corresponding neuron device according to the mobile communication protocol.
  • the neuron device is further provided with a sensing actuator interface, which directly connects the sensing actuator and the sensing actuator through the sensing actuator interface Perform direct information interaction.
  • the receiving module of the neuron device receives the acquisition information from the sensing actuator and stores the collected information in the storage module, the transmitting module of the neuron device A control command is sent to the corresponding sensor actuator, the control command including performing a threshold size adjustment on the sensor actuator.
  • the cloud server receives information from the neuron device and information from the sensor actuator, information about the neuron device, and the sensor actuator The information is processed uniformly, and the result of the processing is returned to the corresponding neuron device and sensor actuator.
  • each of the sensing actuators is configured to have a separate IP address, the cloud server and the neuron device through the configured IP address Address access sensor actuator.
  • the neuron device further includes a call self-starting module, when the information of the corresponding sensor actuator received by the neuron device exceeds the set At the threshold, an automatic call is initiated, and the relevant information is automatically uploaded to the cloud server for the cloud server to make a decision based on the information.
  • each neuron device is configured to have a separate IP address
  • the cloud server is composed of a plurality of virtual hosts having independent IP addresses, each of which The virtual host and the corresponding neuron device are accessed by their respective IP addresses, and different neuron devices are accessed by their respective IP addresses.
  • the invention also discloses a neuron device, which comprises a microprocessor, a receiving module, a transmitting module, an input interface, an output interface and a storage module, wherein the input interface and the output interface are between the neuron device and the cloud server, And a channel for data transmission between the neuron device and the external input device, the receiving module and the transmitting module are channels for transmitting information between the neuron device and the cloud server and each sensing actuator, and the storage module is used for storing and downloading from the cloud server.
  • the data and/or the data collected in each sensing actuator are connected to the receiving module, the transmitting module, the input interface, the output interface and the storage module through the system bus, and the modules and interfaces are controlled.
  • the sensor actuator includes a sensor and a plurality of switch modules.
  • the receiving module of the neuron device receives the acquisition information from the sensing actuator and stores the collected information in the storage module, and the transmitting module of the neuron device transmits to the corresponding sensing actuator A control command is sent, the control command including performing a threshold size adjustment on the sensor actuator.
  • the neuron device further includes a call self-starting module, and when the information of the corresponding sensor actuator received by the neuron device exceeds a set threshold, an automatic call is initiated. Automatically upload relevant information to the cloud server for the cloud server to make decisions based on this information.
  • the neuron device is further provided with a sensing actuator interface, which directly connects the sensing actuator through the sensing actuator interface, and performs direct information interaction with the sensing actuator.
  • each of the neuron devices is configured to have a separate IP address through which the cloud server accesses the neuron device, and the different neuron devices are accessed by IP addresses .
  • the present invention integrates the Internet of Things and the communication network, and assigns each sensor actuator in the Internet of Things and each neuron device in the communication network a separate IP.
  • the address enables the cloud server to access the sensor actuator and the neuron device through the IP address, the neuron device directly accesses the sensor actuator through a wireless network or a physical interface, and the neuron device is accessed by an IP address between each other.
  • the sensor actuator can upload the collected information directly to the neuron device through the wireless transceiver module installed on itself.
  • the neuron device can also be directly imported into the sensor actuator via a physical form of the sensor actuator interface.
  • the present invention establishes an effective communication bridge between the Internet of Things and the communication network, so that the information collected by the sensor actuator can be well used for the neuron device in the communication network, and the cloud is used.
  • the server, the complex operation and processing based on this information can be transferred to the cloud server for unified operation, that is, the value-added application is transferred to the cloud server, which reduces the burden on the terminal neuron device and solves the increasingly complicated terminal.
  • the disadvantages of the implementation make more complex applications available on simple terminals.
  • a neuron device terminal
  • a sensor actuator such as a wearable device
  • FIG. 1 shows a system schematic of a preferred embodiment of a neural network based on the Internet of Things and communication network of the present invention.
  • Fig. 2 is a structural view showing a preferred embodiment of the neuron device of the present invention.
  • Figure 3 illustrates the system principle of another embodiment of the neuronal system of the present invention.
  • the neuron system of the present embodiment includes a plurality of sensing actuators 10 to 1N, a plurality of neuron devices 30 to 3N', a cloud server 4, an Internet of Things 2, and a communication network 5.
  • the communication network may be the Internet, a mobile communication network such as 3G, 4G, or the like, a wireless communication network such as WiFi.
  • the sensor actuators 10 to 1N collect information of the sensing object and upload it to the corresponding neuron devices 30 to 3N'.
  • the cloud server 4 and the neuron devices 30 to 3N' located in the communication network 5 perform information transfer, and uniformly store and process the information uploaded by the neuron devices 30 to 3N', and the information uploaded by the neuron device includes the information received from the sensor actuator. Information and externally entered information.
  • the neuron devices 30 to 3N' serve as dynamic mobile nodes in the communication network 5, and perform information exchange via the communication network 5 and the cloud server 4.
  • FIG. 2 shows the structure of a preferred embodiment of the neuron device of the present invention, see Figure 2.
  • the neuron device 30 (illustrated by taking one of the neuron devices 30 as an example, the other neuron devices are identical in structure) includes a microprocessor 301, a receiving module 302, a transmitting module 303, an input interface 304, an output interface 305, and Storage module 306.
  • the input interface 304 and the output interface 305 are channels for data transmission between the neuron device 30 and the cloud server 4, and between the neuron device 30 and an external input device (not shown).
  • the receiving module 302 and the transmitting module 303 are channels for information transmission between the neuron device 30 and the cloud server 4 and the respective sensing actuators 10 to 1N.
  • the storage module 306 is configured to store data downloaded from the cloud server 4 and/or data collected in the respective sensor actuators 10 to 1N.
  • the microprocessor 301 is connected to the receiving module 302, the transmitting module 303, the input interface 304, the output interface 305, and the storage module 306 through the system bus 307, and controls the modules and interfaces.
  • the neuron device is transferred to the corresponding cloud server, which can realize the three-way of the mobile neuron device: function simplification, terminal deviceization and computing cloud.
  • the receiving module 302 of the neuron device receives the acquisition information from the sensing actuator and stores the acquisition information in the storage module 306.
  • the transmitting module 303 of the neuron device transmits to the corresponding sensing actuator.
  • the control command, the control command to the sensing actuator includes an adjustment of the threshold size of the sensing actuator.
  • the static, dynamic information stored in the storage module 306, including the respective sensor actuators recorded, the neuron device can be directed to transmit information in the storage module 306 to a particular IP address, including in the respective sensor actuators of the record. Static information, dynamic information, change threshold records, and more.
  • the communication between the neuron device 30 and the sensing actuator 10 can be both wireless and physical.
  • a wireless transceiver module (not shown) is provided on the sensor actuator 10, and the collected information is transmitted to the neuron device 30 in accordance with the mobile communication protocol.
  • the sensor actuator interface 309 (there may be multiple) is provided in the neuron device 30, and the sensor actuator interface 309 is directly connected to the sensor actuator to perform the sensor actuator. Direct information interaction.
  • the sensing actuator can also be embedded in the neuron device 30.
  • the sensor actuator includes the sensor itself as a component and may also include a plurality of switches (such as switch 1 to switch n as illustrated).
  • the neuron device 30 further includes a call self-starting module 308.
  • a call self-starting module 308 When the information of the corresponding sensor actuator received by the neuron device 30 exceeds a set threshold, an automatic call is initiated, and the related information is automatically uploaded.
  • the cloud server 4 makes a decision based on the information.
  • the respective sensor actuators 10 to 1N in the Internet of Things are configured to have independent IP addresses, and the cloud server 4 and the neuron devices 30 to 3N' access the sensor actuators 10 to 1N through the configured IP addresses. Further, each of the neuron devices 30 to 3N' is configured to have an independent IP address, and the cloud server 4 accesses the neuron devices 30 to 3N' through the IP address, and the different neuron devices 30 to 3N' pass each other. IP address access (such as reading information about memory modules in other neuron devices).
  • the cloud server 4 receives information from the neuron devices 30 to 3N' and information from the sensor actuators 10 to 1N, and unifies the information of the neuron devices 30 to 3N' and the information of the sensor actuators 10 to 1N.
  • the results of the processing are returned to the corresponding neuron devices 30-3N' and the sensor actuators 10-1N.
  • the cloud server 4 can directly establish a communication connection with the Internet of Things 2.
  • the cloud server 4 is composed of a plurality of virtual hosts having independent IP addresses, wherein each virtual host corresponds to a neuron device to complete necessary value-added applications. Every virtual host and its Corresponding neuron devices are accessed by their respective IP addresses. The value-added applications to be implemented by the neuron device are based on their corresponding virtual host deployment. Neuron devices are only used as data read-in, data readout, data collection and distribution (post to the cloud or other authorized mobile devices, neuron devices), data caching, data monitoring, communication with other neuron devices, and A neuron device that transmits data in real time or at the cloud. All advanced computing, analytics, and value-added applications are all done by virtual hosts in the cloud.
  • the core device of a smart wearable device is a computer that can access the Internet at any time.
  • the increasingly complex application requires the local computer to be more powerful, but the wearable smart device requires lightness, which is a contradiction.
  • the solution to the problem is to use high-speed mobile Internet, just use the neuron device as a hub for the Internet, only the neuron device as an input and output device, cache device, all complex computing has been in the cloud The server is completed, so that the above problem can be solved well.
  • various sensory actuators on the body and various changes in the body data can be transmitted to the cloud virtual host in time through the neuron device, and the virtual host can complete Various value-added applications are transmitted back to the neuron device via the mobile Internet and distributed to various parts of the body. For example: distribution to the eyes for viewing, learning or entertainment, distribution to the body to remind the body state, distribution to the headphones to enjoy music and speech, distributed to the body's various sensory organs to experience virtual reality.
  • the deviceized neuron device is installed on the moving object as a network hub, which can not only transmit the information on the moving object to people, objects and the Internet in time, but also can carry out value-added applications, and instantly make complex analysis and calculation, and promote Expand the application of the Internet of Things.
  • the cost of the neuron device is greatly reduced without limiting its powerful computing power. It can be widely used in a variety of moving objects, and long-term collection of data from various sensing actuators on various objects, for immediate and long-term accumulation of analytical calculations, and will promote the application of big data.
  • the neuron device can be used for node devices in various wireless networks.
  • a protocol is established (in the place where the operator's mobile network cannot cover, a communication mechanism can be established with these nodes), and the moving neurons are close to the "node", automatically
  • the data in the read node is stored in the storage module and automatically transmitted to the specified IP address while waiting for the network.
  • FIG. 3 Another system structure is shown in Figure 3.
  • communication connections can also be established between the sensing actuators through the Internet of Things.
  • the neuron device is mounted on a vehicle such as a car, boat, and aircraft.
  • the input interface of the neuron device is connected to the bus driver's arrival notice button, and the position information of the person (which is the driver's subjective judgment position) is notified to the in-vehicle or off-board passengers and the dispatcher (their neuron device) via the neuron device. .
  • the neuron device on the vehicle (such as through a position sensing actuator) establishes an automatic call mechanism with the neuron device carried by the passenger (such as through a position sensing actuator), confirms the dynamic passenger capacity of the vehicle, and communicates to the required People, things or institutions.
  • the on-vehicle position sensing actuator periodically transmits the position information of the vehicle through the neuron device to the person who subscribes to the information; the person who pre-determines the vehicle position information can actively call the on-board neuron device to inquire the position information of the vehicle.
  • the reservation person may be the geographical location of the family-related private car, and may be the specific geographical location information of the passenger concerned about the upcoming arrival of the vehicle, or the geographical location information of the logistics company monitoring the transportation of the goods.
  • the temperature sensing actuator of the engine on the vehicle monitors the safety of the engine.
  • the neuron device is mounted on a garment worn by a person.
  • the position sensing actuator on the clothes travels in the elderly or the next child, and the neuron device periodically reports the position information to the predetermined terminal.
  • the intended terminal can also actively call and ask for location information.
  • a sensor actuator that monitors the health status (such as a pulse blood pressure sensor actuator) periodically transmits monitoring information to the predetermined person through the portable neuron device. It is also possible to query the instant sensor actuator data by the subscriber through a terminal call.
  • the patient's neuronal device (such as through a position sensing actuator) and the doctor's neuron device (than If an automatic call mechanism is established between the position sensing actuators, the doctor automatically sends his own medical records and medical files to his/her patient, and the patient sends his own medical records, medical files, and personal medical information to his doctor.
  • DSPs digital signal processors
  • ASICs application specific integrated circuits
  • FPGAs field programmable gate arrays
  • Programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein are implemented or executed.
  • a general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine.
  • the processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
  • a software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
  • An exemplary storage medium is coupled to the processor to enable the processor to read and write information to/from the storage medium.
  • the storage medium can be integrated into the processor.
  • Processor and storage media can reside In the ASIC.
  • the ASIC can reside in the user terminal.
  • the processor and the storage medium may reside as a discrete component in the user terminal.
  • the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented as a computer program product in software, the functions may be stored on or transmitted as one or more instructions or code on a computer readable medium.
  • Computer readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another.
  • a storage medium may be any available media that can be accessed by a computer.
  • such computer readable media may comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage or other magnetic storage device, or can be used to carry or store instructions or data structures. Any other medium that is desirable for program code and that can be accessed by a computer.
  • any connection is also properly referred to as a computer readable medium.
  • the software is transmitted from a web site, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave.
  • the coaxial cable, fiber optic cable, twisted pair cable, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of the medium.
  • Disks and discs as used herein include compact discs (CDs), laser discs, optical discs, digital versatile discs (DVDs), floppy discs, and Blu-ray discs, in which disks are often reproduced magnetically. Data, and discs optically reproduce data with a laser. Combinations of the above should also be included within the scope of computer readable media.

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Abstract

本发明公开了一种基于物联网和通信网络的神经元系统及其神经元装置，整合了物联网和通信网络的资源，提高了传感器采集数据的利用程度，降低了移动终端的制造成本，提升了资源利用效率。其技术方案为：系统包括传感执行器、物联网、通信网络、云端服务器以及神经元装置，其中传感执行器，采集感应对象的信息；神经元装置，和传感执行器进行直接的数据通信，且作为通信网络中的动态移动节点，通过通信网络和云端服务器进行信息交互；云端服务器，和通信网络中的各个神经元装置进行信息传递，统一存储和处理神经元装置上传的信息。

Description

基于物联网和通信网络的神经元系统及其神经元装置 发明领域
本发明涉及一种神经元系统，尤其涉及囊括了物联网中的传感执行器以及通信网络(包括互联网以及无线网络)的神经元装置和云端服务器之间的神经元系统。
背景技术
把传感网或RFID网等同于物联网。事实上传感技术也好、RFID技术也好，都仅仅是信息采集技术之一。除传感技术和RFID技术外，GPS、视频识别、红外、激光、扫描等所有能够实现自动识别与物物通信的技术都可以成为物联网的信息采集技术。传感网或者RFID网只是物联网的一种应用，但绝不是物联网的全部。
网际网路经过漫长的发展，至今每个装置都拥有独立的IP位址。而机器对机器(M2M)的通讯也在升级，无需人为参与，装置间即可进行资讯交换和处理。
物联网的终端之一，正是我们每天都使用的电器等装置。这些“物”透过通讯标准如ZigBee、Sub-GHz、Wi-Fi或PLC等连接的基础设施或骨干网路相互联系。然而，物联网中主要的连接装置是位于网路所谓的“最后一寸”(last inch)节点。这些节点包含微控制器(MCU)、无线装置、感测器和执行器，这分别是物联网的大脑、眼睛和手指。
物联网的目标，并非是用户与装置之间的连接，毕竟用户并不希望随时监看家中遍布的感测器以及生产过程中遍布的传感器。物联网的目标在于不仅能收集重要资讯，并且装置之间还可以相互通讯并做出重要的决策。
为物联网实现装置互连应用所面临的挑战，与传统网路连接装置的挑战完全不同。举例来说，照明和家电等OEM制造商，除了核心功能之外，还要导入新的网路、无线和嵌入式软体技术。此外，由于装置通常无法连接电源，所以电源效率也非常关键，需要在没有维护或不更换电池的情况下，藉助能源收集装置或电池工作数年。
开发人员还需要考虑其他因素，例如成本、元件数量、MCU性能、系统 规模、标准、互操性、安全性、易用性和和现场故障排除能力等。最后，软件必须能够桥接装置、汇集感测器资料，并以直观的方式，透过显示器为用户显示资讯，或透过网路传递到用户电脑、平板或手机上。
智慧电表即是物联网应用的典型范例。除了简单地测量功耗，智慧电表使电力公司与客户即时通讯，在用电高峰主动关闭高负荷电器，来为用户节省电费，以及为电力公司减轻负荷。事实上，智慧电表只是物联网于智慧家居的应用之一。物联网不只可以为工业自动化、照明控制、智慧家居、安全和监控、卫生和保健，以及农业应用带来好处之外，在近期兴起的穿戴式应用也可以看到物联网的踪影。
目前的物联网应用(传感器相关)和互联网应用(上网终端相关)并不能很好的结合在一起。传感器采集到的信息很难通过有效便捷的技术手段被互联网应用所吸收和利用。
另一方面，目前的上网终端(例如手机等移动终端)的功能越来越复杂，很多的应用、处理以及计算都在终端上独立实现。但这种实现方式显然提高了终端的制造成本，而且每一个终端独立的计算和处理也对资源造成了浪费。
发明概述
以下给出一个或多个方面的简要概述以提供对这些方面的基本理解。此概述不是所有构想到的方面的详尽综览，并且既非旨在指认出所有方面的关键性或决定性要素亦非试图界定任何或所有方面的范围。其唯一的目的是要以简化形式给出一个或多个方面的一些概念以为稍后给出的更加详细的描述之序。
本发明的目的在于解决上述问题，提供了一种基于物联网和通信网络的神经元系统及其神经元装置，整合了物联网和通信网络的资源，提高了传感器采集数据的利用程度，降低了移动终端的制造成本，提升了资源利用效率。
本发明的技术方案为：本发明一种基于物联网和通信网络的神经元系统，其特征在于，系统包括传感执行器、物联网、通信网络、云端服务器以及神经元装置，其中：
传感执行器，采集感应对象的信息；
神经元装置，和传感执行器进行直接的数据通信，且作为通信网络中的动 态移动节点，通过通信网络和云端服务器进行信息交互；
云端服务器，和通信网络中的各个神经元装置进行信息传递，统一存储和处理神经元装置上传的信息。
根据本发明的基于物联网和通信网络的神经元系统的一实施例，传感执行器中包括传感器和多个开关模块。
根据本发明的基于物联网和通信网络的神经元系统的一实施例，神经元装置包括微处理器、接收模块、发射模块、输入接口、输出接口、存储模块，其中输入接口和输出接口是神经元装置和云端服务器之间、以及神经元装置和外部输入设备之间的数据传输的通道，接收模块和发射模块是神经元装置和云端服务器以及传感执行器之间信息传输的通道，存储模块用于存储从云端服务器下载的数据和/或各个传感执行器中采集的数据，微处理器通过系统总线分别连接接收模块、发射模块、输入接口、输出接口和存储模块，对这些模块和接口进行控制。
根据本发明的基于物联网和通信网络的神经元系统的一实施例，传感执行器上还设有无线收发模块，按照移动通信协议将读取到信息发送至对应的神经元装置。
根据本发明的基于物联网和通信网络的神经元系统的一实施例，神经元装置中还设有传感执行器接口，通过传感执行器接口直接连接传感执行器，和传感执行器进行直接的信息交互。
根据本发明的基于物联网和通信网络的神经元系统的一实施例，神经元装置的接收模块接收来自传感执行器的采集信息，并将采集信息存储于存储模块，神经元装置的发射模块向对应的传感执行器发送控制指令，控制指令包括对传感执行器实施阈值大小的调整。
根据本发明的基于物联网和通信网络的神经元系统的一实施例，云端服务器接收来自神经元装置的信息以及来自传感执行器的信息，对这些神经元装置的信息以及传感执行器的信息进行统一的处理，再将处理的结果返回给对应的神经元装置和传感执行器。
根据本发明的基于物联网和通信网络的神经元系统的一实施例，各个传感执行器被配置成具有独立的IP地址，云端服务器和神经元装置通过配置的IP地 址访问传感执行器。
根据本发明的基于物联网和通信网络的神经元系统的一实施例，神经元装置中还包括一呼叫自启模块，当神经元装置接收到的对应的传感执行器的信息超出设定的阈值时，启动自动呼叫，自动上传相关信息到云端服务器，供云端服务器基于这些信息做出决策。
根据本发明的基于物联网和通信网络的神经元系统的一实施例，每一神经元装置被配置成具有独立的IP地址，云端服务器由多个具有独立IP地址的虚拟主机组成，其中每一虚拟主机和对应的神经元装置之间通过各自的IP地址访问，不同的神经元装置相互之间通过各自的IP地址访问。
本发明还揭示了一种神经元装置，神经元装置包括微处理器、接收模块、发射模块、输入接口、输出接口以及存储模块，其中输入接口和输出接口是神经元装置和云端服务器之间、以及神经元装置和外部输入设备之间的数据传输的通道，接收模块和发射模块是神经元装置和云端服务器以及各个传感执行器之间信息传输的通道，存储模块用于存储从云端服务器下载的数据和/或各个传感执行器中采集的数据，微处理器通过系统总线分别连接接收模块、发射模块、输入接口、输出接口和存储模块，对这些模块和接口进行控制。
根据本发明的神经元装置的一实施例，传感执行器中包括传感器和多个开关模块。
根据本发明的神经元装置的一实施例，神经元装置的接收模块接收来自传感执行器的采集信息，并将采集信息存储于存储模块，神经元装置的发射模块向对应的传感执行器发送控制指令，控制指令包括对传感执行器实施阈值大小的调整。
根据本发明的神经元装置的一实施例，神经元装置中还包括一呼叫自启模块，当神经元装置接收到的对应的传感执行器的信息超出设定的阈值时，启动自动呼叫，自动上传相关信息到云端服务器，供云端服务器基于这些信息做出决策。
根据本发明的神经元装置的一实施例，神经元装置中还设有传感执行器接口，通过传感执行器接口直接连接传感执行器，和传感执行器进行直接的信息交互。
根据本发明的神经元装置的一实施例，每一神经元装置被配置成具有独立的IP地址，云端服务器通过这一IP地址访问神经元装置，不同的神经元装置相互之间通过IP地址访问。
本发明对比现有技术有如下的有益效果：本发明将物联网和通信网络整合在一起，分配给物联网中的每一个传感执行器以及通信网络中的每一个神经元装置一个独立的IP地址，使得云端服务器可以通过这一IP地址访问传感执行器和神经元装置，神经元装置通过无线网络或者物理接口直接访问传感执行器，以及神经元装置相互之间通过IP地址来访问。比如，传感执行器可以通过安装在自身上的无线收发模块将采集到的信息直接上传到神经元装置。神经元装置还可以通过物理形式的传感执行器接口直接导入传感执行器中的数据。相较于传统技术，本发明在物联网和通信网络之间建立起一个有效沟通的桥梁，使得传感执行器采集到的信息能够很好的为通信网络中的神经元装置所用，并且借助云端服务器，基于这些信息的复杂的运算和处理可以转移到云端服务器上进行统一的运行，即增值应用转移到云端的服务器上，减轻了位于终端的神经元装置的负担，解决了终端越来越复杂化的不利，使更复杂的应用得以在功能简单的终端上实现。神经元装置(终端)和传感执行器(例如可穿戴设备)的结合，辅之以云端服务器的复杂处理，可实现多种应用的实现，有助于促进可穿戴设备的发展，促进移动物体的随时上网，而移动终端的成本会随着器件的高度集成而越来越低。
附图说明
图1示出了本发明的基于物联网和通信网络的神经元系统的较佳实施例的系统原理图。
图2示出了本发明的神经元装置的较佳实施例的结构图。
图3示出了本发明的神经元系统的另一实施例的系统原理。
发明的详细说明
在结合以下附图阅读本公开的实施例的详细描述之后，能够更好地理解本 发明的上述特征和优点。在附图中，各组件不一定是按比例绘制，并且具有类似的相关特性或特征的组件可能具有相同或相近的附图标记。
图1示出了本发明的基于物联网和通信网络的神经元系统的较佳实施例的系统原理。请参见图1，本实施例的神经元系统包括：多个传感执行器10～1N、多个神经元装置30～3N’、云端服务器4、物联网2以及通信网络5。通信网络可以是互联网、诸如3G、4G等移动通信网、诸如WiFi等无线通信网。
在这个系统中，传感执行器10～1N采集感应对象的信息，上传到对应的神经元装置30～3N’。位于通信网络5中的云端服务器4和神经元装置30～3N’进行信息传递，统一存储和处理神经元装置30～3N’上传的信息，神经元装置上传的信息包括从传感执行器接收到的信息以及外部输入的信息。
而神经元装置30～3N’作为通信网络5中的动态移动节点，通过通信网络5和云端服务器4进行信息交互。
图2示出了本发明的神经元装置的较佳实施例的结构，请参见图2。神经元装置30(以其中一个神经元装置30为例进行说明，其他的神经元装置的结构是相同的)包括微处理器301、接收模块302、发射模块303、输入接口304、输出接口305以及存储模块306。其中输入接口304和输出接口305是神经元装置30和云端服务器4之间、以及神经元装置30和外部输入设备(未图示)之间的数据传输的通道。接收模块302和发射模块303是神经元装置30和云端服务器4以及各个传感执行器10～1N之间信息传输的通道。存储模块306用于存储从云端服务器4下载的数据和/或各个传感执行器10～1N中采集的数据。微处理器301通过系统总线307分别连接接收模块302、发射模块303、输入接口304、输出接口305和存储模块306，对这些模块和接口进行控制。
神经元装置作为人和移动物体的上网枢纽，增值应用转移到与之对应的云端服务器，这样可以实现移动神经元装置的三化：功能简化、终端器件化和计算云端化。
神经元装置的接收模块302接收来自传感执行器的采集信息，并将采集信息存储于存储模块306。神经元装置的发射模块303向对应的传感执行器发送 控制指令，对传感执行器的控制指令包括对传感执行器实施阈值大小的调整。存储模块306中所存储的包括记录的各个传感执行器中的静态、动态信息，神经元装置可定向向特定的IP地址发送存储模块306中的信息，包括记录的各个传感执行器中的静态信息、动态信息、更改阈值记录等。
神经元装置30和传感执行器10之间的通信可以有无线的和物理接口两种方式。对于无线的通信方式，在传感执行器10上设置无线收发模块(未图示)，按照移动通信协议将采集到的信息传输给神经元装置30。
而对于物理接口的方式，是在神经元装置30中设置传感执行器接口309(可以有多个)，通过这些传感执行器接口309直接连接传感执行器，从而和传感执行器进行直接的信息交互。当然，还可以将传感执行器内嵌在神经元装置30中。
传感器执行器包括传感器这一组件本身，还可以包括多个开关(如图示的开关1至开关n)。
较佳的，在神经元装置30中还包括一个呼叫自启模块308，当神经元装置30接收到的对应的传感执行器的信息超出设定的阈值时，启动自动呼叫，自动上传相关信息到云端服务器4，供云端服务器4基于这些信息做出决策。
物联网中的各个传感执行器10～1N被配置成具有独立的IP地址，云端服务器4和神经元装置30～3N’通过配置的IP地址访问传感执行器10～1N。此外，每一神经元装置30～3N’被配置成具有独立的IP地址，云端服务器4通过这一IP地址访问神经元装置30～3N’，不同的神经元装置30～3N’相互之间通过IP地址访问(比如读取其他的神经元装置中的存储模块的信息)。云端服务器4接收来自神经元装置30～3N’的信息以及来自传感执行器10～1N的信息，对这些神经元装置30～3N’的信息以及传感执行器10～1N的信息进行统一的处理，再将处理的结果返回给对应的神经元装置30～3N’和传感执行器10～1N。云端服务器4除了通过通信网络5和神经元装置和传感执行器建立通信外，还可以直接和物联网2建立通信连接。
较佳的，云端服务器4由多个具有独立IP地址的虚拟主机组成，其中每一个虚拟主机对应一个神经元装置，完成必要的增值应用。每一个虚拟主机和其 对应的神经元装置之间都是通过各自的IP地址来访问的。神经元装置所要实现的增值应用，都基于其对应的虚拟主机展开。神经元装置仅仅作为数据读入、数据读出、数据收集和发布(发布至云端或经授权的其他移动端、神经元装置)、数据缓存、数据监控、可与其他神经元装置通信以及可与云端实时或定时传送数据的神经元装置。所有高级计算、分析和增值应用全部由云端对应的虚拟主机来完成。
智能可穿戴设备的核心器件是可随时上网的计算机。但应用越来复杂的需要，要求本地计算机功能越来强大，但可穿戴智能设备要求轻便，这是一对矛盾。在移动互联网上网速度快到一定程度，解决问题的办法就是运用高速移动互联网，仅仅把神经元装置作为上网的枢纽，仅仅把神经元装置作为输入输出设备、缓存装置，所有的复杂计算都一直云端服务器完成，这样就可以很好地解决上述问题。
因为功能简化的神经元装置，作为我们身上上网的枢纽，身体上的各种传感执行器、身上的各种变化的数据都可以通过神经元装置及时传递给云端的虚拟主机，虚拟主机可以完成各种增值应用，在通过移动互联网把结果传回给神经元装置，分发到身体的各个部位。比如：分发给眼睛进行观赏、学习或娱乐，分发给肌体提醒肌体状态，分发给耳机欣赏音乐和言语，分发给身体的各种感觉器官体验虚拟现实。
可移动物体的信息交换，它与物、与人以及与网的信息交换，还没有充分地运用好移动互联网。将器件化的神经元装置安装在移动物体上作为上网枢纽，不仅可以将移动物体上的信息及时传递到人、物和网上，还可以进行增值应用，即时做出复杂的分析和计算，促进和拓展物联网的应用。
因为功能简化的神经元装置，大大降低了神经元装置的成本，而又不局限它的强大运算能力。使其可以广泛运用于各种移动的物体，并长期收集各种物体上各种传感执行器的数据，进行即时和长期积累的分析计算，同时会促进大数据的应用。
从这一方案可以看出，神经元装置可用于各种无线网络中的节点设备。作为动态无线网络的动态移动节点，建立协议(在运营商移动网络覆盖不到的地方，能够与这些节点建立通信机制)，移动的神经元只要接近“节点”，自动 读取节点中的数据，存储在存储模块中，等待有网络时，自动传送到指定的IP地址。
另一种系统结构如图3所示。图3所示实施例和图1的不同之处在于物联网的位置，在图3中，传感执行器之间还可以通过物联网来建立通信连接。
本发明的应用实例：
实例1：
神经元装置安装在交通工具(比如车、船和飞行器)上。神经元装置的输入接口接入公交车司机的到站预告按键，经神经元装置向车内或车外乘客、调度(他们的神经元装置)通报人为(是司机主观判断的位置)的位置信息。
车上的神经元装置(比如通过位置传感执行器)与乘客随身携带的神经元装置(比如通过位置传感执行器)建立自动呼叫机制，确认交通工具的动态载客量，通报给需要的人、物或机构。车上位置传感执行器定时通过神经元装置发送车的位置信息，给预定这些信息的人；预定车位置信息的人，可以主动呼叫车上神经元装置，询问车的位置信息。预定人可以是家人关系私家车的地理位置，可以是乘客关心即将到达车的具体地理位置信息，也可以是物流公司监控货物运输的地理位置信息。
以此类推，车上发动机的温度传感执行器，监控发动机的安全状况等。
实例2：
神经元装置安装在人穿的衣服上。衣服上的位置传感执行器在老人或下孩子出行，神经元装置定时报位置信息给预定的终端。预定终端也可以主动呼叫，询问位置信息。
监控健康状态的传感执行器(比如脉搏血压传感执行器)通过随身神经元装置，定时向预定者发送监控信息。也可以由预定者通过终端呼叫，查询即时传感执行器数据。
病人的神经元装置(比如通过位置传感执行器)和医生的神经元装置(比 如通过位置传感执行器)之间，建立自动呼叫机制，医生自动向自己的病人发送自己的医疗记录和医疗档案，病人向自己的医生发送自己的医疗记录、医疗档案以及个人体检信息。
尽管为使解释简单化将上述方法图示并描述为一系列动作，但是应理解并领会，这些方法不受动作的次序所限，因为根据一个或多个实施例，一些动作可按不同次序发生和/或与来自本文中图示和描述或本文中未图示和描述但本领域技术人员可以理解的其他动作并发地发生。
本领域技术人员将进一步领会，结合本文中所公开的实施例来描述的各种解说性逻辑板块、模块、电路、和算法步骤可实现为电子硬件、计算机软件、或这两者的组合。为清楚地解说硬件与软件的这一可互换性，各种解说性组件、框、模块、电路、和步骤在上面是以其功能性的形式作一般化描述的。此类功能性是被实现为硬件还是软件取决于具体应用和施加于整体系统的设计约束。技术人员对于每种特定应用可用不同的方式来实现所描述的功能性，但这样的实现决策不应被解读成导致脱离了本发明的范围。
结合本文所公开的实施例描述的各种解说性逻辑板块、模块、和电路可用通用处理器、数字信号处理器(DSP)、专用集成电路(ASIC)、现场可编程门阵列(FPGA)或其它可编程逻辑器件、分立的门或晶体管逻辑、分立的硬件组件、或其设计成执行本文所描述功能的任何组合来实现或执行。通用处理器可以是微处理器，但在替换方案中，该处理器可以是任何常规的处理器、控制器、微控制器、或状态机。处理器还可以被实现为计算设备的组合，例如DSP与微处理器的组合、多个微处理器、与DSP核心协作的一个或多个微处理器、或任何其他此类配置。
结合本文中公开的实施例描述的方法或算法的步骤可直接在硬件中、在由处理器执行的软件模块中、或在这两者的组合中体现。软件模块可驻留在RAM存储器、闪存、ROM存储器、EPROM存储器、EEPROM存储器、寄存器、硬盘、可移动盘、CD-ROM、或本领域中所知的任何其他形式的存储介质中。示例性存储介质耦合到处理器以使得该处理器能从/向该存储介质读取和写入信息。在替换方案中，存储介质可以被整合到处理器。处理器和存储介质可驻留 在ASIC中。ASIC可驻留在用户终端中。在替换方案中，处理器和存储介质可作为分立组件驻留在用户终端中。
在一个或多个示例性实施例中，所描述的功能可在硬件、软件、固件或其任何组合中实现。如果在软件中实现为计算机程序产品，则各功能可以作为一条或更多条指令或代码存储在计算机可读介质上或藉其进行传送。计算机可读介质包括计算机存储介质和通信介质两者，其包括促成计算机程序从一地向另一地转移的任何介质。存储介质可以是能被计算机访问的任何可用介质。作为示例而非限定，这样的计算机可读介质可包括RAM、ROM、EEPROM、CD-ROM或其它光盘存储、磁盘存储或其它磁存储设备、或能被用来携带或存储指令或数据结构形式的合意程序代码且能被计算机访问的任何其它介质。任何连接也被正当地称为计算机可读介质。例如，如果软件是使用同轴电缆、光纤电缆、双绞线、数字订户线(DSL)、或诸如红外、无线电、以及微波之类的无线技术从web网站、服务器、或其它远程源传送而来，则该同轴电缆、光纤电缆、双绞线、DSL、或诸如红外、无线电、以及微波之类的无线技术就被包括在介质的定义之中。如本文中所使用的盘(disk)和碟(disc)包括压缩碟(CD)、激光碟、光碟、数字多用碟(DVD)、软盘和蓝光碟，其中盘(disk)往往以磁的方式再现数据，而碟(disc)用激光以光学方式再现数据。上述的组合也应被包括在计算机可读介质的范围内。
提供对本公开的先前描述是为使得本领域任何技术人员皆能够制作或使用本公开。对本公开的各种修改对本领域技术人员来说都将是显而易见的，且本文中所定义的普适原理可被应用到其他变体而不会脱离本公开的精神或范围。由此，本公开并非旨在被限定于本文中所描述的示例和设计，而是应被授予与本文中所公开的原理和新颖性特征相一致的最广范围。

Claims (16)

  1. 一种基于物联网和通信网络的神经元系统，其特征在于，系统包括传感执行器、物联网、通信网络、云端服务器以及神经元装置，其中：
    传感执行器，采集感应对象的信息；
    神经元装置，和传感执行器进行直接的数据通信，且作为通信网络中的动态移动节点，通过通信网络和云端服务器进行信息交互；
    云端服务器，和通信网络中的各个神经元装置进行信息传递，统一存储和处理神经元装置上传的信息。
  2. 根据权利要求1所述的基于物联网和通信网络的神经元系统，其特征在于，传感执行器中包括传感器和多个开关模块。
  3. 根据权利要求1所述的基于物联网和通信网络的神经元系统，其特征在于，神经元装置包括微处理器、接收模块、发射模块、输入接口、输出接口、存储模块，其中输入接口和输出接口是神经元装置和云端服务器之间、以及神经元装置和外部输入设备之间的数据传输的通道，接收模块和发射模块是神经元装置和云端服务器以及传感执行器之间信息传输的通道，存储模块用于存储从云端服务器下载的数据和/或各个传感执行器中采集的数据，微处理器通过系统总线分别连接接收模块、发射模块、输入接口、输出接口和存储模块，对这些模块和接口进行控制。
  4. 根据权利要求3所述的基于物联网和通信网络的神经元系统，其特征在于，传感执行器上还设有无线收发模块，按照移动通信协议将读取到信息发送至对应的神经元装置。
  5. 根据权利要求1所述的基于物联网和通信网络的神经元系统，其特征在于，神经元装置中还设有传感执行器接口，通过传感执行器接口直接连接传感执行器，和传感执行器进行直接的信息交互。
  6. 根据权利要求3所述的基于物联网和通信网络的神经元系统，其特征在于，神经元装置的接收模块接收来自传感执行器的采集信息，并将采集信息存储于存储模块，神经元装置的发射模块向对应的传感执行器发送控制指令，控制指令包括对传感执行器实施阈值大小的调整。
  7. 根据权利要求1所述的基于物联网和通信网络的神经元系统，其特征在于，云端服务器接收来自神经元装置的信息以及来自传感执行器的信息，对这些神经元装置的信息以及传感执行器的信息进行统一的处理，再将处理的结果返回给对应的神经元装置和传感执行器。
  8. 根据权利要求1所述的基于物联网和通信网络的神经元系统，其特征在于，各个传感执行器被配置成具有独立的IP地址，云端服务器和神经元装置通过配置的IP地址访问传感执行器。
  9. 根据权利要求1所述的基于物联网和通信网络的神经元系统，其特征在于，神经元装置中还包括一呼叫自启模块，当神经元装置接收到的对应的传感执行器的信息超出设定的阈值时，启动自动呼叫，自动上传相关信息到云端服务器，供云端服务器基于这些信息做出决策。
  10. 根据权利要求1所述的基于物联网和通信网络的神经元系统，其特征在于，每一神经元装置被配置成具有独立的IP地址，云端服务器由多个具有独立IP地址的虚拟主机组成，其中每一虚拟主机和对应的神经元装置之间通过各自的IP地址访问，不同的神经元装置相互之间通过各自的IP地址访问。
  11. 一种神经元装置，其特征在于，神经元装置包括微处理器、接收模块、发射模块、输入接口、输出接口以及存储模块，其中输入接口和输出接口是神经元装置和云端服务器之间、以及神经元装置和外部输入设备之间的数据传输的通道，接收模块和发射模块是神经元装置和云端服务器以及各个传感执行器 之间信息传输的通道，存储模块用于存储从云端服务器下载的数据和/或各个传感执行器中采集的数据，微处理器通过系统总线分别连接接收模块、发射模块、输入接口、输出接口和存储模块，对这些模块和接口进行控制。
  12. 根据权利要求11所述的神经元装置，其特征在于，传感执行器中包括传感器和多个开关模块。
  13. 根据权利要求11所述的神经元装置，其特征在于，神经元装置的接收模块接收来自传感执行器的采集信息，并将采集信息存储于存储模块，神经元装置的发射模块向对应的传感执行器发送控制指令，控制指令包括对传感执行器实施阈值大小的调整。
  14. 根据权利要求11所述的神经元装置，其特征在于，神经元装置中还包括一呼叫自启模块，当神经元装置接收到的对应的传感执行器的信息超出设定的阈值时，启动自动呼叫，自动上传相关信息到云端服务器，供云端服务器基于这些信息做出决策。
  15. 根据权利要求11所述的神经元装置，其特征在于，神经元装置中还设有传感执行器接口，通过传感执行器接口直接连接传感执行器，和传感执行器进行直接的信息交互。
  16. 根据权利要求11所述的神经元装置，其特征在于，每一神经元装置被配置成具有独立的IP地址，云端服务器通过这一IP地址访问神经元装置，不同的神经元装置相互之间通过IP地址访问。
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110505565A (zh) * 2018-05-16 2019-11-26 杨代春 一种具有定位功能的移动式环境检测装置

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102018116337A1 (de) * 2018-07-05 2020-01-09 Auma Riester Gmbh & Co. Kg Stellantrieb
CN113222486A (zh) * 2020-01-19 2021-08-06 上海鹏航航空科技有限公司 一种基于物联网技术的智能航材管理方法与系统

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103200242A (zh) * 2013-03-20 2013-07-10 成都康赛电子科大信息技术有限责任公司 基于物联网构建跨层面数据分析枢纽的方法
CN203054137U (zh) * 2013-01-30 2013-07-10 孟宪龙 输电线路杆塔集成监测系统
CN103389719A (zh) * 2013-08-02 2013-11-13 临沂市拓普网络股份有限公司 基于云计算的智能家居监控系统及方法
CN204231422U (zh) * 2014-12-02 2015-03-25 马正方 神经元装置

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102006323A (zh) * 2010-11-19 2011-04-06 上海波顿无线传感技术有限公司 环境监测物联网系统
KR20120071722A (ko) * 2010-12-23 2012-07-03 한국전자통신연구원 응용 필드 통신 방법 및 시스템
US10244500B2 (en) * 2011-03-30 2019-03-26 Wei Lu Open wireless architecture (OWA) mobile cloud infrastructure and method
CN202077194U (zh) * 2011-04-22 2011-12-14 郭永平 物联网服务系统
WO2012178055A1 (en) * 2011-06-23 2012-12-27 Interdigital Patent Holdings, Inc. Mobile network virtualization
US10003652B2 (en) * 2012-03-05 2018-06-19 Omnitracs, Llc Managing selective access of a user equipment to internet-based services based on transport type
US9178883B2 (en) * 2012-12-12 2015-11-03 SocialSign.in, Inc. Leveraging online identities to grant access to private networks
CN103268419B (zh) * 2013-05-27 2016-05-11 中国地质大学（武汉） 物联网腰带式监控装置及云端健康管理系统与操作方法
CN103905558A (zh) * 2014-04-11 2014-07-02 中国农业科学院农业信息研究所 基于物联网的奶牛场无线监测系统
CN104023003A (zh) * 2014-04-16 2014-09-03 青岛山科智汇信息科技有限公司 基于Wifi网络和Zigbee网络的传感器控制系统及控制方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN203054137U (zh) * 2013-01-30 2013-07-10 孟宪龙 输电线路杆塔集成监测系统
CN103200242A (zh) * 2013-03-20 2013-07-10 成都康赛电子科大信息技术有限责任公司 基于物联网构建跨层面数据分析枢纽的方法
CN103389719A (zh) * 2013-08-02 2013-11-13 临沂市拓普网络股份有限公司 基于云计算的智能家居监控系统及方法
CN204231422U (zh) * 2014-12-02 2015-03-25 马正方 神经元装置

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110505565A (zh) * 2018-05-16 2019-11-26 杨代春 一种具有定位功能的移动式环境检测装置

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