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IOT System — TieJun Wang (US20240080363A1)

TieJun Wang · Google Patents

Google Patents · Patents

en google-patents intellectual-property patent tiejun-wang

. In this embodiment, the gateway includes different types such as edge AI, security, positioning, video, mid-range communication, CPE, RFID, technology detection, etc., and can realize network interconnection with different high-level protocols, including wired and wireless networks. Industry … IOT System — TieJun Wang (US20240080363A1)

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ABSTRACT

Abstract

Next generation intelligent IOT system is invented and described.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of application Ser. No. 16/605,191, with a PCT (PCT/US2019/042729) filed on Jul. 22, 2019, which claims priority of 62/701,837 filed on Jul. 22, 2018. This application claims priority to provisional application Ser. No. 63/240,965, entitled âA wireless systemâ and filed on Sep. 5, 2021; This application also claims priority to provisional application Ser. 63/325,613 entitled âIOT Networksâ and filed on Mar. 31, 2022; This application also claims priority to provisional application Ser. No. 63/353,816, entailed âAn IOT Systemâ and filed on Jun. 20, 2022; This application also claims priority to Chinese patent application Ser. No. CN202210571576.8 filed on May 24, 2022 with a title of âInternet of Things Data Application and Deep Learning Methodâ. The entire contents of these applications are hereby incorporated by reference.

TECHNICAL FIELD

This disclosure relates to the Internet of Things system.

BACKGROUND TECHNIQUE

At present, the Internet of Things technology has not yet achieved the interconnection of all things. The Internet of Things system in related technologies still has high latency, high power consumption, and network coverage. Problems such as incompleteness, low data load, insecure data, and failure to effectively allocate communication resources in application terminals are obstacles to the development of the Internet of Things technology.

DESCRIPTION OF DRAWINGS

FIG. 1 is the design schematic diagram of the communication network in the Internet of Things;

FIG. 2 is the composition diagram of the Internet of Things;

FIG. 3 is a global relationship diagram of the Internet of Things;

FIG. 4 is a schematic diagram of communication between terminals;

FIG. 5 is a schematic diagram of timing communication between terminals using different frequency channels;

FIG. 6 is the overall architecture diagram of the Internet of Things;

FIG. 7 is a schematic diagram of a communication network;

FIG. 8 is a schematic diagram of communication resource coordination;

FIG. 9 is a schematic diagram of a communication link in the Internet of Things;

FIG. 10 is the overall architecture diagram of the data intelligence fusion platform;

FIG. 11 is a schematic diagram of an edge computing decision loop;

FIG. 12 is a communication network flow and system relationship diagram;

FIG. 13 is an example diagram of an Internet of Things business flow.

DESCRIPTION OF THE INVENTION

The IoT system in present invention is based on the multi-mode heterogeneous network, which is specially created for the smart twin/smart empowerment of various industries. The multi-mode heterogeneous network is an effective improvement of the existing wireless communication and network with a variety of networking methods and dynamic coordination allocation of network resources, to achieve ubiquitous, dynamic, real-time effective communication, to improve the utilization of spectrum and network resources, and increase the coverage capacity and performance of the network. Among them, ubiquitous mainly refers to the widespread and ubiquitous network. It is impossible for the operator network to realize ubiquity based on its profit-making nature, while the multi-mode heterogeneous IoT can be built according to the location and needs, that is, it can be deployed in the required location. Corresponding multi-mode heterogeneous base stations. For example, in the Daxing'an Mountains, the coverage of operator networks in forest areas is almost non-existent, and it is impossible to achieve large-scale deployment of operator networks. However, multi-mode heterogeneous base stations can be deployed to cover target areas. Low-cost requirements, a single base station requires a large coverage area (corresponding to longer communication distances), and the base station group only provides a limited overall bandwidth. Second, dynamic means that the network is dynamically variable. Dynamically adjust any communication parameters to establish a network according to industry requirements or/and physical location. In addition to mainstream communication modes, it also includes advanced networking methods such as Mesh, relay, and SDN. Finally, real-time refers to the delay of communication. Real-time is relative. In different communication scenarios, the real-time delay is not the same. In order to meet the above three situations, the concept of multi-mode heterogeneity is proposed.

As shown in FIG. 1 , B is dynamically determined according to A. Among them, A includes three situations: (1) the needs of the industrial industry (2) the environment in which the terminal, gateway, and base station are located (such as: time, location, task, channel, etc.) (3) the conditions of the terminal, gateway, and base station itself (such as: energy, noise, interference, etc.). B further includes data, communications, networks, and the like. Specifically, in the first case, the demand of the industrial industry means that different industries have different requirements for communication. For example, the environmental protection industry has the needs of the environmental protection industry, the safety supervision industry has the needs of the safety supervision industry, and the water conservancy industry has the needs of the water conservancy industry. Their needs are different, that is, due to the different content to be delivered, the corresponding communication and network are also different. In the second case, the environment where the terminal, gateway, and base station are located refers to the physical environment, that is, the physical environment where the terminal, gateway, and base station are located, which further includes time, place, task, and channel. In the last case, the conditions of the terminal, gateway, and base station include their own power, sensor value, and sensor value conversion rate. A dynamically determines B. Typically, parameters such as communication interval, transmit power, and modulation mode are adjusted. If the terminal's own battery is low, the sensor value is lower than the set threshold, or the sensor value changes slightly, the transmission frequency will be reduced. Further, as shown in FIG. 1 , the data in B indicates how to collect data, what data to collect, how to process data, how to use data, how to transmit data, etc., and communication indicates what communication settings, radio frequency parameters, radio frequency parameters, etc. are used for transmission. Send and receive mode, etc., the network indicates what networking mode, transmission path, etc. are used in the transmission process. Different communication requirements determine different communication strategies, such as high-quality communication requirements, strategies such as data information splitting-multipath concurrency-aggregation, real-time optimization of communication settings and RF parameters, and construction of high-priority networks through core networks and base stations can be adopted, and can be dynamically allocated in actual situations.

The next-generation artificial intelligence IoT system covers multiple levels: from bottom to top, it is the terminal layer, the transmission layer, the support layer, the artificial intelligence business platform layer and the integrated IOC layer for city operations. In addition, the next-generation artificial intelligence IoT system also includes: a security management platform, a unified operation and maintenance management platform, and IT resource services; wherein, the security management platform and the unified operation and maintenance management platform vertically run through all levels, providing full-chain, end-to-end terminal services; IT resource services provide services for the support layer, the artificial intelligence business platform layer and the integrated IOC layer of city operations.

The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

Please refer to FIG. 2 and FIG. 3 together, the terminal layer contains thousands of terminals of different industries and different types of sensor, linkage, multi-mode heterogeneous communication, mobile and/or video. Among them, the sensing terminal can sense the multi-dimensional state of the city in ubiquitous, real-time and dynamic manner, such as water, gas, electricity, soil, sound, fire, etc. The sensed data is multi-mode heterogeneous by dynamically adjusting any communication parameters according to industry requirements or/and physical location. The network uploads to the central platform. Further, the sensing terminal can be various sensors with data collection function or electronic devices with sensors, for example, it can be temperature sensor, smoke sensor, atmospheric pressure sensor, sound wave sensor, image sensor, camera and so on.

In this embodiment, the linkage terminal can realize the linkage that is perceived and executed by the edge side based on a multi-mode heterogeneous network that dynamically adjusts any communication parameters according to industry requirements or/and physical locations, such as linkage alarm, linkage call, linkage control valve/door, linkage SMS/mail notification, etc. Multi-mode heterogeneous communication terminals provide transmission and interconnection dynamically adjusted according to industry requirements or/and physical locations for sensors that do not have the ability to communicate. It supports composite sensing technology, multi-sensor data fusion, and supports unified access of sensing devices from different manufacturers. Sensor technology combined with edge computing technology realizes edge correction and self-correction of perceptual data, and derives an optimized sampling strategy. Typically, the sampling interval and sampling accuracy are dynamically changed according to the rate of change of perceptual data, preset thresholds, and network conditions. and sending frequency, etc., so it can take into account the response time, power consumption of the whole machine, and network bandwidth occupation at the same time. Further, the edge computing method includes: collecting data by several sensing terminals; judging whether the data collected by the sensing terminals is abnormal; when abnormal, the first device connected to the sensing terminal generates first alarm information, and the first alarm The information is sent to all second devices connected to the first device; the second device sends second alarm information to all alarm devices connected to the second device. Wherein, both the first device and the second device may be edge devices or may also be intermediate devices. In this embodiment, the edge device may be used for data packet transmission between the access device and the core/backbone network device, and may be switches, routers, routing switches, gateways, IADs, and various MAN/WAN and other equipment. With the addition of edge computing, the data collected by the sensing terminal does not need to shuttle between the local and central servers, allowing the local device to know which function to perform. This saves operating costs and investment in storage equipment. In addition, edge computing or fog computing or algorithm platform is used to determine the information that needs to be uploaded by communication terminals (such as sensing terminals or gateways or base stations) and its matching communication and network. The information may include but is not limited to the collection of sensing terminals. The data difference value, feature value of the data and/or the feature value of the image and video. It should be understood that the matched communication and network are output by the dynamic deployment of the multi-mode heterogeneous network. For example, when the data difference of the data collected by the sensing terminal exceeds the threshold range, or conforms to a specific image or video feature value, or conforms to a specific sound wave feature, it can be determined that the collected data is abnormal, and then an alarm message and an alarm message are generated. Perform other further operations (at the same time, the multi-mode heterogeneous network dynamically allocates network and communication resources). When the collected data is not abnormal, the sensing terminal can reduce the frequency of collecting data, and transmit it through the matching communication and network, which reduces the waste of communication resources and saves the energy of the communication terminal.

Mobile terminals include handhelds, walkie-talkies, vehicle-mounted devices, positioning terminals, wearable terminals, etc., which perceive, apply, and communicate in a mobile state, through a multi-mode heterogeneous system that dynamically adjusts any communication parameters according to industry requirements or/and physical locations. The network realizes the application of the combination of wide, medium and narrow band, and the integrated communication of voice/video/text/picture/data/file. Video terminals include cameras, thermal imaging, hyperspectral and other diverse video sensor terminals, which are uploaded through a multi-mode heterogeneous network that dynamically adjusts any communication parameters according to industry requirements or/and physical locations.

Further, as shown in FIG. 4 , all terminals in the terminal layer (including: sensing, linkage, multi-mode heterogeneous communication, mobile and/or video terminals) establish communication By establishing direct communication between the two terminals, any terminal can obtain the sensing data of other terminals, and can make decisions and generate execution commands based on the sensing data of multiple terminals, that is, the sensing data can be comprehensively and comprehensively generated to generate decision-making results, so as to make decision-making possible. The results are more reliable, and even in the case of a gateway network failure, the sensing terminal can still obtain data from other terminals based on direct communication between terminals for edge computing and then generate execution commands under specified conditions, that is, network failures will not affect decision-making. Generation of results. Further, the communication mode between the terminals is different from the communication mode between the terminals and the gateway. For example, different communication channels, modulation methods, synchronization bytes, etc. are used between the terminal and the terminal and between the terminal and the gateway; the payload content transmitted between the terminal and the terminal can use different protocols; the communication between the terminals can use different channels (It may also include different modulation methods, data rates, coding methods, etc.), as shown in FIG. 5 , so as to reduce the conflict with the communication between the terminal and the gateway.

CROSS-REFERENCE TO RELATED APPLICATIONS

TECHNICAL FIELD

This disclosure relates to the Internet of Things system.

BACKGROUND TECHNIQUE

DESCRIPTION OF DRAWINGS

FIG. 1 is the design schematic diagram of the communication network in the Internet of Things;

FIG. 2 is the composition diagram of the Internet of Things;

FIG. 3 is a global relationship diagram of the Internet of Things;

FIG. 4 is a schematic diagram of communication between terminals;

FIG. 5 is a schematic diagram of timing communication between terminals using different frequency channels;

FIG. 6 is the overall architecture diagram of the Internet of Things;

FIG. 7 is a schematic diagram of a communication network;

FIG. 8 is a schematic diagram of communication resource coordination;

FIG. 9 is a schematic diagram of a communication link in the Internet of Things;

FIG. 10 is the overall architecture diagram of the data intelligence fusion platform;

FIG. 11 is a schematic diagram of an edge computing decision loop;

FIG. 12 is a communication network flow and system relationship diagram;

FIG. 13 is an example diagram of an Internet of Things business flow.

DESCRIPTION OF THE INVENTION

The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

Please refer to FIG. 6 and FIG. 3 together, the communication layer/transport layer is a multi-mode heterogeneous intelligent Internet of Things composed of two major parts: base station and gateway, and any communication parameters are dynamically adjusted according to industry requirements or/and physical locations to establish The network, in addition to the mainstream communication modes, also includes advanced networking methods such as Mesh, relay, and SDN, providing network support for fixed-mobile convergence, wide-medium-narrow combination, and voice/video/text/picture/data/file convergence communications for the terminal layer. The communication layer/transport layer can be understood as the root of the tree, which is the bridge connecting the tentacles and the trunk of the big tree. The transmission layer uploads the sensing, control, status and other information of the tentacles to the support layer (the trunk of the tree) by wireless/wired.

Further, the base station covers various communication networks such as satellite, private network, WLAN, bridge, public network, multi-mode heterogeneous network, etc., and dynamically adjusts any communication parameters to establish a network according to industry requirements or/and physical locations. For example, data splitting and aggregation that supports multi-path transmission. As shown in FIG. 7 , the terminal splits the sent data packet into multiple data sub-packets, different data sub-packets are transmitted through different communication methods and different paths, and are spliced into a complete data packet after aggregation at the receiving end. In the figure, terminal 1 has a multi-mode communication mode, and can connect to three base stations of different standards: base station 1 , base station 2 and base station 3 at the same time. When transmitting data and through three base stations at the same time, data aggregation and splicing are performed on the core network/server side. Different strategies are used according to the needs of multi-path transmission. For example, when the blind area device cannot be directly connected to the base station, a mesh network can be established with other devices, and uplink communication can be realized with the help of devices that can be connected to the base station: as shown in FIG. 7 , terminal 6 and terminal 7 pass between A mesh network is established, and terminals

5 and 8 are connected to the base station. Terminal 5 , Terminal 2 and Terminal 8 undertake routing functions. The device can switch between star network and mesh network; when working in mesh network mode, the terminal can be used as a routing node or a common node. The communication network supports point-to-point intercommunication between devices and reduces the bandwidth occupation of the base station. The core network and base station can collect link information of base stations, routing nodes, and terminals, including: communication standard, communication path, signal-to-noise ratio, packet loss rate, delay, channel occupancy rate, etc. Better networking and communication solutions, adaptively adjust the connection mode (directly connected base station, mesh network, point-to-point) and transmission path (single path) of equipment as needed (data transmission rate, response time, reliability, connection distance, etc.), multipath), communication parameters (modulation mode, rate, spectrum occupancy, receiving bandwidth). For example, as shown in FIG. 8 , it provides a method to achieve network coordination only by adjusting power and rate. The higher the power, the longer the transmission distance, but the larger the signal coverage during the transmission process, the more likely it will affect the communication of other nearby devices. In the figure, there are many devices connected to base station 1 , which are relatively busy, while the devices connected to base station 2 are relatively idle. In order to reduce the busyness of base station 1 , terminal 2 and terminal 4 use high-power and high-speed transmission, and the transmission process may affect base station 2 , because base station 2 is relatively idle and can accept this effect. The terminal 3 and the terminal 5 transmit through the base station 2 with low power and low rate as much as possible, and the influence on the base station 1 is small because the power is small. Terminal 1 can only transmit with high power and low rate because it is far away, while terminal 6 can transmit with low power and high rate because it is close enough to base station 1 .

In this embodiment, the gateway includes different types such as edge AI, security, positioning, video, mid-range communication, CPE, RFID, technology detection, etc., and can realize network interconnection with different high-level protocols, including wired and wireless networks. Industry requirements or/and physical location dynamically adjust any communication parameters. The gateway supports the connection of various terminals in various connection modes, including LPWA, Ethernet, Wifi, and other wired and wireless connections (such as Bluetooth, Zigbee, and private wireless communication, etc.) extended through the gateway motherboard. Local terminals in different connection modes have independent identification numbers, and are managed and communicated in the same way as normal terminals. The gateway also has the function of communication network service, which can maintain normal communication in the case of disconnection, and can automatically synchronize status and data with the server after networking. The gateway has an edge computing framework, which can configure edge computing functions arbitrarily, realize data cleaning, aggregation, calculation and decision-making locally, and can directly issue decision-making instructions locally to the designated terminal at the terminal layer. Further, the gateway supports a display screen, which can directly display the system status and data reports generated by edge computing, and also provides user interaction functions such as camera and audio to realize edge multimedia applications. Further, in the embodiment of the present invention, the base station/gateway may have its own distributed edge core network (or communication server), and can automatically switch to the edge core network when the connection with the server core network is interrupted; The base station/gateway can be networked by wireless or wired, and one base station/gateway is used as the core network. The edge core network provides layered and regional communication in the case of disconnection and weak network, and provides the necessary support for data exchange for sub-domain edge computing.

The support layer is the core of the next-generation artificial intelligence IoT system, which can be understood as the trunk of the big tree. All data and services required by the upper-level business are provided by the support layer. Various data such as sensor and control at the root of the tree will enter the crown and branches through the support layer. In the present invention, the support layer mainly includes a multi-mode heterogeneous IoT sensor platform, an intelligent data fusion platform, a digital twin platform, an artificial intelligence industry algorithm platform, a converged communication platform, and a streaming media platform. The above platforms will be described in detail below with reference to the accompanying drawings.

Further, the multi-mode heterogeneous IoT sensor platform is used to aggregate the data of the terminal layer and the transmission layer, support the device management of the terminal layer and the transmission layer, and provide dynamic adjustment of any communication parameters according to industry requirements or/and physical locations. multi-mode heterogeneous network services and edge computing services. Among them, multi-mode heterogeneous network services not only provide separate access and management services for different network communications such as existing satellite links, cellular network links, RFID network management, LTE core network, WLAN network management, and LoRa core network; The wireless access service of the multi-mode heterogeneous core network supports the converged access and unified management of the multi-mode heterogeneous wireless network. Multi-mode heterogeneous network services provide network services that dynamically adjust any communication parameters according to industry requirements or/and physical locations, such as adjustable source coding, channel coding, modulation model, signal unit time slot, transmit power and other physical communication parameters; also The wireless link access and management technology with flexible scheduling and expansion can perform functions such as remote control, upgrade, parameter reading/modification, and management of equipment, support link self-healing, and provide high utilization, strong stability, and easy recovery. Professional wireless network hosting services. For example, please refer to FIG. 9 , which is a schematic diagram of a multi-mode heterogeneous communication link in the next-generation IoT. As shown in the figure, the data is first sampled, and the sampling interval can be set according to the requirements (for example, it can be sampled once in 1 minute, or once in 1 second). Then perform A/D conversion on the sampled data, and convert the analog data into digital data. The precision of the A/D conversion can also be set according to needs: it can be 8 bits, 12 bits, 16 bits, 24 bits, etc. The digital data is then transmitted through the RF (radio frequency circuit) after the source code is used for source coding, the channel code is used for channel coding, and the digital modulator is used for digital modulation. Among them, the source coding technology itself is very mature, mainly reflected in a set of standard protocols to realize its functions, these protocols include MPEG-1, MPEG-2, MPEG-4 and H.263, H.264, H.265, etc., they are mainly formulated and completed by the two major international standardization organizations ITU-T and MPEG, and the most used protocols are MPEG-4, H.264 and H.265. The types of channel coding mainly include: linear block codes, convolutional codes, concatenated codes, Turbo codes and LDPC codes. Digital modulation methods include: FSK (Frequency Shift Keying), QAM (Quadrature Amplitude Modulation), BPSK (Binary Phase Shift Keying) and so on. The above coding and modulation methods are all in the prior art, and will not be described in detail here. Multi-mode heterogeneous network services provide network services that dynamically adjust any communication parameters according to industry requirements or/and physical locations, such as adjustable source coding, channel coding, modulation model, signal time slot, transmit power and other physical communication parameters. For example, the transmit RF signal can be adjusted by PA (determines the transmit power) and fn (determines the transmit frequency). Exemplarily, the adjustment includes allocating different transmission bandwidths to different services. When the data transmission requirements of some terminals change, the multi-mode heterogeneous network adjusts the distribution of network resources to adapt to the changes in requirements. Illustratively, the adjustment includes priority adjustment of signal transmission. For example, the signals of some terminals are preferentially transmitted. For example, data of some base stations or gateways are preferentially transmitted. For example, some service signals of the terminal are preferentially transmitted. The multi-mode heterogeneous network adjusts network parameters in a timely manner based on on-site sensor and service requirements, which can ensure the implementation of important upper-layer services and improve the availability of the multi-mode heterogeneous network. Further, the adjustment includes dividing different data into different data streams and transmitting them through different communication paths. For example, part of the data is transmitted to the upper-layer service through the 4G network, part of the data is transmitted to the edge computing module through the LoRa protocol, and part of the data is transmitted through the customized multi-mode heterogeneous communication network protocol. The consumption of network resources is reduced as much as possible, and the communication and network can be dynamically adjusted in real time according to changing business requirements. In addition, edge computing services are aimed at accessing multi-mode heterogeneous networks, providing dynamic and adaptive network allocation with edge computing capabilities of converged networks, and providing different delays that adapt to the needs according to different industry needs and different physical environment needs. Time, different bandwidth, different time slot network, dynamic, automatic and reasonable allocation of communication and network resources. For example, the environmental protection industry requires data sampling on time and reporting low latency, but thousands of sites report data at the same time, and the concurrency of sending data at the same time is high, but the time interval between two adjacent reports may be long, which requires our Edge computing services provide support, dynamically and reasonably allocate network resources, such as deploying other non-time-sensitive devices to avoid, such as temporarily deploying multiple communication channels, such as site sampling on time but uploading at the wrong time.

Further, as shown in FIG. 10 , the data intelligent fusion platform is used to provide cross-department and cross-industry data collection and aggregation, data cleaning, and data fusion including structured, semi-structured, and unstructured multi-source heterogeneous data, resource catalog and data sharing exchange services. Among them, data aggregation can be connected to the sensing data uploaded by the multi-mode heterogeneous IoT sensing platform, other third-party platforms or data shared by the upper and lower platforms, and unified aggregation to form a data lake. The data lake also aggregates business data/control data/algorithm warning data/data required by different industries/physical location data that are generated or need to be interacted with other sections (business section, other support sections). Data cleaning, fusion, and resource catalogs mainly manage and classify the aggregated data, form various subject libraries, thematic libraries, etc., to facilitate the extraction of data from different businesses, and serve as a digital twin center, artificial intelligence industry algorithm center, and converged communication center. Support platforms such as streaming media platforms and artificial intelligence business platforms provide the data they need. Data sharing and exchange, providing data sharing and exchange with third-party platforms and upper and lower platforms. In this embodiment, the data lake warehouse is composed of a database cluster, a data warehouse and a file system. The database cluster mainly stores business data to ensure daily business flow, and the data warehouse stores the collected raw data and the data ETL (extraction) based on the data; conversion, loading), data governance, and data mining result data, the file system mainly stores unstructured data files including database backup files; data services are based on a complete set of data systems implemented on top of the data lake warehouse, including application systems for Any operation of the data lake warehouse, and provide service support to the business platform. In general, the data intelligent fusion platform can realize multi-industry access, including air, meteorology, soil, transportation, construction, water quality, fire insurance and other multi-industry data including environmental protection, fire protection, municipal administration, etc. Fusion to break through industry barriers; at the same time, the data intelligent fusion platform also provides multi-source heterogeneous data access, including data sources such as databases, file systems, message queues, and structured, semi-structured and unstructured data sources. Data sources can be Unlimited expansion, data capabilities can be replicated indefinitely, providing huge data resources for various business scenarios; its data specifications are unified, providing a unified data dictionary and data specifications, reducing development costs and improving data quality. It should be understood that, precisely because of the network communication data transmission between the multi-mode heterogeneous IoT network and the data intelligent fusion platform, the continuous access and downlink of data in different formats in the data intelligent fusion platform is dynamically realized. operation, so that the data sources in the data lake of the data intelligence fusion platform can be expanded infinitely, and the data capabilities can be replicated infinitely, providing huge data resources for various business scenarios. In this embodiment, the data sources in the data lake of the data intelligent fusion platform include: data of the sensing terminal, communication big data, external data, and data generated by the algorithm middle station, and the like.

Further, the functions of the streaming media platform mainly include two parts: the first is to provide video recording, PTZ control, streaming media, SDK, ONVIF, national standard agreement and other services support the artificial intelligence business platform. In addition, the interaction between the streaming media platform and the data intelligent fusion platform includes that the streaming media platform receives information such as video, pictures and streaming media access from the data intelligent fusion platform, and the streaming media platform feeds back control information, screenshot information, etc. to the data intelligent fusion platform And stored in the corresponding theme/topic library. The streaming media platform supports sending control commands to terminals in corresponding industries and physical locations through a multi-mode heterogeneous network to realize terminal control. In this embodiment, the access layer of the streaming media platform is responsible for the realization of the connection between devices and subordinate domains, as well as the acquisition of original media data, and the information is abstracted and reported uniformly. The core layer is responsible for the unified management and control of devices and services, shielding the differences between different access methods, and providing core APIs (such as streaming, recording, PTZ control, and device control). Cascading layer services are connected to upper-level domains. The application service layer handles business logic and permission control. The streaming media platform supports multi-protocol access (GB/T28181, ONVIF, various SDKs, network video streaming, live streaming); supports multi-protocol playback (RTSP, RTMP, FLV, HLS). It can adapt to various network environments (such as multi-mode heterogeneous networks), dynamically configure policies to control when the flow is disconnected and when to start, and supports screenshot plans and video plans; it can be connected to algorithms to deeply mine data, and at the same time, the Streaming media platform supports national standard platform cascade, supports GA/T1400 view library.

Further, the converged communication middle station provides a multi-mode heterogeneous network that dynamically adjusts any communication parameters according to industry requirements or/and physical locations to achieve text, voice, pictures, videos, locations, attachments and other different types of data or files. Converged Communication Services. Converged communication services include the uplink and downlink of data, the uplink includes the upload of different types of data and files, and the downlink includes the download of different types of data and files to terminals in corresponding industries and/or physical locations. Its main services include: (1) Provide integrated communication services of different types of data or files such as text, voice, pictures, videos, locations, attachments, etc., to support the artificial intelligence business platform. For example, in addition to voice, voice chat also supports the sending and receiving of different types of data and files, while event reporting supports the use of text, and additional information such as voice, video, pictures, location, or attachments. (2) Access to data such as text, voice, pictures, video, location, and files provided by the data intelligent fusion platform. The data of the data intelligent fusion platform comes from the multi-mode heterogeneous network of the terminal and communication layer. It supports to feed back the data generated by the fusion communication to the data intelligent fusion platform and store it in the corresponding theme/topic database. (3) For video-based converged communications, the streaming media platform provides camera control, streaming media services, etc. for the converged communications middle station. Some control information can be downlinked to the terminal corresponding to the industry and the corresponding physical location through the multi-mode heterogeneous network. In general, the converged communication platform can be understood as an interactive system (data types include video, voice, text, pictures, locations, files, etc.), data is bidirectional, and data can be circulated between the platform and the terminal and/or, between terminals and terminals, and between multiple terminals and platforms (similar groups). The streaming media platform mainly focuses on data upstream collection and downstream control of cameras. The integrated communication platform of the present invention realizes comprehensive sensor, information fusion, instant communication and intelligent control through the interconnection of âpeople to peopleâ, âthings to peopleâ and âthings to thingsâ (based on a multi-mode heterogeneous network).

Further, the artificial intelligence industry algorithm middle platform is used to provide management services such as algorithm deployment, algorithm configuration, algorithm training, and algorithm viewing/importing/deleting/upgrading for artificial intelligence algorithms. The input parameters or video sources of the artificial intelligence industry algorithm platform come from the multi-mode heterogeneous network aggregation and uploading dynamically allocated according to industry requirements or/and physical locations, including various sensors, alarms, video data, etc. At the same time, the linkage control, linkage call, linkage alarm, linkage SMS/email notification and other data generated by the artificial intelligence industry algorithm center are dynamically downloaded to the corresponding terminal through the multi-mode heterogeneous network according to industry requirements or/and physical location. In this embodiment, the artificial intelligence industry algorithm center supports unified management and operation and maintenance of computing power and service resources, and can implement fog computing, edge computing and artificial intelligence according to industry applications, computing power, network and communication conditions. The computing power of the platform in the industry algorithm and the dynamic allocation of algorithm tasks. The containerized cluster mode is adopted to support the flexible scheduling of computing resources. According to the actual configuration scenario and the dynamic allocation of multi-mode heterogeneous communication networks, it can automatically expand and shrink, and improve the utilization of computing resources. Secondly, the artificial intelligence industry algorithm middle station can access the input parameters and video data required by different algorithms uploaded by the data intelligent fusion platform, and can output alarms/eigenvalues, etc. to the artificial intelligence business platform, so as to realize artificial intelligence-based and algorithmic warning view. In addition, the alarms/feature values generated by the AI industry algorithm center will also be fed back to the data intelligence fusion platform and stored in the corresponding theme/topic library. For example, for video-based algorithms, the AI industry algorithm center can retrieve the required videos/pictures through the streaming media center. For example, for prediction algorithms such as fire spread prediction and gas diffusion prediction, it is necessary to display the predicted diffusion range after a period of time (for example, one hour) in a three-dimensional form. In such cases, the artificial intelligence industry algorithm center will provide data such as eigenvalues and prediction simulations to the digital twin center described below.

The method for implementing mirroring in the artificial intelligence industry algorithm of the present invention is described in detail below:

The self-iteration steps of implementing the mirroring algorithm in the algorithm center include: First, upload the algorithm image to the algorithm center; Then, based on the algorithm image, install the corresponding algorithm instance in the artificial intelligence industry algorithm platform; Running an algorithm mirroring service based on the algorithm instance; Collect negative samples of running algorithm mirror service production data; Then, retrain the algorithm image to improve the model accuracy and generalization ability, and produce a new algorithm image. The algorithm center provides external processing capabilities through APIs or push messages.

In general, the artificial intelligence industry algorithm platform of the embodiment of the present invention takes the computer vision algorithm as the core, the algorithm model covers the mainstream industry, supports the rapid deployment, management, and integration of the massive mature algorithms in the demonstration platform, and is suitable for any algorithm. In scenarios where the model has automation requirements, through a unified portal, integrated computing resources are provided, services are shared, and development costs are reduced. It is suitable for scenarios that require centralized management and maintenance of algorithm models, provides standardized API interfaces and documents, and develops standardized AI capabilities. The artificial intelligence industry algorithm middle-end can be standardized and platform-based management, the integration is simple, and the development process is simplified; it provides an operation and monitoring mechanism for the algorithm model to ensure the stability of the service provided by the model; provides access to the algorithm data set. Unify channels, standardize and unify data format standards; provide a unified evaluation index system for algorithm models to reflect the generalization ability of algorithm models on the platform; perform data aggregation and analysis on algorithm calculation results; The model can also provide a system for continuous improvement and iterative model quality; it has the whole-process management of algorithm model generation and optimization; it provides a system for operation and maintenance management and performance evaluation of algorithm models, and dynamically allocates and manages computing resources; As an independent middle-end product, it provides external service capabilities, and conducts statistical analysis on the resources, data and operation of the provided services and instances.

Further, the digital twin platform is based on the dynamic sensor data of different industries and different locations uploaded by the multi-mode heterogeneous network, and provides the city 3D twin service for the artificial intelligence business platform. The CIM, AR, VR, BIM, GIS, etc. required by the artificial intelligence business platform all need the support of the digital twin platform. In this embodiment, the data generated by some modifications and definitions of the map, layers, key points, etc. made by the digital twin platform will also be fed back to the data intelligent fusion platform and stored in the corresponding theme/topic library. The digital twin mid-stage of the embodiment of the present invention provides synchronization and operation mapping capabilities between various types of entity devices and twin models; provides a mid-stage architecture and implementation method for the general capabilities of digital twins; Dimensional performance-balanced technical architecture; provides the capability of unified management of AR engine, VR engine, and CIM visualization engine, and the ability to provide services through integrated publishing. Specifically, the digital twin middle-end provided in an embodiment of the present invention is a middle-end that provides a unified digital twin service, and provides CIM model engine support and interaction layer docking for the business system.

Further, the AI business platform layer displays, analyzes, predicts, forecasts, and rehearses data from different industries and different physical locations uploaded by the multi-mode heterogeneous network, providing AI-based unified module component management and the wisdom of different industries. Application, receive the data of each support platform, and feed back the operation information of the business side to each support platform. At the same time, some operational data can be dynamically adjusted according to industry requirements or/and physical location, and sent to the terminal through the communication layer to achieve linkage. Specifically, the artificial intelligence business platform layer provided by an embodiment of the present invention includes: an organization management module, a user management module, a role management module, a rights management module, a log management module, a special project module, and a general component library module. The artificial intelligence service platform layer provided by an embodiment of the present invention can flexibly and quickly configure cross-application, cross-system, and cross-role projects through unified authentication, and establish a unified authentication center and authentication gateway from a business perspective. Through the decentralized authentication method, the bottleneck of authority reuse and unification of various technology middle-end and business platforms is broken. In a nutshell, through the unified authentication of the present invention, cross-application, cross-system, and cross-role projects can be flexibly and quickly configured; by decoupling and stripping business modules, each independent module supports asynchronous development, reducing the overall situation in the development process. problems and improve development efficiency; through a unified public technology module, a service is formed by separation, and when the service is needed again, it is completed through an interface call, which avoids the lengthening of the research and development cycle, and saves development time and resource sampling business processes. Modules are encapsulated into public business process modules, which can be directly reused when encountering the same business process scenarios, reducing trial and error costs; solving the pain points of many project R&D links, inability to integrate uniformly, and lack of uniform development standards and operation and maintenance mechanisms; implementation technology The integrated application of, business and data can reduce research and development costs, realize rapid business response, data accumulation, and efficiency improvement.

Further, the integrated IOC layer of urban operation is used to synthesize the data of various industries to realize the overall situation overview of the city, monitoring and early warning, command and dispatch, event handling, operation decision-making, etc. The city operation integrates various aggregation and downlink data bridges/supports at the IOC layer, relying on a multi-mode heterogeneous network established by dynamically adjusting any communication parameters according to industry requirements or/and physical locations. The comprehensive IOC layer for urban operation provided by the present invention is suitable for the comprehensive operation scenarios of cities at the district and county level, prefecture level, provincial level and ministerial level, and is suitable for hierarchical deployment of departments at all levels, forming a cascade of urban big data dynamic monitoring and early warning, urban Plan management, hierarchical event handling, big data operation decision analysis and leadership hierarchical management decision-making. In addition, the integrated IOC layer for urban operations is suitable for accessing and converging data and processes of various government agencies, enterprises and institutions, and for unified data cleaning, data normalization, early warning rule definition, and monitoring and early warning. It is suitable for various secure network environments, providing secure data access management and comprehensive urban operation functions. It is suitable for use by departments and personnel of government commissioned units, enterprises and institutions at all levels. It is suitable for centralized deployment and distributed deployment environment, suitable for different user groups and various complex flow processes. Specifically, the urban integrated operation IOC platform provided by an embodiment of the present invention is divided into five components, namely: dynamic monitoring and early warning, plan management, inter-departmental event handling, operation decision analysis, and leadership cockpit. The city operation integrated IOC layer provided by an embodiment of the present invention solves the problem of data island barriers in the existing city integrated operation system products, and integrates the information system data of various industries in the smart city, unifies data standards, and unifies data cleaning. and unified data exchange; the invention solves the problem that the urban comprehensive operation system cannot open up the event handling process between various departments; establishes a closed loop of the urban comprehensive operation function, making the urban comprehensive operation more efficient. Further, as shown in FIG. 6 , the functions of the dynamic monitoring and early warning module and the visual command and dispatch included in the integrated urban operation IOC are as follows: Data, artificial intelligence industry algorithm middle-end, and visualization function of digital twin; visual command and dispatch module is used to use converged communication middle-end, and then associate multi-mode heterogeneous core network, use streaming media platform to view camera terminal, use digital twin The platform displays personnel, resources, terminals, etc.

In the present inven

CLAIMS

Claims ( 1 )

1 . An Internet of Thing (IOT) node comprising:

memory, firmware, and communication interface for communicating with other nodes; wherein said communication with the other nodes is adjusted with one or more of the following: communication interval, transmit power, and modulation mode in connection with modification of carrier frequency, source coding, and/or channel coding; and wherein sampling interval and sampling accuracy for the sensor data are adjusted in connection one or more of: change of the sensor data, preset threshold, network condition, relationship among sensor data from other nodes

US17/902,825

2018-09-14

2022-09-03

IOT System

Abandoned

US20240080363A1

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US20240080363A1

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2022-09-03

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US18/688,784

US20250071040A1

( en )

2018-09-14

2022-09-03

Internet of things system

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2018-09-14

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Internet of things system

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