CN109862011B - Real-time monitoring system for environment of Internet of things based on fog calculation - Google Patents
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Abstract
The invention discloses a fog-calculation-based real-time monitoring system for the environment of the Internet of things, and particularly relates to the technical field of enterprise production safety monitoring; the environmental information acquisition module acquires environmental data of the monitoring center and then transmits the data to the fog computing node through a wireless or wired communication protocol; the fog computing node preprocesses the received data, including data analysis, compression, filtering and encryption, and then sends the data to the background system. And the cloud server of the background system decodes, analyzes and stores the received data packet, and sends early warning information to the terminal equipment when the environmental parameter exceeds a preset threshold value. The system comprehensively applies the Internet of things technology based on fog calculation, realizes the omnibearing real-time dynamic networking monitoring of the enterprise production environment, enhances the system intelligence, and meets the requirements of the system in various aspects such as real-time monitoring, data optimization, high reliability, low delay response and the like.
Description
Technical Field
The invention relates to the technical field of enterprise production safety monitoring, in particular to a fog-calculation-based real-time monitoring system for the environment of the Internet of things.
Background
The development of the internet of things provides an effective monitoring means for environment monitoring, the development of cloud computing greatly reduces the computing and storage cost through cloud processing, and gateways generally serve as hubs between a sensor layer and cloud servers, but the fixed nature of the gateways determines that the gateways have resource-limited processing capacity, power consumption and communication bandwidth. Meanwhile, compared with sensors in other network fields, the enterprise environment sensor monitoring nodes, particularly the implanted nodes, require lower processing power, storage, transmission speed and energy supply. However, as the amount of data becomes larger and larger, the data transmission poses a considerable challenge, even a large network delay sometimes occurs, and the real-time requirement is considered to consume a considerable amount of energy in the transmission process, which also poses an obstacle to the real-time monitoring of the environment. It should be noted that such intelligent ubiquitous environmental monitoring leads to new requirements such as high reliability, interoperability, energy efficiency, low latency response and safety, etc. The application of fog calculation greatly improves the situation, especially the requirements of real-time monitoring, data optimization, high reliability and low delay response. Undoubtedly, the real-time monitoring system for the environment of the Internet of things based on the fog calculation has great application value.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides the real-time monitoring system for the environment of the Internet of things based on fog calculation.
The purpose of the invention is realized by the following technical scheme.
The real-time monitoring system for the environment of the Internet of things based on fog computing is characterized by comprising an environment information acquisition module, a fog layer and a background system; the environment information acquisition module comprises a plurality of acquisition units, and each acquisition unit comprises at least more than one sensor and at least more than one monitoring camera; the fog layer comprises a plurality of fog computing nodes, and each fog computing node is provided with a hardware module and a software module; the hardware module performs protocol conversion and format conversion of the sensing data; the software module provides local services, and the local services comprise data preprocessing and data storage; the background system comprises a cloud server and terminal equipment; the cloud server decodes, analyzes and stores the received data packet, and sends early warning information to the terminal equipment when the environmental parameter exceeds a preset threshold value; a sensor and a monitoring camera of the acquisition unit acquire environmental parameters and images of a monitored area, and then transmit data to a fog computing node through a wireless or wired communication protocol; the fog computing node receives data from different sensors, preprocesses the data and sends the preprocessed data to the background system;
the software module comprises an operating system, a local database, namely a local storage, an embedded Web server, an IP address tunnel interface, a local data processing module, a database management module, a local notification module and a self-adaptive module; the self-adaptive module comprises a sensing part and a control part, and is used for adjusting the transmission rate of data from the fog layer to the cloud server, namely the priority;
the self-adaptive module consists of a sensing part and a control part and is used for adjusting the transmission rate of data from the fog layer to the cloud server; the sensing part is used for acquiring sensing data from a local storage and judging whether the data is within a preset threshold value; the control part is used for scheduling the priority of the data transmission task, and if the acquired sensing data is within a preset threshold value, the sensing data is continuously in a sensing state; if the acquired sensing data is lower than or exceeds a preset threshold, the control part adjusts the transmission task of the sensing data to the highest priority.
A sensor and a monitoring camera of the acquisition unit acquire environmental parameters and images of a monitored area, and then transmit data to a fog computing node through a wireless or wired communication protocol; the fog computing node receives data from different sensors, executes protocol conversion, preprocesses the data, and then sends the preprocessed data to the background system.
Further, the communication protocol is Bluetooth (Bluetooth), Wi-Fi (Wireless Fidelity), ZigBee or 6LoWPAN (IPv6 over IEEE 802.15.4) for data transmission; the acquisition unit adopts a restricted Application Protocol (CoAP) to carry out data communication; the environmental parameters include temperature, humidity, carbon monoxide concentration, carbon dioxide concentration and atmospheric pressure; the preprocessing includes data analysis, compression, filtering, and encryption.
Further, the fog computing node supports wireless protocols of Bluetooth, Wi-Fi, ZigBee or 6LoWPAN (IPv6 over IEEE 802.15.4), is responsible for inter-device communication, forms a coordinated gateway network, and serves as a storage library, namely a local database, for temporarily storing data of the sensor, analyzing, compressing, filtering and encrypting the data, and provides the capability of preprocessing the sensor data.
Further, the fog computing node comprises a hardware module and a software module; the hardware module includes a GPRS module, a DSP (Digital Signal Processing) module, a GSM (Global System for Mobile communications) module, a GPS module, a RF (Radio Frequency) module, a POWER supply module, a RAM (Random Access Memory) module, and a CPU.
Furthermore, the fog computing node provides local data processing for real-time notification, and according to the environment monitoring requirement, the fog computing node needs to continuously process a large amount of sensing data in a short time and perform effective information transmission.
Further, the fog computing node has computing power, and meets the requirements of sensor data preprocessing on intermediate computing layers (namely computing, network and storage).
Furthermore, the fog computing node continuously processes sensing data and transmits information according to the environment monitoring requirement so as to provide real-time notification; the fog computing node can be loaded with an Advanced RISC Machine (ARM) mainboard of a Linux system, can be increased randomly according to the increase of the monitoring area range, and has good expansibility.
Further, the fog computing node sends information through a local network server or a Global System for Mobile communications (GSM), so that the user can receive a notification in time even when the cloud server is unavailable.
Further, the terminal device is a mobile phone, a tablet Computer or a PC (Personal Computer).
Further, the fog computing node implements data preprocessing so that the system can effectively reduce the transmission amount of data, thereby reducing the energy required for data transmission.
Furthermore, the data preprocessing realized by the fog computing node can improve the sensitivity of the system, the response can be faster and more reliable when the emergency situation is handled, the delay of processing key parameters can be minimized, and the real-time response can be realized.
Further, the fog compute node implements data pre-processing (i.e., data analysis, compression, filtering, and encryption), all of which require local temporary storage. Because the speed of data transmission is limited by network bandwidth from the fog computing node to the cloud end, the computing processing is limited by the processing capacity of the fog computing node, and under the condition that the data processing and data transmission are limited by resources, the local storage serves as a cache to realize continuous data flow, namely when the processing capacity of the fog computing node is limited, the incoming data is stored in the local storage in a compressed or encrypted mode and can be exported to the monitoring center in an Excel text format.
Further, to ensure that the system can successfully recover the data, the fog computing node stores the incoming data in a local storage, and an operating system on the fog computing node processes the local storage and stores the data in a non-volatile memory, where the data may be stored in a compressed or encrypted manner, depending on the type and importance of the data. The data in the repository can be exported to the monitoring center in Excel text format.
Further, the local storage includes a file store and database for storing attributes and indexes of files. In case the data processing and data transmission is resource limited, the local storage acts as a cache to enable a continuous data flow.
The system work flow is as follows:
1) a sensor and a monitoring camera of the acquisition unit acquire environmental parameters and images of a monitoring area, and then transmit data to the fog computing node through a wireless or wired communication protocol (such as Bluetooth (Bluetooth), Wi-Fi (Wireless Fidelity), ZigBee or 6LoWPAN (Wireless personal area network));
2) the method comprises the following steps that a fog computing node receives data from different sensors, executes network protocol conversion, preprocesses the data (namely, analyzes, compresses, filters and encrypts the data), stores the preprocessed data in a local storage (MySQL), and backs up the compressed data to deal with the condition of network connection interruption;
3) the cloud computing node transmits the preprocessed data to a background system, the cloud server decodes, analyzes and stores the received data packet, sends early warning information to the terminal equipment when judging that the environmental parameter exceeds a preset threshold value, and displays the result to monitoring personnel through the terminal equipment;
4) the background system sends a user instruction to the fog computing node through a TCP/IP protocol, the user instruction is forwarded to a sensor and a monitoring camera of the acquisition unit through the gateway server, the sensor and the monitoring camera of the acquisition unit execute the user instruction, and then the acquired new environmental parameters and images are displayed to monitoring personnel after being processed through the processes 1), 2) and 3).
Compared with the prior art, the invention has the advantages that:
the real-time monitoring system for the environment of the Internet of things based on the fog calculation fully utilizes the characteristic of local individuation of the area where the fog calculation node is located, can apply more fog calculation nodes according to the requirement of the monitored area, and has good expansibility. In addition, on one hand, the fog computing node can effectively reduce the data volume by realizing data preprocessing, so that the energy required by data transmission is reduced; on the other hand, the sensitivity of the system can be improved, the reaction can be quicker and more reliable when the emergency situation is dealt with, the delay of processing key parameters can be minimized, and real-time response can be realized. The application of the fog calculation meets the requirements of the internet of things environment in various aspects such as real-time monitoring, data optimization, high reliability, low delay response and the like, realizes the omnibearing real-time dynamic networking monitoring on the production environment of an enterprise, and has great application value.
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FIG. 1 is a system architecture diagram of the present invention;
FIG. 2 is a schematic diagram of a fog computing node structure of the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.
The invention discloses a fog-computing-based real-time monitoring system for the environment of the Internet of things, which mainly comprises an environmental information acquisition module, a fog layer and a background system, wherein the system architecture of the system is shown in figure 1;
the environment information acquisition module comprises n acquisition units, each acquisition unit comprises n sensors and at least one monitoring camera so as to acquire environment parameters and images of a monitoring area, and then data are transmitted to the fog computing node through a wireless or wired communication protocol (such as Bluetooth, Wi-Fi, ZigBee or 6 LoWPAN); the acquired environmental parameters comprise temperature, humidity, carbon monoxide concentration, carbon dioxide concentration, atmospheric pressure and other environmental information required by enterprise production monitoring, and corresponding digital sensors are adopted to acquire environmental data.
The fog layer comprises a plurality of fog computing nodes, the fog computing nodes are provided with hardware modules and software modules, receive data from different sensors, execute protocol conversion, preprocess the data such as data analysis, compression, filtering and encryption, and then send the preprocessed data to the background system.
The structure diagram of the fog computing nodes is shown in fig. 2, and each fog computing node comprises a hardware module and a software module; the hardware module comprises a GPRS (General Packet Radio Service) module, a DSP (Digital Signal Processing) module, a GSM (Global System for Mobile communications) module, a GPS module, a RF (Radio Frequency) module, a POWER module, a RAM (Random Access Memory) module, and a CPU (Central Processing Unit/Processor); the software module comprises an operating system (Linux), a local database, namely local storage (MySQL), an embedded Web server, an IP address tunnel interface, a local data processing module, a database management module, a local notification module and an adaptive module. The hardware module performs protocol conversion and format conversion of the sensing data; the software modules provide local services such as data pre-processing and data storage.
The background system comprises a cloud server and terminal equipment, the cloud server comprises a plurality of DB (Database) servers, the cloud server decodes, analyzes and stores received data packets, and sends early warning information to the terminal equipment when judging that environmental parameters exceed a preset threshold value; the terminal device is a mobile phone, a tablet Computer, a notebook or a PC (Personal Computer) and the like, and is used for a web browser to check the condition of the monitoring area and receive the warning information notification.
In a specific implementation, a CoAP (restricted Application Protocol) client runs on each sensor, and performs data communication by using the CoAP Protocol, where a CoAP message format is shown in table 1.
TABLE 1 CoAP message Format
The acquisition unit transmits data to the fog computing node through a wireless or wired communication protocol (such as Bluetooth (Bluetooth), Wi-Fi (Wireless Fidelity), ZigBee or 6LoWPAN (Wireless personal area network)); the adaptation layer in the fog computing node promotes protocol conversion and format conversion of the message, the uploaded message is packaged in a JSON/XML format, the UDP server detects the message and judges whether the message is a standard JSON/XML format message, and if not, the message is retransmitted.
The UDP server running on the fog computing node receives the transmitted data, the UDP protocol does not need to establish connection, only needs to know the IP address and the port of the other side, can utilize Socket to send and receive the data, and the same data is forwarded to the cloud server for backup.
The notification is a necessary function of the fog computing node, and the fog computing node can improve the reliability of the System to the maximum extent even when the cloud server is unavailable through a local network server or a Global System for Mobile communications (GSM), so as to ensure that a user can receive an important notification in time. When the fog computing node acts as a local web-server, it will send a response request in XML or JSON format, achieving a minimum use of resources by effectively utilizing the fog computing node resources. If the new notice exists, the fog computing node sends a communication message with an XML format; the XML format has two parts: title and content. The header section contains the code and descriptive status of the current request. When the mobile application receives a response, it first checks the code in the status header and if the status returns '0', it will pass the status header description, i.e. it is an illegal request or error; if the state returns to '1', it will continue to check the content part; if the status returns to '2', meaning no new notification, it will continue to wait for new message notifications. The XML state description is shown in Table 2.
TABLE 2 XML State description
| Code | Description of the invention |
| 0 | Illegal requests or errors |
| 1 | Notification |
| 2 | No new notice |
While analyzing and notifying in real time, the fog computing node applies compression and encryption to the filtered and processed data, sends feedback and notification to the sensors, and stores the data in local storage. The situation of network connection interruption is dealt with by backing up the compressed data in the fog computing node.
The fog compute node implements data pre-processing (i.e., data analysis, compression, filtering, and encryption), all of which require local temporary storage. Since the speed of transferring data from the cloud computing node to the cloud is limited by the network bandwidth and the computing is limited by the processing power of the cloud computing node, the local storage will act as a cache to enable continuous data flow in the case of resource limitations for data processing and data transfer. Further, to ensure that the system can recover the data smoothly, the fog computing node will store the incoming data in local storage. The operating system on the fog computing node handles local storage and stores data in non-volatile memory. Depending on the type and importance, the data may be stored in a compressed or encrypted manner in the local storage. The data in the repository can be exported to the monitoring center in Excel text format.
The local storage includes a file store and database to maintain attributes and indexes for files. In the final phase, the fog computing node checks the availability of Internet, IPv4(Internet Protocol Version 4), IPv6(Internet Protocol Version 6) connections and sends the data to the cloud server. If a connection problem occurs, it marks the unsent data to be transmitted in the future. The local storage will check and synchronize data in the storage cloud server, delete old and duplicate files from storage, and delete their indices from the database. If the information is received 30 minutes ago and it is ensured that the data synchronization with the cloud server has been successfully completed, the fog computing node will clear the information stored locally in the repository. If the connection to the cloud server is not available, it will store the data for as long as possible and start deleting old data; if the memory is not sufficient, new data is accommodated.
And finally, the preprocessed data are transmitted to a cloud end through the fog computing node, then the cloud server collects, analyzes and processes the data, and finally the data are presented to monitoring personnel in different forms, so that the automatic and intelligent management of environmental information is realized, and the monitoring, alarming and early warning capabilities of the production environment of an enterprise are improved.
The system work flow is as follows:
1) the sensors and the monitoring cameras of the acquisition unit acquire environmental parameters and images of a monitored area and then transmit the data to the fog computing node through a wireless or wired communication protocol (such as Bluetooth (Bluetooth), Wi-Fi, ZigBee or 6 LoWPAN).
2) The fog computing node receives data from different sensors, performs network protocol conversion, pre-processes the data (i.e., data analysis, compression, filtering, and encryption), then stores the pre-processed data in a local storage (MySQL), and backs up the compressed data to cope with network connection interruptions.
3) The cloud computing node transmits the preprocessed data to the background system, the cloud server decodes, analyzes and stores the received data packet, and the result is displayed to monitoring personnel through the terminal equipment.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.
Claims (10)
1. The real-time monitoring system for the environment of the Internet of things based on fog computing is characterized by comprising an environment information acquisition module, a fog layer and a background system; the environment information acquisition module comprises a plurality of acquisition units, and each acquisition unit comprises at least more than one sensor and at least more than one monitoring camera; the fog layer comprises a plurality of fog computing nodes, and each fog computing node is provided with a hardware module and a software module; the hardware module performs protocol conversion and format conversion of the sensing data; the software module provides local services, and the local services comprise data preprocessing and data storage; the background system comprises a cloud server and terminal equipment; the cloud server decodes, analyzes and stores the received data packet, and sends early warning information to the terminal equipment when the environmental parameter exceeds a preset threshold value; a sensor and a monitoring camera of the acquisition unit acquire environmental parameters and images of a monitored area, and then transmit data to a fog computing node through a wireless or wired communication protocol; the fog computing node receives data from different sensors, preprocesses the data and sends the preprocessed data to the background system;
the software module comprises an operating system, a local database, namely a local storage, an embedded Web server, an IP address tunnel interface, a local data processing module, a database management module, a local notification module and a self-adaptive module; the self-adaptive module comprises a sensing part and a control part, and is used for adjusting the transmission rate of data from the fog layer to the cloud server, namely the priority;
the self-adaptive module consists of a sensing part and a control part and is used for adjusting the transmission rate of data from the fog layer to the cloud server; the sensing part is used for acquiring sensing data from a local storage and judging whether the data is within a preset threshold value; the control part is used for scheduling the priority of the data transmission task, and if the acquired sensing data is within a preset threshold value, the sensing data is continuously in a sensing state; if the acquired sensing data is lower than or exceeds a preset threshold, the control part adjusts the transmission task of the sensing data to the highest priority.
2. The real-time environment monitoring system for the internet of things of claim 1, wherein the data transmission adopts a bluetooth, Wi-Fi, ZigBee or 6LoWPAN communication protocol; the acquisition unit adopts a restricted Application Protocol (CoAP) to carry out data communication; the environmental parameters include temperature, humidity, carbon monoxide concentration, carbon dioxide concentration and atmospheric pressure; the preprocessing includes analysis, compression, filtering, and encryption of data.
3. The system for monitoring the environment of the internet of things in real time as claimed in claim 1, wherein the fog computing node supports wireless protocols of bluetooth, Wi-Fi, ZigBee or 6LoWPAN and is responsible for communication among devices to form a coordinated gateway network, and the fog computing node also serves as a storage library, namely a local database.
4. The real-time environment monitoring system for the internet of things of claim 1, wherein the hardware module comprises a GPRS module, a DSP module, a GSM module, a GPS module, an RF module, a POWER module, a RAM module and a CPU.
5. The real-time environment monitoring system for the internet of things according to claim 1, wherein the fog computing node continuously processes sensing data and performs information transmission according to environment monitoring requirements so as to provide real-time notification; the fog computing node is loaded with an ARM mainboard of the Linux system and is increased randomly according to the increase of the monitoring area range.
6. The internet-of-things environment real-time monitoring system of claim 1, wherein the fog computing nodes meet pre-processed computing, networking and storage requirements.
7. The internet-of-things environment real-time monitoring system of claim 1, wherein the fog computing node sends information through a local web server or a global system for mobile communications.
8. The real-time environment monitoring system for the internet of things of claim 1, wherein the terminal device is a mobile phone, a tablet computer or a personal computer.
9. The internet of things environment real-time monitoring system of claim 1, wherein the fog computing node stores incoming data in a local database, the operating system is responsible for storing the data locally and in a non-volatile memory, the data is stored in the local database in a compressed or encrypted manner and exported to the monitoring center in an Excel text format.
10. The real-time environment monitoring system for the internet of things of claim 1, wherein the local storage comprises a file storage and a database for storing attributes and indexes of files; in case the data processing and data transmission is resource limited, the local storage acts as a cache to enable a continuous data flow.
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| CN108922186A (en) * | 2018-07-20 | 2018-11-30 | 大连理工大学 | It is a kind of that analyzing and alarming system and method are monitored based on the streaming for vehicle that mist calculates |
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