A dangerous chemical warehouse edge data processing method, device and readable storage medium

Abstract

The application discloses a dangerous chemical warehouse edge data processing method and device and a readable storage medium. The method comprises the following steps: acquiring a plurality of environment parameter information and video data information; connecting the plurality of environment parameter information and the video data information to an ICN network through an Internet of Things gateway; and sending the information to a blockchain network for storage through the ICN network. Since the information center network (ICN) is a data-centered mechanism, the solution of the application can reduce network bandwidth and data retrieval time. Meanwhile, the blockchain has the characteristics of decentralization, non-tamperability and traceability, which can help to provide tamper-proof records as reliable evidence for any event investigation.

Description

Technical Field

[0001] The present application relates to the field of data processing and data transmission, and more specifically, to a method, device and readable storage medium for edge data processing in a hazardous chemicals warehouse. Background Art

[0002] Information-centric networking (ICN) explores the evolution from today's host-centric network architectures, such as IP networks, to a data-centric one. Its starting point is that communications networks should allow users to focus on the data content they need, rather than referencing the specific physical location from which data is retrieved from the host. Information-centric networking (ICN) offers a wide range of benefits, including content caching to reduce congestion and improve network responsiveness, simplified configuration of network devices, and security built into the network at the data level.

[0003] Information-centric networking (ICN) is built on top of named data networking (NDN) [1]. Communication in NDN is driven by data consumers and is achieved by exchanging two types of data packets: interest packets and data packets. Both types of packets carry a name that identifies a piece of data that can be transmitted in the packet. A common process is as follows, as shown in Figure 5:

[0004] (i) The consumer puts the name of the desired data into an Interest packet and sends it to the network.

[0005] (ii) The router uses this name to forward the Interest packet to the data producer.

[0006] (iii) Once the Interest packet reaches the node with the requested data, the node will return a Data packet containing the name and content, as well as the signature of the producer key binding the two.

[0007] (iv) The Data packet is returned to the requesting consumer along the reverse path of the Interest packet.

[0008] Blockchain technology,Blockchain is essentially a technology that supports distributed databases, enabling participants to store and share information in a secure and instant manner. Blockchain retains the characteristics of traceability, immutability, transparent data and instant sharing, and has great potential in data storage and processing at the edge of hazardous chemical warehouses. The following are the key disruptive features that blockchain platforms can provide [2]. Tamper-proof blockchain systems are known for their tamper-proof properties, which in turn helps to build trust in the integrity of the system among participants. Its tamper-proof nature is achieved through two elements: proof-of-work system and cryptographic technology. Conceptually, a blockchain is a chain of blocks. Each block contains a set of entries called transactions. Nodes collect new entries into new blocks and then add new blocks to the chain. As more new entries are collected, more blocks are created and the length of the chain increases. The blockchain ensures that this chain is difficult to tamper with. Any attempt to modify the chain requires the tamperer to provide proof of the authenticity of the modification. Generating such a proof involves performing cryptographic operations that are both lengthy and expensive. In addition, forged proofs can be easily detected by other nodes in the blockchain network. The blocks in the chain are connected together by links built using hash functions. A block's link is integral to its content. Any attempt to change the content of a block in the chain will also change the value of its hash link. This breaks the original chain, leaving the remaining chain much shorter than the original. This is immediately detectable by other participants, who will reject the change and continue using the original chain. A hash function is a one-way mathematical function that converts data into a random string of characters called a hash. Any change to the data, no matter how slight, will significantly alter the hash value in unpredictable ways. This makes it impossible to derive the original data from the hash value.

[0009] Edge computing. Traditional perception computing, such as object detection, runs on high-performance servers, enabling high-speed processing of each image and real-time detection. The goal of object detection is to accurately identify the type of object and its location in each image. In the past, edge devices lacked the computing power to run object detection AI models. Therefore, images captured by edge device cameras often needed to be transmitted over the network to a cloud server for object detection. The performance of this solution is affected by factors such as network quality, latency, and stability. In recent years, the development of edge devices has significantly increased their computing power, making edge computing technology a leading AI solution. Using edge computing can reduce the time it takes to transmit images / videos to cloud servers over the network, enabling faster object detection results.

[0010] The current state of hazardous chemical warehouses involves storing hazardous chemicals, including chemical raw materials, fertilizers, pesticides, and chemical reagents. These chemicals are commonly flammable, explosive, corrosive, and toxic. Hazardous chemical warehouses are typically located far from residential areas, and many are not suitable for manual patrols due to the nature of the goods they store. To ensure the safe storage of hazardous chemicals, a more optimized remote monitoring system is urgently needed. Summary of the Invention

[0011] In view of the above problems, the purpose of the present invention is to provide a method, device and readable storage medium for edge data processing of hazardous chemicals warehouses. The present invention will introduce the design of the edge data processing method of hazardous chemicals warehouses. This solution aims to solve the problems of redundant edge data transmission, processing and storage in the hazardous chemicals warehouse monitoring industry.

[0012] A first aspect of the present invention provides a method for processing edge data in a hazardous chemicals warehouse, comprising:

[0013] Obtain multiple environmental parameter information and video data information;

[0014] Connecting the multiple environmental parameter information and video data information to the ICN network through the Internet of Things gateway;

[0015] Sending to the blockchain network through the ICN network for storage;

[0016] The multiple environmental parameter information includes temperature information, humidity information, gas information, photosensitivity information, and smoke concentration information.

[0017] In this solution, multiple environmental parameter information and video data information are obtained, including:

[0018] Obtain the producer's digital signature information;

[0019] Performing signature processing on the plurality of environmental parameter information and video data information according to the digital signature information of the producer;

[0020] Get multiple data packets containing the producer's digital signature.

[0021] In this solution, before the multiple environmental parameter information and video data information are connected to the ICN network through the Internet of Things gateway, the following steps are also included:

[0022] Get multiple environmental parameter information;

[0023] Determining whether the plurality of environmental parameter information is within corresponding preset alarm thresholds;

[0024] If not, send an alarm message to the edge device.

[0025] In this solution, before the multiple environmental parameter information and video data information are connected to the ICN network through the Internet of Things gateway, the following steps are also included:

[0026] Preprocessing the video data information;

[0027] Get preprocessed data;

[0028] The pre-processed data is connected to the ICN network through the Internet of Things gateway.

[0029] In this solution, before sending the data to the blockchain network for storage via the ICN network, the following steps are also included:

[0030] Obtaining first current parameter information and second current parameter information;

[0031] Determining whether the first current parameter information and the second current parameter information are the same environmental parameter data;

[0032] If yes, send any set of current parameter information to the NDN data receiver.

[0033] In this solution, determining whether the first current parameter information and the second current parameter information are the same current parameter data is specifically as follows:

[0034] Obtaining hash value data of the first current parameter information and hash value data of the second current parameter information;

[0035] If the hash value data of the first current parameter information is the same as the hash value data of the second current parameter information;

[0036] It is determined that the first current parameter information and the second current parameter information are the same current parameter data.

[0037] In this solution, the data is sent to the blockchain network for storage via the ICN network, including:

[0038] The blockchain network is a consortium blockchain network;

[0039] Among them, a consortium blockchain network corresponds to 4 endorsement nodes and 1 consensus node.

[0040] A second aspect of the present invention provides a device. The device includes:

[0041] An acquisition module is used to obtain multiple environmental parameter information and video data information;

[0042] The processing module connects the multiple environmental parameter information and video data information to the ICN network through the Internet of Things gateway;

[0043] The sending module is used to send the plurality of environmental parameter information and video data information to the storage slot for data storage.

[0044] In this solution, multiple environmental parameter information and video data information are obtained, including:

[0045] Obtain the producer's digital signature information;

[0046] Performing signature processing on the plurality of environmental parameter information and video data information according to the digital signature information of the producer;

[0047] Get multiple data packets containing the producer's digital signature.

[0048] In this solution, before the multiple environmental parameter information and video data information are connected to the ICN network through the Internet of Things gateway, the following steps are also included:

[0049] Get multiple environmental parameter information;

[0050] Determining whether the plurality of environmental parameter information is within corresponding preset alarm thresholds;

[0051] If not, send an alarm message to the edge device.

[0052] In this solution, before the multiple environmental parameter information and video data information are connected to the ICN network through the Internet of Things gateway, the following steps are also included:

[0053] Preprocessing the video data information;

[0054] Get preprocessed data;

[0055] The pre-processed data is connected to the ICN network through the Internet of Things gateway.

[0056] In this solution, before sending the data to the blockchain network for storage via the ICN network, the following steps are also included:

[0057] Obtaining first current parameter information and second current parameter information;

[0058] Determining whether the first current parameter information and the second current parameter information are the same environmental parameter data;

[0059] If yes, send any set of current parameter information to the NDN data receiver.

[0060] In this solution, determining whether the first current parameter information and the second current parameter information are the same current parameter data is specifically as follows:

[0061] Obtaining hash value data of the first current parameter information and hash value data of the second current parameter information;

[0062] If the hash value data of the first current parameter information is the same as the hash value data of the second current parameter information;

[0063] It is determined that the first current parameter information and the second current parameter information are the same current parameter data.

[0064] In this solution, the data is sent to the blockchain network for storage via the ICN network, including:

[0065] The blockchain network is a consortium blockchain network;

[0066] Among them, a consortium blockchain network corresponds to 4 endorsement nodes and 1 consensus node.

[0067] In a third aspect of the present disclosure, an electronic device is provided, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor implements the above method when executing the program.

[0068] In a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the method according to the first aspect of the present disclosure is implemented.

[0069] This invention discloses a method, device, and readable storage medium for edge data processing in hazardous chemical warehouses. The method includes obtaining multiple environmental parameter information and video data, connecting this information to an ICN network via an IoT gateway, and then transmitting it to a blockchain network via the ICN for storage. Due to the data-centric nature of the Information-Centric Network (ICN), the solution described in this invention can reduce network bandwidth and data retrieval time. Furthermore, blockchain's decentralized, tamper-proof, and traceable characteristics help provide tamper-proof records as reliable evidence for any incident investigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 A flow chart showing a method for processing edge data of a hazardous chemicals warehouse according to the present invention is shown;

[0071] Figure 2 A flow chart of an environmental parameter early warning method according to the present invention is shown;

[0072] Figure 3 A flowchart of a method for determining identical parameter information according to the present invention is shown;

[0073] Figure 4 A block diagram of an edge data processing device for a hazardous chemicals warehouse according to the present invention is shown;

[0074] Figure 5shows an architecture diagram of an NDN data packet of the present invention;

[0075] Figure 6 A diagram of an edge data processing solution for a hazardous chemicals warehouse according to the present invention is shown;

[0076] Figure 7 A vehicle detection result diagram of the present invention is shown;

[0077] Figure 8.1 A conventional solution diagram of a Content Store module of the present invention is shown;

[0078] Figure 8.2 A diagram showing an optimization solution for the Content Store module of the present invention is shown;

[0079] Figure 9 A blockchain browser diagram of the present invention is shown. DETAILED DESCRIPTION

[0080] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of the present application and the features therein can be combined with each other.

[0081] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0082] Figure 1 A flow chart of a hazardous chemicals warehouse edge data processing method according to the present invention is shown.

[0083] like Figure 1 As shown, the present invention discloses a method for processing edge data of a hazardous chemicals warehouse, comprising:

[0084] S102, obtaining multiple environmental parameter information and video data information;

[0085] S104, connecting the multiple environmental parameter information and video data information to the ICN network through the Internet of Things gateway;

[0086] S106, sending to the blockchain network through the ICN network for storage.

[0087] According to an embodiment of the present invention, due to the high security requirements of the hazardous chemical warehouse monitoring industry, redundant twin devices are deployed to prevent single points of failure in the entire system and maintain high availability. Data collected from twin devices at the same time is likely identical, which incurs additional overhead for data transmission and storage. This invention collects environmental data using temperature, humidity, gas, light, and smoke sensors, captures video and audio using network cameras, and preprocesses the video and audio using edge computing programs on edge devices, such as for sampling and object detection. The environmental data and preprocessed audio and video data are then connected to the ICN network via an IoT gateway and sent to a blockchain network for storage. To obtain multiple environmental parameter information and video data, a Raspberry Pi 4B with 4GB of RAM is used as the edge device platform to run the data collection and edge computing programs. The environmental parameter information and video data are connected to the ICN network via the IoT gateway, using an NDN data transmitter for data transmission. The data is then sent to the blockchain network for storage, and then filtered and stored by an NDN data receiver.

[0088] According to an embodiment of the present invention, obtaining multiple environmental parameter information and video data information includes:

[0089] Obtain the producer's digital signature information;

[0090] Performing signature processing on the plurality of environmental parameter information and video data information according to the digital signature information of the producer;

[0091] Get multiple data packets containing the producer's digital signature.

[0092] It should be noted that the solution of the present invention is not restricted by the type of blockchain. Any blockchain that can provide similar smart contract functionality can be implemented. Adaptive optimization of the Content Store module in NDN nodes can save cache and improve network processing speed. NDN requires producers to sign data content to ensure its reliability and integrity, providing a more comprehensive data and network security mechanism. Furthermore, in an NDN network, each data packet is named and carries the producer's digital signature. Any node in the network that caches requested data can act as a content provider, satisfying data consumption requests from downstream consumers. This reduces bandwidth and allows for more flexible handling of issues such as congestion control.

[0093] According to an embodiment of the present invention, Figure 2 As shown, before the multiple environmental parameter information and video data information are connected to the ICN network through the Internet of Things gateway, the following steps are also included:

[0094] S202, obtaining multiple environmental parameter information;

[0095] S204, determining whether the plurality of environmental parameter information is within corresponding preset alarm thresholds;

[0096] S206: If not, send an alarm message to the edge device.

[0097] It should be noted that the edge devices mentioned in these steps are edge devices. Furthermore, the solution of this invention uses a Raspberry Pi 4B with 4GB of RAM as the edge device platform to run data collection and edge computing programs. Data collection uses sensors for temperature, humidity, gas, light, and smoke. This collected environmental data is packaged and serialized by data type and time, and then sent to the ICN network. Each type of data has preset alarm thresholds, allowing edge devices to provide early warnings.

[0098] According to an embodiment of the present invention, before the plurality of environmental parameter information and video data information are connected to the ICN network through the Internet of Things gateway, the method further includes:

[0099] Preprocessing the video data information;

[0100] Get preprocessed data;

[0101] The pre-processed data is connected to the ICN network through the Internet of Things gateway.

[0102] It should be noted that the present invention needs to pre-process the collected video, image and other data on the edge device before transmitting them to the ICN network. For example, the present invention uses 960x540 and 640x480 resolution road videos as the input source of the YOLO Fastest model [5] and uses the ncnn high-performance neural network forward computing framework to run vehicle target detection. The detected vehicle type and its coordinate image results are then transmitted to the blockchain network for storage through the information center network (ICN). The task of object detection is to determine the type of object and its location in the image, so the dataset needs to contain images and labels to form a pair of files. In this paper, the present invention uses the open source image library Pascal VOC 2012 organized by PASCAL to extract images containing pedestrian labels as a dataset for pedestrian target detection. Mask detection uses the Wider Face of the Chinese University of Hong Kong and the mask object detection dataset of MAFA. Vehicle detection uses PascalVOC 2007, Pascal VOC 2012, the COCO dataset of the COCO organization and Google's Open Image V6 dataset to extract cars, trucks and buses. The present invention removes some inappropriate data, such as toy cars, from the dataset to form an integrated vehicle object detection dataset. The present invention uses the Logitech webcam C930c model as the input camera to detect cars on the road. The detection results are as follows: Figure 7 The detected image and a short video clip (10 seconds) will be sent back to the ICN network and blockchain network for further processing.

[0103] According to an embodiment of the present invention, before sending the data to the blockchain network for storage via the ICN network, the method further includes:

[0104] Obtaining first current parameter information and second current parameter information;

[0105] Determining whether the first current parameter information and the second current parameter information are the same environmental parameter data;

[0106] If yes, send any set of current parameter information to the NDN data receiver.

[0107] It is also necessary to explain that the Information Centric Network (ICN) is built on the Named Data Network (NDN) as the backbone network for information transmission. The traditional NDN node routing Content Store module needs to store the mapping from each data name to the original data content, such as Figure 8.1As shown. Even if the original data content corresponding to two different data names is the same, two copies of the same original data content will be stored, which is not efficient. Once the original data content is relatively large, such as video and audio files, the memory occupied by the Content Store module will increase rapidly. The present invention transforms the Content Store module in the NDN data receiving end routing and optimizes it by adding adaptive functions. The basic concept is that a copy of the two sets of duplicate data from the twin devices will be saved in the NDN data receiving end. Figure 8.2 As shown in the figure, the ContentStore optimization module can reduce the storage of redundant data.

[0108] According to an embodiment of the present invention, Figure 3 As shown, determining whether the first current parameter information and the second current parameter information are the same current parameter data is specifically as follows:

[0109] S302, obtaining hash value data of the first current parameter information and hash value data of the second current parameter information;

[0110] S302, if the hash value data of the first current parameter information is the same as the hash value data of the second current parameter information;

[0111] S302: Determine whether the first current parameter information and the second current parameter information are the same current parameter data.

[0112] It should be noted that the Content Store optimization module proposed in this invention fully utilizes the unidirectional and efficient nature of hash functions. In NDN packets, the signature, signature information, and data are separate fields, and this invention can extract these three fields separately. If consumer A first subscribes to data Da_1 from device 1, device 1, as the producer, will send data Da_1 to NDN node router R. The Content Store optimization module of NDN router R will store a mapping from the data name / data / device_1 to the hash value H_1 of Da_1 and the mapping from the hash value H_1 to the data Da_1. The data Da_1, its corresponding signature, and signature information will also be stored separately. Next, consumer A subscribes to data Da_2 from device 2. As the producer, device 2 also sends data Da_2 to NDN node router R. Upon receiving Da_2, router R first calculates its hash value H_2. If a query in router R's Content Store module finds that hash value H_1 equals H_2, router R no longer allocates new memory to store data Da_2. Instead, it only stores the signature and signature information corresponding to data Da_2, and a mapping from the data name / data / device_2 to the hash value H_1 of Da_1. Router R then adds device Da_2's signature and signature information to this data Da_1 and transmits it to A as " / data / device_1."

[0113] According to an embodiment of the present invention, the further embodiment includes:

[0114] The blockchain network is a consortium blockchain network;

[0115] Among them, a consortium blockchain network corresponds to 4 endorsement nodes and 1 consensus node.

[0116] It should be noted that the present invention uses Hyperledger Fabric[3] to build a consortium blockchain network, which includes 4 endorsement nodes and 1 consensus node, and a block browser webpage to check the data stored in the block, such as Figure 9 As shown, the present invention can see that the temperature data from the edge device is saved in the blockchain through the smart contract.

[0117] According to an embodiment of the present invention, after the data is sent to the blockchain network for storage via the ICN network, the method further includes:

[0118] Obtain hash value data of multiple environmental parameter information and video data information in the blockchain;

[0119] Determining whether hash value data of multiple environmental parameter information and video data information in the blockchain has changed;

[0120] If so, a warning message is sent to the user terminal.

[0121] It should be noted that the present invention obtains hash values ​​of multiple pieces of environmental parameter information and video data in a blockchain, determines whether the hash values ​​of the environmental parameter information and video data in the blockchain have been altered, and if so, sends a warning message to the user terminal. This ensures data authenticity. Specifically, blockchain systems are known for their tamper-resistant properties, which in turn help build trust in the integrity of the system among participants. This tamper-resistant nature is achieved through two elements: a proof-of-work system and cryptographic technology. Conceptually, a blockchain is a chain of blocks. Each block contains a set of entries called transactions. Nodes collect new entries into new blocks, which are then added to the chain. As more new entries are collected, more blocks are created, and the length of the chain increases. The blockchain ensures that this chain is difficult to tamper with. Any attempt to modify the chain requires the tamperer to provide proof of the authenticity of the modification. Generating such proof involves performing lengthy and expensive cryptographic operations. Furthermore, forged proofs can be easily detected by other nodes in the blockchain network. Blocks in the chain are connected by links constructed using hash functions. The links of a block are integral to its content. Any attempt to change the contents of a block in the chain will also cause the value of its hash link to change. This breaks the original chain, leaving the remaining chain much shorter than the original. This is immediately detectable by other participants, who will reject the change and continue using the original chain. A hash function is a one-way mathematical function that converts data into a random string of characters called a hash. Any change to the data, no matter how slight, will significantly alter the hash value in unpredictable ways. This makes it impossible to reverse engineer the hash value to the original data.

[0122] According to an embodiment of the present invention, the further embodiment includes:

[0123] Get the mapping structure information between named data and original data content;

[0124] A content hash value is added to the mapping structure information between the named data and the original data content to obtain new mapping structure information between the named data and the original data content.

[0125] It should be noted that if Figure 6As shown, the design of this invention abandons the IP-based network structure and replaces it with a distributed network structure composed of ICN. Furthermore, the present invention modifies the mapping structure between named data and raw data content in the original NDN Content Store model design, adding a mapping structure from content hash values ​​to raw data content. This allows the new Content Store model to save cache space. The key idea behind the NDN project stems from observations of changes in applications on the current Internet. At its inception, the primary application requirement for the current Internet was the sharing of computing resources. However, after more than 50 years of development, the Internet's usage has undergone significant changes, with the primary use case now being content acquisition and distribution. Despite these significant changes in applications, the Internet's architecture remains based on a host-to-host communication model. For an Internet primarily focused on publishing and retrieving information, this host-to-host communication model has significant shortcomings. For example, each access to content requires an indirect mapping to the device where the content resides. To address this issue, NDN draws upon the DONA architecture proposed by Professor Scott Shenker and others at UC Berkeley. It utilizes name routing, caching content through routers, thereby accelerating data transmission and improving content retrieval efficiency. A specific implementation example of NDN is HYPERLINK "https: / / baike.baidu.com / item / %E6%96%BD%E4%B9%90%E5%85%AC%E5%8F%B8 / 10245160?fromModule=lemma_inlink" \t "https: / / baike.baidu.com / item / %E5%91%BD%E5%90%8D%E6%95%B0%E6%8D%AE%E7%BD%91%E7%BB%9C / _blank" Content-Centric Networking (CCN) was proposed by Van Jacobson et al. of Xerox's Palo Alto Research Center (PARC).

[0126] Figure 4 A block diagram of an edge data processing device for a hazardous chemicals warehouse according to the present invention is shown.

[0127] like Figure 4 As shown, the second aspect of the present invention provides a device. The device includes:

[0128] An acquisition module is used to obtain multiple environmental parameter information and video data information;

[0129] The processing module connects the multiple environmental parameter information and video data information to the ICN network through the Internet of Things gateway;

[0130] The sending module is used to send the plurality of environmental parameter information and video data information to the storage slot for data storage.

[0131] According to an embodiment of the present invention, due to the high security requirements of the hazardous chemical warehouse monitoring industry, redundant twin devices are deployed to prevent single points of failure and maintain high availability. Data collected from twin devices at the same point in time is likely identical, which incurs additional overhead for data transmission and storage. This invention collects environmental data using temperature, humidity, gas, light, and smoke sensors, captures video and audio using network cameras, and preprocesses the video and audio using edge computing programs on edge devices, such as for sampling and object detection. The environmental data and preprocessed audio and video data are then connected to the ICN network via an IoT gateway and sent to a blockchain network for storage. To obtain multiple environmental parameter information and video data, a Raspberry Pi 4B with 4GB of RAM is used as the edge device platform to run the data collection and edge computing programs. The data is then connected to the ICN network via the IoT gateway using an NDN data transmitter for data transmission. The data is then sent to the blockchain network for storage, and then filtered and stored by an NDN data receiver.

[0132] According to an embodiment of the present invention, the acquisition module acquires multiple environmental parameter information and video data information, including:

[0133] Obtain the producer's digital signature information;

[0134] Performing signature processing on the plurality of environmental parameter information and video data information according to the digital signature information of the producer;

[0135] Get multiple data packets containing the producer's digital signature.

[0136] It should be noted that the solution of the present invention is not restricted by the type of blockchain. Any blockchain that can provide similar smart contract functionality can be implemented. Adaptive optimization of the Content Store module in NDN nodes can save cache and improve network processing speed. NDN requires producers to sign data content to ensure its reliability and integrity, providing a more comprehensive data and network security mechanism. Furthermore, in an NDN network, each data packet is named and carries the producer's digital signature. Any node in the network that caches requested data can act as a content provider, satisfying data consumption requests from downstream consumers. This reduces bandwidth and allows for more flexible handling of issues such as congestion control.

[0137] According to an embodiment of the present invention, before the processing module connects the multiple environmental parameter information and video data information to the ICN network through the Internet of Things gateway, it also includes:

[0138] Get multiple environmental parameter information;

[0139] Determining whether the plurality of environmental parameter information is within corresponding preset alarm thresholds;

[0140] If not, send an alarm message to the edge device.

[0141] It should be noted that the edge devices mentioned in these steps are edge devices. Furthermore, the solution of this invention uses a Raspberry Pi 4B with 4GB of RAM as the edge device platform to run data collection and edge computing programs. Data collection uses sensors for temperature, humidity, gas, light, and smoke. This collected environmental data is packaged and serialized by data type and time, and then sent to the ICN network. Each type of data has preset alarm thresholds, allowing edge devices to provide early warnings.

[0142] According to an embodiment of the present invention, before the processing module connects the multiple environmental parameter information and video data information to the ICN network through the Internet of Things gateway, it also includes:

[0143] Preprocessing the video data information;

[0144] Get preprocessed data;

[0145] The pre-processed data is connected to the ICN network through the Internet of Things gateway.

[0146] It should be noted that the present invention needs to pre-process the collected video, image and other data on the edge device before transmitting them to the ICN network. For example, the present invention uses 960x540 and 640x480 resolution road videos as the input source of the YOLO Fastest model [5] and uses the ncnn high-performance neural network forward computing framework to run vehicle target detection. The detected vehicle type and its coordinate image results are then transmitted to the blockchain network for storage through the information center network (ICN). The task of object detection is to determine the type of object and its location in the image, so the dataset needs to contain images and labels to form a pair of files. In this paper, the present invention uses the open source image library Pascal VOC 2012 organized by PASCAL to extract images containing pedestrian labels as a dataset for pedestrian target detection. Mask detection uses the Wider Face of the Chinese University of Hong Kong and the mask object detection dataset of MAFA. Vehicle detection uses PascalVOC 2007, Pascal VOC 2012, the COCO dataset of the COCO organization and Google's Open Image V6 dataset to extract cars, trucks and buses. The present invention removes some inappropriate data, such as toy cars, from the dataset to form an integrated vehicle object detection dataset. The present invention uses the Logitech webcam C930c model as the input camera to detect cars on the road. The detection results are as follows: Figure 7 The detected image and a short video clip (10 seconds) will be sent back to the ICN network and blockchain network for further processing.

[0147] According to an embodiment of the present invention, before the processing module connects the multiple environmental parameter information and video data information to the ICN network through the Internet of Things gateway, it also includes:

[0148] Obtaining first current parameter information and second current parameter information;

[0149] Determining whether the first current parameter information and the second current parameter information are the same environmental parameter data;

[0150] If yes, send any set of current parameter information to the NDN data receiver.

[0151] It is also necessary to explain that the Information Centric Network (ICN) is built on the Named Data Network (NDN) as the backbone network for information transmission. The traditional NDN node routing Content Store module needs to store the mapping from each data name to the original data content, such as Figure 8.1As shown. Even if the original data content corresponding to two different data names is the same, two copies of the same original data content will be stored, which is not efficient. Once the original data content is relatively large, such as video and audio files, the memory occupied by the Content Store module will increase rapidly. The present invention transforms the Content Store module in the NDN data receiving end routing and optimizes it by adding adaptive functions. The basic concept is that a copy of the two sets of duplicate data from the twin devices will be saved in the NDN data receiving end. Figure 8.2 As shown in the figure, the ContentStore optimization module can reduce the storage of redundant data.

[0152] According to an embodiment of the present invention, the processing module determines whether the first current parameter information and the second current parameter information are the same current parameter data, further comprising:

[0153] Obtaining hash value data of the first current parameter information and hash value data of the second current parameter information;

[0154] If the hash value data of the first current parameter information is the same as the hash value data of the second current parameter information;

[0155] It is determined that the first current parameter information and the second current parameter information are the same current parameter data.

[0156] It should be noted that the Content Store optimization module proposed in this invention fully utilizes the unidirectional and efficient nature of hash functions. In NDN packets, the signature, signature information, and data are separate fields, and this invention can extract these three fields separately. If consumer A first subscribes to data Da_1 from device 1, device 1, as the producer, will send data Da_1 to NDN node router R. The Content Store optimization module of NDN router R will store a mapping from the data name / data / device_1 to the hash value H_1 of Da_1 and the mapping from the hash value H_1 to the data Da_1. The data Da_1, its corresponding signature, and signature information will also be stored separately. Next, consumer A subscribes to data Da_2 from device 2. As the producer, device 2 also sends data Da_2 to NDN node router R. Upon receiving Da_2, router R first calculates its hash value H_2. If a query in router R's Content Store module finds that hash value H_1 equals H_2, router R no longer allocates new memory to store data Da_2. Instead, it only stores the signature and signature information corresponding to data Da_2, and a mapping from the data name / data / device_2 to the hash value H_1 of Da_1. Router R then adds device Da_2's signature and signature information to this data Da_1 and transmits it to A as " / data / device_1."

[0157] According to an embodiment of the present invention, after being sent to the blockchain network for storage via the ICN network, the process includes:

[0158] Obtain hash value data of multiple environmental parameter information and video data information in the blockchain;

[0159] Determining whether hash value data of multiple environmental parameter information and video data information in the blockchain has changed;

[0160] If so, a warning message is sent to the user terminal.

[0161] It should be noted that the present invention obtains hash values ​​of multiple pieces of environmental parameter information and video data in a blockchain, determines whether the hash values ​​of the pieces of environmental parameter information and video data in the blockchain have been altered, and if so, sends a warning message to the user terminal. This ensures data authenticity. Specifically, blockchain is known for its tamper-resistant properties, which in turn helps build trust in integrity among participants. This tamper-resistant nature is achieved through two elements: proof-of-work and cryptography. Conceptually, a blockchain is a chain of blocks. Each block contains a set of entries called transactions. Nodes collect new entries into new blocks, which are then added to the chain. As more new entries are collected, more blocks are created, and the length of the chain increases. Blockchain ensures that this chain is difficult to tamper with. Any attempt to modify the chain requires the tamperer to provide proof of the authenticity of the modification. Generating such proof involves performing lengthy and expensive cryptographic operations. Furthermore, forged proofs can be easily detected by other nodes in the blockchain network. Blocks in the chain are connected by links constructed using hash functions. The links of a block are integral to its content. Any attempt to change the contents of a block in the chain will also cause the value of its hash link to change. This breaks the original chain, leaving the remaining chain much shorter than the original. This is immediately detectable by other participants, who will reject the change and continue using the original chain. A hash function is a one-way mathematical function that converts data into a random string of characters called a hash. Any change to the data, no matter how slight, will significantly alter the hash value in unpredictable ways. This makes it impossible to reverse engineer the hash value to the original data.

[0162] According to an embodiment of the present invention, the processing module includes:

[0163] Get the mapping structure information between named data and original data content;

[0164] A content hash value is added to the mapping structure information between the named data and the original data content to obtain new mapping structure information between the named data and the original data content.

[0165] It should be noted that if Figure 6As shown, the design of this invention abandons the IP-based network structure and replaces it with a distributed network structure composed of ICN. Furthermore, the present invention modifies the mapping structure between named data and raw data content in the original NDN Content Store model design, adding a mapping structure from content hash values ​​to raw data content. This allows the new Content Store model to save cache space. The key idea behind the NDN project stems from observations of changes in applications on the current Internet. At its inception, the primary application requirement for the current Internet was the sharing of computing resources. However, after more than 50 years of development, the Internet's usage has undergone significant changes, with the primary use case now being content acquisition and distribution. Despite these significant changes in applications, the Internet's architecture remains based on a host-to-host communication model. For an Internet primarily focused on publishing and retrieving information, this host-to-host communication model has significant shortcomings. For example, each access to content requires an indirect mapping to the device where the content resides. To address this issue, NDN draws upon the DONA architecture proposed by Professor Scott Shenker and others at UC Berkeley. It utilizes name routing, caching content through routers, thereby accelerating data transmission and improving content retrieval efficiency. A specific implementation example of NDN is HYPERLINK "https: / / baike.baidu.com / item / %E6%96%BD%E4%B9%90%E5%85%AC%E5%8F%B8 / 10245160?fromModule=lemma_inlink" \t "https: / / baike.baidu.com / item / %E5%91%BD%E5%90%8D%E6%95%B0%E6%8D%AE%E7%BD%91%E7%BB%9C / _blank" Content-Centric Networking (CCN) was proposed by Van Jacobson et al. of Xerox's Palo Alto Research Center (PARC).

[0166] In a third aspect of the present disclosure, an electronic device is provided, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor implements the above method when executing the program.

[0167] In a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the method according to the first aspect of the present disclosure is implemented.

[0168] This invention discloses a method, device, and readable storage medium for edge data processing in hazardous chemical warehouses. The method includes obtaining multiple environmental parameter information and video data, connecting this information to an ICN network via an IoT gateway, and then transmitting it to a blockchain network via the ICN for storage. Due to the data-centric nature of the Information-Centric Network (ICN), the solution described in this invention can reduce network bandwidth and data retrieval time. Furthermore, blockchain's decentralized, tamper-proof, and traceable characteristics help provide tamper-proof records as reliable evidence for any incident investigation.

[0169] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0170] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0171] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0172] Those skilled in the art will appreciate that all or part of the steps of the above-mentioned method embodiments may be implemented by hardware associated with program instructions, and the aforementioned program may be stored in a computer-readable storage medium. When the program is executed, the program executes the steps of the above-mentioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0173] Alternatively, if the integrated units described above are implemented as software modules and sold or used as standalone products, they can also be stored on a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product, stored on a storage medium, includes instructions for enabling a computer device (such as a personal computer, server, or network device) to execute all or part of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as removable storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. A method for processing edge data in a hazardous chemicals warehouse, characterized in that: include: Obtain multiple environmental parameter information and video data information; Connecting the multiple environmental parameter information and video data information to the ICN network through the Internet of Things gateway; Sending to the blockchain network through the ICN network for storage; The plurality of environmental parameter information includes temperature information, humidity information, gas information, photosensitivity information, and smoke concentration information; Before being sent to the blockchain network for storage via the ICN network, the following is also included: Obtaining first current parameter information and second current parameter information; Determine whether the first current parameter information and the second current parameter information are the same environmental parameter data; specifically, obtain a hash value of the first current parameter information and a hash value of the second current parameter information; if the hash value of the first current parameter information is the same as the hash value of the second current parameter information; determine that the first current parameter information and the second current parameter information are the same current parameter data; If so, the mapping of the name corresponding to the third current parameter information to the hash value and the mapping of the hash value to the data are stored in the Content Store optimization module of the NDN routing, and the third current parameter information, the signature corresponding to the fourth current parameter information, the signature information and the mapping of the name of the fourth current parameter information to the hash value of the third current parameter information are stored in the Content Store optimization module of the NDN routing; the third current parameter information and the signature and signature information corresponding to the fourth current parameter information are sent to the NDN data receiving end; wherein, the third current parameter information is any group of the first current parameter information and the second current parameter information, and the fourth current parameter information is another group of current parameter information of the first current parameter information and the second current parameter information except the third current parameter information; wherein, the first current parameter information and the second current parameter information are respectively the environmental parameter information obtained by the twin detection device.

2. A method for processing edge data of a hazardous chemicals warehouse according to claim 1, characterized in that: Obtain multiple environmental parameter information and video data information, including: Obtain the producer's digital signature information; Performing signature processing on the plurality of environmental parameter information and video data information according to the digital signature information of the producer; Get multiple data packets containing the producer's digital signature.

3. The method for processing edge data of a hazardous chemicals warehouse according to claim 1, characterized in that: Before connecting the plurality of environmental parameter information and video data information to the ICN network through the Internet of Things gateway, the method further includes: Get multiple environmental parameter information; Determining whether the plurality of environmental parameter information is within corresponding preset alarm thresholds; If not, send an alarm message to the edge device.

4. The method for processing edge data of a hazardous chemicals warehouse according to claim 1, characterized in that: Before connecting the plurality of environmental parameter information and video data information to the ICN network through the Internet of Things gateway, the method further includes: Preprocessing the video data information; Get preprocessed data; The pre-processed data is connected to the ICN network through the Internet of Things gateway.

5. The method for processing edge data of a hazardous chemicals warehouse according to claim 1, characterized in that: The blockchain network is a consortium blockchain network; Among them, a consortium blockchain network corresponds to 4 endorsement nodes and 1 consensus node.

6. A hazardous chemicals warehouse edge data processing device based on the method according to any one of claims 1 to 5, comprising: An acquisition module is used to obtain multiple environmental parameter information and video data information; A processing module, performing signature processing on the plurality of environmental parameter information and video data information according to the digital signature information of the producer; The sending module is used to send the plurality of environmental parameter information and video data information to the storage slot for data storage.

7. An electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 5.

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