Situation awareness method and system based on Internet of Things

Abstract

The invention belongs to the technical field of the Internet of Things, and discloses a situation awareness method and system based on the Internet of Things, and the method comprises the steps: collecting environment awareness data, and extracting environment features and mineral features from the environment awareness data; storing the environment features and the mineral features in a block chain, and respectively judging whether the environment features and the mineral features meet preset standards or not; respectively predicting the environment situation and the mineral situation based on the judgment results of the environment characteristics and the mineral characteristics; and comprehensively evaluating the ore exploitability through a pre-established decision cluster on the basis of the prediction results of the environment situation and the mineral product situation. According to the system and the method, through a mechanism of sensing surrounding environment parameters and extracting specified mineral signs and other attributes, the environment parameters and the mineral signs can be accurately sensed and collected, and powerful data support is provided for accurate monitoring and resource management.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to a situation awareness method and system based on the Internet of Things. Background Art

[0002] Wide-area IoT terminals are IoT devices designed to be deployed over wide areas. They enable data collection, processing, and communication across geographical locations. They are particularly suitable for applications covering large areas or remote areas. These terminals utilize network connections for remote monitoring and control.

[0003] Traditional wide-area IoT terminals often only have a single information function for network communication. They simply transmit front-end data back to the background and perform complex artificial intelligence detection and algorithms in the background. Their intelligent benefits rely heavily on network construction, and it is difficult to achieve the real-time and universality of IoT computing. For some simple application scenarios, they also lack flexibility, which leads to excessive costs.

[0004] Therefore, how to provide a situation awareness method and system based on the Internet of Things is a problem that needs to be solved urgently. Summary of the invention

[0005] The embodiment of the present invention provides a situation awareness method and system based on the Internet of Things to solve the problem that it is difficult to achieve real-time and universality of Internet of Things computing in the prior art.

[0006] In order to have a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not a general review, nor is it intended to identify key / important components or to describe the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a prelude to the detailed description that follows.

[0007] According to a first aspect of an embodiment of the present invention, a situation awareness method based on the Internet of Things is provided.

[0008] In one embodiment, the situation awareness method based on the Internet of Things includes: Collect environmental perception data and extract environmental characteristics and mineral characteristics from the environmental perception data; The environmental characteristics and mineral characteristics are stored in the blockchain, and the environmental characteristics and mineral characteristics are judged to see whether they meet the preset standards; Based on the judgment results of environmental characteristics and mineral characteristics, the environmental situation and mineral situation are predicted respectively; Based on the prediction results of environmental situation and mineral situation, the mineability of ore is comprehensively evaluated through the pre-established decision cluster.

[0009] In one embodiment, collecting environmental perception data and extracting environmental features and mineral features from the environmental perception data includes: Integrate data collected by multiple types of sensors to obtain environmental perception data, convert the environmental perception data into digital signals and store them in local cache; Analyze environmental perception data, identify environmental characteristics and mineral characteristics from environmental perception data, and learn mineral characteristics based on the identification results of mineral characteristics In one embodiment, analyzing the environmental perception data, identifying environmental features and mineral features from the environmental perception data, and learning mineral characteristics based on the identification results of the mineral features includes: The environmental perception data is subjected to denoising and standardization processing in turn to obtain optimized environmental perception data; Extracting environmental features from the optimized environmental perception data, wherein the environmental features include temperature, humidity, light intensity, wind speed, water content, and acidity and alkali; Mineral characteristic parameters are calculated based on environmental perception data, and the mineral characteristic parameters are used as input of the regression analysis model, and the regression analysis model is used to learn the relationship between ore characteristics.

[0010] In one embodiment, the calculation of mineral characteristic parameters based on environmental perception data includes: The light transmittance of the ore is calculated using the Beer-Lambert law, wherein the calculation formula of the Beer-Lambert law is: ; In the formula, T Indicates light transmittance; I Indicates the intensity of transmitted light; I 0 represents the incident light intensity; α represents the absorption coefficient; L represents the optical path length; The Mohs hardness test technology is used to simulate the application of different stresses to test the toughness and obtain the toughness of the ore.

[0011] In one embodiment, the environmental characteristics and mineral characteristics are stored in the blockchain, and the environmental characteristics and mineral characteristics are judged to be in accordance with the preset standards, respectively, including: The environmental characteristics and mineral characteristics are respectively compared with the standard data in the local database. If the environmental characteristics and mineral characteristics are both within the preset range, it is determined that the environmental characteristics and mineral characteristics meet the standards; Generate certificate parameters and geographical attributes corresponding to environmental characteristics and mineral characteristics that meet the standards, and store the generated certificate parameters and geographical attributes in the blockchain; The stored environmental characteristics and mineral characteristics are compared with historical data for the second time, and early warning measures are formulated based on the results of the secondary comparison.

[0012] In one embodiment, the prediction of the environmental situation and the mineral situation based on the judgment results of the environmental characteristics and the mineral characteristics respectively includes: The optimized environmental perception data is preliminarily predicted using a linear regression model to obtain preliminary prediction results of the environmental situation and mineral situation; Expand the data range of the optimized environmental perception data, and use the random forest algorithm to perform secondary prediction on the expanded environmental perception data to obtain secondary prediction results of environmental situation and mineral situation; The preliminary and secondary forecast results of environmental and mineral situations are integrated and analyzed to form a comprehensive situation forecast report, and mining measures are formulated based on the comprehensive situation forecast report.

[0013] In one embodiment, the expression for performing secondary prediction on the expanded environmental perception data using the random forest algorithm is: ; In the formula, f ( x ) represents the secondary prediction output result; N represents the number of numbers in the forest; h i ( x ) indicates the i The prediction results of the tree.

[0014] In one embodiment, the comprehensive evaluation of ore mineability based on the prediction results of environmental situation and mineral situation through a pre-established decision cluster includes: Define fuzzy sets and use membership functions to describe the fuzzy states of ore characteristics; Self-organize decision clusters through wireless networks, and individuals in the decision clusters share environmental characteristics, mineral characteristics and individual decision evaluation data in real time; Collect individual decision evaluation data and assign weights to individual decisions based on the accuracy of individual historical decisions; combine the weight assignment results with pre-set decision principles to comprehensively evaluate the mineability of the ore; The cluster decision results are integrated to generate a decision report, and a feedback mechanism is established to verify the accuracy of cluster decisions.

[0015] According to a second aspect of an embodiment of the present invention, a situation awareness system based on the Internet of Things is provided.

[0016] In one embodiment, the situational awareness system based on the Internet of Things includes: Environmental perception module, used to collect environmental perception data and extract environmental characteristics and mineral characteristics from the environmental perception data; A local computing module is used to store environmental characteristics and mineral characteristics in the blockchain and to determine whether the environmental characteristics and mineral characteristics meet the preset standards; A situation prediction module is used to predict the environmental situation and mineral situation based on the judgment results of environmental characteristics and mineral characteristics respectively; The decision-making evaluation module is used to comprehensively evaluate the mineability of ore based on the prediction results of environmental situation and mineral situation through a pre-established decision cluster.

[0017] In one embodiment, the environment perception module includes: The environment acquisition module is used to integrate the data collected by multiple types of sensors to obtain environment perception data, and convert the environment perception data into digital signals and store them in the local cache; The feature recognition module is used to analyze environmental perception data, identify environmental features and mineral features from the environmental perception data, and learn mineral characteristics based on the recognition results of mineral features.

[0018] According to a third aspect of an embodiment of the present invention, a computer device is provided.

[0019] In one embodiment, the computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0020] According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided.

[0021] In one embodiment, the computer-readable storage medium stores a computer program, and the computer program implements the steps of the above method when executed by a processor.

[0022] The technical solution provided by the embodiment of the present invention may have the following beneficial effects: 1. The present invention can accurately sense and collect environmental parameters and mineral characteristics through the mechanism of sensing surrounding environmental parameters and extracting specified mineral characteristics and other attributes, providing strong data support for accurate monitoring and resource management.

[0023] 2. The present invention uses a mechanism to identify whether environmental conditions and mineral characteristics meet specified standards through local calculations, which can reduce dependence on external networks, improve response speed, and make continuous predictions of environmental and mineral situations based on real-time data. It supports from immediate short-term predictions to long-term trend analysis, which in turn helps to timely adjust mining strategies and environmental protection measures, and help users identify potential risks and opportunities in advance.

[0024] 3. The present invention can realize information sharing and decision coordination among IoT terminals through fuzzy judgment and group terminal cluster decision-making mechanism, which not only improves the accuracy of decision-making, but also optimizes the allocation and use of resources, and can flexibly adjust the working mode according to actual environmental conditions and mineral signs.

[0025] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0027] Figure 1 is a flow chart of a situation awareness method based on the Internet of Things according to an exemplary embodiment; Figure 2 is a principle block diagram of a situation awareness system based on the Internet of Things according to an exemplary embodiment; Figure 3 The figure is a schematic diagram showing the structure of a computer device according to an exemplary embodiment. DETAILED DESCRIPTION

[0028] The following description and accompanying drawings fully illustrate the specific embodiments of this article so that those skilled in the art can practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments of this article includes the entire scope of the claims, as well as all available equivalents of the claims. Herein, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the structure, device or equipment including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also include elements inherent to such structure, device or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the structure, device or equipment including the elements. Each embodiment is described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0029] The terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this document and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of this document, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a mechanical connection or an electrical connection, it can also be the internal communication of two elements, it can be a direct connection, or it can be an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0030] As used herein, the term "plurality" means two or more than two, unless otherwise specified.

[0031] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0032] In this article, the term "and / or" is a description of the association relationship between objects, indicating that three relationships may exist. For example, A and / or B means: A or B, or, A and B.

[0033] It should be understood that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0034] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, or a combination thereof. The above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above modules.

[0035] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0036] Figure 1An embodiment of a situation awareness method based on the Internet of Things of the present invention is shown.

[0037] In this optional embodiment, the situation awareness method based on the Internet of Things includes: Step S101, collecting environmental perception data, and extracting environmental characteristics and mineral characteristics from the environmental perception data; Step S103: storing the environmental characteristics and mineral characteristics in the blockchain, and determining whether the environmental characteristics and mineral characteristics meet the preset standards; Step S105: predicting the environmental situation and the mineral situation based on the judgment results of the environmental characteristics and the mineral characteristics respectively; Step S107: Based on the prediction results of the environmental situation and the mineral situation, the mineability of the ore is comprehensively evaluated through a pre-established decision cluster.

[0038] In this optional embodiment, collecting environmental perception data and extracting environmental characteristics and mineral characteristics from the environmental perception data includes: Integrate data collected by multiple types of sensors to obtain environmental perception data, convert the environmental perception data into digital signals and store them in local cache; analyze the environmental perception data, identify environmental characteristics and mineral characteristics from the environmental perception data, and learn mineral characteristics based on the identification results of mineral characteristics.

[0039] In this optional embodiment, multiple sensors (such as temperature sensors, humidity sensors, gas sensors, etc.) are integrated in the IoT terminal to monitor the surrounding environment in real time. Environmental data is collected regularly through each sensor and converted into digital signals and stored in a local cache.

[0040] In this optional embodiment, the analyzing the environmental perception data, identifying environmental features and mineral features from the environmental perception data, and learning the mineral characteristics based on the identification results of the mineral features includes: The environmental perception data is subjected to denoising and standardization processing in turn to obtain optimized environmental perception data; environmental characteristics are extracted from the optimized environmental perception data, and the environmental characteristics include temperature, humidity, light intensity, wind speed, moisture, and acidity and alkali; mineral characteristic parameters are calculated based on the environmental perception data, and the mineral characteristic parameters are used as inputs of a regression analysis model, and the regression analysis model is used to learn the relationship between ore characteristics.

[0041] In this optional embodiment, the calculation of mineral characteristic parameters based on environmental perception data includes: The Beer-Lambert law is used to calculate the light transmittance of the ore; and the Mohs hardness test technology is used to simulate the application of different stresses to test the toughness and obtain the toughness of the ore.

[0042] In this optional embodiment, the collected environmental data is analyzed through a machine learning algorithm to identify characteristics related to specific minerals (such as temperature anomalies, chemical composition anomalies, etc.), and the extracted characteristics are matched with a database of known minerals to confirm the type and properties of the mineral.

[0043] In this optional embodiment, the present invention has a mechanism for sensing ambient environmental parameters and extracting specified mineral characteristics and other attributes, and the ability to obtain ambient environmental parameters such as temperature, humidity, light intensity, wind force, moisture, acidity and alkali and other physical and chemical parameters, and at the same time has the ability to extract mineral characteristics such as ore shape, ore toughness, ore light transmittance and other mineral body characteristics. To achieve this function, it should have physical interception and local detection capabilities, wherein the mineral body characteristic extraction process includes: Sensor selection: Optical sensors are used to measure the light transparency and color of the ore, and can provide spectral data; mechanical sensors are used to measure the toughness of the ore (for example, measuring the compressive strength of the ore by applying pressure); geometric sensors are used to measure the shape and volume of the ore (such as laser rangefinder sensors).

[0044] Sensors detect events or changes in the environment and send information to other electronic devices, usually computer processors. They are used in manufacturing and machinery, aircraft and aerospace, automobiles, medicine, robotics and many aspects of daily life. The application of sensors has gone beyond the traditional field of temperature, pressure or flow measurement. The characteristics of sensors include miniaturization, digitization, intelligence, multi-function, systematization and networking. They are the primary link to achieve automatic detection and automatic control. They are usually divided into more than a dozen categories according to their basic sensing functions, including thermal sensors, photosensitive elements, gas sensors, force sensors, magnetic sensors, humidity sensors, sound sensors, radiation sensors, color sensors and taste sensors.

[0045] Temperature sensor refers to a sensor that can sense temperature and convert it into a usable output signal. It is an important part of energy sensing and can sense energy conversion in a relatively fixed space. Temperature sensor is the core part of temperature measuring instruments and there are many varieties. According to the measurement method, it can be divided into contact and non-contact types. According to the sensor material and electronic component characteristics, it can be divided into thermal resistors and thermocouples.

[0046] Optical sensor is a sensor that measures based on optical principles. It has many advantages, such as non-contact and non-destructive measurement, almost no interference, high-speed transmission, and remote measurement and remote control. It mainly includes general optical metrology instruments, laser interferometer, grating, encoder, and fiber optic optical sensors and instruments. It is mainly designed to detect whether the target object appears, or to perform motion detection in various industries, automobiles, electronic products, and retail automation.

[0047] Integrated sensors are sensors made using silicon semiconductor integration technology, so they are also called silicon sensors or monolithic integrated sensors. Analog integrated sensors are special ICs that integrate sensors on a chip and can complete measurement and analog signal output functions. The main features of analog integrated sensors are single function (only measuring a certain physical quantity), small measurement error, low price, fast response speed, long transmission distance, small size, micro power consumption, etc. They are suitable for long-distance measurement and control, do not require nonlinear calibration, and have simple peripheral circuits.

[0048] Data acquisition: The physical and chemical parameter data of the ore are collected in real time through sensors and converted into digital signals.

[0049] Noise filtering: Use digital filtering algorithms (such as Kalman filtering) to remove noise during data collection and standardize the collected data to make it suitable for subsequent analysis and modeling.

[0050] Characteristic calculation: Calculate the characteristic parameters of the ore, including toughness, light transmittance, etc.

[0051] Light transmittance calculation: The light transmittance of the ore is calculated using the Beer-Lambert law, where the calculation formula of the Beer-Lambert law is: ; In the formula, T Indicates light transmittance; I Indicates the intensity of transmitted light; I 0 represents the incident light intensity; α represents the absorption coefficient; L Indicates the optical path length.

[0052] Algorithms such as support vector machines, decision trees, and random forests can be used for classification and regression analysis to identify different ore types and characteristics. These models can learn the relationship between ore characteristics and their chemical composition and physical properties through training data.

[0053] Standard data communication protocols (such as MQTT, CoAP, etc.) are used to achieve communication between devices, ensuring that the collected parameters and feature data can be transmitted to the cloud in a timely manner for deeper analysis.

[0054] In this optional embodiment, the environmental characteristics and mineral characteristics are stored in the blockchain, and the environmental characteristics and mineral characteristics are judged to be in accordance with the preset standards respectively, including: The environmental characteristics and mineral characteristics are compared with the standard data in the local database respectively. If the environmental characteristics and mineral characteristics are within the preset range, they are judged to meet the standards; certificate parameters and geographical attributes corresponding to the environmental characteristics and mineral characteristics that meet the standards are generated, and the generated certificate parameters and geographical attributes are stored in the blockchain; the stored environmental characteristics and mineral characteristics are compared with the historical data for a second time, and early warning measures are formulated based on the results of the second comparison.

[0055] In this optional embodiment, the local calculation identifies whether the environmental conditions and mineral physical characteristics meet the specified standards. After extracting the basic parameters, the environmental parameters and mineral physical characteristics parameters are judged in the local computing environment, and compared with the basic database stored locally to determine whether they meet the specified standards. In order to achieve this function, the present invention should have a certain computing power and storage capacity of the local parameter library. Since the local detection time is short, local calculation can quickly obtain detection results and improve detection accuracy on the one hand, and get rid of the dependence on large bandwidth networks on the other hand, which is more suitable for areas with poor basic networks, such as mines. In the local computing environment, the process of judging environmental parameters and mineral physical characteristics parameters generally includes the steps of data collection, feature extraction, data comparison and judgment result output, and its main implementation process includes: Remove noise and outliers from the data, such as using the Z-score (standard score) technique to identify and remove outliers, where the expression of the Z-score is: ; In the formula, Z Indicates Z-score; X represents the sample value; μ represents the sample mean; σ represents the sample standard deviation.

[0056] The feature calculation is performed based on the collected parameters, and the set threshold is used to determine whether the collected parameters meet the standard. T > T min and T < T max , then the judgment result meets the standard, otherwise, it means that the judgment result does not meet the standard, where T Indicates the acquisition parameters, T min Indicates the lower limit standard of temperature, T max Indicates the upper limit standard of temperature.

[0057] Use SQL query or NoSQL query function to compare the collected parameters with the standard data in the local database, which contains environmental standards and mineral characteristics standard data. The database can be a relational database (such as SQLite) or a non-relational database (such as MongoDB).

[0058] In this optional embodiment, the standard data includes environmental parameter standards and mineral physical characteristics standards, wherein the environmental parameter standards include: Temperature: Set minimum and maximum temperature range, e.g. 20°C <T<30°C; Humidity: standard range of relative humidity, for example, 30% ≤ H ≤ 70%; Light intensity: the minimum light intensity that needs to be achieved, for example, light intensity>100lx; Wind force: Wind speed should be within a certain range, for example 0m / s <V≤10m / s; Moisture: Standard range of moisture content, e.g. 5% <W<15%; Acidity: pH range, for example 6.0≤pH<8.0.

[0059] Mineral physical characteristics standards include: Ore shape: The geometric characteristics (such as size, shape, etc.) of a specific ore, usually expressed in standard shapes and size ranges.

[0060] Ore toughness: Based on Mohs hardness, it may be set to a certain range, such as 3≤hardness<7; Light transmittance: Light transmittance should be within a certain range, for example T>0.5.

[0061] Furthermore, the present invention should store the full-cycle parameters of the target environment and target mineral body, such as the climate fluctuations of the mine since spring, the morphological characteristics of the ore since mining, and generate unique certificate parameters or regional attributes to achieve the non-replicability and information accuracy of the target environment and target mineral body. In order to achieve the extraction and collection of premature mature minerals, the present invention can have the ability to collect mineral bodies in batches, such as mining capabilities, and should also be synchronized to the network for reference at any time, which mainly includes: Climate data collection: Since spring, the terminal has regularly collected and stored climate factors, including temperature, humidity, precipitation, light intensity, wind speed, etc. The real-time data obtained by the sensor will be recorded in the local database.

[0062] Data timestamp: Each data collection is attached with a timestamp so that it can be traced back to the specific time during subsequent analysis.

[0063] Recording of ore morphological characteristics: Starting from the ore sprouting stage, regularly record the ore's shape, color, toughness, light transmittance and other parameters. The changes of each parameter at different growth stages should be recorded in detail.

[0064] Growth cycle data: Completely record the growth cycle of the ore, including the germination, growth, maturity and other stages, to form a complete ore growth file.

[0065] Certificate parameter generation: Use environmental data and mineral data to generate a unique certificate parameter, such as a fingerprint generated by a hash algorithm. The expression of the hash algorithm is: ; In the formula, E A string representing climate and environmental parameters; M A string representing the characteristic parameters of the ore; It means to concatenate two strings. Hash Indicates the generated hash value, which is used as the unique identifier of the certificate parameter.

[0066] Regional attribute recording: Collected environmental and mineral data are combined with specific geographic coordinates and terrain features to form regional attributes. For example, GPS coordinates, terrain type and soil composition are combined to form a unique description of the area.

[0067] Data uniqueness: The uniqueness of each data set is ensured by the timestamp of each collection, the history of environmental changes, and the growth cycle of the ore. Even if similar sampling is carried out at different times and conditions, the data results will be different due to environmental changes, thus achieving non-replicability.

[0068] Blockchain technology: Store the generated certificate parameters and geographical attributes on the blockchain to ensure the security and immutability of the data.

[0069] Data consistency verification: By comparing the currently collected environmental and ore parameters with historical data, statistical methods (such as mean, standard deviation, etc.) are used to check data consistency.

[0070] Real-time monitoring and alarms: Set thresholds and issue alarms in time when the collected parameters exceed the historical data range to ensure data accuracy.

[0071] In this optional embodiment, the prediction of the environmental situation and the mineral situation based on the judgment results of the environmental characteristics and the mineral characteristics respectively includes: A linear regression model is used to make a preliminary prediction of the optimized environmental perception data to obtain preliminary prediction results of the environmental situation and mineral situation; the data range of the optimized environmental perception data is expanded, and the random forest algorithm is used to make a secondary prediction of the expanded environmental perception data to obtain secondary prediction results of the environmental situation and mineral situation; the preliminary prediction results and secondary prediction results of the environmental situation and mineral situation are integrated and analyzed to form a comprehensive situation prediction report, and mining measures are formulated based on the comprehensive situation prediction report.

[0072] In this optional embodiment, the mechanism of multi-stage prediction of environmental situation and mineral situation in local and cloud is not enough if it only has the judgment of current environmental and mineral signs. The present invention should have the ability to predict environmental situation and mineral situation. Considering that the prediction itself requires large data storage, the present invention should have the mechanism of multi-stage prediction of environmental situation and mineral situation in local and cloud, that is, with the help of small sample library locally, complete the preliminary environmental situation and mineral situation prediction. For example, when the target environment is a mine and the target mineral is ore, its current storage location can be determined, and later with the help of networked big data, more accurate and comprehensive information situation prediction can be carried out, which mainly includes: Local data storage should include environmental and mineral data over a period of time, such as climate change, ore morphology, and mining activity data. These data form a preliminary sample library and provide a basis for small sample predictions.

[0073] Environmental parameters (such as temperature, humidity, air pressure) and mineral parameters (such as ore type, shape, quality) are collected and recorded regularly.

[0074] The linear regression model is used to make preliminary predictions on environmental and mineral data, and future trends are predicted through historical data. The linear regression model is expressed as: ; In the formula, Y represents the parameter to be predicted (e.g. future temperature); X represents an independent variable (such as time or other environmental factors); represents the intercept; represents the slope (reflecting the degree of influence of environmental factors on the predicted parameters); e represents the error term.

[0075] In this optional embodiment, the prediction result is combined to determine whether the current storage location of the ore meets the conditions for mining or observation. For example, by comparing the predicted temperature and humidity with the threshold value of the historical data, it is determined whether the ore is in a safe storage state.

[0076] Through network connection, a wider range of environmental and mineral data can be obtained, including data from other mining areas, meteorological stations and research institutions. The data in the cloud will provide a more comprehensive reference for small local samples.

[0077] In the cloud, more complex models (such as random forests, neural networks, etc.) are used for multivariate prediction. These models can handle more complex data relationships and large-scale data sets, and improve the accuracy of predictions. The expression for secondary prediction of the expanded environmental perception data using the random forest algorithm is: ; In the formula, f ( x ) represents the secondary prediction output result; N represents the number of numbers in the forest; h i ( x ) indicates the i The prediction results of the tree.

[0078] Combine local preliminary forecast results with detailed data analysis results in the cloud to form a comprehensive situation report, which includes environmental risk assessment and mineral mining recommendations.

[0079] Set up an automated monitoring system to issue alerts based on forecast results. For example, when it is predicted that certain weather conditions may cause safety hazards in mines, the system should promptly notify relevant personnel for early warning.

[0080] Based on the comprehensive forecast results, managers can make more accurate decisions, such as adjusting mining plans, optimizing storage methods, and arranging maintenance.

[0081] By combining the prediction mechanism of local small samples with cloud big data, the present invention realizes efficient monitoring and prediction of environmental and mineral situations. This multi-stage prediction mechanism not only provides preliminary trend analysis, but also can make more in-depth situation judgments with the advantages of big data, ensuring the scientificity and timeliness of mineral management. At the same time, this system also provides real-time support for responding to potential risks and improves the safety and efficiency of overall mine operations.

[0082] In this optional embodiment, the comprehensive evaluation of ore mineability based on the prediction results of the environmental situation and the mineral situation through a pre-established decision cluster includes: Define fuzzy sets and use membership functions to describe the fuzzy state of ore characteristics; self-organize decision clusters through wireless networks, and individuals in the decision cluster share environmental characteristics, mineral characteristics and individual decision evaluation data in real time; collect individual decision evaluation data and assign weights to individual decisions based on the accuracy of individual historical decisions; combine the weight allocation results with pre-set decision principles to comprehensively evaluate the mineability of the ore; integrate the cluster decision results to generate a decision report, and establish a feedback mechanism to verify the accuracy of cluster decisions.

[0083] In this optional embodiment, the fuzzy judgment and group terminal cluster decision-making mechanism can form a decision cluster when judging some fuzzy indicators that cannot be accurately quantified, and make majority decisions based on their respective decision-making capabilities. For some indicators that are difficult to quantify, the present invention proposes self-organizing network group decision-making and the ability of the minority to obey the majority. For example, for the goal of whether the ore can be picked, the evaluation data of the group decision-making working in the current area should be collected, and the judgment should be made according to the weight distribution principle, and the typical principle is that the minority obeys the majority.

[0084] In mineral mining, some indicators such as the mineability of ore and environmental safety are often difficult to express with precise numerical values. For example, the texture, hardness, and adaptability of the ore to the environment may be affected by multiple factors, and there is uncertainty and ambiguity between these factors. For example, the membership function is used to describe the fuzzy state of ore characteristics between "mineable" and "unmineable".

[0085] Fuzzy set theory provides a method to deal with fuzziness and uncertainty. By defining fuzzy sets, elements are allowed to belong to the set to some extent, which facilitates the quantification of uncertainty. It mainly includes: Cluster formation: In the mining area, multiple terminals with decision-making capabilities can form a cluster through wireless networks. Each terminal is relatively independent in geographical location, but shares data and information through mutual connection.

[0086] Data Sharing: Environmental monitoring data, ore characteristics and personal decision-making assessments are shared between terminals in real time to form a holistic understanding of a specific situation.

[0087] Collect assessment data: Each terminal independently assesses the mineability of the ore, taking into account the environment and ore characteristics it perceives, and generates an assessment result. For example, a terminal may consider the mineability of the ore to be 0.6 (60% mineable).

[0088] Weight distribution principle: In order to ensure the fairness and accuracy of decision-making, each terminal in the cluster needs to be assigned a weight based on its historical decision accuracy, measurement capability and other factors. The weight can be calculated according to the following formula: The minority obeys the majority principle: After collecting the evaluations of all terminals, the cluster will make decisions through a simple voting mechanism, adopting the principle of "the minority obeys the majority". That is, if the evaluation results of most terminals indicate that the ore is mineable, it will be finally judged as mineable. For example, if 7 out of 10 terminals evaluate it as mineable and 3 evaluate it as unmineable, the final decision is that it is mineable.

[0089] Actual decision report: The cluster decision result will form a specific report, which should include the evaluation results, weight distribution and final selected decision of each terminal.

[0090] Real-time update: The report should be dynamically updated during the execution process to reflect the changes in the environment and ore in real time.

[0091] Subsequent evaluation: After the decision is implemented, it is necessary to continuously monitor the actual situation and collect data on the implementation effect to verify the accuracy of the decision. Through subsequent evaluation, the terminal can provide feedback on the accuracy of its decision and adjust the future weight distribution.

[0092] Learning and Optimization: The cluster can optimize its decision-making process by learning from historical decision-making results. Based on feedback data, the model can adjust itself to improve the accuracy of future decisions.

[0093] The present invention should be in a fixed form or three mobile forms. The fixed form is fixed at a certain location such as a signal post or a signal tower. The mobile form includes air-based forms such as aircraft, drones, airships, etc., land-based forms such as unmanned vehicles, conventional vehicles, water-based forms such as unmanned ships, boats, submarines, and portable forms such as human or animal power. The power supply method can be solar energy, hydropower, wind energy, or nuclear energy.

[0094] Figure 2 An embodiment of a situation awareness system based on the Internet of Things of the present invention is shown.

[0095] In this optional embodiment, the situational awareness system based on the Internet of Things includes: The environment perception module 201 is used to collect environment perception data and extract environmental characteristics and mineral characteristics from the environment perception data; The local computing module 203 is used to store the environmental characteristics and the mineral characteristics in the blockchain, and to determine whether the environmental characteristics and the mineral characteristics meet the preset standards; The situation prediction module 205 is used to predict the environmental situation and the mineral situation based on the judgment results of the environmental characteristics and the mineral characteristics respectively; The decision evaluation module 207 is used to comprehensively evaluate the mineability of the ore based on the prediction results of the environmental situation and the mineral situation through a pre-established decision cluster.

[0096] In this optional embodiment, the environment perception module 201 includes: The environment acquisition module is used to integrate the data collected by multiple types of sensors to obtain environment perception data, and convert the environment perception data into digital signals and store them in the local cache; The feature recognition module is used to analyze environmental perception data, identify environmental features and mineral features from the environmental perception data, and learn mineral characteristics based on the recognition results of mineral features.

[0097] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0098] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0099] In addition, the present invention also provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiment when executing the computer program.

[0100] In addition, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented.

[0101] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0102] The present invention is not limited to the structures which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A situation awareness method based on the Internet of Things, characterized in that: The IoT-based situational awareness approach includes: Collect environmental perception data and extract environmental characteristics and mineral characteristics from the environmental perception data; The environmental characteristics and mineral characteristics are stored in the blockchain, and the environmental characteristics and mineral characteristics are judged to see whether they meet the preset standards; Based on the judgment results of environmental characteristics and mineral characteristics, the environmental situation and mineral situation are predicted respectively; Based on the prediction results of environmental situation and mineral situation, the mineability of ore is comprehensively evaluated through the pre-established decision cluster.

2. The situation awareness method based on the Internet of Things according to claim 1 is characterized in that: The collecting of environmental perception data and extracting environmental characteristics and mineral characteristics from the environmental perception data include: Integrate data collected by multiple types of sensors to obtain environmental perception data, convert the environmental perception data into digital signals and store them in local cache; Analyze environmental perception data, identify environmental characteristics and mineral characteristics from the environmental perception data, and learn mineral characteristics based on the identification results of mineral characteristics.

3. A situation awareness method based on the Internet of Things according to claim 2, characterized in that: The analyzing of the environmental perception data, identifying environmental features and mineral features from the environmental perception data, and learning the mineral characteristics based on the identification results of the mineral features include: The environmental perception data is subjected to denoising and standardization processing in turn to obtain optimized environmental perception data; Extracting environmental features from the optimized environmental perception data, wherein the environmental features include temperature, humidity, light intensity, wind speed, water content, and acidity and alkali; Mineral characteristic parameters are calculated based on environmental perception data, and the mineral characteristic parameters are used as input of the regression analysis model, and the regression analysis model is used to learn the relationship between ore characteristics.

4. The situation awareness method based on the Internet of Things according to claim 3 is characterized in that: The calculation of mineral characteristic parameters based on environmental perception data includes: The light transmittance of the ore is calculated using the Beer-Lambert law, wherein the calculation formula of the Beer-Lambert law is: ； In the formula, T Indicates light transmittance; I Indicates the intensity of transmitted light; I 0 represents the incident light intensity; α represents the absorption coefficient; L represents the optical path length; The Mohs hardness test technology is used to simulate the application of different stresses to test the toughness and obtain the toughness of the ore.

5. A situation awareness method based on the Internet of Things according to claim 4, characterized in that: The storing of environmental characteristics and mineral characteristics in the blockchain and respectively judging whether the environmental characteristics and mineral characteristics meet the preset standards include: The environmental characteristics and mineral characteristics are respectively compared with the standard data in the local database. If the environmental characteristics and mineral characteristics are both within the preset range, it is determined that the environmental characteristics and mineral characteristics meet the standards; Generate certificate parameters and geographical attributes corresponding to environmental characteristics and mineral characteristics that meet the standards, and store the generated certificate parameters and geographical attributes in the blockchain; The stored environmental characteristics and mineral characteristics are compared with historical data for the second time, and early warning measures are formulated based on the results of the secondary comparison.

6. A situation awareness method based on the Internet of Things according to claim 5, characterized in that: The prediction of the environmental situation and the mineral situation based on the judgment results of the environmental characteristics and the mineral characteristics respectively includes: The optimized environmental perception data is preliminarily predicted using a linear regression model to obtain preliminary prediction results of the environmental situation and mineral situation; Expand the data range of the optimized environmental perception data, and use the random forest algorithm to perform secondary prediction on the expanded environmental perception data to obtain secondary prediction results of environmental situation and mineral situation; The preliminary and secondary forecast results of environmental and mineral situations are integrated and analyzed to form a comprehensive situation forecast report, and mining measures are formulated based on the comprehensive situation forecast report.

7. A situation awareness method based on the Internet of Things according to claim 6, characterized in that: The expression for performing secondary prediction on the expanded environmental perception data using the random forest algorithm is: ； In the formula, f ( x ) represents the secondary prediction output result; N represents the number of numbers in the forest; h i ( x ) indicates the i The prediction results of the tree.

8. The situation awareness method based on the Internet of Things according to claim 7 is characterized in that: The above-mentioned comprehensive evaluation of ore mineability based on the prediction results of environmental situation and mineral situation through the pre-established decision cluster includes: Define fuzzy sets and use membership functions to describe the fuzzy states of ore characteristics; Self-organize decision clusters through wireless networks, and individuals in the decision clusters share environmental characteristics, mineral characteristics and individual decision evaluation data in real time; Collect individual decision evaluation data and assign weights to individual decisions based on the accuracy of individual historical decisions; combine the weight assignment results with pre-set decision principles to comprehensively evaluate the mineability of the ore; The cluster decision results are integrated to generate a decision report, and a feedback mechanism is established to verify the accuracy of cluster decisions.

9. A situational awareness system based on the Internet of Things, characterized in that: The IoT-based situational awareness system includes: Environmental perception module, used to collect environmental perception data and extract environmental characteristics and mineral characteristics from the environmental perception data; A local computing module is used to store environmental characteristics and mineral characteristics in the blockchain and to determine whether the environmental characteristics and mineral characteristics meet the preset standards; A situation prediction module is used to predict the environmental situation and mineral situation based on the judgment results of environmental characteristics and mineral characteristics respectively; The decision-making evaluation module is used to comprehensively evaluate the mineability of ore based on the prediction results of environmental situation and mineral situation through a pre-established decision cluster.

10. The situational awareness system based on the Internet of Things according to claim 9, characterized in that: The environment perception module comprises: The environment acquisition module is used to integrate the data collected by multiple types of sensors to obtain environment perception data, and convert the environment perception data into digital signals and store them in the local cache; The feature recognition module is used to analyze environmental perception data, identify environmental features and mineral features from the environmental perception data, and learn mineral characteristics based on the recognition results of mineral features.

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