Smart forest management system and its management method

Abstract

A smart forest management system and its management method, which solves the problems of inaccurate wood classification, low efficiency of resource management and insufficient carbon emission analysis in the existing forestry management, through the front-end equipment, the types of forestry materials can be automatically classified and labeled to reduce manual errors and improve the accuracy of classification, the system is equipped with cloud data processing and artificial intelligence (AI) analysis functions, and is integrated with geographic information system (GIS) to accurately record the geographical location, stock and health status of wood resources, the system also has a wood inventory management and sales management module to update the wood inventory in real time and improve the efficiency of market transactions. Further, a carbon emission calculation module can accurately calculate the carbon footprint based on wood sales data to support the decision-making of enterprises in environmental, social and governance (ESG) assessment.

Description

Technical Field

[0001] This invention relates to the field of forestry material management, and in particular to a smart forestry management system and its management methods. Prior Technology

[0002] Forestry today faces a number of challenges, including inaccurate timber classification, inefficient resource management, and a lack of data to support carbon emissions analysis. These issues limit the sustainable development of the forestry industry and its contribution to environmental, social, and governance (ESG) assessments.

[0003] First, timber is diverse in species and characteristics, and traditional manual classification methods are time-consuming and labor-intensive, and prone to errors due to human factors. Incorrect timber classification can affect downstream processing and market pricing, further leading to resource waste.

[0004] Secondly, timber stacking and storage management is inefficient. Traditional methods often lack systematic planning regarding the location and quantity of timber, resulting in low space utilization and an inability to respond quickly to changes in demand. For timber resources distributed across different forest farms or schools, the lack of a real-time monitoring system further exacerbates management difficulties, making it impossible to accurately grasp inventory status.

[0005] Third, with the increasing demand for ESG assessments from enterprises, carbon emissions have become a key indicator in forestry management. However, traditional timber production and management methods lack the technical support for accurate calculation and analysis of carbon emissions, which makes it difficult for enterprises to formulate environmentally friendly policies or conduct ESG reports.

[0006] Furthermore, "afforestation adoption," as a solution for companies to improve their environmental scores in ESG assessments, faces implementation difficulties. Companies lack quantifiable references for the long-term effectiveness of afforestation adoption, making it difficult to accurately assess carbon absorption capacity or other environmental benefits. At the same time, the long-term maintenance and management after afforestation exceeds the scope of companies' core competencies, leading to low adoption willingness or poor actual results.

[0007] Therefore, in response to the above challenges, there is an urgent need for a forestry timber classification and management system that features automated timber classification, efficient resource management, and carbon emission analysis data support. This system would improve forestry management efficiency and the accuracy of corporate ESG assessments, thereby promoting sustainable development and commercial value in forestry. Summary of the Invention

[0008] To overcome the aforementioned technical problems, the present invention aims to provide a smart forestry management system and its management method to solve the problems of inaccurate timber classification, low resource management efficiency, and insufficient carbon emission analysis in traditional forestry management. The present invention uses front-end devices for image acquisition, combining Global Positioning System (GPS) and image recognition technology to achieve automatic classification and labeling of timber species, improving classification accuracy and reducing human error. Simultaneously, the present invention provides cloud data processing and artificial intelligence (AI) analysis functions for image data processing and integration with Geographic Information System (GIS) to accurately record the geographical location, inventory, and health status of timber resources. Furthermore, the system has built-in timber inventory management and sales management modules, which can automatically update timber inventory information based on real-time data, improving the efficiency of timber dispatch and market transactions.

[0009] To achieve the above objectives, the present invention provides a smart forestry management system, comprising at least one front-end device, a cloud system, and at least one interactive electronic device; wherein, Each of the front-end devices includes an image recognition module and a positioning module; the image recognition module is used to capture images to form image information, and the positioning module is used to provide geographical location information for forming the image information; each of the front-end devices is connected to the cloud system via a first communication module. The cloud system includes a central processing unit (CPU) and an application interface, an AI data analysis module, a timber inventory management module, a timber sales management module, and a database connected to the CPU. The CPU receives image information and geographic location information, and uses this information to annotate and form a spatial image dataset that maps the spatial coordinates of the timber to the corresponding images. The AI ​​data analysis module receives and processes the image information, geographic location information, and spatial image dataset through the CPU to output geographic data and forest resource data. The timber sales management module has built-in timber sales data. The timber inventory management module has built-in timber inventory data and updates the timber inventory data by reading the geographic data, forest resource data, and / or timber sales data. The database stores historical data built into, input, or processed by the smart forestry management system. Each interactive electronic device is connected to the application interface of the cloud system via a second communication module. Each interactive electronic device reads the image information, the geographical location information, the geographical data, the forest resource data, the timber sales data, and the timber inventory data through the application interface. The interactive electronic device updates the timber sales data of the timber sales management module by connecting to the application interface.

[0010] According to the intelligent forestry management system of the present invention, the cloud system further includes a graphic presentation module and a report generation module; the graphic presentation module is communicatively connected to the central processing unit to read the geographic data, the forest resource data, the timber sales data and the timber inventory data, process the data, and output a report generation data; the report generation module is communicatively connected to the central processing unit to read the report generation data and output a forestry material report accordingly.

[0011] According to the intelligent forestry management system of the present invention, the cloud system further includes a carbon emission calculation module. This module contains carbon emission conversion data for calculating the carbon emissions of timber. The module communicates with the central processing unit to read timber sales data and, based on the carbon emission conversion data, outputs a carbon emission calculation result. Thus, by incorporating this carbon emission calculation module, the present invention achieves accurate calculation of the forestry carbon footprint by reading timber sales data and carbon emission conversion data, thereby enhancing enterprises' data support and decision-making capabilities in environmental, social, and governance (ESG) assessments.

[0012] According to the intelligent forestry management system of the present invention, the front-end device is selected from a drone or photographic device with a built-in Global Positioning System (GPS). In embodiments of the present invention, the photographic device can be selected from a camera, surveillance camera, mobile phone or tablet computer with built-in camera function, etc.

[0013] According to the intelligent forestry management system of the present invention, the AI ​​data analysis module is based on deep learning for image processing using a convolutional neural network (CNN) to extract image features and perform classification.

[0014] This invention also provides a smart forestry management method, the steps of which include: Data collection steps: Use at least one front-end device to collect timber data from the forest farm or timber yard; each front-end device captures images through its built-in image recognition module to form image information, and embeds geographic location information into the image information through its built-in positioning module; Data annotation steps: Through manual annotation or automatic annotation by front-end devices, a spatial image dataset is formed that corresponds to the spatial coordinates of the timber and the image. AI model training steps: Upload the image information, the geographic location information, and the spatial image dataset to an AI data analysis module in a cloud system for model building and deep learning, and output geographic data and forest resource data after processing; Timber management steps: One of the cloud systems, the timber sales management module, has built-in timber sales data; another of the cloud systems, the timber inventory management module, has built-in timber inventory data and updates the timber inventory data by reading the geographic data, the forest resource data, and / or the timber sales data; and a database in the cloud system stores historical data that is built-in, input, or calculated. Forestry material data output steps: Using at least one interactive electronic device, a communication connection is made from one of the application interfaces of the cloud system to the timber inventory management module, the timber sales management module, and the database to read the image information, the geographic location information, the geographic data, the forest resource data, the spatial image dataset, the timber sales data, and the timber inventory data. The interactive electronic device updates the timber sales data of the timber sales management module by connecting to the application interface.

[0015] According to the intelligent forestry management method of the present invention, the cloud system further includes a graphic presentation module and a report generation module; in the forestry material data output step, the graphic presentation module reads the geographic data, the forest resource data, the spatial image dataset, the timber sales data and / or the timber inventory data to perform data processing and output a report generation data; the report generation module reads the report generation data to output a forestry material report.

[0016] According to the smart forestry management method of the present invention, in the data collection step, the front-end device is selected from a drone or a photography device with a built-in Global Positioning System (GPS).

[0017] According to the intelligent forestry management method of the present invention, in the AI ​​model training step, the AI ​​data analysis module is based on deep learning for image processing using convolutional neural networks (CNN) to extract image features and perform classification.

[0018] Regarding the techniques, means, and other effects adopted by the present invention to achieve the above objectives, preferred embodiments are described in detail below with reference to the accompanying drawings. Simple Explanation of the Diagram

[0019] Figure 1 is a schematic diagram of the architecture of the intelligent forestry management system of the present invention; Figure 2 is a schematic diagram of the steps of the intelligent forestry management method of the present invention. Implementation

[0020] To facilitate understanding of the present invention, the following description is provided in conjunction with the embodiments shown in Figures 1 and 2.

[0021] As shown in Figure 1, the smart forestry management system of the present invention includes at least one front-end device 10, a cloud system 30, and at least one interactive electronic device 40; wherein, the front-end device 10 can communicate with the cloud system 30 through a first communication module 20, and the interactive electronic device 40 can communicate with the cloud system 30 through a second communication module 50.

[0022] Specifically, as shown in Figure 1, each front-end device 10 has an image recognition module 11 and a positioning module 12; the image recognition module 11 is used to capture images to form image information, and the positioning module 12 is used to provide geographic location information for forming the image information; each front-end device 10 is connected to the cloud system 30 through a first communication module 20. The image information may include image and / or video data; the geographic location information may include data on the location of the front-end device 10 and the location of the forestry materials being captured.

[0023] In this embodiment of the invention, the front-end device 10 is selected from a drone or a camera device with a built-in Global Positioning System (GPS). More specifically, the camera device can be selected from a camera, surveillance camera, mobile phone or tablet computer with built-in camera function, etc. Further, taking a drone as an example, the image recognition module 11 can be a high-resolution camera and / or LiDAR (Light Detection and Ranging, LIDAR), and the positioning module 12 can be the GPS built into the drone; thereby, it is possible to quickly cover a large area of ​​forest, accurately measure the height, crown width and density of trees, generate three-dimensional forest structure data, and realize large-scale monitoring of forest farms and / or timber yards and inventory of timber resources.

[0024] Specifically, as shown in Figure 1, the cloud system 30 includes a central processing unit 31 and an application interface 32, an AI data analysis module 33, a timber inventory management module 34, a timber sales management module 35, a carbon emission calculation module 36, a graphic presentation module 37, a report generation module 38, and a database 39 connected to the central processing unit 31.

[0025] The central processing unit 31 receives the image information and the geographic location information, and uses them to annotate and form a spatial image dataset that corresponds to the spatial coordinates of the timber and the image. The AI ​​data analysis module 33 receives and processes the image information, the geographic location information, and the spatial image dataset through the central processing unit 31 to output geographic data and forest resource data. The timber sales management module 35 has timber sales data built in. The timber inventory management module 34 has timber inventory data built in and updates the timber inventory data by reading the geographic data, the forest resource data, and / or the timber sales data. The database 39 stores historical data built in, input, or calculated by the smart forestry management system.

[0026] The geographic data includes geographical and spatial data such as the location and topography of forestry materials; the timber resource data includes data on the type, size, quantity, and health status of forestry materials; the timber inventory data includes data on the type, size, quantity, location, and health status of managed forestry materials; and the timber sales data includes data on the purchase and sale quantities of managed forestry materials. All of the aforementioned data are aggregated and stored in this database 39 to form this historical data.

[0027] In this embodiment of the invention, the AI ​​data analysis module 33 is based on deep learning using a convolutional neural network (CNN) for image processing to extract and classify image features. More specifically, the convolutional neural network (CNN) refers to a deep learning architecture specifically designed for image processing to automatically extract and classify image features. During the operation of the CNN, the AI's inference can be divided into two main stages: feature extraction and classification, ultimately generating a probabilistic distribution to determine the classification of the image content.

[0028] More specifically, the AI ​​data analysis module 33 of this invention is combined with a geographic information system (GIS) to integrate geographic data, forest resource data and spatial image datasets to record and analyze the geographical location, species and health status of each tree, and provide visualized data analysis and prediction functions to achieve the purpose of asset management and planning decisions.

[0029] The graphic presentation module 37 is connected to the central processing unit 31 to read the geographic data, forest resource data, timber sales data and timber inventory data, process the data and output a report generation data; the report generation module 38 is connected to the central processing unit 31 to read the report generation data and output a forestry material report accordingly.

[0030] The carbon emission calculation module 36 has built-in carbon emission conversion data for calculating the carbon emissions of wood. The carbon emission calculation module 36 is connected to the central processing unit 31 to read the wood sales data and output a carbon emission calculation result after calculating based on the carbon emission conversion data.

[0031] Specifically, as shown in Figure 1, each of the interactive electronic devices 40 is connected to the application interface 32 of the cloud system 30 through a second communication module 50. Each of the interactive electronic devices 40 reads the image information, the geographical location information, the geographical data, the forest resource data, the timber sales data, and the timber inventory data through the application interface 32. The interactive electronic devices 40 update the timber sales data of the timber sales management module 35 by connecting to the application interface 32.

[0032] In this embodiment of the invention, the interactive electronic device 40, connected to the application interface 32, forms an interface tool for users of the system to interact with the smart forestry management system. Users can read required data or input sales data through the interactive electronic device 40 and receive personalized reports generated by the system. Specifically, the interactive electronic device 40 refers to a device with wireless and / or wired communication functions, and input and display functions. It can be a smartphone, tablet computer, desktop computer, or laptop computer. As shown in Figure 1, the interactive electronic device 40 is bidirectionally connected to the application interface 32 and the report generation module 38 to constitute the main interaction method between the user and the system.

[0033] In this embodiment of the invention, the first communication module 20 may be a short-range, medium-range, and / or long-range wireless communication network, specifically Wi-Fi, Bluetooth, Zigbee, LoRa (Long Range), NB-IoT (Narrowband IoT), Sigfox, LTE network, and / or satellite communication, in that order. The second communication module 50 is preferably a wireless communication network; specifically, it may be a Wi-Fi and / or LTE network.

[0034] The above describes the specific implementation of the intelligent forestry management system of the present invention. The following, with reference to Figure 2, illustrates the implementation of the operation of the present invention based on the step flow of the intelligent forestry management method.

[0035] As shown in Figure 2, the steps of the intelligent forestry management method of the present invention include a data collection step S1, a data labeling step S2, an AI model training step S3, a timber management step S4, a carbon emission calculation step S5, and a forestry material data output step S6.

[0036] In the data collection step S1, at least one of the aforementioned front-end devices 10 is used to collect timber data from the forest farm or timber yard. Each front-end device 10 captures images through its built-in image recognition module 11 to form image information, and embeds the corresponding geographical location information into the image information through its built-in positioning module 12.

[0037] In the data annotation step S2, a spatial image dataset is formed by manually annotating or automatically annotating by the front-end device 10 to correspond the spatial coordinates of the timber to the image. In this embodiment of the invention, manual annotation is performed by the user accessing the cloud system 30 through the interactive electronic device 40, and then reading and inputting the data corresponding to the spatial coordinates of the timber to the image through the application interface 32 to achieve the purpose of annotating the timber. Automatic annotation by the front-end device 10 is performed by the built-in central processing unit of the front-end device 10 to annotate the data corresponding to the spatial coordinates of the timber to the image based on the image information and the geographical location information.

[0038] In the AI ​​model training step S3, the image information, the geographic location information, and the spatial image dataset are uploaded to an AI data analysis module 33 in a cloud system 30 for model building and deep learning, and after processing, geographic data and forest resource data are output.

[0039] In the timber management step S4, timber sales data is built into the timber sales management module 35 of the cloud system 30; timber inventory data is built into the timber inventory management module 34 of the cloud system 30 and the timber inventory data is updated by reading the geographic data, the forest resource data and / or the timber sales data; and historical data generated by the built-in, input or calculation is stored in the database 39 of the cloud system 30.

[0040] In the carbon emission calculation step S5, the carbon emission calculation module 36 has built-in carbon emission conversion data for calculating the carbon emission of wood. The carbon emission calculation module 36 reads the wood sales data and calculates and outputs a carbon emission calculation result based on the carbon emission conversion data.

[0041] In the forestry material data output step S6, at least one interactive electronic device 40 is used to communicate with the timber inventory management module 34, the timber sales management module 35 and the database 39 from one of the application interfaces 32 of the cloud system 30 to read the image information, the geographic location information, the geographic data, the forest resource data, the spatial image dataset, the timber sales data and the timber inventory data. The interactive electronic device 40 updates the timber sales data of the timber sales management module 35 by connecting to the application interface 32.

[0042] In this embodiment of the invention, the forestry material data output step S6 further includes the following steps: the image and text presentation module 37 reads the geographic data, the forest resource data, the spatial image dataset, the timber sales data, and / or the timber inventory data and processes the data to output a report generation data; then the report generation module 38 reads the report generation data to output a forestry material report, allowing users to quickly grasp relevant information about forestry materials.

[0043] In summary, the intelligent forestry management system and its management method of this invention utilize drones or photographic devices for image acquisition and geolocation, and process and analyze data through a cloud system to provide comprehensive forest resource management. This system integrates image recognition, Global Positioning System (GPS), AI deep learning, and Geographic Information System (GIS) technologies, enabling accurate labeling of timber spatial coordinates and automatic generation of three-dimensional forest structure data to facilitate monitoring of forest farms and timber yards and timber resource inventory. The AI ​​data analysis module employs Convolutional Neural Network (CNN) technology to automatically extract image features, analyze timber species, health status, and geographical distribution, and combine this with GIS for visual management to optimize asset management and decision-making. Furthermore, the system includes a timber inventory and sales management module that automatically updates timber inventory information based on real-time data, improving the transparency and efficiency of timber transactions. Simultaneously, the built-in carbon emission calculation module can estimate the carbon emissions of timber based on sales data, facilitating environmental supervision and carbon trading assessment. Through an application programming interface (API), users can access forestry data anytime via interactive electronic devices, query forest resource status, and obtain real-time reports, realizing an intelligent, data-driven forestry management model. Accordingly, this invention, through advanced wireless communication, cloud computing, and AI analysis technologies, significantly improves the accuracy and automation of forestry management, helps improve resource utilization efficiency, optimize forest conservation strategies, and supports carbon emission monitoring, providing an efficient and feasible solution for modern smart forestry.

[0044] 10: Front-end devices 11: Image Recognition Module 12: Positioning Module 20: First Communication Module 30: Cloud System 31: Central Processing Unit 32: Application Interface 33: AI Data Analysis Module 34: Timber Inventory Management Module 35: Timber Sales Management Module 36: Carbon Emission Calculation Module 37: Image and Text Presentation Module 38: Report Generation Module 39: Database 40: Interactive electronic devices 50: Second communication module S1: Data Collection Steps S2: Data Labeling Steps S3: AI Model Training Steps S4: Timber Management Steps S5: Carbon Emission Calculation Steps S6: Forestry Material Data Output Steps

Claims

1. A smart forestry management system, comprising at least one front-end device, a cloud system, and at least one interactive electronic device; wherein, Each of the front-end devices has an image recognition module and a positioning module; the image recognition module is used to capture images to form image information, and the positioning module is used to provide geographic location information for forming the image information; each of the front-end devices is connected to the cloud system via a first communication module; the cloud system includes a central processing unit (CPU) and an application interface, an AI data analysis module, a timber inventory management module, a timber sales management module, a carbon emission calculation module, and a database connected to the CPU; the CPU receives the image information and the geographic location information, and uses them to annotate and form a spatial image dataset corresponding to the spatial coordinates of the timber and the image; the AI ​​data analysis module receives and processes the image information, the geographic location information, and the spatial image dataset through the CPU to output geographic data and forest resource data; the timber The timber sales management module has built-in timber sales data; the timber inventory management module has built-in timber inventory data and updates the timber inventory data by reading geographic data, forest resource data, and / or timber sales data; the carbon emission calculation module has built-in carbon emission conversion data for calculating timber carbon emissions. The carbon emission calculation module communicates with the central processing unit to read the timber sales data and outputs a carbon emission calculation result after calculating based on the carbon emission conversion data; the database stores historical data built into, input, or calculated by the smart forestry management system; each interactive electronic device communicates with the application interface of the cloud system through a second communication module. Each interactive electronic device reads the image information, geographic location information, geographic data, forest resource data, timber sales data, timber inventory data, and carbon emission calculation result through the application interface; the interactive electronic device updates the timber sales data of the timber sales management module by connecting to the application interface.

2. The intelligent forestry management system as described in claim 1, wherein, The cloud system also includes a graphic presentation module and a report generation module; the graphic presentation module is connected to the central processing unit to read the geographic data, the forest resource data, the timber sales data and the timber inventory data, process the data and output a report generation data; the report generation module is connected to the central processing unit to read the report generation data and output a forestry material report accordingly.

3. The intelligent forestry management system as described in claim 1 or 2, wherein, The front-end device is selected from drones or photography devices with a built-in Global Positioning System (GPS).

4. The intelligent forestry management system as described in claim 1 or 2, wherein, This AI data analysis module is based on deep learning for image processing using convolutional neural networks (CNNs) to extract image features and perform classification.

5. A smart forestry management method, wherein, The method includes the following steps: Data collection: collecting timber data from forest farms or timber yards using at least one front-end device; each front-end device captures images using its built-in image recognition module to form image information, and embeds geographic location information into the image information using its built-in positioning module; Data annotation: automatically annotating the images using the front-end device to form a spatial image dataset corresponding to the spatial coordinates of the timber and the images; AI model training: uploading the image information, geographic location information, and spatial image dataset to an AI data analysis module in a cloud system for model building and deep learning, and outputting geographic data and forest resource data after processing; Timber management: a timber sales management module in the cloud system contains timber sales data; a timber inventory management module in the cloud system contains timber inventory data and updates the timber inventory data by reading the geographic data, forest resource data, and / or timber sales data; and a database in the cloud system stores historical data that is built-in, input, or processed. Carbon emission calculation steps: The carbon emission calculation module of the cloud system is used to read the timber sales data, and a carbon emission calculation result is calculated and output based on the carbon emission conversion data built into the carbon emission calculation module; Forestry material data output steps: At least one interactive electronic device is used to communicate with the timber inventory management module, the timber sales management module and the database through the application interface of the cloud system to read the image information, the geographic location information, the geographic data, the forest resource data, the spatial image dataset, the timber sales data, the timber inventory data and the carbon emission calculation result, and the interactive electronic device updates the timber sales data of the timber sales management module by connecting to the application interface.

6. The smart forestry management method as described in claim 6, wherein, The cloud system also includes a graphic presentation module and a report generation module; in the forestry material data output step, the graphic presentation module reads the geographic data, the forest resource data, the spatial image dataset, the timber sales data and / or the timber inventory data to process the data and output a report generation data; the report generation module reads the report generation data to output a forestry material report.

7. The smart forestry management method as described in claim 5, wherein, In this data collection step, the front-end device is selected from a drone or photographic device with a built-in GPS.

8. The smart forestry management method as described in claim 5, wherein, In the training step of this AI model, the AI ​​data analysis module is based on deep learning for image processing using convolutional neural networks to extract image features and perform classification.

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