Outdoor information collection device wireless data transmission method and system

Abstract

The application provides an outdoor information collection device wireless data transmission method and system, and relates to the technical field of outdoor information collection device wireless data transmission. The method comprises the following steps: acquiring the self remaining power of a monitoring unit, the priority of to-be-transmitted data, the real-time link quality and the remaining power of surrounding communication nodes; based on the self remaining power, the priority of to-be-transmitted data and the real-time link quality and the remaining power of surrounding communication nodes, performing multi-dimensional evaluation on potential transmission paths to generate a transmission path priority list; and selecting an optimal transmission path according to the transmission path priority list and transmitting to-be-transmitted data through the optimal transmission path. The application improves the robustness, efficiency and energy utilization rate of outdoor information collection device wireless data transmission, and provides a strong guarantee for the stable operation of an outdoor monitoring network.

Description

Technical Field

[0001] This application relates to the field of wireless data transmission technology for outdoor information collection equipment, and in particular to a method and system for wireless data transmission of outdoor information collection equipment. Background Technology

[0002] In the field of outdoor data acquisition, equipment is typically deployed in vast and challenging environments to collect various environmental data and transmit it wirelessly to a central processing unit or data aggregation point. To ensure the stability and efficiency of data transmission while considering the equipment's energy consumption, traditional wireless communication methods often pre-define certain static parameters and logic. However, in practical outdoor applications, due to the complexity and variability of the environment and resource constraints, these pre-determined static methods often struggle to cope, leading to data transmission problems and even affecting the long-term operation of the equipment. Summary of the Invention

[0003] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a wireless data transmission method and system for outdoor information acquisition equipment, aiming to improve the robustness, efficiency, and energy utilization of wireless data transmission for outdoor information acquisition equipment, thus providing a strong guarantee for the stable operation of outdoor monitoring networks.

[0004] In a first aspect, this application discloses a wireless data transmission method for an outdoor information collection device, comprising:

[0005] The system acquires the remaining battery power of the monitoring unit, the priority of the data to be transmitted, and the real-time link quality and remaining battery power of surrounding communication nodes.

[0006] Based on its own remaining power, the priority of the data to be transmitted, and the real-time link quality and remaining power of surrounding communication nodes, the potential transmission paths are evaluated from multiple dimensions to generate a priority list of transmission paths.

[0007] Based on the priority list of transmission paths, select the optimal transmission path and transmit the data to be transmitted through the optimal transmission path.

[0008] This technical solution comprehensively considers the monitoring unit's own status, data importance, and surrounding communication environment, dynamically evaluates and selects the optimal transmission path, effectively solving the problems of unstable data transmission, low efficiency, and unreasonable energy consumption in complex outdoor environments caused by traditional static transmission methods, and significantly improving the robustness of data transmission and the service life of the equipment.

[0009] Furthermore, when the data to be transmitted is high-priority data, the steps for evaluating potential transmission paths from multiple dimensions and generating a transmission path priority list include:

[0010] Obtain the instantaneous radio frequency energy intensity of the wireless channel used by the potential transmission path;

[0011] Based on the instantaneous radio frequency energy intensity, it is determined that there is transient interference in the wireless channel;

[0012] If there is transient interference in the wireless channel, the priority of potential transmission paths in the transmission path priority list is reduced.

[0013] Based on the adjusted priorities, potential transmission paths are evaluated from multiple dimensions to generate a priority list of transmission paths.

[0014] More specifically, in some implementations, the step of obtaining the instantaneous radio frequency energy intensity of the wireless channel used by a potential transmission path includes:

[0015] Within a preset initial time period, radio frequency energy is sampled from the wireless channel used by the potential transmission path to obtain the initial radio frequency energy sample value.

[0016] When the initial radio frequency energy sampling value exceeds a preset threshold, the duration of radio frequency energy sampling is extended to obtain a second radio frequency energy sampling value that includes transient interference.

[0017] The instantaneous radio frequency energy intensity of the wireless channel used by the potential transmission path is determined based on the initial radio frequency energy sample value and / or the second radio frequency energy sample value.

[0018] Based on the above, this application further proposes that the steps for determining the presence of transient interference in a wireless channel based on instantaneous radio frequency energy intensity include:

[0019] Obtain the background radio frequency energy value of the wireless channel during non-transmission periods to determine the current noise floor of the wireless channel;

[0020] The interference judgment threshold of the wireless channel is calculated based on the background radio frequency energy value during non-transmission periods.

[0021] The instantaneous radio frequency energy intensity is compared with the interference judgment threshold;

[0022] If the instantaneous radio frequency energy intensity exceeds the interference judgment threshold, it is determined that there is instantaneous interference in the wireless channel.

[0023] Preferably, the step of calculating the interference judgment threshold of the wireless channel based on the background radio frequency energy value during non-transmission periods includes:

[0024] The current noise floor of the wireless channel is determined based on the background radio frequency energy value during non-transmission periods.

[0025] Obtain background radio frequency energy values ​​during the transmission period and identify instantaneous noise peaks in the wireless channel over a recent period;

[0026] Determine the upper limit of noise fluctuation in the wireless channel based on the current noise floor and instantaneous noise peak.

[0027] Based on the current noise floor and the upper limit of noise fluctuation, calculate the interference judgment threshold of the wireless channel.

[0028] In some preferred embodiments, the steps of obtaining the background radio frequency energy value during the transmission period and identifying the instantaneous noise peak of the wireless channel in a recent period include:

[0029] Continuously monitor background radio frequency energy sampling values ​​and identify instantaneous increases in background radio frequency energy sampling values ​​relative to their local average values;

[0030] When a transient rise is detected, high-frequency sampling is performed around the time point when the transient rise occurs within a defined time window to obtain detailed sampled values ​​of the transient noise peak.

[0031] Determine the actual maximum value of the instantaneous noise peak from the detailed sampled values;

[0032] Over a recent period, the actual maximum values ​​of all known instantaneous noise peaks are continuously compared, and the highest value is selected as the instantaneous noise peak of the wireless channel over the recent period.

[0033] Furthermore, the step of identifying the instantaneous rise of the background radio frequency energy sample value relative to its local average includes:

[0034] Maintain a sliding window that contains background RF energy samples over a recent period;

[0035] The average value of the background radio frequency energy samples within the sliding window is calculated as the local average value;

[0036] Compare the currently acquired background radio frequency energy sample value with the local average value;

[0037] If the currently acquired background radio frequency energy sample value exceeds the offset threshold of the local average value, then the instantaneous rise of the background radio frequency energy sample value relative to its local average value is identified.

[0038] Based on this, the steps for determining the offset threshold of the local average include:

[0039] Obtain the current noise floor of the wireless channel;

[0040] Obtain the upper limit of noise fluctuation in the wireless channel;

[0041] Based on the current noise floor and the upper limit of noise fluctuation, the offset threshold of the local average value is calculated using a preset scaling factor or empirical formula.

[0042] Furthermore, the step of calculating the offset threshold of the local average value using a preset scaling factor or empirical formula includes:

[0043] Calculate the difference between the current noise floor and the upper limit of noise fluctuation;

[0044] Multiply the difference by a preset scaling factor;

[0045] Obtain the offset threshold of the local average value.

[0046] Secondly, this application also discloses a wireless data transmission system for outdoor information collection equipment, the system comprising:

[0047] The acquisition module is used to acquire the remaining power of the monitoring unit, the priority of the data to be transmitted, and the real-time link quality and remaining power of the surrounding communication nodes;

[0048] The evaluation module is used to evaluate potential transmission paths from multiple dimensions based on its own remaining power, the priority of the data to be transmitted, and the real-time link quality and remaining power of the surrounding communication nodes, and generate a transmission path priority list.

[0049] The transmission module is used to select the optimal transmission path according to the transmission path priority list, and transmit the data to be transmitted through the optimal transmission path.

[0050] This technical solution provides a system integrating multi-dimensional evaluation and dynamic path selection, enabling intelligent management of wireless data transmission from outdoor information collection devices. It effectively improves the reliability, efficiency, and energy utilization of data transmission, solving the performance limitations of traditional systems in complex outdoor environments. This application discloses a wireless data transmission method for outdoor information collection devices. By acquiring the remaining battery power of the monitoring unit, the priority of the data to be transmitted, the real-time link quality and remaining battery power of surrounding communication nodes, and evaluating potential transmission paths based on this multi-dimensional information, a priority list of transmission paths is generated, and finally, the optimal transmission path is selected for data transmission. This method effectively solves the problems of unstable data transmission, low efficiency, unreasonable energy consumption, and premature device failure caused by the inability of static transmission strategies to adapt to complex and changing outdoor environments in existing technologies.

[0051] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0052] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0053] Figure 1 A flowchart illustrating a wireless data transmission method for an outdoor information collection device according to an embodiment of this application;

[0054] Figure 2 This is a schematic diagram of a wireless data transmission system for an outdoor information collection device provided in one embodiment of this application. Detailed Implementation

[0055] To make the objectives, technical methods, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0056] Based on the above, this application proposes a wireless data transmission method and system for outdoor information acquisition equipment, aiming to improve the robustness, efficiency, and energy utilization of wireless data transmission for outdoor information acquisition equipment, and to provide strong support for the stable operation of outdoor monitoring networks.

[0057] See Figure 1 , Figure 1 This is a flowchart illustrating a wireless data transmission method for an outdoor information collection device according to an embodiment of this application. The embodiment includes, but is not limited to, steps S110 to S130, which will be described in detail below.

[0058] S110. Obtain the remaining power of the monitoring unit, the priority of the data to be transmitted, and the real-time link quality and remaining power of the surrounding communication nodes;

[0059] S120. Based on its own remaining power, the priority of the data to be transmitted, and the real-time link quality and remaining power of the surrounding communication nodes, the potential transmission paths are evaluated in multiple dimensions to generate a priority list of transmission paths.

[0060] S130. Select the optimal transmission path according to the transmission path priority list, and transmit the data to be transmitted through the optimal transmission path.

[0061] To better understand the implementation methods of this application, some key terms involved are explained below.

[0062] "Monitoring Unit" refers to a device deployed in an outdoor environment to collect various environmental data and possessing wireless communication capabilities. These monitoring units are typically battery-powered and may be equipped with solar panels for recharging. "Priority of Data to be Transmitted" refers to the importance or urgency of the data to be transmitted; for example, early warning data may be given high priority, while routine environmental data may be given low priority. "Surrounding Communication Nodes" refers to other monitoring units or data aggregation devices located within the communication range of the monitoring unit; they can serve as intermediate hops or final destinations for data transmission. "Real-time Link Quality" refers to the performance indicators of the current wireless communication link, such as signal strength, signal-to-noise ratio, and bit error rate; these indicators reflect the reliability of data transmission. "Remaining Battery Power" refers to the current available battery power of the monitoring unit or surrounding communication nodes, a key factor affecting the continuous operation of the equipment. "Potential Transmission Paths" refers to all possible combinations of wireless communication links from the current monitoring unit to the target receiver.

[0063] Firstly, various methods can be employed to acquire the monitoring unit's remaining battery power, the priority of data to be transmitted, the real-time link quality of surrounding communication nodes, and the remaining battery power. For example, the monitoring unit can have a built-in battery sensor to monitor battery voltage or current in real time and convert it into its remaining battery percentage. The priority of data to be transmitted can be marked by the application layer based on data type or business requirements during data generation; for example, fire warning data can be marked as the highest priority, while temperature and humidity data can be marked as a normal priority. The real-time link quality of surrounding communication nodes can be obtained by periodically sending probe packets and measuring Received Signal Strength Indication (RSSI), Signal-to-Noise Ratio (SNR), or Packet Success Rate (PDR). Simultaneously, surrounding communication nodes can also broadcast their remaining battery power information for other nodes to receive.

[0064] Secondly, based on its remaining battery power, the priority of the data to be transmitted, and the real-time link quality and remaining battery power of surrounding communication nodes, potential transmission paths are evaluated from multiple dimensions to generate a priority list of transmission paths. Specifically, a comprehensive evaluation score can be calculated for each potential transmission path. For example, the evaluation score for a potential transmission path can comprehensively consider the following factors: the remaining battery power of all nodes on the path (avoiding selecting nodes with low battery power as intermediate hops), the real-time link quality of the path (prioritizing links with strong signals and low interference), and the priority of the data to be transmitted (high-priority data may allow for slightly weaker but faster paths). These factors can be weighted and summed according to preset weights to obtain the comprehensive evaluation score for each path. For example, an evaluation function can be set up, taking battery power, link quality, and data priority as input, and outputting a path's merit value.

[0065] Finally, based on the transmission path priority list, the optimal transmission path is selected, and the data to be transmitted is transmitted through the optimal transmission path. After generating the transmission path priority list, the system sorts the paths from highest to lowest according to their evaluation scores. The optimal transmission path is the path with the highest priority. Once the optimal transmission path is determined, the monitoring unit will send the data to be transmitted through that path. For example, if the optimal path is through node A to node B, then the data will first be sent to node A, and then forwarded by node A to node B, until it reaches its final destination.

[0066] The wireless data transmission method for outdoor information acquisition equipment proposed in this application achieves intelligent and adaptive data transmission by comprehensively considering the monitoring unit's own status, the characteristics of the data to be transmitted, and the surrounding communication environment. When the monitoring unit needs to transmit data, it first obtains its remaining power and the priority of the data to be transmitted, enabling the system to understand the current energy status of the device and the urgency of the data. Simultaneously, the monitoring unit also detects the real-time link quality and remaining power of surrounding communication nodes, thereby assessing the availability and reliability of potential communication partners.

[0067] Based on this multi-dimensional information, the system evaluates all possible potential transmission paths. For example, if the data to be transmitted is high-priority, the system may prioritize a path with high link quality and fast transmission speed, even if some nodes on this path have slightly low power, as long as timely data delivery is ensured, it is acceptable. Conversely, if the data to be transmitted has low priority and the monitoring unit itself has insufficient power, the system may choose a path with average link quality but sufficient power at the nodes and low energy consumption to extend the device's operating time. This multi-dimensional evaluation mechanism allows the system to dynamically adjust its transmission strategy according to the actual situation, avoiding the limitations of traditional static strategies.

[0068] After the evaluation is completed, the system generates a priority list of transmission paths, which contains all potential paths and their corresponding priorities. The monitoring unit selects the optimal transmission path with the highest priority based on this list. Transmitting data through the optimal transmission path ensures that data is transmitted in the most suitable way for current conditions in complex and ever-changing outdoor environments. For example, when a sudden interference in a certain area causes a sharp decline in the quality of a link, this method can promptly identify and select other, more stable paths, thereby avoiding data loss and transmission delays.

[0069] The wireless data transmission method for outdoor information acquisition equipment proposed in this application achieves intelligent and adaptive data transmission by comprehensively considering the monitoring unit's own status, the characteristics of the data to be transmitted, and the surrounding communication environment. When the monitoring unit needs to transmit data, it first obtains its remaining power and the priority of the data to be transmitted, enabling the system to understand the current energy status of the device and the urgency of the data. Simultaneously, the monitoring unit also detects the real-time link quality and remaining power of surrounding communication nodes, thereby assessing the availability and reliability of potential communication partners.

[0070] One embodiment of this application provides a method for evaluating potential transmission paths in step S120 based on the user's remaining power, the priority of the data to be transmitted, and the real-time link quality and remaining power of surrounding communication nodes, and generating a transmission path priority list, including but not limited to steps S210 to S240. Each step will be described in turn below.

[0071] S210. Obtain the instantaneous radio frequency energy intensity of the wireless channel used by the potential transmission path;

[0072] S220. Based on the instantaneous radio frequency energy intensity, it is determined that there is instantaneous interference in the wireless channel;

[0073] S230. If there is transient interference in the wireless channel, reduce the priority of the potential transmission path in the transmission path priority list.

[0074] S240. Based on the adjusted priorities, perform a multi-dimensional evaluation of potential transmission paths to generate a transmission path priority list. Specifically, obtaining the instantaneous radio frequency energy intensity of the wireless channel used by the potential transmission path refers to real-time or near-real-time radio frequency energy monitoring of the target wireless channel to capture its energy fluctuations over a short period. This instantaneous radio frequency energy intensity reflects the channel's activity level and potential interference level at a specific moment. The instantaneous radio frequency energy intensity can be understood as the wireless channel energy value measured within an extremely short time window, its purpose being to identify interference signals that are short-lived but have high energy intensity.

[0075] Furthermore, determining the presence of transient interference in the wireless channel based on the instantaneous radio frequency energy intensity means comparing the acquired instantaneous radio frequency energy intensity with a preset or dynamically calculated interference judgment threshold. If the instantaneous radio frequency energy intensity exceeds the threshold, the wireless channel is considered to currently experience transient interference. Transient interference may originate from sudden electromagnetic noise, brief transmissions from other devices, etc. Although these interferences are short-lived, their impact on data transmission can be very significant.

[0076] Therefore, if the wireless channel experiences transient interference, the priority of the potential transmission path in the transmission path priority list is reduced. This means that even if the path performs well in other evaluation dimensions (such as link quality and node power), its suitability as a high-priority data transmission path will significantly decrease due to transient interference. Reducing priority aims to avoid transmitting high-priority data to the currently interfered channel, thereby reducing the risk of transmission failure or retransmission.

[0077] Finally, the potential transmission paths are evaluated from multiple dimensions based on the adjusted priorities, generating a transmission path priority list. After considering transient interference factors and adjusting the priorities of affected paths, the system will re-perform or update the multi-dimensional evaluation to generate a more accurate and reliable transmission path priority list. This list will more realistically reflect the actual availability and reliability of each potential path when transmitting high-priority data.

[0078] Through the above technical solution, this application can significantly improve the reliability and real-time performance of outdoor information collection equipment when transmitting high-priority data. By monitoring and responding to transient interference in the wireless channel in real time, the system can effectively avoid transmission interruptions or data loss caused by sudden interference, ensuring that high-priority data can reach its destination stably and promptly. This is of great significance for application scenarios requiring rapid response and high reliability (such as environmental early warning, equipment failure alarms, etc.). In addition, this solution optimizes the utilization efficiency of wireless resources by dynamically adjusting the transmission path priority, reduces retransmission overhead caused by channel interference, and thus improves the overall data transmission efficiency.

[0079] In some preferred embodiments, suppose an outdoor environmental monitoring station needs to transmit high-priority data about a sudden extreme weather event (e.g., a flash flood warning). The monitoring station first obtains its remaining battery power, the priority (high priority) of the warning data, and the real-time link quality and remaining battery power of multiple surrounding communication nodes (e.g., relay stations or base stations). When performing a multi-dimensional evaluation of potential transmission paths, the system additionally performs the following steps:

[0080] First, for each potential transmission path using a wireless channel, the system acquires its instantaneous radio frequency (RF) energy intensity. For example, by sampling RF energy within a very short time window, it can be detected that an abnormally high RF energy peak occurs at a certain moment in the channel of a particular path.

[0081] Next, based on the instantaneous radio frequency energy intensity, the system determines that there is transient interference in the wireless channel. For example, if the instantaneous radio frequency energy intensity far exceeds the normal background noise floor and noise fluctuation limit of the channel, then transient interference is determined to exist.

[0082] If transient interference is detected on the wireless channel, the system will immediately lower the priority of the potential transmission path in the transmission path priority list. This means that even if the path performs well in other aspects (such as link quality and node power), its suitability as a high-priority data transmission path is considered low due to the presence of transient interference.

[0083] Finally, based on the adjusted priorities, the system performs a final multi-dimensional evaluation of all potential transmission paths, generating an updated priority list of transmission paths. In this way, the system can select the most stable path, least affected by transient interference, to transmit this high-priority weather warning data, ensuring that the warning information is delivered promptly and reliably, and avoiding delays in the transmission of important information due to transient channel interference.

[0084] One embodiment of this application provides information regarding the instantaneous radio frequency energy intensity of the wireless channel used by the potential transmission path in step S210, including but not limited to steps S310 to S330, which will be described in turn below.

[0085] S310. Within a preset initial time, the radio frequency energy of the wireless channel used by the potential transmission path is sampled to obtain the initial radio frequency energy sample value.

[0086] S320. When the initial radio frequency energy sampling value exceeds a preset threshold, extend the duration of radio frequency energy sampling to obtain a second radio frequency energy sampling value that includes transient interference.

[0087] S330. Determine the instantaneous radio frequency energy intensity of the wireless channel used by the potential transmission path based on the initial radio frequency energy sample value and / or the second radio frequency energy sample value.

[0088] Specifically, the preset initial time can be understood as a short period of time used for preliminary detection of the channel's radio frequency (RF) energy status, for example, it can be set to tens to hundreds of milliseconds. During this initial time, RF energy sampling is performed on the wireless channel used by potential transmission paths to quickly obtain a baseline initial RF energy sample value to determine if there are any potential interference signs. The purpose is to make a preliminary judgment on the channel status without significantly increasing system overhead. The preset threshold is a reference value used to determine whether the initial RF energy sample value is abnormal; it can be set based on historical data, the average noise level of the channel environment, or empirical values. When the initial RF energy sample value exceeds the preset threshold, it indicates that there may be abnormal RF energy activity in the channel, which is usually a signal of transient interference.

[0089] In practical applications, when the initial RF energy sample value exceeds a preset threshold, the system triggers an operation to extend the duration of RF energy sampling. The purpose of extending the sampling duration is to more comprehensively capture the complete waveform and duration of transient interference, as transient interference may still exist or reappear after the initial sampling ends. By extending the sampling, a second RF energy sample value containing transient interference can be obtained, providing richer and more accurate interference information. For example, the extended duration can be several times the initial time, or a fixed but relatively long duration to ensure coverage of typical transient interference durations. Therefore, after obtaining the initial and / or second RF energy sample values, the transient RF energy intensity of the wireless channel used by the potential transmission path can be determined based on these sample values. Specifically, this can be done in various ways. For example, the maximum value among all sample values ​​can be taken as the transient RF energy intensity to reflect the worst interference situation; all sample values ​​can be averaged or weighted to obtain a smoother transient RF energy intensity; or, in some cases, if the initial sample value is already high enough and stable, the initial sample value can be used directly. Its purpose is to comprehensively utilize the acquired radio frequency energy sampling data to obtain the most representative assessment results on the current instantaneous interference situation of the channel.

[0090] This application's solution effectively addresses the problem of missed transient interference in traditional fixed-duration sampling by introducing a dynamic radio frequency (RF) energy sampling mechanism. Specifically, RF energy sampling is first performed within a preset initial time to quickly assess the channel condition. When the initial RF energy sampling value does not exceed a preset threshold, it indicates that the channel may be in a relatively stable state, requiring no additional sampling and thus saving system resources. However, once the initial RF energy sampling value exceeds the preset threshold, the system intelligently extends the RF energy sampling duration. This mechanism allows the device to monitor the channel for a longer period, significantly increasing the likelihood of capturing short-term, sudden transient interference. In this way, even short-duration interference can be effectively detected, and a second RF energy sampling value containing its complete characteristics can be obtained. Finally, the instantaneous RF energy intensity is determined by combining the initial and / or second RF energy sampling values, ensuring a more comprehensive and accurate assessment of the channel's transient interference status and providing reliable data support for subsequent judgments regarding the presence of transient interference in the wireless channel.

[0091] One embodiment of this application provides a method for determining whether there is transient interference in the wireless channel based on the instantaneous radio frequency energy intensity in step S220, including but not limited to steps S410 to S440. Each step will be described in turn below.

[0092] S410. Obtain the background radio frequency energy value of the wireless channel during non-transmission periods to determine the current noise floor of the wireless channel;

[0093] S420. Calculate the interference judgment threshold of the wireless channel based on the background radio frequency energy value during non-transmission periods.

[0094] S430. Compare the instantaneous radio frequency energy intensity with the interference judgment threshold;

[0095] S440. If the instantaneous radio frequency energy intensity exceeds the interference judgment threshold, it is determined that there is instantaneous interference in the wireless channel.

[0096] The acquisition of background radio frequency energy values ​​during non-transmission periods of the wireless channel to determine the current noise floor of the wireless channel refers to the continuous monitoring and sampling of the radio frequency energy of the target wireless channel during specific time periods when the outdoor information acquisition device is not transmitting data or when other known devices are not transmitting data. In this way, the background noise level and potential persistent interference in the current environment can be accurately captured, thereby establishing a current noise floor that reflects the actual condition of the wireless channel. This noise floor serves as a reference benchmark for subsequent judgment of transient interference.

[0097] Furthermore, calculating the interference judgment threshold of the wireless channel based on the background radio frequency energy value during the non-transmission period refers to, after determining the current noise floor, adding a safety margin or offset to the noise floor using a specific algorithm or a preset empirical formula to obtain a threshold for distinguishing between normal noise fluctuations and actual instantaneous interference. This interference judgment threshold aims to ensure that only when the instantaneous radio frequency energy intensity is significantly higher than the normal background noise is it identified as instantaneous interference, avoiding misjudgments caused by normal channel fluctuations.

[0098] Therefore, comparing the instantaneous radio frequency energy intensity with the interference judgment threshold means comparing the real-time monitored instantaneous radio frequency energy intensity of the wireless channel with the interference judgment threshold calculated above. If the instantaneous radio frequency energy intensity exceeds the interference judgment threshold, it is determined that there is instantaneous interference in the wireless channel. This means that the radio frequency energy level in the current channel has exceeded the normal background noise and acceptable fluctuation range, and there is a high probability that there are one or more external interference sources, which may have a potential impact on data transmission.

[0099] The proposed solution first acquires the background radio frequency energy value of the wireless channel during non-transmission periods, enabling dynamic determination of the channel's current noise floor and thus adapting to the complex and variable noise conditions in outdoor environments. Based on this dynamic noise floor, an interference judgment threshold is calculated, allowing for flexible adjustment to more accurately reflect the channel's actual interference tolerance. When the instantaneous radio frequency energy intensity is compared with this adaptive interference judgment threshold, it effectively distinguishes between normal channel noise fluctuations and actual instantaneous interference, avoiding misjudgments or omissions that might occur with a fixed threshold. This mechanism ensures more accurate and reliable identification of instantaneous interference, providing a solid foundation for subsequent high-priority data transmission path selection.

[0100] One embodiment of this application provides a method for calculating the interference judgment threshold of the wireless channel based on the background radio frequency energy value during non-transmission periods in step S420, including but not limited to steps S510 to S540. Each step will be described in turn below.

[0101] S510. Determine the current noise floor of the wireless channel based on the background radio frequency energy value during non-transmission periods;

[0102] S520: Obtain the background radio frequency energy value during the transmission period and identify the instantaneous noise peak of the wireless channel in the recent period.

[0103] S530. Determine the upper limit of noise fluctuation in the wireless channel based on the current noise floor and instantaneous noise peak.

[0104] S540. Based on the current noise floor and the upper limit of noise fluctuation, calculate the interference judgment threshold of the wireless channel.

[0105] Specifically, when determining the current noise floor of a wireless channel, the background radio frequency energy value during non-transmission periods can be sampled and averaged over a long period to obtain a relatively stable reference value. This current noise floor reflects the basic noise level of the wireless channel when there is no data transmission.

[0106] The purpose of acquiring background RF energy values ​​during transmission periods and identifying instantaneous noise peaks is to capture brief, non-sustained noise increases that may occur in the channel under actual operating conditions. This can be achieved by continuously monitoring the channel's RF energy during transmission periods and using specific algorithms (e.g., moving average, peak detection algorithms) to identify instantaneous energy spikes that are significantly higher than the current noise floor. These instantaneous noise peaks may not be caused by persistent interference, but rather by sporadic events in the environment.

[0107] In practical applications, when determining the upper limit of noise fluctuation in a wireless channel, the current noise floor can be combined with the identified instantaneous noise peak. For example, the instantaneous noise peak can be compared with the current noise floor, and based on the relationship between the two, an upper limit that can reasonably cover normal noise fluctuations can be calculated using a preset empirical formula or statistical method. This upper limit of noise fluctuation aims to distinguish between normal noise fluctuations and genuine instantaneous interference.

[0108] Therefore, based on the current noise floor and the upper limit of noise fluctuation, a more accurate and robust interference judgment threshold can be calculated. This threshold considers not only the average noise level of the channel but also the noise fluctuation range of the channel under normal operating conditions, thereby avoiding misjudging normal noise fluctuations as transient interference.

[0109] This application's solution introduces the identification of instantaneous noise peaks in the background RF energy value during transmission periods and combines this with the current noise floor to determine the upper limit of noise fluctuations, thereby making the calculation of the interference judgment threshold more refined and adaptive. Traditionally, relying solely on the background RF energy value outside of transmission periods to set the threshold may not effectively distinguish between normal, transient noise fluctuations in the channel and true instantaneous interference. With this solution, the system can more accurately understand the actual noise characteristics of the channel, taking instantaneous noise peaks into account, thus setting a threshold that can tolerate normal noise fluctuations while responding promptly to real interference. This helps avoid unnecessary reduction in transmission path priority due to misjudging normal noise as interference, or missing actual interference due to an excessively high threshold.

[0110] One embodiment of this application provides for obtaining the background radio frequency energy value during the transmission period in step S520 and identifying the instantaneous noise peak of the wireless channel in a recent period of time, including but not limited to steps S610 to S640. Each step is described in turn below.

[0111] S610: Continuously monitor background radio frequency energy sampling values ​​and identify instantaneous increases in background radio frequency energy sampling values ​​relative to their local average values;

[0112] S620. When a transient rise is detected, high-frequency sampling is performed around the time point when the transient rise occurs within a defined time window to obtain detailed sampled values ​​of the transient noise peak.

[0113] S630. Determine the actual maximum value of the instantaneous noise peak from the detailed sampled values;

[0114] S640. In the recent period, continuously compare the actual maximum values ​​of all known instantaneous noise peaks, and select the highest value as the instantaneous noise peak of the wireless channel in the recent period.

[0115] Specifically, continuous monitoring of the background radio frequency energy sampling value refers to the device continuously or periodically sampling the radio frequency energy of the wireless channel during non-transmission periods to obtain sampling data reflecting the channel's background noise level. Identifying a sudden increase in the background radio frequency energy sampling value relative to its local average can be understood as analyzing the changing trend of the background radio frequency energy sampling value in real time to determine whether there is a sudden energy increase significantly higher than the normal background noise level, which usually indicates the occurrence of transient interference. For example, a sliding window can be maintained, and the average value within the window can be calculated as a local average. When a new sampling value deviates significantly from this local average, it is considered that a transient increase has occurred.

[0116] Furthermore, upon detecting the instantaneous rise, high-frequency sampling is performed around the time point of the instantaneous rise within a defined time window to obtain detailed sampled values ​​of the instantaneous noise peak. This means that once a potential sign of instantaneous interference is detected, the system immediately initiates a more intensive sampling mode to capture the complete waveform and intensity information of the interference signal within a short time. High-frequency sampling provides finer data granularity, ensuring that no peak value of instantaneous interference is missed. Determining the actual maximum value of the instantaneous noise peak from the detailed sampled values ​​refers to analyzing the data obtained from high-frequency sampling to accurately identify the highest energy point in the instantaneous interference event, i.e., its true peak value.

[0117] Furthermore, within the aforementioned recent period, the actual maximum values ​​of all determined instantaneous noise peaks are continuously compared, and the highest value is selected as the instantaneous noise peak of the wireless channel within the aforementioned recent period. The purpose is to ensure that when assessing channel interference, the most severe instantaneous interference situation occurring within a specific time window is always considered, thereby providing the most conservative and secure basis for subsequent interference judgment and transmission path assessment.

[0118] This application's solution effectively addresses the shortcomings of traditional methods in identifying instantaneous noise peaks by introducing mechanisms such as continuous monitoring, instantaneous rise identification, high-frequency sampling, and maximum value selection. Specifically, continuous monitoring of background radio frequency energy sampling values ​​enables the system to grasp the channel's noise status in real time; identifying instantaneous rises in background radio frequency energy sampling values ​​relative to their local average values ​​allows for sensitive detection of sudden interference events, avoiding misjudgments of persistent low-intensity noise. This precise capture of instantaneous rises allows the system to obtain detailed sampling values ​​of the interference signal through high-frequency sampling within a defined time window at the first moment of interference occurrence, thus avoiding peak omissions due to insufficient sampling frequency. Finally, by determining the actual maximum value from the detailed sampling values ​​and continuously comparing all maximum values ​​within a recent period, the highest value is selected as the instantaneous noise peak. This ensures that the identified peak accurately reflects the worst interference conditions experienced by the channel within a specific time period, providing more reliable data support for subsequent interference judgment and transmission path assessment.

[0119] As a specific implementation method, a concrete example is given below. Assume an outdoor data acquisition device is monitoring its surrounding wireless channels. The device continuously monitors background radio frequency (RF) energy samples at a low frequency (e.g., 10 times per second). At a certain moment, the device detects a sudden increase in the background RF energy sample value from -90 dBm to -70 dBm, exceeding a preset offset threshold of its local average (e.g., -85 dBm). At this point, the system recognizes the transient increase and immediately initiates a high-frequency sampling mode, sampling at a frequency of 100 times per millisecond for the next 100 milliseconds. Through high-frequency sampling, the system obtains a series of detailed RF energy sample values, with the highest value reaching -65 dBm. The system records this -65 dBm as the actual maximum value of this transient interference event. In the past 5 minutes, the system may have identified and recorded multiple such transient interference events with actual maximum values, such as -68 dBm, -72 dBm, etc. By continuously comparing these determined actual maximum values, the system ultimately selects the highest value, -65dBm, as the instantaneous noise peak of the wireless channel over a recent period. This precise instantaneous noise peak will be used for subsequent interference judgment threshold calculations, thereby more accurately assessing the channel's interference status and guiding the selection of transmission paths.

[0120] One embodiment of this application provides for identifying the instantaneous rise of the background radio frequency energy sample value relative to its local average value in step S610, including but not limited to steps S710 to S740, which are described in turn below.

[0121] S710, maintains a sliding window containing background RF energy sample values ​​over a recent period;

[0122] S720. Calculate the average value of the background radio frequency energy sampled within the sliding window as the local average value;

[0123] S730: Compare the currently acquired background radio frequency energy sample value with the local average value;

[0124] S740. If the currently acquired background radio frequency energy sample value exceeds the offset threshold of the local average value, then identify the instantaneous increase of the background radio frequency energy sample value relative to its local average value.

[0125] The sliding window can be understood as a data structure used to store continuously acquired background radio frequency energy sampling values ​​over a recent period. This window is maintained in a first-in, first-out (FIFO) manner; that is, when a new sampling value is acquired, the oldest sampling value is removed to ensure that the window always contains the latest set of data. The "recent period" can be configured according to the actual application scenario and the real-time requirements for responding to transient interference; for example, it can be several seconds, tens of seconds, or longer.

[0126] The local average value refers to the arithmetic mean of all background radio frequency energy samples within the sliding window. By calculating the local average value, the average noise level of the wireless channel over a recent period can be obtained, thus providing a dynamic benchmark for judging instantaneous increases.

[0127] The offset threshold is a preset or dynamically calculated value used to define how much the current background radio frequency energy sample value needs to exceed the local average value to be considered an instantaneous increase. Specifically, when the difference between the currently acquired background radio frequency energy sample value and the local average value exceeds the offset threshold, an instantaneous increase is considered to have occurred. The setting of the offset threshold needs to comprehensively consider the noise characteristics of the wireless channel, the typical intensity of environmental interference, and the system's tolerance for false positives and false negatives.

[0128] The proposed solution introduces a sliding window mechanism to dynamically track the background radio frequency energy variation trend of a wireless channel. By calculating the local average value within the sliding window, the average noise level of the channel over a recent period can be reflected in real time, rather than relying on a fixed global noise floor. When the currently acquired background radio frequency energy sample value is significantly higher than its local average value and exceeds a preset offset threshold, this indicates that a sudden, short-lived high-energy event, i.e., transient interference, may exist in the channel. This comparison method based on local average values ​​enables the system to more sensitively capture transient interference, effectively distinguishing genuine transient interference events even when the overall noise floor changes slowly.

[0129] Through the above technical solution, this application can accurately identify the instantaneous rise in the sampled value of background radio frequency energy in a wireless channel. Compared with methods that rely solely on fixed thresholds or global averages for judgment, the sliding window and local averaging method allows the system to better adapt to the dynamic changes in wireless channel noise, improving the sensitivity and accuracy of instantaneous interference detection. This effectively avoids misjudgments or missed judgments caused by the slow drift of channel background noise, thus providing a more reliable basis for subsequent transmission path priority adjustment and further optimizing the transmission strategy for high-priority data.

[0130] One embodiment of this application provides an offset threshold for calculating the local average value in step S740, including but not limited to steps S810 to S830, which are described in turn below.

[0131] S810: Obtain the current noise floor of the wireless channel;

[0132] S820: Obtain the upper limit of noise fluctuation in the wireless channel;

[0133] S830: Based on the current noise floor and the upper limit of noise fluctuation, calculate the offset threshold of the local average value using a preset scaling factor or empirical formula.

[0134] Specifically, when identifying an instantaneous increase in the background radio frequency energy sample value relative to its local average, a suitable offset threshold is required. Determining this offset threshold first requires obtaining the current noise floor of the wireless channel. The current noise floor can be understood as the average background radio frequency energy value of the wireless channel during non-transmission periods, reflecting the basic noise level of the channel when there is no signal transmission. Secondly, it is necessary to obtain the upper limit of noise fluctuation of the wireless channel. The upper limit of noise fluctuation refers to the maximum instantaneous peak value that the background noise of the wireless channel may reach in a recent period, reflecting the dynamic range of channel noise changes. After obtaining the current noise floor and the upper limit of noise fluctuation, the offset threshold of the local average can be calculated based on these two parameters using a preset scaling factor or empirical formula. For example, the scaling factor can be a constant determined based on actual environmental testing and experience, used to proportionally convert the difference between the noise floor and the upper limit of noise fluctuation into an offset threshold. The empirical formula can be a mathematical model derived from a large amount of historical data and statistical analysis, which can more accurately reflect the relationship between noise characteristics and the offset threshold.

[0135] Through the above technical solution, the determined offset threshold of the local average value can more accurately reflect the actual noise characteristics of the wireless channel, avoiding misjudgments or omissions caused by improper threshold settings. This significantly improves the recognition accuracy and robustness of the instantaneous rise of the background radio frequency energy sample value relative to its local average value, thereby enhancing the accuracy of the overall instantaneous interference judgment. In the wireless data transmission scenario of outdoor information collection equipment, this means that instantaneous interference can be identified and avoided more reliably, thereby optimizing the selection of transmission paths, ensuring the stable transmission of high-priority data, and effectively improving the reliability and efficiency of data transmission.

[0136] In some preferred embodiments, a specific example is given below. Suppose that at a certain moment, an outdoor data acquisition device detects a current noise floor of -90 dBm for a wireless channel, and through continuous monitoring and analysis over a recent period, determines that the upper limit of noise fluctuation for this wireless channel is -80 dBm. To calculate the offset threshold of the local average, a preset scaling factor, such as 0.5, can be used. In this case, the difference between the current noise floor and the upper limit of noise fluctuation is -80 dBm - (-90 dBm) = 10 dBm. Multiplying this difference by the preset scaling factor 0.5 yields an offset threshold of 5 dBm. This means that only when the current background radio frequency energy sample value exceeds its local average by 5 dBm will it be identified as an instantaneous increase. In this way, the offset threshold can be dynamically adjusted according to the actual noise floor and the upper limit of noise fluctuation, thus providing a reasonable and effective judgment basis under different environmental conditions.

[0137] One embodiment of this application provides a method for calculating the offset threshold of the local average value using a preset scaling factor or empirical formula in step S830, including but not limited to steps S910 to S920. Each step will be described in turn below.

[0138] S910. Calculate the difference between the current noise floor and the upper limit of noise fluctuation;

[0139] S920. Multiply the difference by a preset scaling factor to obtain the offset threshold of the local average value.

[0140] Specifically, the current noise floor refers to the background radio frequency energy value of the wireless channel during non-transmission periods, reflecting the inherent noise level of the channel when there is no signal transmission. The noise fluctuation upper limit is a higher boundary set for the channel noise level after considering instantaneous noise peaks. Calculating the difference between the current noise floor and the noise fluctuation upper limit aims to quantify the maximum possible variation in channel noise within the normal fluctuation range. Subsequently, this difference is multiplied by a preset scaling factor, which can be adjusted according to the actual application scenario, channel characteristics, and sensitivity requirements for instantaneous interference identification. In this way, the offset threshold of the local average value can be accurately obtained. This threshold is used to determine whether the background radio frequency energy sample value has an instantaneous increase relative to its local average value, thereby effectively identifying potential instantaneous noise peaks.

[0141] The proposed solution uses the difference between the current noise floor and the upper limit of noise fluctuation as a basis, and adjusts it by introducing a preset scaling factor, enabling dynamic and accurate calculation of the offset threshold of the local average value. This calculation method allows the offset threshold to adapt to the actual noise environment and fluctuation characteristics of the wireless channel, rather than using a fixed empirical value. Therefore, when the background radio frequency energy sample value exceeds this adaptive offset threshold, the instantaneous rise relative to the local average value can be identified more accurately, thereby effectively capturing the instantaneous noise peaks present in the channel. This method of threshold calculation based on the actual noise characteristics of the channel significantly improves the accuracy and robustness of instantaneous interference identification.

[0142] See Figure 2 , Figure 2 This is a schematic diagram of a wireless data transmission system for an outdoor information collection device according to an embodiment of this application. The outdoor information collection device wireless data transmission system 1000 includes:

[0143] The acquisition module 1010 is used to acquire the remaining power of the monitoring unit, the priority of the data to be transmitted, the real-time link quality of the surrounding communication nodes, and the remaining power.

[0144] The evaluation module 1020 is used to evaluate potential transmission paths in multiple dimensions based on its own remaining power, the priority of the data to be transmitted, and the real-time link quality and remaining power of the surrounding communication nodes, and generate a transmission path priority list.

[0145] The transmission module 1030 is used to select the optimal transmission path according to the transmission path priority list, and transmit the data to be transmitted through the optimal transmission path.

[0146] Specifically, the acquisition module is configured to perform data acquisition functions. For example, the acquisition module may include a sensor interface, a wireless communication interface, and a data parsing unit, used to monitor the remaining power of the monitoring unit itself in real time, identify the priority of the data to be transmitted, and obtain the real-time link quality and remaining power of surrounding communication nodes wirelessly. This information can be implemented by dedicated hardware circuitry or by software programs running on a general-purpose processor.

[0147] The evaluation module is configured to perform multi-dimensional evaluation. For example, the evaluation module could be a microcontroller or digital signal processor, internally storing evaluation algorithms and weight parameters. Upon receiving information from the acquisition module, the evaluation module calculates for all potential transmission paths based on these parameters, generating a priority list of transmission paths containing a comprehensive evaluation score for each path. This evaluation process can be implemented using heuristic algorithms, machine learning models, or rule-based expert systems.

[0148] The transmission module is configured to perform data transmission functions. For example, the transmission module can be a wireless communication controller integrating an RF transceiver and a baseband processing unit. Upon receiving a priority list generated by the evaluation module, the transmission module selects the highest priority path as the optimal transmission path and, based on the topology of the selected path, sends the data to be transmitted through the wireless communication interface. The transmission module can support multiple wireless communication protocols and may include retransmission mechanisms and flow control functions to ensure the reliability of data transmission.

[0149] Specifically, the system of this application effectively solves the following problems existing in the prior art: First, by coordinating the acquisition and evaluation modules, it avoids selecting nodes with nearly depleted power as intermediate hops, thereby reducing data transmission interruptions caused by node failures. Second, by evaluating real-time link quality, it can effectively avoid interfered or congested channels, reducing packet collision rates and transmission delays. Third, by combining the priority of the data to be transmitted, high-priority data can preferentially select more reliable and faster paths, ensuring the timely delivery of critical information. Finally, by comprehensively considering its remaining power, the monitoring unit can select a more energy-efficient transmission strategy when power is insufficient, extending the equipment's operating life. This dynamic adaptive transmission system significantly improves the robustness, efficiency, and energy management capabilities of data transmission in outdoor information acquisition equipment, providing a more reliable and efficient solution for the field of outdoor information acquisition.

Claims

1. A wireless data transmission method for an outdoor information collection device, characterized by, The method comprises the following steps: acquiring the residual power of the monitoring unit, the priority of the data to be transmitted, the real-time link quality and the residual power of the surrounding communication nodes; based on the residual power of the monitoring unit, the priority of the data to be transmitted, and the real-time link quality and the residual power of the surrounding communication nodes, performing multi-dimensional evaluation on the potential transmission path to generate a transmission path priority list; selecting an optimal transmission path according to the transmission path priority list, and transmitting the data to be transmitted through the optimal transmission path; when the data to be transmitted is high-priority data, the step of performing multi-dimensional evaluation on the potential transmission path to generate a transmission path priority list comprises: acquiring the instantaneous radio frequency energy intensity of the wireless channel used by the potential transmission path; judging whether the wireless channel has instantaneous interference according to the instantaneous radio frequency energy intensity; if the wireless channel has instantaneous interference, reducing the priority of the potential transmission path in the transmission path priority list; performing multi-dimensional evaluation on the potential transmission path according to the adjusted priority to generate a transmission path priority list.

2. The wireless data transmission method for outdoor information collection equipment according to claim 1, characterized in that, The step of acquiring the instantaneous radio frequency energy intensity of the wireless channel used by the potential transmission path comprises: sampling the radio frequency energy of the wireless channel used by the potential transmission path within a preset initial time to obtain an initial radio frequency energy sampling value; when the initial radio frequency energy sampling value exceeds a preset threshold, extending the duration of the radio frequency energy sampling to obtain a second radio frequency energy sampling value containing instantaneous interference; determining the instantaneous radio frequency energy intensity of the wireless channel used by the potential transmission path according to the initial radio frequency energy sampling value and / or the second radio frequency energy sampling value.

3. The wireless data transmission method for outdoor information collection equipment according to claim 1, characterized in that, The step of judging whether the wireless channel has instantaneous interference according to the instantaneous radio frequency energy intensity comprises: acquiring the non-transmission period background radio frequency energy value of the wireless channel to determine the current noise floor of the wireless channel; calculating the interference judgment threshold of the wireless channel based on the non-transmission period background radio frequency energy value; comparing the instantaneous radio frequency energy intensity with the interference judgment threshold; if the instantaneous radio frequency energy intensity exceeds the interference judgment threshold, it is judged that the wireless channel has instantaneous interference.

4. The wireless data transmission method of an outdoor information collection device according to claim 3, wherein, The step of calculating the interference judgment threshold of the wireless channel based on the non-transmission period background radio frequency energy value comprises: determining the current noise floor of the wireless channel according to the non-transmission period background radio frequency energy value; acquiring the transmission period background radio frequency energy value to identify the instantaneous noise peak value of the wireless channel in the recent period of time; determining the noise fluctuation upper limit of the wireless channel according to the current noise floor and the instantaneous noise peak value; calculating the interference judgment threshold of the wireless channel based on the current noise floor and the noise fluctuation upper limit. The step of acquiring the transmission period background radio frequency energy value to identify the instantaneous noise peak value of the wireless channel in the recent period of time comprises:

5. The wireless data transmission method of an outdoor information collection device according to claim 4, wherein, continuously monitoring the background radio frequency energy sampling value to identify the instantaneous rise of the background radio frequency energy sampling value relative to its local average value; ​ When the transient rise is identified, high frequency sampling is performed around the time point where the transient rise occurs to obtain detailed sampling values of the transient noise peak in a defined time window; An actual maximum value of the transient noise peak is determined from the detailed sampling values; All determined actual maximum values of the transient noise peak are continuously compared in the recent time period, and the highest value is selected as the transient noise peak of the wireless channel in the recent time period.

6. The wireless data transmission method of an outdoor information collection device according to claim 5, wherein, The step of identifying the transient rise of the background radio frequency energy sampling value relative to its local average value comprises: A sliding window containing background radio frequency energy sampling values in the recent time period is maintained; An average value of the background radio frequency energy sampling values in the sliding window is calculated as the local average value; The currently obtained background radio frequency energy sampling value is compared with the local average value; If the currently obtained background radio frequency energy sampling value exceeds the offset threshold of the local average value, the transient rise of the background radio frequency energy sampling value relative to its local average value is identified.

7. The wireless data transmission method of an outdoor information collection device according to claim 6, wherein, The step of calculating the offset threshold of the local average value comprises: The current noise floor of the wireless channel is obtained; The upper limit of noise fluctuation of the wireless channel is obtained; Based on the current noise floor and the upper limit of noise fluctuation, the offset threshold of the local average value is calculated through a preset proportion factor or an empirical formula.

8. The wireless data transmission method of an outdoor information collection device according to claim 7, wherein, The step of calculating the offset threshold of the local average value through a preset proportion factor or an empirical formula comprises: The difference between the current noise floor and the upper limit of noise fluctuation is calculated; The difference is multiplied by a preset proportion coefficient; The offset threshold of the local average value is obtained.

9. An outdoor information collection device wireless data transmission system, characterized by comprising: The system comprises: An acquisition module is configured to acquire the remaining power of the monitoring unit, the priority of the data to be transmitted, the real-time link quality and the remaining power of the surrounding communication nodes; An evaluation module is configured to perform multi-dimensional evaluation on potential transmission paths based on the remaining power of the monitoring unit, the priority of the data to be transmitted, and the real-time link quality and the remaining power of the surrounding communication nodes, and generate a transmission path priority list; The evaluation module is further configured to acquire the instantaneous radio frequency energy intensity of the wireless channel used by the potential transmission paths; According to the instantaneous radio frequency energy intensity, it is determined that the wireless channel has transient interference; If the wireless channel has transient interference, the priority of the potential transmission path in the transmission path priority list is reduced; According to the adjusted priority, the multi-dimensional evaluation on the potential transmission paths is performed to generate a transmission path priority list; A transmission module is configured to select an optimal transmission path according to the transmission path priority list, and transmit the data to be transmitted through the optimal transmission path.

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