Sewage toxicity monitoring site credibility analysis method and device
By analyzing data from wastewater toxicity monitoring sites and using GIS visualization, the problems of misjudgment, insufficient prediction, and unintuitive early warning in wastewater toxicity monitoring have been solved, achieving more accurate risk assessment and timely early warning.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA INNOVATION INSTR CO LTD
- Filing Date
- 2025-12-31
- Publication Date
- 2026-04-28
AI Technical Summary
Existing wastewater toxicity monitoring technologies suffer from problems such as misjudgment, lack of prediction, insufficient accuracy in judgment, and unintuitive early warning and response, making it difficult to reflect drug abuse trends at the community level in a real-time and objective manner.
By collecting wastewater monitoring data from various locations, the hazard level is calculated using the weighting formula R = W1×S + W2×T + W3×P. Combined with GIS visualization to display the monitoring locations and risk levels, the credibility analysis of wastewater toxicity is achieved.
It improves the accuracy of test results, has predictive capabilities, and through visual early warning and response, intuitively displays the risk level, helping staff to pay attention to and deal with potential threats in advance.
Smart Images
Figure CN121933669A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to wastewater monitoring technology, and in particular to a method and apparatus for analyzing the reliability of wastewater toxicity monitoring sites. Background Technology
[0002] Wastewater drug monitoring stems from the integration of environmental epidemiology and analytical chemistry, against the backdrop of the increasingly covert and complex global drug problem. Traditional drug assessment methods, relying on crime reports, seizures, and self-report questionnaires, suffer from significant lag and bias, failing to reflect real-time and objective drug abuse trends at the community level. With the substantial improvement in the sensitivity of trace substance detection technologies (such as liquid chromatography-mass spectrometry), scientists can accurately detect extremely low concentrations of narcotics and their metabolites in urban wastewater systems, giving rise to this revolutionary monitoring method. Furthermore, the emergence of new psychoactive substances globally places higher demands on rapid response and accurate early warning in drug control efforts; wastewater monitoring precisely fills this gap, becoming an internationally recognized "barometer" of drug activity.
[0003] Currently, while the detection and analysis results of wastewater samples can accurately identify abnormalities exceeding standards, there are still many shortcomings, such as: 1. It can lead to misjudgment. When the detection result and the warning threshold are very close, it may cause false alarms or omissions.
[0004] 2. Lack of foresight: Over time, each monitoring point has accumulated a lot of data. Although the data may not exceed the standard, the deteriorating trend may have appeared long ago but was not detected.
[0005] 3. The judgment is not precise enough, only providing the test value and whether it exceeds the standard. For non-professionals, it is difficult to determine the severity of the test results.
[0006] 4. The early warning and response mechanisms are not intuitive enough. There is no information display on the actual map showing the sampling points, test results, early warning status, and whether any action is required. Summary of the Invention
[0007] To address the shortcomings of the existing technical solutions, this invention provides a method for analyzing the reliability of wastewater toxicity monitoring points.
[0008] The objective of this invention is achieved through the following technical solution: A method for analyzing the reliability of wastewater toxicity monitoring sites, the method comprising the following steps: A1. Collect current monitoring data of wastewater at each location, including drug content detection values, time, and location; A2. Obtain the R corresponding to each monitoring point based on the current monitoring data and historical monitoring data; R = W1×S + W2×T + W3×P; W1, W2 and W3 are weights, and W1+W2+W3=1; S = (current detection value - warning threshold) / warning threshold, T = (recent average value - baseline average value) / baseline average value, P = number of times the threshold is exceeded consecutively / total number of assessments; A3. Locate the danger level range where R is located and obtain the current danger level corresponding to the location; A4. Visualize the monitoring points and their corresponding hazard levels.
[0009] The present invention also aims to provide a reliability analysis device for wastewater toxicity monitoring points that implements the above-mentioned analysis method. This objective is achieved through the following technical solution: A reliability analysis device for wastewater toxicity monitoring sites, the analysis device comprising: The data acquisition module is used to collect current monitoring data of wastewater at various locations, including drug content detection values, time, and location. The storage module is used to store the current monitoring data, historical monitoring data, hazard level ranges, and early warning thresholds; The calculation module is used to call the data of the storage module to obtain R corresponding to each point, find the danger level interval where R is located, and obtain the current danger level corresponding to the point. R = W1×S + W2×T + W3×P; W1, W2 and W3 are weights, and W1+W2+W3=1; S = (current detection value - warning threshold) / warning threshold, T = (recent average value - baseline average value) / baseline average value, P = number of times the threshold is exceeded consecutively / total number of assessments; A visualization module is used to visually display the monitoring points and the corresponding hazard levels.
[0010] Compared with the prior art, the present invention has the following beneficial effects.
[0011] 1. More accurate judgment; Compared with the traditional method of directly comparing a single result with the warning threshold, this method incorporates historical data analysis, thus avoiding accidental errors. This application can also demonstrate the severity level reached or exceeded, making it very clear to frontline staff what to do next; 2. Possesses predictive ability; Based on the risk level assessment results, the staff can detect the deterioration process of the test results before the warning is issued, so that they can pay attention to and deal with it in advance; 3. Visualized early warning and response; The system issues warnings on a large GIS visualization screen, and colors the background of sampling points with red, orange, yellow, and green based on the risk level assessment results to visually display the assessment results and generate a heat map. Points requiring action are marked with red and orange flags to remind staff to take immediate action. Attached Figure Description
[0012] The disclosure of this invention will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are merely illustrative of the technical solutions of this invention and are not intended to limit the scope of protection of this invention. In the drawings: Figure 1 This is a flowchart of the reliability analysis method for wastewater toxicity monitoring points; Figure 2 It is a visual display effect diagram. Detailed Implementation
[0013] Figures 1-2 The following description illustrates optional embodiments of the invention to teach those skilled in the art how to implement and reproduce the invention. Some conventional aspects have been simplified or omitted to teach the technical solutions of the invention. Those skilled in the art should understand that variations or substitutions derived from these embodiments will be within the scope of the invention. Those skilled in the art should understand that the following features can be combined in various ways to form multiple variations of the invention. Therefore, the invention is not limited to the optional embodiments described below, but is defined only by the claims and their equivalents.
[0014] Example 1
[0015] The reliability analysis method for wastewater toxicity monitoring points in this embodiment, such as... Figure 1 As shown, the steps include: A1. Collect current monitoring data of wastewater at each location, including drug content detection values, time, and location (including name and coordinates).
[0016] The storage module stores the current monitoring data, historical monitoring data, danger level ranges, and warning thresholds.
[0017] A2. Obtain the R corresponding to each monitoring point based on the current monitoring data and historical monitoring data; R = W1×S + W2×T + W3×P; W1, W2 and W3 are weights, and W1+W2+W3=1; S = (Current Detected Value - Warning Threshold) / Warning Threshold, T = (Recent Average Value - Baseline Average Value) / Baseline Average Value, P = Number of Times the Threshold is Exceeded Consecutively / Total Number of Assessments. For example, the recent average value is the average of the last 3 detected values, and the extreme average value is the average of the last 6 months. The total number of assessments is the number of the last 6 monitoring sessions.
[0018] A3. Locate the hazard level range where R is located, and obtain the current hazard level corresponding to the location. For example: If R ≥ 1.0, the test result far exceeds the threshold, indicating a high risk.
[0019] If 0.6 ≤ R < 1.0, the detection results consistently exceed the threshold, indicating a medium risk.
[0020] If 0.2 ≤ R < 0.6, the detection result is close to the threshold and the risk is low.
[0021] If R < 0.2, the test result does not reach the threshold, shows no upward trend, and there is no risk.
[0022] A4. Visualize the monitoring points and their corresponding hazard levels.
[0023] like Figure 2 As shown, different colored dots indicate different levels of danger at each location: High-risk is marked with a red background dot, medium-risk with an orange background dot, low-risk with a yellow background dot, and no-risk with a green background dot.
[0024] At the same time, high-risk areas are marked with red triangles, and medium-risk areas are marked with orange triangles.
[0025] A5. Regulatory personnel conduct source tracing based on the hazard level marked at the location, and take further source tracing actions based on the color of the flag.
[0026] The wastewater toxicity monitoring point reliability analysis device of this embodiment is used to implement the analysis method of this embodiment. The analysis device includes: The data acquisition module is used to collect current monitoring data of wastewater at various locations, including drug content detection values, time, and location.
[0027] The storage module is used to store the current monitoring data, historical monitoring data, danger level ranges, and warning thresholds.
[0028] The calculation module is used to call the data of the storage module to obtain the R corresponding to each point, find the danger level interval where R is located, and obtain the current danger level corresponding to the point.
[0029] R = W1×S + W2×T + W3×P; W1, W2 and W3 are weights, and W1 + W2 + W3 = 1.
[0030] S = (current detection value - warning threshold) / warning threshold, T = (recent average value - baseline average value) / baseline average value, P = number of times the threshold is exceeded consecutively / total number of assessments.
[0031] A visualization module is used to visually display the monitoring points and the corresponding hazard levels.
[0032] Example 2
[0033] An example of the reliability analysis method and device for wastewater toxicity monitoring points according to Example 1 of this application, applied to toxicity monitoring in a certain area in Southeast China.
[0034] Taking a sampling point at a pumping station on a certain street in a certain district as an example, the results of sewage toxicity monitoring were determined.
[0035] Wastewater samples were obtained from the sampling points and sent to the instrument for drug content detection.
[0036] The current test results are as follows: {"Detection value": "Cocaine 0.4ng / L","Detection time": "2020-07-15 14:00:00", "Sampling point name": "Pumping station on a certain road in a certain street of a certain district","Sampling point coordinates": "x,y"}.
[0037] The test results for the most recent 6 months are as follows: {"Detected value": "Cocaine 0.2ng / L","Detection time": "202×-01-15 14:00:00"}.
[0038] {"Detection value": "Cocaine 0.1ng / L","Detection time": "202×-02-15 14:00:00"}.
[0039] {"Detection value": "Cocaine 0.3ng / L","Detection time": "202×-03-15 14:00:00"}.
[0040] {"Detection value": "Cocaine 0.2ng / L","Detection time": "202×-04-15 14:00:00"}.
[0041] {"Detection value": "Cocaine 0.3ng / L","Detection time": "202×-05-15 14:00:00"}.
[0042] {"Detection value": "Cocaine 0.3ng / L","Detection time": "202×-06-15 14:00:00"}.
[0043] Conduct risk level assessment.
[0044] The current detection value {0.4}, the detection values of the past 6 months {0.2, 0.1, 0.3, 0.2, 0.3, 0.3}, the cocaine warning threshold of 0.5, and the weight values W1=0.5, W2=0.25, W3=0.25 are substituted into the risk level assessment formula R= (W1× S) + (W2×T)+ (W3×P) for calculation.
[0045] S = (current detection value - warning threshold) / warning threshold = (0.4 - 0.5) / 0.5 = -0.2.
[0046] T = (Recent average - Baseline average) / Baseline average = (0.27 - 0.23) / 0.23 = 0.17. The recent average is the average of the test values in April, May, and June, and the baseline average is the average of the test values over the past 6 months.
[0047] P = (Number of consecutive times exceeding the threshold) / (Total number of assessments) = 0 / 6 = 0. The total number of assessments is for the most recent 6 months.
[0048] R=(0.5×(-0.2)) + (0.25×0.17) + (0.25×0)=-0.06.
[0049] The risk level assessment result R is obtained.
[0050] Based on the risk level assessment result R, the detection value, the detection time, the sampling point name, and the sampling point coordinates.
[0051] { "R": "-0.06","Detection Value": "Cocaine 0.4ng / L","Detection Time":"202×-07-15 14:00:00","Sampling Point Name": "Pumping Station of a Certain Street in a Certain District", "Sampling Point Coordinates": "x,y"}.
[0052] A risk heat map was drawn on the GIS map. Since R=-0.06<0.2 indicates no risk, the sampling points are only green background dots.
[0053] Since there were no triangular flags at the sampling sites, staff did not need to process the risk level assessment results.
[0054] Example 3
[0055] An example of the reliability analysis method and device for wastewater toxicity monitoring points according to Example 1 of this application, applied to toxicity monitoring in a certain area in Southwest China.
[0056] Taking the sampling point at the entrance of No. 8, a certain avenue in a certain county as an example, the results of sewage toxicity monitoring were determined.
[0057] Wastewater samples were obtained from the sampling points and sent to the instrument for drug content detection.
[0058] The current test results are as follows: {"Detection value": "Cocaine 1.1ng / L","Detection time": "2020-07-05 15:00:00", "Sampling point name": "Entrance of No. 8, a certain avenue","Sampling point coordinates": "x,y"}.
[0059] Test results from the last 6 months: {"Detection value": "Cocaine 0.4ng / L","Detection time": "202×-01-05 15:00:00"}.
[0060] {"Detected value": "Cocaine 0.4ng / L","Detection time": "202×-02-05 15:00:00"}.
[0061] {"Detection value": "Cocaine 0.4ng / L","Detection time": "202×-03-05 15:00:00"}.
[0062] {"Detection value": "Cocaine 0.9ng / L","Detection time": "202×-04-05 15:00:00"}.
[0063] {"Detection value": "Cocaine 0.8ng / L","Detection time": "202×-05-05 15:00:00"}.
[0064] {"Detection value": "Cocaine 0.9ng / L","Detection time": "202×-06-05 15:00:00"}.
[0065] Conduct risk level assessment.
[0066] The current detection value {1.1}, the detection values of the past 6 months {0.4, 0.4, 0.4, 0.9, 0.8, 0.9}, the cocaine warning threshold of 0.5, and the weight values W1=0.5, W2=0.25, W3=0.25 are substituted into the risk level assessment formula R= (W1 ×S) + (W2×T)+ (W3×P) for calculation.
[0067] S = (current detection value - warning threshold) / warning threshold = (1.1 - 0.5) / 0.5 = 1.2.
[0068] T = (Recent average - Baseline average) / Baseline average = (0.87 - 0.63) / 0.63 = 0.38. The recent average is the average of the test values in April, May, and June, and the baseline average is the average of the test values over the past 6 months.
[0069] P = (Number of consecutive times exceeding the threshold) / (Total number of assessments) = 3 / 6 = 0.5. The total number of assessments is for the most recent 6 months.
[0070] R=(0.5×1.2) + (0.25×0.38) + (0.25×0.5)=0.82.
[0071] The risk level assessment result R is obtained.
[0072] Based on the risk level assessment result R, the detected value, the detection time, the sampling point name, and the sampling point coordinates. {"R": "0.82", "Detection Value":"Cocaine 1.1ng / L","Detection Time":"202×-07-05 15:00:00","Sampling Point Name": "Entrance of No. 8, a certain avenue","Sampling Point Coordinates": "x,y"} A risk heat map is drawn on the GIS map. Since R=0.82 and 0.6≤R<1.0, it belongs to medium risk. Therefore, the sampling point is represented by an orange background dot, and the icon is an orange triangle flag.
[0073] Based on the orange triangular flag icon displayed at the sampling point, staff need to take action and arrange for source tracing and investigation.
Claims
1. A method for analyzing the reliability of wastewater toxicity monitoring sites, characterized in that, The analytical method includes the following steps: A1. Collect current monitoring data of wastewater at each location, including drug content detection values, time, and location; A2. Obtain the R corresponding to each location based on the current monitoring data and historical monitoring data; R = W1×S + W2×T + W3×P; W1, W2 and W3 are weights, and W1+W2+W3=1; S = (current detection value - warning threshold) / warning threshold, T = (recent average value - baseline average value) / baseline average value, P = number of times the threshold is exceeded consecutively / total number of assessments; A3. Locate the danger level range where R is located and obtain the current danger level corresponding to the location; A4. Visualize the monitoring points and their corresponding hazard levels.
2. The analytical method according to claim 1, characterized in that, The danger level is displayed in the following way: Different colors are used to indicate different levels of danger.
3. The analytical method according to claim 2, characterized in that, The markings are dots and / or flags.
4. The analytical method according to claim 1, characterized in that, The baseline average is the average of the long-term detection values.
5. The analytical method according to claim 4, characterized in that, The recent average value is the average of the three most recent detection values, and the extreme average value is the average value of the six most recent months.
6. The analytical method according to claim 1, characterized in that, The hazard level is: If R ≥ 1.0, the test result far exceeds the threshold, indicating a high risk. If 0.6 ≤ R < 1.0, the test results consistently exceed the threshold, indicating a medium risk. If 0.2 ≤ R < 0.6, the detection result is close to the threshold, indicating low risk. If R < 0.2, the test result does not reach the threshold, shows no upward trend, and there is no risk.
7. The analytical method according to claim 1, characterized in that, The analytical method further includes the following steps: A5. Regulatory personnel conduct source tracing based on the hazard level marked at the location.
8. A device for analyzing the reliability of wastewater toxicity monitoring points, characterized in that, The analytical apparatus includes: The data acquisition module is used to collect current monitoring data of wastewater at various locations, including drug content detection values, time, and location. The storage module is used to store the current monitoring data, historical monitoring data, hazard level ranges, and early warning thresholds; The calculation module is used to call the data of the storage module to obtain R corresponding to each point, find the danger level interval where R is located, and obtain the current danger level corresponding to the point. R = W1×S + W2×T + W3×P; W1, W2 and W3 are weights, and W1+W2+W3=1; S = (current detection value - warning threshold) / warning threshold, T = (recent average value - baseline average value) / baseline average value, P = number of times the threshold is exceeded consecutively / total number of assessments; A visualization module is used to visually display the monitoring points and the corresponding hazard levels.
9. The analytical apparatus according to claim 8, characterized in that, The danger level is displayed in the following way: Different colors are used to mark different levels of danger.
10. The analytical apparatus according to claim 8, characterized in that, The hazard level is: If R ≥ 1.0, the test result far exceeds the threshold, indicating a high risk. If 0.6 ≤ R < 1.0, the test results consistently exceed the threshold, indicating a medium risk. If 0.2 ≤ R < 0.6, the detection result is close to the threshold, indicating low risk. If R < 0.2, the test result does not reach the threshold, shows no upward trend, and there is no risk.