Integrated pole internet of things device cooperative control system

Abstract

The application relates to the technical field of Internet of Things, and particularly discloses a collaborative control system for an Internet of Things device based on a comprehensive pole, which comprises a rainfall monitoring module arranged on the comprehensive pole and used for monitoring real-time rainfall; a water immersion sensor arranged on the comprehensive pole and used for monitoring real-time water depth; an intelligent sensing well lid used for monitoring the state and operation data of the well lid; a comprehensive pole analysis module in communication connection with the rainfall monitoring module, the water immersion sensor and the intelligent sensing well lid respectively and used for analyzing the drainage state of the region where the comprehensive pole is located; and a warning module arranged on the comprehensive pole and in communication connection with the comprehensive pole analysis module and used for warning and early warning control of traffic according to the analysis result of the comprehensive pole analysis module. The application can judge the drainage risk of the current region in advance through predictive analysis of the water depth and comparison and analysis of real-time water level information.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Things, in particular to a collaborative control system for Internet of Things devices based on a comprehensive pole. BACKGROUND

[0002] The comprehensive pole, also known as the all-in-one pole, is a pole that integrates the functions of multiple poles to solve the problem of poles and overhead lines in urban roads. The comprehensive pole integrates multiple functions through Internet of Things devices and intelligent hardware, such as setting water level sensors on the pole body, setting environmental and meteorological sensor components on the pole body to monitor the environmental status of the area where the comprehensive pole is located, setting information publishing devices on the pole body to assist in directing the road, and connecting with Internet of Things devices to analyze the data of the Internet of Things devices and realize the intelligence of the comprehensive pole.

[0003] In the prior art, although the comprehensive pole integrates a variety of functions and can analyze and manage multiple Internet of Things devices, the management process is independent and lacks collaborative management and control of associated Internet of Things devices. For example, in the analysis process of the road water accumulation state, the prior art mainly uses water level sensors to monitor the real-time water level and issues a warning when the water level exceeds a preset value to notify relevant personnel to clear the risk of road rainwater pipe blockage. Obviously, this method considers only a single factor and has a lag in the judgment process, which cannot timely determine the state of the road rainwater pipe. SUMMARY

[0004] The present application aims to provide a collaborative control system for Internet of Things devices based on a comprehensive pole to solve the following technical problems:

[0005] How to realize timely warning of the state of the road rainwater pipe based on the collaborative control of the comprehensive pole on the Internet of Things devices.

[0006] The purpose of the present application can be achieved by the following technical solutions:

[0007] The collaborative control system for Internet of Things devices based on a comprehensive pole comprises:

[0008] A rainfall monitoring module is arranged on the comprehensive pole to monitor the real-time rainfall;

[0009] A water immersion sensor is arranged on the comprehensive pole to monitor the real-time water accumulation depth;

[0010] An intelligent sensing well cover is used to monitor the state and operation data of the well cover;

[0011] The comprehensive rod analysis module is in communication connection with the rainfall monitoring module, the water immersion sensor and the intelligent sensing well lid respectively, and is used for analyzing the drainage state of the area where the comprehensive rod is located.

[0012] The warning module is arranged on the comprehensive rod and is in communication connection with the comprehensive rod analysis module, and is used for warning and prewarning control of traffic according to the analysis result of the comprehensive rod analysis module.

[0013] Further, the analysis process of the comprehensive rod analysis module comprises:

[0014] Obtaining the well lid state, the well lid state comprising an open state and a closed state;

[0015] When the well lid is in the closed state:

[0016] The predicted water depth value H (t) in the closed state of the well lid is calculated by the formula cpre (t);

[0017] Wherein, r(t) is the real-time rainfall monitored by the rainfall monitoring module, d(t) is the rated drainage capacity, t0 is the rainfall start time point, t A is the first critical time point, and satisfies Ac is the rated drainage capacity influence function, and Ac≤1; f h is the water depth conversion function;

[0018] The predicted water depth value H cpre (t) is compared and analyzed with the real-time water depth H(t) monitored by the water immersion sensor:

[0019] According to the comparison and analysis result, the drainage state of the area where the comprehensive rod is located is prewarned;

[0020] The warning module is used for prewarning control of traffic according to the real-time water depth and the comparison and analysis result.

[0021] Further, when the well lid is in the open state:

[0022] S1, collecting the real-time flow in the operation data of each intelligent sensing well lid, and judging whether the real-time flow reaches the rated flow:

[0023] If it reaches, step S2 is performed;

[0024] Otherwise, it is judged whether H(t) > H0:

[0025] If H(t) > H0, the well lid state is prewarned;

[0026] Otherwise, step S2 is performed;

[0027] S2, by formula The predicted water depth value H is calculated in the open state of the manhole cover oper (t);

[0028] Wherein, H0 is the water depth reference value; t B is the second critical time point, and satisfies n is the number of intelligent perception manhole covers in the area where the comprehensive rod is located, i∈[1, n]; Q i (t) is the real-time flow data obtained by the i-th intelligent perception manhole cover;

[0029] The predicted water depth value H oper (t) is compared and analyzed with the real-time water depth H(t) monitored by the water immersion sensor:

[0030] According to the comparison and analysis result, the drainage state of the area where the comprehensive rod is located is warned.

[0031] Further, the comparison and analysis process is:

[0032] The water depth deviation coefficient δ H (t) at time t is calculated by formula

[0033] Wherein, H pre (t) is any one of H cpre (t) and H oper (t), when H pre (t) is H cpre (t), t x =t A ; when H pre (t) is H opre (t), t x =t B ; x is a fixed coefficient;

[0034] The water depth deviation coefficient δ H (t) is compared with the preset deviation coefficient threshold δ Hth :

[0035] If δ H (t)≥δ Hth , the drainage state of the area where the comprehensive rod is located is warned.

[0036] Further, the warning module performs the process of warning control, which includes:

[0037] The real-time water depth H(t) is compared with the warning water depth interval [H WA , H WB ​Comparison is made:

[0038] If H(t) > H WB , the area is limited by the warning module;

[0039] If H(t) < H WA , normal traffic is maintained;

[0040] If H(t) ∈ [H WA , H WB ], the risk coefficient w(t) is calculated by the formula w(t) = H(t) + τ*δ H (t), and w(t) is compared with the preset threshold W th ;

[0041] If w(t) ≥ W th , the area is limited by the warning module;

[0042] Otherwise, normal traffic is maintained, and a warning is given by the warning module;

[0043] Wherein, τ is a preset adjustment coefficient.

[0044] Further, the system further comprises:

[0045] An environment monitoring module, in communication connection with the comprehensive rod analysis module, for monitoring environmental parameter data of an area where the comprehensive rod is located;

[0046] The comprehensive rod analysis modules of different areas are in communication connection;

[0047] The warning module is used for monitoring area environmental abnormalities according to environmental parameter data of different areas.

[0048] Further, the process of the area environmental abnormality monitoring comprises:

[0049] The environmental abnormality coefficient E k (t) of the kth area is calculated by the formula ;

[0050] Wherein, Z is the number of areas; M is the environmental monitoring parameter item; k ∈ [1, M]; y1 and y2 are weight coefficients, and y1 + y2 = 1; Δt is a preset time interval; α j is the de-dimensioning coefficient of the jth environmental monitoring parameter item;

[0051] The environmental abnormality coefficient E k (t) is compared with a preset abnormality coefficient threshold E thr ;

[0052] If Ek (t) >= E thr Then, the environment state of the kth region is warned.

[0053] Further, the process of the region environment anomaly monitoring further comprises:

[0054] The environment state coefficient U of the kth region is calculated by the formula k (t);

[0055] Wherein, g jt (t) is the standard reference value of the jth environment monitoring parameter item; f j (x) is a piecewise function, and satisfies is the maximum value of in the period of t-Δt~t, and μ is a preset correction coefficient;

[0056] The environment state coefficient U k (t) is compared with a preset state coefficient threshold U thr :

[0057] If U k (t) >= U thr , then a warning is given.

[0058] The beneficial effects of the present application are:

[0059] (1) The present application can judge the drainage risk of the current region before the real-time water level reaches the warning value by the predictive analysis of the accumulated water depth based on the rainfall and the state of the intelligent sensing well lid through the comprehensive rod analysis module, and the comparison and analysis of the real-time water level information obtained by the water immersion sensor, and then realize the warning of the existing risk through the warning module, remind the relevant personnel to investigate in time, and at the same time, control the traffic when the driving risk is large, so as to ensure the safety of road driving. BRIEF DESCRIPTION OF DRAWINGS

[0060] The present application will be further described below in combination with the drawings.

[0061] Figure 1 is a schematic diagram of the outline of the comprehensive rod Internet of Things device cooperative control system based on the present application. DETAILED DESCRIPTION

[0062] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present application.

[0063] Please refer to Figure 1 As shown in the figure, in one embodiment, a comprehensive pole Internet of Things device cooperative control system is provided, which comprises:

[0064] A rainfall monitoring module is arranged on the comprehensive pole and is used for monitoring real-time rainfall;

[0065] A water immersion sensor is arranged on the comprehensive pole and is used for monitoring real-time water depth;

[0066] An intelligent sensing well lid is used for monitoring the state and operation data of the well lid;

[0067] A comprehensive pole analysis module is in communication connection with the rainfall monitoring module, the water immersion sensor and the intelligent sensing well lid, and is used for analyzing the drainage state of the area where the comprehensive pole is located;

[0068] A warning module is arranged on the comprehensive pole and is in communication connection with the comprehensive pole analysis module, and is used for warning and pre-warning control of traffic according to the analysis result of the comprehensive pole analysis module.

[0069] Through the above technical solution, in the embodiment, the rainfall monitoring module and the water immersion sensor are integrated on the comprehensive pole and are in communication connection with the intelligent sensing well lid, so that based on the real-time rainfall and the state of the intelligent sensing well lid, the comprehensive pole analysis module can perform predictive analysis on the water depth based on the rainfall and the state of the intelligent sensing well lid, and can compare and analyze the real-time water level information obtained by the water immersion sensor, so that the drainage risk of the current area can be judged before the real-time water level reaches the warning value, and the warning module can be used to warn the existing risk and remind relevant personnel to timely investigate, and the traffic can be pre-warning controlled when the driving risk is large, so that the safety of road driving can be ensured.

[0070] It should be noted that the hardware of the rainfall monitoring module, the water immersion sensor, the intelligent sensing well lid and the warning module can be obtained by the prior art, and will not be described in detail here.

[0071] As an embodiment of the present application, the process of analysis performed by the comprehensive pole analysis module comprises:

[0072] Obtaining the state of the well lid, wherein the state of the well lid comprises an open state and a closed state;

[0073] When the manhole cover is closed:

[0074] Through formula The predicted water depth H is calculated when the manhole cover is closed. cpre (t);

[0075] Where r(t) is the real-time rainfall monitored by the rainfall monitoring module, d(t) is the rated drainage capacity, t0 is the rainfall start time, and t A This is the first critical time point, and it satisfies... Ac is the influence function of rated drainage capacity, and Ac≤1; f h This is the water depth transformation function;

[0076] Predict the water depth H cpre Comparison and analysis were performed between (t) and the real-time water depth H(t) monitored by the water immersion sensor:

[0077] Based on the results of comparative analysis, an early warning is issued regarding the drainage status of the area where the integrated pole is located.

[0078] The warning module is used to provide early warning and control for traffic based on real-time water depth and comparative analysis results.

[0079] Through the above technical solution, this embodiment provides an analysis method for the manhole cover in the closed state, using formulas. The water depth under this condition is predicted to obtain the predicted water depth value H when the manhole cover is closed. cpre (t), where r(t) is the real-time rainfall monitored by the rainfall monitoring module, d(t) is the rated drainage capacity, and Ac is the rated drainage capacity influence function, which is a decreasing function, obtained by data fitting based on the rainfall and water accumulation data of the area. Therefore, through It can process water accumulation exceeding the area's natural drainage capacity, converting the water volume into a depth value using a water depth conversion function, thereby obtaining the predicted water depth value when the manhole cover is closed; then, it uses the predicted water depth value H... cpre The system compares and analyzes the real-time water depth H(t) monitored by the water immersion sensor to provide an early warning of the drainage status in the area where the integrated pole is located; at the same time, the warning module will also conduct traffic warning control based on the real-time water depth and the comparison analysis results to maintain the safety of driving in the area.

[0080] It should be noted that the water depth conversion function f in the above technical solution h This data was obtained through data fitting analysis based on historical data of the region, and will not be described in further detail here.

[0081] As one embodiment of the present invention, when the manhole cover is in the open state:

[0082] S1, collecting real-time flow in each intelligent sensing manhole cover operation data, judging whether the real-time flow reaches the rated flow:

[0083] If so, step S2 is performed;

[0084] Otherwise, it is determined whether H(t) > H0:

[0085] If H(t) > H0, the manhole cover state is warned;

[0086] Otherwise, step S2 is performed;

[0087] S2, the predicted water depth value H (t) under the opening state of the manhole cover is obtained by the formula opre (t);

[0088] Wherein, H0 is the water depth reference value; t B is the second critical time point, and satisfies n is the number of intelligent sensing manhole covers in the region where the comprehensive rod is located, i ∈ [1, n]; Q i (t) is the real-time flow data obtained by the i-th intelligent sensing manhole cover;

[0089] The predicted water depth value H opre (t) is compared and analyzed with the real-time water depth H(t) monitored by the water immersion sensor:

[0090] According to the comparison and analysis result, the drainage state of the region where the comprehensive rod is located is warned.

[0091] Through the above technical solution, the embodiment gives a process of analyzing by the comprehensive rod analysis module when the manhole cover is in the opening state. First, the real-time flow in each intelligent sensing manhole cover operation data is collected, and it is judged whether the real-time flow reaches the rated flow. If so, it means that the corresponding drainage port state is normal, so step S2 is performed for analysis. If not, it is determined whether H(t) > H0. H0 is the water depth reference value. Under this water depth reference value, the real-time flow corresponding to the drainage port should reach the rated flow. Therefore, if H(t) > H0, it means that there is a risk of blockage of the drainage port, and the manhole cover state is warned. In the analysis process of step S2, The predicted water depth value H opre (t) under the opening state of the manhole cover is obtained by calculation. Compared with the calculation process under the closed state of the manhole cover, the embodiment eliminates the influence of the drainage port of the manhole cover on the water level by subtraction and then obtains the predicted water depth value H opre(t) is compared and analyzed, and the drainage state of the area where the comprehensive rod is located is warned according to the comparison and analysis result.

[0092] As an embodiment of the present application, the comparison and analysis process is:

[0093] The water depth deviation coefficient δ at time t is calculated by the formula H (t);

[0094] Wherein, H pre (t) is H cpre (t) and H opre (t) is any one of H pre (t) is H cpre (t), t x =t A ; when H pre (t) is H opre (t), t x =t B ; x is a fixed coefficient.

[0095] The water depth deviation coefficient δ H (t) is compared with the preset deviation coefficient threshold δ Hth :

[0096] If δ H (t)≥δ Hth , the drainage state of the area where the comprehensive rod is located is warned.

[0097] Through the above technical solution, the embodiment provides a comparison and analysis method, that is, the water depth deviation coefficient δ H (t) at time t is calculated by the formula pre , wherein H(t)-H x (t) is the real-time state at time t, is the average state in the t H period, therefore, when the water depth deviation coefficient δ Hth (t) and the preset deviation coefficient threshold δ H , it means that the two are out-of-tolerance and abnormal, and there are factors affecting the normal drainage of rainwater, including drainage pipe blockage, etc., therefore, when δ Hth (t)≥δ Hth , the drainage state of the area where the comprehensive rod is located is warned, and the abnormal drainage state can be judged.

[0098] It should be noted that the fixed coefficient x and the preset deviation coefficient threshold δ WA in the above technical solution are set according to empirical data.

[0099] As an embodiment of the present application, the process of the warning module for early warning control comprises:

[0100] comparing the real-time water depth H(t) with the early warning water depth interval [H WA , H WB ];

[0101] if H(t) > H WB , limiting the traffic in the area through the warning module;

[0102] if H(t) < H WA , keeping normal traffic;

[0103] if H(t) ∈ [H WA , H WB ], calculating the risk coefficient w(t) through the formula w(t) = H(t) + τ*δ H (t), and comparing w(t) with the preset threshold W th ;

[0104] if w(t) ≥ W th , limiting the traffic in the area through the warning module;

[0105] otherwise, keeping normal traffic while early warning through the warning module;

[0106] wherein τ is a preset adjustment coefficient.

[0107] Through the above technical solution, the embodiment provides a process of early warning control by the warning module. First, the real-time water depth H(t) is compared with the early warning water depth interval [H WA , H WB ]. The early warning water depth interval [H WA , H WB ] is set according to the safety alert water level in the traffic process, so that when H(t) > H WB , it indicates that the area is not suitable for traffic, and thus the traffic in the area is limited through the warning module; when H(t) < H WA , it indicates that the water has no effect on normal traffic, and thus normal traffic is kept; and when H(t) ∈ [H WA , H WB ], further analysis is needed in combination with the water depth deviation coefficient δ H (t). Specifically, the risk coefficient w(t) is calculated through the formula w(t) = H(t) + τ*δ H (t), wherein the preset adjustment coefficient τ is set according to the range of historical data of δ H (t), and the preset threshold Wth According to H WB The size is obtained after the reference fitting correction, so w(t) is compared with a preset threshold W th Comparison is made, and then when w(t) ≥ W th The area is limited by the warning module; when w(t) < W th Normal traffic is maintained, and a warning is given by the warning module.

[0108] As an embodiment of the present application, the system further comprises:

[0109] An environment monitoring module, in communication connection with the comprehensive rod analysis module, is configured to monitor environmental parameter data of an area where the comprehensive rod is located;

[0110] The comprehensive rod analysis modules of different areas are in communication connection;

[0111] The warning module is configured to perform regional environmental anomaly monitoring according to the environmental parameter data of different areas.

[0112] The process of the regional environmental anomaly monitoring comprises:

[0113] The environmental anomaly coefficient E of the kth area is calculated by the formula k (t);

[0114] Wherein, Z is the number of areas; M is an environmental monitoring parameter item; k ∈ [1, M]; y1 and y2 are weight coefficients, and y1 + y2 = 1; Δt is a preset time interval; α j is a de-dimensioning coefficient of the jth environmental monitoring parameter item;

[0115] The environmental anomaly coefficient E k (t) is compared with a preset anomaly coefficient threshold E thr

[0116] If E k (t) ≥ E thr , the environmental state of the kth area is warned.

[0117] Through the above technical solution, the present embodiment further monitors and judges the environmental anomaly of each area through the mutual communication process of the comprehensive rod analysis modules of different areas. Specifically, the environmental monitoring item data of a single area is compared with the average value of the data of multiple areas. Since the environmental parameter item data of an area is relatively small, when the environmental parameter item data of a certain area is significantly different from the overall data, it indicates that the area has an abnormal condition, i.e., through the formula ​comprehensive analysis is performed on the environmental parameter item data in real-time state and historical state, wherein, the preset time interval Δt can be set according to the region where the user is located, the weight coefficients y1 and y2 are used to assign different weights to real-time data and historical data, and the weight coefficients y1 and y2 are set according to the historical environmental parameter data of the region; the dimensionless coefficient α j is set according to the value range of different environmental monitoring parameter items, therefore, the environmental anomaly coefficient E k (t) reflects the difference state of the environmental parameter of the kth region relative to the average state of the entire region, and then the environmental anomaly coefficient E k (t) is compared with the preset anomaly coefficient threshold E thr , and the early warning of the environmental state of each region is realized.

[0118] It should be noted that the preset anomaly coefficient threshold E thr is obtained by fitting according to the specific environmental monitoring parameter item, which is not described in detail herein.

[0119] As an embodiment of the present application, the process of the regional environmental anomaly monitoring further comprises:

[0120] The environmental state coefficient U k (t) of the kth region is obtained by calculation through the formula

[0121] wherein, g jt (t) is the standard reference value of the jth environmental monitoring parameter item; f j (x) is a piecewise function, and satisfies is the maximum value of f (x) in the period of t-Δt~t, and μ is a preset correction coefficient;

[0122] The environmental state coefficient U k (t) is compared with the preset state coefficient threshold U thr :

[0123] If U k (t) ≥ U thr , early warning is performed.

[0124] Through the above technical solution, the present embodiment further monitors and analyzes the environmental anomaly of the kth region by comparing the environmental monitoring parameter item data of the single region with the standard reference value to obtain the environmental state coefficient U k (t) of the kth region through the formula , wherein, ​Therefore, when the corresponding values ​​of environmental monitoring parameters are high or when there are large abnormal increases in parameters, this will be reflected in the obtained environmental state coefficient U. k (t) and then through the environmental state coefficient U k (t) and the preset state coefficient threshold U thr By comparing data, early warning of the environmental status of the area can be achieved.

[0125] It should be noted that the preset correction coefficient μ is based on Historical data selection and fitting settings, preset state coefficient threshold U thr The settings are then selected based on multiple sets of empirical data, which will not be detailed here.

[0126] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A comprehensive pole-based IoT device collaborative control system, characterized in that, The system comprises: A rainfall monitoring module arranged on the comprehensive pole and used for monitoring real-time rainfall; A water immersion sensor arranged on the comprehensive pole and used for monitoring real-time water depth; An intelligent sensing manhole cover used for monitoring manhole cover state and operation data; A comprehensive pole analysis module in communication connection with the rainfall monitoring module, the water immersion sensor and the intelligent sensing manhole cover and used for analyzing drainage state of a region where the comprehensive pole is located; A warning module arranged on the comprehensive pole and in communication connection with the comprehensive pole analysis module and used for warning and prewarning control of traffic according to analysis result of the comprehensive pole analysis module; The analysis process of the comprehensive pole analysis module comprises: Obtaining manhole cover state, which comprises an open state and a closed state; When the manhole cover is in the closed state: The predicted water depth value H in the closed state of the manhole cover is calculated by the formula cpre (t);​ Wherein, r(t) is the rainfall monitoring module monitoring real-time rainfall, d(t) is the rated displacement, t0 is the rainfall starting time point, t A is the first critical time point, and satisfies Ac is the rated displacement influence function, and Ac≤1; f h is the water depth conversion function; The predicted water depth value H cpre (t) is compared with the water immersion sensor monitored real-time water depth H(t): Prewarning the drainage state of the region where the comprehensive pole is located according to the comparison and analysis result; The warning module is used for prewarning control of traffic according to real-time water depth and the comparison and analysis result. 2.The integrated-rod IoT device collaborative control system according to claim 1, wherein, When the manhole cover is in the open state: S1, collecting real-time flow in operation data of each intelligent sensing manhole cover and judging whether the real-time flow reaches rated flow: If yes, step S2 is performed; Otherwise, judging whether H(t) > H0: If H(t) > H0, prewarning the manhole cover state; Otherwise, step S2 is performed; S2, by the formula The predicted water depth value H in the open state of the well lid is calculated opre (t); Wherein, H0 is the water depth reference value; t B is the second critical time point, and satisfies n is the number of intelligent sensing manhole covers in the region where the rod is located, i∈[1, n]; Q i (t) is the real-time flow data obtained by the ith intelligent sensing manhole cover; The predicted water depth value H opre (t) is compared with the water immersion sensor monitored real-time water depth H(t): Prewarning the drainage state of the region where the comprehensive pole is located according to the comparison and analysis result. 3.The integrated-rod IoT device collaborative control system according to claim 2, wherein, The comparison and analysis process comprises: The water depth deviation coefficient δ at time t is calculated by the formula H (t);​ wherein H pre (t) is H cpre (t) and H opre (t) are any of the above, when H pre (t) is H cpre (t), t x = t A ; when H pre (t) is H opre (t), t x = t B ; ω is a constant coefficient; The water depth deviation coefficient δ H (t) is compared with a preset deviation coefficient threshold δ Hth Comparison is made: If δ H (t)≥δ Hth , a warning is given for the drainage state of the area where the comprehensive rod is located. 4.The integrated-rod IoT device collaborative control system according to claim 3, wherein, The prewarning control process of the warning module comprises: The real-time water depth H(t) is compared with the warning water depth interval [H WA ,H WB ]: If H(t) > H WB then restrict access to this area by the alert module; If H(t) < H WA Normal traffic is maintained. If H(t)∈[H WA , H WB ], the risk coefficient w(t) is calculated by the formula w(t) = H(t) + τ*δ H (t), and w(t) is compared with a preset threshold W th . If w(t) ≥ W th then restrict access to this area by the alert module; Otherwise, keeping normal traffic and prewarning through the warning module; Wherein, τ is a preset adjustment coefficient. 5.The integrated-rod IoT device collaborative control system of claim 1, wherein, The system further comprises: An environment monitoring module in communication connection with the comprehensive pole analysis module and used for monitoring environmental parameter data of the region where the comprehensive pole is located; The comprehensive pole analysis modules of different regions are in communication connection; The warning module is used for regional environmental anomaly monitoring according to environmental parameter data of different regions. 6.The integrated-rod IoT device collaborative control system of claim 5, wherein, The regional environmental anomaly monitoring process comprises: The environmental anomaly coefficient E of the kth region is calculated by the formula k (t);​ wherein, Z is the number of zones; M is the environmental monitoring parameter item; j ∈ [1, M]; y1, y2 are weight coefficients, and y1 + y2 = 1; Δt is a preset time interval; α j is the dimensionless coefficient of the jth environmental monitoring parameter item; The environmental anomaly coefficient E k (t) is compared with a preset anomaly coefficient threshold E thr is compared with a preset anomaly coefficient threshold E If E k (t) ≥ E thr then an alert is issued for the environmental state of the kth region.

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