CN111508182A - Novel monitoring alarm system for community fire fighting through Internet of things - Google Patents
Novel monitoring alarm system for community fire fighting through Internet of things Download PDFInfo
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- CN111508182A CN111508182A CN202010353229.9A CN202010353229A CN111508182A CN 111508182 A CN111508182 A CN 111508182A CN 202010353229 A CN202010353229 A CN 202010353229A CN 111508182 A CN111508182 A CN 111508182A
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/04—Inference or reasoning models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/04—Inference or reasoning models
- G06N5/048—Fuzzy inferencing
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/06—Electric actuation of the alarm, e.g. using a thermally-operated switch
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/10—Actuation by presence of smoke or gases, e.g. automatic alarm devices for analysing flowing fluid materials by the use of optical means
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/10—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using wireless transmission systems
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y20/00—Information sensed or collected by the things
- G16Y20/10—Information sensed or collected by the things relating to the environment, e.g. temperature; relating to location
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/10—Detection; Monitoring
Abstract
The invention discloses a novel monitoring alarm system for community fire protection by using the Internet of things, and belongs to the field of community fire protection alarm systems. The utility model provides a novel thing networking is used for monitoring alarm system of district fire control, combine the temperature detection, the combined type detector that smog detected and CO detected, comprehensive analysis through three kinds of signals, improve detector sensitivity, and propose the mode that zigBee technique and CAN bus technique combined together, realize the transmission of fire signal, and avoided traditional signal to judge not intelligent enough, when the condition when environmental change condition and conflagration take place is extremely similar, the fire signal is hardly distinguished, the wrong report takes place easily, utilize fuzzy neural network to constantly train the experimental sample, obtain one and CAN regard as the reliable mathematical model that fire signal judged.
Description
Technical Field
The invention relates to the field of community fire-fighting alarm systems, in particular to a novel monitoring alarm system for community fire fighting based on the Internet of things.
Background
The automatic fire alarm system consists of trigger, fire alarm, linkage output unit and other auxiliary functional units, and it can convert the physical quantities of smoke, heat and flame produced by burning into electric signal through fire detector and transmit the electric signal to fire alarm controller in the initial stage of fire and inform the evacuation of the whole floor in the form of sound or light.
The existing novel Internet of things is used for monitoring and alarming systems for community fire fighting, judgment is not intelligent enough, and the condition of misinformation caused by environmental change cannot be avoided.
Disclosure of Invention
The invention aims to solve the problems that judgment is not intelligent enough and false alarm caused by environmental change cannot be avoided, and provides a novel monitoring and alarming system for community fire protection based on the Internet of things.
In order to achieve the purpose, the invention adopts the following technical scheme:
a novel monitoring alarm system for community fire fighting of the Internet of things comprises the following steps:
s1, monitoring smoke concentration, temperature and CO concentration in the cell re-ignition disaster area by adopting a composite fire detector, and making an initial judgment on whether a fire disaster occurs by taking the information as a basis for analyzing whether the fire disaster occurs;
s2, transmitting signals of the monitoring information in the S1 in a ZigBee wireless mode and a CAN bus mode, wherein the monitoring information is transmitted to a coordinating node through a routing node in a wireless mode in an underlying network; the upper network adopts a CAN bus mode, and the coordination node transmits information to the server;
s3, carrying out final analysis on the acquired fire information by the monitoring information transmitted in S2 through a server, if the information is judged to be alarm information through a fuzzy neural network algorithm, displaying the alarm information in a client, and if not, directly giving up the alarm information without any processing on the signal; continuing to collect by the composite fire detector and circulating the operations;
s4, when the server judges that fire occurs in S3, the buzzer connected with the server immediately gives out sound alarm; residents quickly evacuate from the site; staff in a community fire alarm control room quickly contacts with a 119 command center and informs the fire position in time;
s5, when the server judges that fire occurs in S3, the server and S4 start the routing node wireless control linkage control equipment to start; automatically storing water in the fire-fighting double-bolt, starting emergency lighting and evacuation indication, starting fire-fighting broadcasting and informing the position where a fire disaster occurs;
and S6, storing the fire information and fault alarm information of each occurrence in a database through a program pre-programmed in the server, and enabling staff to inquire relevant data of the fire at any time.
Preferably, the internal chips of the combined fire detector and the linkage control device in S1 are ZigBee chips, and a CC3530 chip is used as a terminal node of the fire alarm control system, the former is installed in a district important fire area for completing composite detection of fire signals, and the latter is installed in a public corridor for linkage control.
Preferably, the server in S3 is installed in a monitoring center of a cell property, and is connected to a coordination node in a CAN bus manner to manage all networks and nodes, and grasp all services, including database services, network supervision services, data storage, monitoring services, and support services of a client, and the client is connected to the server via a TCP/P protocol.
Preferably, the fuzzy neural network processing in S3 includes the steps of:
a1, carrying out normalization treatment on the collected smoke concentration and temperature according to the CO concentration before entering a fuzzy neural network system;
a2, fuzzifying the original data in A1, mapping the exact digital quantity and the corresponding language, and ensuring the accuracy of data fuzzification;
a3, establishing a rule meeting the specification, wherein the data processing process is mainly carried out by inputting data and language rules, and the final expression form of the inference rule is that if the condition A is met, the conclusion B is true;
and A4, converting the data after logical inference of A3 into a determined value.
Preferably, the specific inference rule in a3 is as follows: when the inference rules are established, contradiction relationships among different rules cannot occur; for all input data needing to be processed, an inference result can be obtained through the established inference rule; and establishing rational number reasoning rules under the condition of ensuring accurate results.
Preferably, the a4 is converted into a specific value by a weighted average method.
Compared with the prior art, the invention provides a novel monitoring alarm system for community fire fighting by using the Internet of things, which has the following beneficial effects:
1. the invention combines a composite detector for temperature detection, smoke detection and CO detection, improves the sensitivity of the detector by comprehensively analyzing three signals, and provides a mode of combining a ZigBee technology and a CAN bus technology to realize the transmission of fire signals, and avoids the problem that the traditional signal judgment is not intelligent enough, so that the fire signals are difficult to distinguish and false alarm is easy to occur when the environmental change condition and the condition of fire are extremely similar, and a reliable mathematical model which CAN be used for judging the fire signals is obtained by continuously training an experimental sample by using a fuzzy neural network.
Drawings
Fig. 1 is a schematic flow diagram of a fuzzy neural network of a monitoring alarm system for fire protection in a community based on the internet of things.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
Example 1:
a novel monitoring alarm system for community fire fighting of the Internet of things comprises the following steps:
s1, monitoring smoke concentration, temperature and CO concentration in the cell re-ignition disaster area by adopting a composite fire detector, and making an initial judgment on whether a fire disaster occurs by taking the information as a basis for analyzing whether the fire disaster occurs;
s2, transmitting signals of the monitoring information in the S1 in a ZigBee wireless mode and a CAN bus mode, wherein the monitoring information is transmitted to a coordinating node through a routing node in a wireless mode in an underlying network; the upper network adopts a CAN bus mode, and the coordination node transmits information to the server;
s3, carrying out final analysis on the acquired fire information by the monitoring information transmitted in S2 through a server, if the information is judged to be alarm information through a fuzzy neural network algorithm, displaying the alarm information in a client, and if not, directly giving up the alarm information without any processing on the signal; continuing to collect by the composite fire detector and circulating the operations;
s4, when the server judges that fire occurs in S3, the buzzer connected with the server immediately gives out sound alarm; residents quickly evacuate from the site; staff in a community fire alarm control room quickly contacts with a 119 command center and informs the fire position in time;
s5, when the server judges that fire occurs in S3, the server and S4 start the routing node wireless control linkage control equipment to start; automatically storing water in the fire-fighting double-bolt, starting emergency lighting and evacuation indication, starting fire-fighting broadcasting and informing the position where a fire disaster occurs;
and S6, storing the fire information and fault alarm information of each occurrence in a database through a program pre-programmed in the server, and enabling staff to inquire relevant data of the fire at any time.
Further, preferably, the internal chips of the combined fire detector and the linkage control device in S1 are ZigBee chips, and a CC3530 chip is used as a terminal node of the fire alarm control system, the former is installed in a district important fire area and used for completing composite detection of fire signals, and the latter is installed in a public corridor and used for linkage control.
Further, preferably, the server in S3 is installed in a monitoring center of the cell property, and is connected to the coordination node in a CAN bus manner, so as to manage all networks and nodes, grasp all services including database services, network supervision services, data storage, monitoring services, support services of the client, and the like, and the client is connected to the server via a TCP/P protocol.
Further, preferably, the fuzzy neural network processing in S3 includes the steps of:
a1, carrying out normalization treatment on the collected smoke concentration and temperature according to the CO concentration before entering a fuzzy neural network system;
a2, fuzzifying the original data in A1, mapping the exact digital quantity and the corresponding language, and ensuring the accuracy of data fuzzification;
a3, establishing a rule meeting the specification, wherein the data processing process is mainly carried out by inputting data and language rules, and the final expression form of the inference rule is that if the condition A is met, the conclusion B is true;
and A4, converting the data after logical inference of A3 into a determined value.
Further, preferably, the specific inference rule in a3 is as follows: when the inference rules are established, contradiction relationships among different rules cannot occur; for all input data needing to be processed, an inference result can be obtained through the established inference rule; and establishing rational number reasoning rules under the condition of ensuring accurate results.
Further, it is preferable that the value of a4 is converted to a specific value by a weighted average method.
Example 2: based on example 1, but with the difference that:
s1, adopting S, T and C to represent smoke concentration, temperature and CO concentration, preprocessing the three signals and outputting the preprocessed signals, and adopting W1、W2、W3And W4Representing the weight between layers, X, Z and D representing the small, medium and large in fuzzy inference, and W1And W2The three signals are divided into X, Z and D according to W3Selecting appropriate fuzzy rule, depending on W4Normalization processing is carried out on the fuzzy rule, the probability of fire is output, and N, Y and M represent no fire, no open fire combustion and open fire;
s2, preprocessing the signals S, T and C and outputting the signals as follows:
Os1＝Is1＝S；Ot1＝It1＝T；Oc1＝Ic1＝C；
x, Z and D are output via the membership function as:
s3, substituting the data in S1 into the formula in S2, and outputting the result as follows:
wherein i, j, k is 1,2,3, which corresponds to X, Z and D linguistic variables respectively;
s4, substituting the data in S1 into the formula in S2, and outputting the result as follows:
s5, realizing the creation and operation of fuzzy rules, and the output formula is as follows:
s6, normalizing the output result, wherein the output formula is as follows:
s7, deblurring the output result, wherein the output formula is as follows:
the above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (6)
1. The utility model provides a novel thing networking is used for monitoring alarm system of district fire control which characterized in that includes following step:
s1, monitoring smoke concentration, temperature and CO concentration in the cell re-ignition disaster area by adopting a composite fire detector, and making an initial judgment on whether a fire disaster occurs by taking the information as a basis for analyzing whether the fire disaster occurs;
s2, transmitting signals of the monitoring information in the S1 in a ZigBee wireless mode and a CAN bus mode, wherein the monitoring information is transmitted to a coordinating node through a routing node in a wireless mode in an underlying network; the upper network adopts a CAN bus mode, and the coordination node transmits information to the server;
s3, carrying out final analysis on the acquired fire information by the monitoring information transmitted in S2 through a server, if the information is judged to be alarm information through a fuzzy neural network algorithm, displaying the alarm information in a client, and if not, directly giving up the alarm information without any processing on the signal; continuing to collect by the composite fire detector and circulating the operations;
s4, when the server judges that fire occurs in S3, the buzzer connected with the server immediately gives out sound alarm; residents quickly evacuate from the site; staff in a community fire alarm control room quickly contacts with a 119 command center and informs the fire position in time;
s5, when the server judges that fire occurs in S3, the server and S4 start the routing node wireless control linkage control equipment to start; automatically storing water in the fire-fighting double-bolt, starting emergency lighting and evacuation indication, starting fire-fighting broadcasting and informing the position where a fire disaster occurs;
and S6, storing the fire information and fault alarm information of each occurrence in a database through a program pre-programmed in the server, and enabling staff to inquire relevant data of the fire at any time.
2. The novel internet of things monitoring and alarming system for community fire protection as claimed in claim 1, wherein: and the internal chips of the combined type fire detector and the linkage control equipment in the S1 are ZigBee chips, and a CC3530 chip is adopted as a terminal node of a fire alarm control system, wherein the ZigBee chip is installed in a key fire area of a cell and used for completing composite detection of fire signals, and the CC3530 chip is installed in a public corridor and used for linkage control.
3. The novel internet of things monitoring and alarming system for community fire protection as claimed in claim 1, wherein: the server in the S3 is installed in a monitoring center of the community property, is connected with the coordination node in a CAN bus mode, manages all networks and nodes, masters all services including database service, network supervision service, data storage, monitoring service, support service of a client and the like, and the client is connected with the server through a TCP/P protocol.
4. The novel internet of things monitoring and alarming system for community fire protection as claimed in claim 1, wherein: the fuzzy neural network processing in S3 includes the steps of:
a1, carrying out normalization treatment on the collected smoke concentration and temperature according to the CO concentration before entering a fuzzy neural network system;
a2, fuzzifying the original data in A1, mapping the exact digital quantity and the corresponding language, and ensuring the accuracy of data fuzzification;
a3, establishing a rule meeting the specification, wherein the data processing process is mainly carried out by inputting data and language rules, and the final expression form of the inference rule is that if the condition A is met, the conclusion B is true;
and A4, converting the data after logical inference of A3 into a determined value.
5. The novel monitoring and alarming system for community fire protection of the Internet of things as claimed in claim 4, wherein: the specific inference rule in a3 is as follows: when the inference rules are established, contradiction relationships among different rules cannot occur; for all input data needing to be processed, an inference result can be obtained through the established inference rule; and establishing rational number reasoning rules under the condition of ensuring accurate results.
6. The novel monitoring and alarming system for community fire protection of the Internet of things as claimed in claim 4, wherein: the A4 is converted into a specific value by a weighted average method.
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Cited By (2)
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| CN113033096A (en) * | 2021-03-24 | 2021-06-25 | 应急管理部四川消防研究所 | Deep learning-based building risk early warning analysis method |
| CN113223264A (en) * | 2021-05-08 | 2021-08-06 | 南通理工学院 | QPSO-BP neural network-based intelligent fire early warning system and method |
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Application publication date: 20200807 |