CN110044409A - A kind of big transport intellectual monitoring early warning system of dangerous material based on Internet of Things and method - Google Patents
A kind of big transport intellectual monitoring early warning system of dangerous material based on Internet of Things and method Download PDFInfo
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- CN110044409A CN110044409A CN201910232098.6A CN201910232098A CN110044409A CN 110044409 A CN110044409 A CN 110044409A CN 201910232098 A CN201910232098 A CN 201910232098A CN 110044409 A CN110044409 A CN 110044409A
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- G—PHYSICS
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- H—ELECTRICITY
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Abstract
The invention discloses a kind of big transport intellectual monitoring early warning systems of dangerous material based on Internet of Things and method, system to be made of data acquisition unit, mobile terminal, cloud server, Database Systems；The data acquisition unit is for acquiring the status datas such as temperature and humidity, gas concentration, pressure inside and outside hazardous materials transportation vehicle car；The mobile terminal is used to the status data received uploading to cloud server, and interacts with vehicle driver；The cloud server is for carrying out the regressing calculation based on TensorFlow platform for the data in combination with historic data received and providing real-time status prediction result；The Database Systems are for saving historical data；This system realizes the monitoring and judgement of high-performance, low cost, the hazardous materials transportation vehicle safety state of flexible expansion, and early warning result is fed back into vehicle driver eventually by mobile terminal, so that it is understood dangerous material description of the goods in time and handle, avoids accident.
Description
Technical field
The present invention relates to dangerous material monitoring field more particularly to a kind of big transport intellectual monitorings of dangerous material based on Internet of Things
Early warning system and method.
Background technique
Road haulage industry is a basic and advanced sector of socio-economic development, and constitutes land transportation
One of two basic means of transportation.As modern logistics and national economic development foundation, transport service plays more and more important
Effect.Among these, hazardous materials transportation is an important branch, according to incompletely statistics: 2015, national dangerous material road road transport
About 1,000,000,000 tons of throughput rate, about 1.1 ten thousand family of hazardous material road transportation enterprise, about 1,200,000 people of practitioner, haulage vehicle about 310,000.
However during transportation, the transport of hazardous goods such as inflammables and explosives is hazardous in recent years there are many security risks
The accidents such as product haulage vehicle rollover, collision, leakage and explosion frequently occur, and cause huge casualties and property loss.
At present China hazardous materials transportation monitoring, in terms of there are many deficiencies, existing product is mostly for single vehicle
Dangerous material monitoring, make full use of big data and the technical advantage of Internet of Things not yet to improve the safety of transport.
Summary of the invention
The present invention provides a kind of big transport intellectual monitoring early warning systems of dangerous material based on Internet of Things, realize high property
The judgement of energy, low cost, the hazardous materials transportation vehicle safety state of flexible expansion.
In order to achieve the above object, the present invention adopts the following technical scheme:
A kind of big transport intellectual monitoring early warning system of the dangerous material based on Internet of Things, system is by data acquisition unit, movement
Terminal, cloud server, Database Systems are constituted；The data acquisition unit is for acquiring inside and outside hazardous materials transportation vehicle car
The status datas such as temperature and humidity, gas concentration, pressure；The mobile terminal is used for the status number that will be received from data acquisition unit
Cloud server is uploaded to according to by wireless network, and is interacted with vehicle driver；The cloud service will be for that will receive
To status data combined data library in the historical data that saves carry out the regressing calculation based on TensorFlow platform and provide
Real-time status prediction；Database Systems are for saving historical data.
The data acquisition unit is based on 3 development board of Raspberry Pi of Android Things platform and its institute
The sensor of carrying, sensor include temperature sensor, humidity sensor, gas concentration sensor, pressure transducer etc.；Data
State acquisition unit periodically sends the mobile terminal based on android system for status data.
The status data includes temperature and humidity (inside and outside tank), oxygen concentration (in tank), (tank is inside and outside, safe for gas concentration
Valve), pressure (top tank structure), air concentration (inside and outside tank), liquid detecting (safety valve).
The mobile terminal receives the status data that the data acquisition unit is sent, by status data and preset safety
Threshold value is compared, and is sounded an alarm by way of interactive voice if being more than secure threshold and is reminded vehicle driver, either
No is more than secure threshold, and status data is all uploaded to the cloud server by the mobile terminal.
The cloud server carries out the step of regressing calculation based on TensorFlow platform are as follows:
(1) the laggard line number Data preprocess of the status data is received；
(2) the current dangerous index of single collection point is calculated；
(3) predict that following several minutes of the danger refers to by Time Series Forecasting Methods in conjunction with historical data and current data
Number；
(4) producing cause and solution of hazard index are mapped.
Bluetooth communication, the mobile terminal and the cloud are used between the data acquisition unit and the mobile terminal
Pass through 3G/4G wireless communication between server.
A kind of big transport intellectual monitoring method for early warning of the dangerous material based on Internet of Things, using above-mentioned system, step is such as
Under:
(1) vehicle driver manually selects dangerous material type: flammable and combustible liquids, flammable explosive gas, noxious material liquid
Body or noxious material gas；
(2) data acquisition unit is placed in corresponding position inside and outside hazardous materials transportation vehicle car, and powered；
(3) data acquisition unit connects bluetooth communication, and the status data inside and outside collected compartment is periodically sent out
It is sent to the mobile terminal；
(4) mobile terminal is held by driver, receives the status data of data acquisition unit acquisition, and judgement has off status
Whether data are more than preset secure threshold.If exceeding preset secure threshold, executes step (5), otherwise execute
Step (6)；
(5) mobile terminal sounds an alarm prompt vehicle driver by interactive voice；
(6) monitoring data are uploaded to the cloud server by 3G/4G network by mobile terminal；
(7) cloud server operates in TensorFlow platform, the historical data and current number stored in combined data library
According to regressing calculation is carried out, real-time hazard index is obtained, and operation result is stored in database；If hazard index is more than to preset
Threshold value, then warning information is transmitted back to mobile terminal, mobile terminal sounds an alarm prompt vehicle in time by interactive voice and drives
The person of sailing.
Beneficial effects of the present invention are as follows:
The status data for dispersing independent hazardous materials transportation vehicle is uploaded to cloud service by mobile terminal by the present invention
Device provides the hazardous materials transportation vehicle peace of high-performance, low cost, reliable intelligence as the training data for carrying out regressing calculation
Total state monitoring and early warning, reduce accident probability.
Detailed description of the invention
Fig. 1 is the system frame of the big transport intellectual monitoring early warning system of the dangerous material of the invention based on Android Things
Figure；
Fig. 2 is the warning algorithm flow chart of cloud server of the invention based on 0TensorFlow platform；
Fig. 3 is system flow chart of the invention.
Specific embodiment
It is clear in order to be more clear the objectives, technical solutions, and advantages of the present invention, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, is not used to limit
The fixed present invention.
Application principle of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, a kind of big transport intellectual monitoring early warning system of the dangerous material based on Internet of Things, including data acquisition are single
Member, mobile terminal, cloud server, Database Systems；The data acquisition unit is for monitoring hazardous materials transportation vehicle car
The status datas such as interior temperature and humidity, gas concentration, pressure, the mobile terminal are used for the state that will be received from data acquisition unit
Data upload to cloud server by wireless network, and interact with vehicle driver；The cloud service will be for that will connect
The historical data saved in the status data combined data library received carry out the regressing calculation based on TensorFlow platform and to
Abnormal judgement and early warning are reminded in real time out, and the Database Systems are for saving historical data.
The data acquisition unit be 3 development board of Raspberry Pi based on Android Things platform and its
Sensor mounted, sensor include temperature sensor, humidity sensor, gas concentration sensor, pressure transducer, affiliated
Status data is sent the mobile terminal based on android system by state acquisition unit timing.
The type of institute's hazmats and the corresponding relationship of monitoring index are as shown in table 1.
1 dangerous material monitoring index of table
After the mobile terminal receives the status data that the data acquisition unit is sent, first determine whether data surpass
Preset secure threshold out is sounded an alarm by way of interactive voice if being more than secure threshold and reminds vehicle driver, nothing
Whether by being more than secure threshold, status data is all uploaded to the cloud server by the mobile terminal.
Wherein, common are noxious material, maximum permissible concentration is as shown in table 2 in air, common flammable and explosive substance it is quick-fried
The fried limit is as shown in table 3.
The common noxious material maximum permissible concentration of table 2
| Substance title | Maximum permissible concentration mg/m3 | Substance title | Maximum permissible concentration mg/m3 |
| Carbon monoxide | 30 | Formaldehyde | 3 |
| Ammonia | 30 | Benzene | 40 |
| Hydrogen sulfide | 10 | Toluene | 100 |
| Sulfur dioxide | 15 | Gasoline | 350 |
| Chlorine | 1 | Methanol | 50 |
The common combustible explosion limit of table 3
The cloud server is carried out for historical data in combined data library and current data based on TensorFlow's
Regressing calculation provides abnormal judgement and early warning in real time and reminds, and calculating process is as shown in Figure 2:
(1) the laggard line number Data preprocess of the status data is received；
(2) the current dangerous index of single collection point is calculated；
(3) predict that following several minutes of the danger refers to by Time Series Forecasting Methods in conjunction with historical data and current data
Number；
(4) producing cause and solution of hazard index are mapped.
Wherein, Time Series Forecasting Methods can use the existing method of weighted moving average, and this method is to observed value point
Different flexible strategy are not given, acquire moving average by different flexible strategy, and based on last moving average, determine prediction
The method of value.Since recent observed value has larger impact to predicted value, it can more reflect the trend of Recent Changes, so, it is right
Larger flexible strategy value is given in the observed value close to time span of forecast；And observed value farther away for the range prediction phase then accordingly give it is smaller
Flexible strategy value, each observed value is adjusted to predicted value role with different flexible strategy value, keeps predicted value more approximately anti-
Reflect following development trend.Specific formula is as follows:
YiIndicate the predicted value at i-th of time point, λiIndicate the weight at i-th of time point, n indicates to go through used by prediction
History time point number, Yn+1Indicate predicted value.
As shown in figure 3, a kind of big transport intellectual monitoring method for early warning of the dangerous material based on Internet of Things, using above system,
Its step are as follows:
(1) vehicle driver manually selects dangerous material type: flammable and combustible liquids, flammable explosive gas, noxious material liquid
Body or noxious material gas；
(2) data acquisition unit is placed in corresponding position inside and outside hazardous materials transportation vehicle car, and powered；
(3) data acquisition unit connects bluetooth communication, by the status data period inside and outside collected compartment
Property is sent to the mobile terminal；
(4) mobile terminal is held by driver, receives the status data of data acquisition unit acquisition, judges related
Whether status data is more than preset secure threshold.If exceeding preset secure threshold, execute step (5), otherwise
It executes step (6)；
(5) mobile terminal sounds an alarm prompt vehicle driver by interactive voice；
(6) monitoring data are uploaded to the cloud server by 3G/4G network by the mobile terminal；
(7) cloud server operates in TensorFlow platform, the historical data stored in combined data library and works as
Preceding data carry out regressing calculation, obtain real-time hazard index, and operation result is stored in database；If hazard index is more than preparatory
The threshold value of setting, then be transmitted back to mobile terminal for warning information, and mobile terminal sounds an alarm prompt vehicle in time by interactive voice
Driver.
Claims (7)
1. a kind of big transport intellectual monitoring early warning system of the dangerous material based on Internet of Things, it is characterised in that: system includes that data are adopted
Collect unit, mobile terminal, cloud server, Database Systems；The data acquisition unit is for acquiring hazardous materials transportation vehicle
Temperature and humidity inside and outside compartment, gas concentration, pressure status data；The mobile terminal from data acquisition unit for that will receive
Status data cloud server is uploaded to by wireless network, and interacted with vehicle driver；The cloud service is used
The historical data saved in the status data combined data library that will be received carries out the fortune of the recurrence based on TensorFlow platform
It calculates and provides real-time status prediction.
2. the big transport intellectual monitoring early warning system of a kind of dangerous material based on Internet of Things according to claim 1, special
Sign is: the data acquisition unit is 3 development board of Raspberry Pi based on Android Things platform and its is taken
The sensor of load, the sensor include temperature sensor, humidity sensor, gas concentration sensor, pressure transducer；It is described
Data acquisition unit periodically sends the mobile terminal based on android system for status data.
3. the big transport intellectual monitoring early warning system of a kind of dangerous material based on Internet of Things according to claim 2, feature
Be: the status data include the temperature and humidity inside and outside the tank of hazardous materials transportation vehicle, the oxygen concentration in tank, inside and outside tank and
The gas concentration of safety valve, the pressure of top tank structure, the air concentration inside and outside tank, safety valve liquid detecting.
4. the big transport intellectual monitoring early warning system of a kind of dangerous material based on Internet of Things according to claim 1, feature
Be: the mobile terminal receives the status data that the data acquisition unit is sent, by status data and preset safety threshold
Value is compared, and is sounded an alarm by way of interactive voice if being more than secure threshold and is reminded vehicle driver, regardless of whether
More than secure threshold, status data is all uploaded to the cloud server by the mobile terminal.
5. the big transport intellectual monitoring early warning system of a kind of dangerous material based on Internet of Things according to claim 1, feature
Be: the cloud server carries out the step of regressing calculation based on TensorFlow platform are as follows:
(a) the laggard line number Data preprocess of status data is received；
(b) the current dangerous index of single collection point is calculated；
(c) predict that following several minutes of the danger refers to by a kind of Time Series Forecasting Methods in conjunction with historical data and current data
Number；
(d) producing cause and solution of hazard index are mapped.
6. the big transport intellectual monitoring early warning system of a kind of dangerous material based on Internet of Things according to claim 1, feature
It is: is taken between the data acquisition unit and the mobile terminal using Bluetooth communication, the mobile terminal and the cloud
It is engaged in passing through 3G/4G wireless communication between device.
7. a kind of big transport intellectual monitoring method for early warning of the dangerous material based on Internet of Things, it is characterised in that utilize claim 1 institute
The big transport intellectual monitoring early warning system of the dangerous material based on Internet of Things stated, its step are as follows:
(1) vehicle driver manually selects dangerous material type: flammable and combustible liquids, flammable explosive gas, noxious material liquid or
Noxious material gas；
(2) data acquisition unit is placed in corresponding position inside and outside hazardous materials transportation vehicle car, and powered；
(3) data acquisition unit connects bluetooth communication, and the status data periodicity sending inside and outside collected compartment is arrived
Mobile terminal；
(4) mobile terminal is held by driver, receives the status data of data acquisition unit acquisition, judges related status data
It whether is more than preset secure threshold；If exceeding preset secure threshold, execute step (5), it is no to then follow the steps
(6)；
(5) mobile terminal sounds an alarm prompt vehicle driver by interactive voice；
(6) monitoring data are uploaded to cloud server by 3G/4G network by mobile terminal；
(7) cloud server operates in TensorFlow platform, the historical data and current data stored in combined data library into
Row regressing calculation obtains real-time hazard index, and operation result is stored in database；If hazard index is more than preset threshold
Value, then be transmitted back to mobile terminal for warning information, and mobile terminal sounds an alarm prompt vehicle driver in time by interactive voice.
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