CN109348189A - A kind of long-range geological disaster monitoring system based on Internet of Things - Google Patents

A kind of long-range geological disaster monitoring system based on Internet of Things Download PDF

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Publication number
CN109348189A
CN109348189A CN201811475359.9A CN201811475359A CN109348189A CN 109348189 A CN109348189 A CN 109348189A CN 201811475359 A CN201811475359 A CN 201811475359A CN 109348189 A CN109348189 A CN 109348189A
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Prior art keywords
monitoring
early warning
region
sensor node
node
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肖鑫茹
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肖鑫茹
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00Television systems
    • H04N7/18Closed circuit television systems, i.e. systems in which the signal is not broadcast
    • GPHYSICS
    • G08SIGNALLING
    • G08BSIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00Alarms responsive to a single specified undesired or abnormal operating condition and not elsewhere provided for
    • G08B21/02Alarms for ensuring the safety of persons
    • G08B21/10Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications
    • H04L67/02Network-specific arrangements or communication protocols supporting networked applications involving the use of web-based technology, e.g. hyper text transfer protocol [HTTP]
    • H04L67/025Network-specific arrangements or communication protocols supporting networked applications involving the use of web-based technology, e.g. hyper text transfer protocol [HTTP] for remote control or remote monitoring of the application
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W84/00Network topologies
    • H04W84/18Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

The present invention provides a kind of long-range geological disaster monitoring system based on Internet of Things, including the first monitoring subsystem, second monitoring subsystem and remote monitoring center, first monitoring subsystem is monitored early warning to monitoring region using wireless sensor network, and monitoring and warning information is sent to remote monitoring center, second monitoring subsystem is used to acquire the video image in monitoring region, and video image information is sent to remote monitoring center, monitoring and warning information and video image information remotely monitor address disaster to the remote monitoring center based on the received.The invention has the benefit that providing a kind of long-range geological disaster monitoring system based on Internet of Things, it is based on wireless sensor network and video image, guarantees the long-range monitoring for realizing geological disaster under personnel safety.

Description

A kind of long-range geological disaster monitoring system based on Internet of Things
Technical field
The present invention relates to geological technique fields, and in particular to a kind of long-range geological disaster monitoring system based on Internet of Things.
Background technique
Catastrophic failure due to nature and artificial geological process to geological environment, in recent years, in world wide, especially China, geological disaster show frequently-occurring situation, mainly include avalanche, landslide, mud-rock flow, surface collapse and ground fissure etc..It is right The security of the lives and property of people causes great threat.
Summary of the invention
In view of the above-mentioned problems, the present invention is intended to provide a kind of long-range geological disaster monitoring system based on Internet of Things.
The purpose of the present invention is realized using following technical scheme:
Provide a kind of long-range geological disaster monitoring system based on Internet of Things, including the first monitoring subsystem, the second prison Subsystem and remote monitoring center are surveyed, first monitoring subsystem is monitored monitoring region using wireless sensor network Early warning, and monitoring and warning information is sent to remote monitoring center, second monitoring subsystem is used to acquire monitoring region Video image, and video image information is sent to remote monitoring center, the remote monitoring center monitors in advance based on the received Alert information and video image information remotely monitor address disaster.
The invention has the benefit that providing a kind of long-range geological disaster monitoring system based on Internet of Things, it is based on nothing Line sensor network and video image guarantee the long-range monitoring that geological disaster is realized under personnel safety.
Detailed description of the invention
The present invention will be further described with reference to the accompanying drawings, but the embodiment in attached drawing is not constituted to any limit of the invention System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings Other attached drawings.
Fig. 1 is structural schematic diagram of the invention;
Appended drawing reference:
First monitoring subsystem 1, the second monitoring subsystem 2, remote monitoring center 3.
Specific embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of long-range geological disaster monitoring system based on Internet of Things of the present embodiment, including the first monitoring System 1, the second monitoring subsystem 2 and remote monitoring center 3, first monitoring subsystem 1 use wireless sensor network pair Monitoring region is monitored early warning, and monitoring and warning information is sent to remote monitoring center 3, second monitoring subsystem 2 Remote monitoring center 3 is sent to for acquiring the video image in monitoring region, and by video image information, in the long-range monitoring Monitoring and warning information and video image information remotely monitor address disaster to the heart 3 based on the received.
A kind of long-range geological disaster monitoring system based on Internet of Things is present embodiments provided, wireless sensor network is based on And video image, guarantee the long-range monitoring that geological disaster is realized under personnel safety.
Preferably, first monitoring subsystem 1 includes data collection system, monitoring and warning system and Alarm Assessment system System, the data collection system is used to acquire to be acquired using data of the sensor node to monitoring region, and the monitoring is pre- Alert system is used for being monitored according to the collected data to monitoring region and carrying out early warning according to monitoring result, and the early warning is commented Valence system is for evaluating early warning effect.
This preferred embodiment realizes the evaluation to the accurate measurements early warning in monitoring region and to early warning effect.
Preferably, the monitoring and warning system includes modeling module, node monitoring modular, area monitoring module, described to build Mould module is used to carry out real-time monitoring to key point for establishing radio sensor network monitoring model, the node monitoring modular And early warning, the area monitoring module are used to carry out real-time monitoring and early warning to monitoring region;
The modeling module is used to establish radio sensor network monitoring model, specifically:
It is the unique nodal scheme of sensor node of system distribution, nodal scheme is if monitoring region altogether by n sensor node { 1,2 ..., n }, gi(t) indicate sensor node i in the perception data of moment t, wherein i ∈ { 1,2 ..., n };
The node monitoring modular is used to carry out real-time monitoring and early warning to key point, specifically:
For a certain monitoring point, given monitoring threshold range Y=[Y1, Y2], Y1Indicate monitoring threshold lower limit, Y2It indicates The monitoring threshold upper limit;
The first early warning factor of sensor node is calculated using following formula:
In formula, J1iIndicate the first early warning factor of sensor node i, P [gi(t)-Y2] indicate sensor node i at the moment The perception data of t is greater than Y1Probability;
The second early warning factor of sensor node is calculated using following formula:
In formula, J2iIndicate the second early warning factor of sensor node i, P [gi(t)-Y2] indicate sensor node i at the moment The perception data of t is greater than Y2Probability;
For each monitoring point, key point threshold value of warning is set, when the first early warning factor of sensor node is less than key When second early warning factor of point threshold value of warning or sensor node is greater than key point threshold value of warning, sensor node sounds an alarm letter Breath;
The first early warning factor that this preferred embodiment passes through calculating sensor node With the second early warning factor of sensor nodeRealize the accurate of key point Monitoring and early warning;
Preferably, the area monitoring module is used to carry out real-time monitoring and early warning to monitoring region, specifically:
For n sensor node in monitoring region, given monitoring threshold range X=[X1, X2], X1Indicate monitoring Bottom threshold, X2Indicate the monitoring threshold upper limit;
Monitoring the first early warning factor of region is obtained using following formula:
In formula, A1Indicate monitoring the first early warning factor of region,Indicate monitoring region inner sensor node when The sum of the perception data of t is carved,It indicatesGreater than X1Probability;
Monitoring the second early warning factor of region is obtained using following formula:
In formula, A2Indicate monitoring the second early warning factor of region,It indicatesGreater than X2It is general Rate;
Setting regions threshold value of warning, when monitoring the first early warning factor of region is less than regional early warning threshold value or sensor node When second early warning factor is greater than regional early warning threshold value, send a warning;
This preferred embodiment monitors first early warning factor in region by calculating With second early warning factor in monitoring regionRealize the accurate measurements in region And early warning;When the threshold range that the data of sensor node acquisition give beyond user, sensor node is sent out to aggregation node Send warning information.It is influenced by perception hardware error and ambient noise, uncertain and error is universally present in sensor In the perception data of node acquisition.When noise disturbance or instrument error cause the substantial deviation of perception value, it is based on single threshold value Monitoring method will lead to higher alarm rate of false alarm and alarm rate of failing to report;The present invention and traditional single threshold monitoring method phase Than the monitoring result guaranteed with probability can reduce the influence of hardware error and disturbance to alarm accuracy rate, be more suitable for reality Monitoring application.
Preferably, the Alarm Assessment system includes the first evaluation module and the second evaluation module, the first evaluation mould For evaluating the early warning effect of node monitoring modular, second evaluation module is used for the pre- of area monitoring module block Alert effect is evaluated;
First evaluation module is used to evaluate the early warning effect of node monitoring modular, specifically:
Using the following formula calculate node Alarm Assessment factor:
In formula, RiIndicate the node Alarm Assessment factor of sensor node i, b1Indicate sensor node i false alarm rate, b2Table Show sensor node i false dismissed rate;The node Alarm Assessment factor is smaller, indicates that node monitoring modular early warning effect is better;
Second evaluation module is used to evaluate the early warning effect of area monitoring module, specifically:
Using the following formula zoning Alarm Assessment factor:
In formula, Q indicates regional early warning evaluation points, c1Indicate region false alarm rate, c2Indicate region false dismissed rate;The region The Alarm Assessment factor is smaller, indicates that area monitoring module early warning effect is better;
This preferred embodiment passes through the calculate node Alarm Assessment factorIt is commented with regional early warning The valence factorIt realizes to the accurate of the early warning effect of node monitoring modular and area monitoring module Evaluation.
Be monitored using the long-range geological disaster monitoring system the present invention is based on Internet of Things, choose 5 monitoring regions into Row experiment, respectively monitoring region 1, monitoring region 2, monitoring region 3, monitoring region 4, monitoring region 5, to monitoring cost and prison Control accuracy rate is counted, and compared with the existing technology, generation has the beneficial effect that shown in table:
Monitoring cost reduces Accuracy rate is monitored to improve
Monitor region 1 29% 27%
Monitor region 2 27% 26%
Monitor region 3 26% 26%
Monitor region 4 25% 24%
Monitor region 5 24% 22%
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected The limitation of range is protected, although explaining in detail referring to preferred embodiment to the present invention, those skilled in the art are answered Work as understanding, it can be with modification or equivalent replacement of the technical solution of the present invention are made, without departing from the reality of technical solution of the present invention Matter and range.

Claims (8)

1. a kind of long-range geological disaster monitoring system based on Internet of Things, which is characterized in that including the first monitoring subsystem, second Monitoring subsystem and remote monitoring center, first monitoring subsystem supervise monitoring region using wireless sensor network Early warning is surveyed, and monitoring and warning information is sent to remote monitoring center, second monitoring subsystem is for acquiring monitoring region Video image, and video image information is sent to remote monitoring center, the remote monitoring center monitors based on the received Warning information and video image information remotely monitor address disaster.
2. the long-range geological disaster monitoring system according to claim 1 based on Internet of Things, which is characterized in that described first Monitoring subsystem includes data collection system, monitoring and warning system and Alarm Assessment system, and the data collection system is for adopting Collection is acquired using data of the sensor node to monitoring region, and the monitoring and warning system is used for according to the collected data Monitoring region is monitored and early warning is carried out according to monitoring result, the Alarm Assessment system is for commenting early warning effect Valence.
3. the long-range geological disaster monitoring system according to claim 2 based on Internet of Things, which is characterized in that the monitoring Early warning system includes modeling module, node monitoring modular, area monitoring module, and the modeling module is for establishing wireless sensor Network Monitoring Model, the node monitoring modular are used to carry out real-time monitoring and early warning, the area monitoring module to key point For carrying out real-time monitoring and early warning to monitoring region.
4. the long-range geological disaster monitoring system according to claim 3 based on Internet of Things, which is characterized in that the modeling Module is used to establish radio sensor network monitoring model, specifically:
If monitoring region altogether by n sensor node, for the unique nodal scheme of sensor node of system distribution, nodal scheme for 1, 2 ..., n }, gi(t) indicate sensor node i in the perception data of moment t, wherein i ∈ { 1,2 ..., n }.
5. the long-range geological disaster monitoring system according to claim 4 based on Internet of Things, which is characterized in that the node Monitoring modular is used to carry out real-time monitoring and early warning to key point, specifically:
For a certain monitoring point, given monitoring threshold range Y=[Y1, Y2], Y1Indicate monitoring threshold lower limit, Y2Indicate monitoring threshold It is worth the upper limit;
The first early warning factor of sensor node is calculated using following formula:
In formula, J1iIndicate the first early warning factor of sensor node i, P [gi(t)-Y2] indicate sensor node i in the sense of moment t Primary data is greater than Y1Probability;
The second early warning factor of sensor node is calculated using following formula:
In formula, J2iIndicate the second early warning factor of sensor node i, P [gi(t)-Y2] indicate sensor node i in the sense of moment t Primary data is greater than Y2Probability;
For each monitoring point, key point threshold value of warning is set, when the first early warning factor of sensor node is pre- less than key point When second early warning factor of alert threshold value or sensor node is greater than key point threshold value of warning, sensor node sends a warning.
6. the long-range geological disaster monitoring system according to claim 5 based on Internet of Things, which is characterized in that the region Monitoring modular is used to carry out real-time monitoring and early warning to monitoring region, specifically:
For n sensor node in monitoring region, given monitoring threshold range X=[X1, X2], X1Indicate monitoring threshold Lower limit, X2Indicate the monitoring threshold upper limit;
Monitoring the first early warning factor of region is obtained using following formula:
In formula, A1Indicate monitoring the first early warning factor of region,Indicate monitoring region inner sensor node moment t's The sum of perception data,It indicatesGreater than X1Probability;
Monitoring the second early warning factor of region is obtained using following formula:
In formula, A2Indicate monitoring the second early warning factor of region,It indicatesGreater than X2Probability;
Setting regions threshold value of warning, when monitoring the first early warning factor of region is less than the second of regional early warning threshold value or sensor node When early warning factor is greater than regional early warning threshold value, send a warning.
7. the long-range geological disaster monitoring system according to claim 6 based on Internet of Things, which is characterized in that the early warning Evaluation system includes the first evaluation module and the second evaluation module, and first evaluation module is used for the pre- of node monitoring modular Alert effect is evaluated, and second evaluation module is for evaluating the early warning effect of area monitoring module.
8. the long-range geological disaster monitoring system according to claim 7 based on Internet of Things, which is characterized in that described first Evaluation module is used to evaluate the early warning effect of node monitoring modular, specifically:
Using the following formula calculate node Alarm Assessment factor:
In formula, RiIndicate the node Alarm Assessment factor of sensor node i, b1Indicate sensor node i false alarm rate, b2It indicates to pass Sensor node i false dismissed rate;The node Alarm Assessment factor is smaller, indicates that node monitoring modular early warning effect is better.
CN201811475359.9A 2018-12-04 2018-12-04 A kind of long-range geological disaster monitoring system based on Internet of Things Withdrawn CN109348189A (en)

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Application publication date: 20190215