CN102111843A - Method for realizing energy conservation of wireless sensing node in greenhouse tomato irrigating system - Google Patents
Method for realizing energy conservation of wireless sensing node in greenhouse tomato irrigating system Download PDFInfo
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Abstract
The invention discloses a method for realizing energy conservation of a wireless sensing node in a greenhouse tomato irrigating system. A ZigBee tree routing mechanism is improved through analyzing the requirement of tomato irrigating environment information and a ZigBee tree routing algorithm; during the data forwarding process of a sensing node, a next-hop routing node is selected by an energy comprehensive evaluation function; during the irrigation decision-making process, a coordinator judges whether the irrigation is needed according to the illumination, air temperature, humidity, relative humidity of the soil, and the current crop growth cycle acquired by the sensing node; when the irrigation is not needed, the coordinator predicts when the irrigation is needed; and prior to this process, the sensing node is in a dormancy state. By the improved ZigBee tree routing and the coordinator irrigation decision-making data request mechanism of the invention, the transmission of a data packet in an overall wireless sensing network is greatly reduced, the energy utilization ratio of the node is effectively improved, and the stable period of the wireless sensing network is prolonged.
Description
Technical field
The present invention relates to ZigBee radio sensing network and intelligent irrigation field, relate in particular to a kind of in the greenhouse tomato irrigation system the energy-conservation implementation method of wireless sensing node.
Background technology
In the data acquisition platform of intelligent irrigation system, mainly be based on wired mode at present, be not easy to the layout and the expansion of system, ZigBee is widely used in data acquisition and monitoring field as a kind of emerging radio sensing network technology.But radio node generally is a powered battery, and life cycle is limited.The original tree Routing Protocol of ZigBee tree network is based on logic tree and transmits, and can cause the multi-hop of packet under a lot of situations, thereby cause the energy dissipation of whole sensing net.
At present, Chinese scholars also has corresponding research and improvement to ZigBee tree route, but what have is foundation with the packet minimum hop count just, what only consider is the energy consumption of whole network, the life cycle of failing to take into account individual node is (referring to Teahong Kim, Daeyoung Kim, Noseong Park, Seong-eun Yoo, and Tomas Sanchez Lopez, " Shortcut Tree Routing in ZigBee Networks, " Information and Communications University.).Also have and consider the strict balanced research that consumes of whole network energy, but can cause whole network to lose efficacy simultaneously having a large amount of nodes sometime like this, bring very big influence (gorgeous can for whole network referring to class, the bavin high forest, Wang Chen. based on the ZigBee network tree routing algorithm of balancing energy. computer application, 2008,28 (11): 2791-2794).
In addition, domestic automatic irrigation system data acquisition and control strategy majority is based on timing mechanism at present, the environmental information data send and lack foundation, cause the utilance of data not high, and the environmental information of gathering is more, wherein the coupling between data is relatively large, thereby causes the energy dissipation of data acquisition platform.
Summary of the invention
The objective of the invention is the some shortcomings of irrigating data acquisition platform at existing, provide a kind of in the greenhouse tomato irrigation system the energy-conservation implementation method of wireless sensing node.
The step of the energy-conservation implementation method of wireless sensing node is as follows in the greenhouse tomato irrigation system:
1) tomato is irrigated current air temperature/humidity T/RH, intensity of illumination lx, the relative moisture of the soil RH of sensing node collection in the radio sensing network
eEnvironmental information;
2) environmental information that collects of sensing node is before transmitting, the node of next jumping of evaluation function determination data by neighbors energy synthesis evaluation function or simplification;
3) environmental information that collects of sensing node calculated the fewest number of hops L of purpose sensing node earlier before transmitting
R, can be in transmitting the environmental information process data packet according to the jumping figure L that has transmitted
sWith fewest number of hops L to the purpose sensing node
RRelation change the adjustment factor α of node energy composite evaluation function, thereby avoid annular transmission to cause the energy dissipation of sensing node;
4) the wireless sense network telegon, is inferred tomato present located growth period, and is determined to irrigate the optimum soil moisture RH that determines by readjust-loss during this growth period through Fuzzy Processing by real-time clock
Eo, by with optimum soil moisture RH
EoRelatively judgement at current soil humidity RH
eSituation under whether need to water;
5) when not needing to water, call the irrigation prediction algorithm, infer the moment T that relevant sensing node need water
q, being carved into when having only this, the wireless sense network telegon is sent out data request command again to corresponding sensing node, and the corresponding environmental information of sensing node collection of waking resting state up is to the wireless sense network telegon, and whether make a decision once more needs to water.
The environmental information that described sensing node collects is before transmitting, and the node step of next jumping of evaluation function determination data by neighbors energy synthesis evaluation function or simplification comprises: sensing node energy synthesis evaluation function F (k
i) consider the energy consumption in the whole network and the energy state of node itself simultaneously, prolong the life cycle of whole network and individual node simultaneously, concrete formula is as follows:
Wherein, E
ΔFor setting the energy that transmission information is saved, E along improved route with along primitive logic
rBe the energy that this node factor consumes according to forwarding, E
%Be the percentage of this residue energy of node, α is for adjusting coefficient;
In concrete network environment, sensing node energy synthesis evaluation function abbreviation, concrete formula is as follows:
Wherein, L
TBe the strict jumping figure that when tree is transmitted, arrives destination node, L
RBe the shortest path of source node to destination node, d is the node network degree of depth of living in, C
SkipBe the ZigBee network address block.
The environmental information that described sensing node collects calculated the fewest number of hops L of purpose sensing node earlier before transmitting
R, can be in transmitting the environmental information process data packet according to the jumping figure L that has transmitted
sWith fewest number of hops L to the purpose sensing node
RRelation change the adjustment factor α of node energy composite evaluation function, thereby avoid annular transmission to cause the energy dissipation step of sensing node, comprise: sensing node energy synthesis evaluation function is formed the weight of item and can be adjusted along with the jumping figure that has transmitted, avoid the appearance of route ring, cause the energy consumption of whole network, the concrete computing formula of adjustment factor α of node energy composite evaluation function is as follows:
α=L
R/2L
s
L wherein
RBe the fewest number of hops of source node to destination node, L
sBe the jumping figure that packet has been transmitted, L
s≧ 1.
Described source node is to the shortest path L of destination node
RComputational methods are: the network degree of depth of calculating source node and destination node is poor earlier, if both are in three jumpings, promptly || and d
k-d
Des||＜3, then in the neighbor table of query source node whether destination node is arranged, it's not true, and whether the neighbors that searches each neighbors again has destination node, has, and next hop address is this neighbors, L
RBe 2, all it's not true, calculates with following formula:
L
R=?(d
des-?d
pub)?+?(d
k?-d
pub)
D wherein
DesBe the network degree of depth of destination node, d
kBe the network degree of depth of source node, d
PubCommon node for source node and destination node.
Described irrigation prediction algorithm calculation procedure comprises: irrigate policing algorithm and judge when relevant sensing node does not need to water, by the estimation of transpiration rate ET and soil permeability coefficient I, dope and irrigate T constantly
q, irrigating T constantly
qRelevant before sensing node is in resting state, wherein irrigates T constantly
qComputing formula is:
T
q=?(RH-RH
eo)/(ET+I)
The infiltration coefficient I of transpiration rate ET and soil draws by linear regression by recording envirment factor, and formula is:
ET=k
1×T+k
2×RH+k
3×lx+k
4
Wherein, T is the mean temperature in the unit interval, and RH is the air medial humidity, and lx is average intensity of illumination, k
1, k
2, k
3, k
4Be respectively the regression coefficient of respective items;
I=I
0×t
-m3，I
0=m
1×RH
e+m
2
Wherein, I
0Be initial soil permeability coefficient, t is an elapsed time, RH
eBe the relative humidity of soil, m
1, m
2, m
3Be respectively regression coefficient.
The present invention provides a kind of effective solution for transfer of data in the intelligent irrigation system, not only makes things convenient for the installation of irrigation system, modular sensing node also to be convenient to systemic-function based on the data acquisition of radio sensing network and expands; Tree route improvement in the data transmission procedure and telegon irrigation decision have significantly reduced packet in the whole wireless sense network to the request mechanism of environmental information data transmission, improve the capacity usage ratio of node effectively, prolonged the stable period of whole radio sensing network and the life cycle of single sensing node.Simulated effect is seen accompanying drawing Fig. 4,5.
Description of drawings
Fig. 1 is that the present invention irrigates the algorithm flow block diagram;
Fig. 2 is a remain_hops computing function flow chart of the present invention;
Fig. 3 is that ZigBee tree route of the present invention is improved algorithm flow;
Fig. 4 (a) is under the non-energy model, and when source node and destination node all were random node, the emulation that original tree routing algorithm and improved ZigBee tree routing algorithm sends total jumping figure that 100 packets walk at random relatively;
Fig. 4 (b) is under the non-energy model, and when source node and destination node all were random node, original tree routing algorithm and improved ZigBee tree routing algorithm sent 100 packets at random, and the emulation of the average number of hops that each packet is walked relatively;
Fig. 5 (a) is under the non-energy situation, and when source node was random node, when destination node was stationary nodes, the emulation that original tree routing algorithm and improved ZigBee tree routing algorithm sends total jumping figure that 100 packets walk at random relatively;
Fig. 5 (b) is under the non-energy situation, and when source node was random node, when destination node was stationary nodes, original tree routing algorithm and improved ZigBee tree routing algorithm sent 100 packets at random, and the emulation of the average number of hops that each packet is walked relatively.
Embodiment
The step of the energy-conservation implementation method of wireless sensing node is as follows in the greenhouse tomato irrigation system:
1) tomato is irrigated current air temperature/humidity T/RH, intensity of illumination lx, the relative moisture of the soil RH of sensing node collection in the radio sensing network
eEnvironmental information;
2) environmental information that collects of sensing node is before transmitting, the node of next jumping of evaluation function determination data by neighbors energy synthesis evaluation function or simplification;
3) environmental information that collects of sensing node calculated the fewest number of hops L of purpose sensing node earlier before transmitting
R, can be in transmitting the environmental information process data packet according to the jumping figure L that has transmitted
sWith fewest number of hops L to the purpose sensing node
RRelation change the adjustment factor α of node energy composite evaluation function, thereby avoid annular transmission to cause the energy dissipation of sensing node;
4) the wireless sense network telegon, is inferred tomato present located growth period, and is determined to irrigate the optimum soil moisture RH that determines by readjust-loss during this growth period through Fuzzy Processing by real-time clock
Eo, by with optimum soil moisture RH
EoRelatively judgement at current soil humidity RH
eSituation under whether need to water;
5) when not needing to water, call the irrigation prediction algorithm, infer the moment T that relevant sensing node need water
q, being carved into when having only this, the wireless sense network telegon is sent out data request command again to corresponding sensing node, and the corresponding environmental information of sensing node collection of waking resting state up is to the wireless sense network telegon, and whether make a decision once more needs to water.
The environmental information that described sensing node collects is before transmitting, and the node step of next jumping of evaluation function determination data by neighbors energy synthesis evaluation function or simplification comprises: sensing node energy synthesis evaluation function F (k
i) consider the energy consumption in the whole network and the energy state of node itself simultaneously, prolong the life cycle of whole network and individual node simultaneously, concrete formula is as follows:
Wherein, E
ΔFor setting the energy that transmission information is saved, E along improved route with along primitive logic
rBe the energy that this node factor consumes according to forwarding, E
%Be the percentage of this residue energy of node, α is for adjusting coefficient;
In concrete network environment, sensing node energy synthesis evaluation function abbreviation, concrete formula is as follows:
Wherein, L
TBe the strict jumping figure that when tree is transmitted, arrives destination node, L
RBe the shortest path of source node to destination node, d is the node network degree of depth of living in, C
SkipBe the ZigBee network address block.
The environmental information that described sensing node collects calculated the fewest number of hops L of purpose sensing node earlier before transmitting
R, can be in transmitting the environmental information process data packet according to the jumping figure L that has transmitted
sWith fewest number of hops L to the purpose sensing node
RRelation change the adjustment factor α of node energy composite evaluation function, thereby avoid annular transmission to cause the energy dissipation step of sensing node, comprise: sensing node energy synthesis evaluation function is formed the weight of item and can be adjusted along with the jumping figure that has transmitted, avoid the appearance of route ring, cause the energy consumption of whole network, the concrete computing formula of adjustment factor α of node energy composite evaluation function is as follows:
α=L
R/2L
s
L wherein
RBe the fewest number of hops of source node to destination node, L
sBe the jumping figure that packet has been transmitted, L
s≧ 1.
Described source node is to the shortest path L of destination node
RComputational methods are: the network degree of depth of calculating source node and destination node is poor earlier, if both are in three jumpings, promptly || and d
k-d
Des||＜3, then in the neighbor table of query source node whether destination node is arranged, it's not true, and whether the neighbors that searches each neighbors again has destination node, has, and next hop address is this neighbors, L
RBe 2, all it's not true, calculates with following formula:
L
R=?(d
des-?d
pub)?+?(d
k?-d
pub)
D wherein
DesBe the network degree of depth of destination node, d
kBe the network degree of depth of source node, d
PubCommon node for source node and destination node.
Described irrigation prediction algorithm calculation procedure comprises: irrigate policing algorithm and judge when relevant sensing node does not need to water, by the estimation of transpiration rate ET and soil permeability coefficient I, dope and irrigate T constantly
q, irrigating T constantly
qRelevant before sensing node is in resting state, wherein irrigates T constantly
qComputing formula is:
T
q=?(RH-RH
eo)/(ET+I)
The infiltration coefficient I of transpiration rate ET and soil draws by linear regression by recording envirment factor, and formula is:
ET=k
1×T+k
2×RH+k
3×lx+k
4
Wherein, T is the mean temperature in the unit interval, and RH is the air medial humidity, and lx is average intensity of illumination, k
1, k
2, k
3, k
4Be respectively the regression coefficient of respective items;
I=I
0×t
-m3，I
0=m
1×RH
e+m
2
Wherein, I
0Be initial soil permeability coefficient, t is an elapsed time, RH
eBe the relative humidity of soil, m
1, m
2, m
3Be respectively regression coefficient.
Embodiment
1) JN5139 wireless sense network chip, the TSL2550 numeric type optical sensor of TAOS company, the SHT11 numeric type aerial temperature and humidity transducer of Sensirion company and the FDS-100 soil humidity sensor of your company of Hangzhou remittance that uses Jennic company to produce formed the modularization sensing node.Sensing node collects air temperature/humidity T/RH, intensity of illumination lx, relative moisture of the soil RH in the greenhouse
eEnvironmental information;
2) environmental information that collects of sensing node was called improved ZigBee tree Routing Protocol before transmitting, and obtained each neighbors dump energy E from neighbor table
%, network depth d, ZigBee address block C
Skip(d) parameter;
3) improved ZigBee tree Routing Protocol calls subfunction remain_hops () and calculates current sensing node passes node to purpose shortest path L
R, idiographic flow such as accompanying drawing Fig. 2.Calculate and calculate current sensing node passes node to purpose shortest path L
RAfter, obtain the energy synthesis evaluation function f (k that each neighbors is simplified
i) value, the energy synthesis evaluation function f (k that select to simplify
i) being worth the node of maximum neighbors as next jumping, whole improved ZigBee sets flow process such as accompanying drawing Fig. 3 of Routing Protocol;
4) after environmental information passed to the wireless sense network telegon, the intelligent irrigation algorithm on the telegon, was inferred tomato present located growth period, and is determined to irrigate the optimum soil moisture RH that determines by readjust-loss during this growth period through Fuzzy Processing by real-time clock
Eo, by current soil humidity RH
eWith optimum soil moisture RH
EoComparison, whether judge needs to water under present case;
5) when not needing to water, air temperature/humidity T/RH, the intensity of illumination lx that is sent by sensing node obtains current transpiration rate ET by linear regression, and formula is as follows:
ET=k
1×T+k
2×RH+k
3×lx+k
4
Wherein, k
1, k
2, k
3, k
4Be respectively the regression coefficient of respective items;
6) the relative RH of current soil that sends by sensing node
eObtain the soil permeability coefficient I of initial condition by linear regression
0Formula is as follows: obtain current transpiration rate ET by linear regression, formula is as follows:
I
0=m
1×RH
e+m
2
Wherein, m
1, m
2Be respectively regression coefficient;
Obtained the infiltration coefficient I of soil again by nonlinear regression, formula is as follows:
I=I
0×t
-m3
Wherein, m
3Be regression coefficient;
7) irrigate prediction algorithm by current soil moisture RH
e, the current growth cycle optimum of current tomato soil moisture RH
EoAnd calculate by the infiltration coefficient I that the environmental information that sensing node sends returns the transpiration rate ET that obtains and soil and when to need to irrigate, concrete formula is as follows:
T
q=?(RH-RH
eo)/(ET+I)
8) telegon calculates the moment T that corresponding sensing node need be irrigated
qAfter, corresponding sensing node enters resting state, and Tq has arrived when the moment, and telegon hair ring environment information data request command wakes corresponding sensing node image data up to telegon to corresponding sensing node, and telegon begins to judge from step 2 again.Greenhouse tomato intelligent irrigation algorithm overall procedure such as accompanying drawing Fig. 1.
Claims (5)
1. energy-conservation implementation method of wireless sensing node in the greenhouse tomato irrigation system is characterized in that its step is as follows:
1) tomato is irrigated current air temperature/humidity T/RH, intensity of illumination lx, the relative moisture of the soil RH of sensing node collection in the radio sensing network
eEnvironmental information;
2) environmental information that collects of sensing node is before transmitting, the node of next jumping of evaluation function determination data by neighbors energy synthesis evaluation function or simplification;
3) environmental information that collects of sensing node calculated the fewest number of hops L of purpose sensing node earlier before transmitting
R, can be in transmitting the environmental information process data packet according to the jumping figure L that has transmitted
sWith fewest number of hops L to the purpose sensing node
RRelation change the adjustment factor α of node energy composite evaluation function, thereby avoid annular transmission to cause the energy dissipation of sensing node;
4) the wireless sense network telegon, is inferred tomato present located growth period, and is determined to irrigate the optimum soil moisture RH that determines by readjust-loss during this growth period through Fuzzy Processing by real-time clock
Eo, by with optimum soil moisture RH
EoComparison, judge at current soil humidity RH
eSituation under whether need to water;
5) when not needing to water, call the irrigation prediction algorithm, infer the moment T that relevant sensing node need water
q, have only this moment T
qArrived, the wireless sense network telegon is sent out data request command again to corresponding sensing node, and the corresponding environmental information of sensing node collection of waking resting state up is to the wireless sense network telegon, and whether telegon makes a decision once more needs to water.
2. according to claim 1 a kind of in the greenhouse tomato irrigation system the energy-conservation implementation method of wireless sensing node, it is characterized in that environmental information that described sensing node collects is before transmitting, the node step of next jumping of evaluation function determination data by neighbors energy synthesis evaluation function or simplification comprises: sensing node energy synthesis evaluation function F (k
i) consider the energy consumption in the whole network and the energy state of node itself simultaneously, prolong the life cycle of whole network and individual node simultaneously, concrete formula is as follows:
Wherein, E
ΔFor setting the energy that transmission information is saved, E along improved route with along primitive logic
rBe the energy that this node factor consumes according to forwarding, E
%Be the percentage of this residue energy of node, α is for adjusting coefficient;
In concrete network environment, sensing node energy synthesis evaluation function abbreviation is:
Wherein, L
TBe the strict jumping figure that when tree is transmitted, arrives the purpose sensing node, L
RBe the shortest path of current sensing node to the purpose sensing node, d is the current sensing node network degree of depth of living in, C
SkipBe the ZigBee network address block.
3. according to claim 1 a kind of in the greenhouse tomato irrigation system the energy-conservation implementation method of wireless sensing node, it is characterized in that environmental information that described sensing node collects before transmitting, calculates the fewest number of hops L of purpose sensing node earlier
R, can be in transmitting the environmental information process data packet according to the jumping figure L that has transmitted
sWith fewest number of hops L to the purpose sensing node
RRelation change the adjustment factor α of node energy composite evaluation function, thereby avoid annular transmission to cause the energy dissipation step of sensing node, comprise: sensing node energy synthesis evaluation function is formed the weight of item and can be adjusted along with the jumping figure that has transmitted, avoid the appearance of route ring, cause the energy consumption of whole network, the concrete computing formula of adjustment factor α of node energy composite evaluation function is as follows:
α=L
R/2L
s
L wherein
RBe the fewest number of hops of current sensing node to the purpose sensing node, L
sBe the jumping figure that packet has been transmitted, L
s≧ 1.
4. according to claim 2 a kind of in the greenhouse tomato irrigation system the energy-conservation implementation method of wireless sensing node, it is characterized in that described source node is to the shortest path L of destination node
RComputational methods are: the network degree of depth of calculating source node and destination node is poor earlier, if both are in three jumpings, promptly || and d
k-d
Des||＜3, then in the neighbor table of query source node whether the purpose sensing node is arranged, it's not true, and whether the neighbors that searches each neighbors again has destination node, has, and next hop address is this neighbors, L
RBe 2, all it's not true, calculates with following formula:
L
R=?(d
des-?d
pub)?+?(d
k?-d
pub)
D wherein
DesBe the network degree of depth of destination node, d
kBe the network degree of depth of source node, d
PubCommon node for source node and destination node.
5. according to claim 1 a kind of in the greenhouse tomato irrigation system the energy-conservation implementation method of wireless sensing node, it is characterized in that described irrigation prediction algorithm calculation procedure, comprise: irrigate policing algorithm and judge when relevant sensing node does not need to water, by the estimation of transpiration rate ET and soil permeability coefficient I, dope and irrigate T constantly
q, irrigating T constantly
qRelevant before sensing node is in resting state, wherein irrigates T constantly
qComputing formula is:
T
q=?(RH-RH
eo)/(ET+I)
The infiltration coefficient I of transpiration rate ET and soil draws by linear regression by recording envirment factor, and formula is as follows:
ET=k
1×T+k
2×RH+k
3×lx+k
4
Wherein, T is the mean temperature in the unit interval, and RH is the air medial humidity, and lx is average intensity of illumination, k
1, k
2, k
3, k
4Be respectively the regression coefficient of respective items;
I=I
0×t
-m3
I
0=m
1×RH
e+m
2
Wherein, I
0Be initial soil permeability coefficient, t is an elapsed time, RH
eBe the relative humidity of soil, m
1, m
2, m
3Be respectively regression coefficient.
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| CN104012376B (en) * | 2014-06-12 | 2017-06-20 | 张和暄 | Intelligent flower watering system, method and its device based on pressures on ecology and environment |
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| CN110100708A (en) * | 2019-06-14 | 2019-08-09 | 安徽大学 | Water-saving irrigation method and water-saving irrigation system based on fuzzy logic control theory |
| CN112213954A (en) * | 2020-10-27 | 2021-01-12 | 重庆工程职业技术学院 | Multi-mode control system and method for smart home |
| CN112213954B (en) * | 2020-10-27 | 2024-02-02 | 重庆工程职业技术学院 | Multi-mode control system and method for smart home |
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