CN203324781U - Pest trapping apparatus and pest remote identifying and monitoring system - Google Patents
Pest trapping apparatus and pest remote identifying and monitoring system Download PDFInfo
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- CN203324781U CN203324781U CN2013203347096U CN201320334709U CN203324781U CN 203324781 U CN203324781 U CN 203324781U CN 2013203347096 U CN2013203347096 U CN 2013203347096U CN 201320334709 U CN201320334709 U CN 201320334709U CN 203324781 U CN203324781 U CN 203324781U
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- 241000607479 Yersinia pestis Species 0.000 title claims abstract description 92
- 238000012544 monitoring process Methods 0.000 title abstract description 17
- 230000006698 induction Effects 0.000 claims abstract description 26
- 241000238631 Hexapoda Species 0.000 claims description 126
- 230000002459 sustained effect Effects 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 abstract description 2
- 241000894007 species Species 0.000 abstract 1
- 238000012549 training Methods 0.000 description 21
- 238000012360 testing method Methods 0.000 description 18
- 239000011159 matrix material Substances 0.000 description 9
- 238000006243 chemical reaction Methods 0.000 description 6
- 238000003860 storage Methods 0.000 description 5
- 210000002683 foot Anatomy 0.000 description 4
- 238000000034 method Methods 0.000 description 4
- 238000012935 Averaging Methods 0.000 description 2
- 239000005667 attractant Substances 0.000 description 2
- 230000031902 chemoattractant activity Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 239000003016 pheromone Substances 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000019771 cognition Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 239000000575 pesticide Substances 0.000 description 1
- 230000014860 sensory perception of taste Effects 0.000 description 1
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Abstract
The utility model discloses a pest trapping apparatus and a pest remote identifying and monitoring system. The pest trapping apparatus comprises a top cover, a funnel seat, a pest collecting device and a control unit, wherein a passageway which pests can pass through only in a one-by-one manner is arranged between the funnel seat and the pest collecting device, the side wall of the passageway is provided with a counting device and at least four infrared induction mini-sized cameras, and the at least four infrared induction mini-sized cameras are arranged at the same height of the passageway and are uniformly distributed along the circumferential direction of the passageway. The pest remote identifying and monitoring system comprises the pest trapping apparatus of the utility model and a remote data center. Compared with the technology of the prior art, the pest trapping apparatus is advantageous in that the at least four infrared induction mini-sized cameras mounted in passageway which pests can pass through only in a one-by-one manner are used for collecting image information of a single pest, the cameras are used for collecting image information of a pest population, the pests are counted, and therefore comprehensive analysis carried on the quantity and the species of the pests can be benefited, and the condition of pest damage can be effectively monitored.
Description
Technical field
The utility model relates to pest trap and identification monitoring field, is specifically related to a kind of pest trap device and insect remote identification supervisory system.
Background technology
China is a large agricultural country, and the statistical fluctuation work of the monitoring of agricultural pests, insect pest situation disaster is very important.If monitoring and prediction is accurately and timely, just early Control pests, reduce pesticide dosage, avoid crops to suffer heavy losses.By experienced peasant and classification of insect expert, insect is identified, but artificial cognition labour intensity is large, efficiency is low.
And, in recent ten years, agricultural pests occur seriously, insect density is large, it is many that kind occurs, and Chinese farmers plant protection lack of knowledge, experienced classification of insect expert and the plant protection personnel of basic unit are less, can not meet the demand that monitoring occurs current insect, thereby can't realize the forecast of agricultural pests Accurate Prediction, more can not reach the wireless remote of insect is monitored automatically.Therefore, develop some intelligent wireless insect remote automatic monitoring devices, will contribute to improve insect identification and accuracy rate and the efficiency counted, reduce the loss that insect pest brings, and then promote the enforcement of precision agriculture, improve the science popularization level of insect knowledge.
In prior art, be generally to realize identification and the remote monitoring to insect on the basis that insect is traped.At present, the kind of pest trap is a lot of both at home and abroad, and it catches principle is mainly to utilize the biological natures such as the photoaxis of insect, the sense of taste, adopts revulsive, light source, information source etc. to carry out trapping pests.
The Chinese patent literature that is CN2867873Y as notification number discloses a kind of pest trap, it is by upper cover, the funnel seat, lure core and pest catcher to form, the passage that the worm inlet bottom of this pest trap or inboard-be worm inlet leads to conical surface funnel or pest catcher is provided with by elasticity is anti-and escapes the release apparatus of putting that line forms, 1～6 block of gear worm plate is housed under described upper cover, when insect is lured wicking to draw to fly to trapper, at first bump against and fall downwards with gear worm plate, encounter thin and smooth, can not support the upper anti-of insect weight escapes to fall in the funnel seat after line, rely on the weight of itself to rush open the lower anti-line of escaping, fall into concentrator.Anti-ly in this pest trap utilization escape line and the lower anti-line of escaping stops insect to escape from trapper.
But this pest trap can only carry out the trapping of insect, can't, to the insect information be entrapped, cause being difficult to insect is identified and any type of monitoring.
The Chinese patent literature that notification number is CN202566059U discloses the system of a kind of real-time remote monitoring insect, comprising: trapper, storage storage, power system and analytic system; Trap interior is placed different pheromone attractant, the porch installation infrared line robot scaler of trapper, this Infrared Automatic Counting Equipment records quantity and the time that insect enters trapper automatically, and by the communication that gathers to storage storage (gsm module), gsm module can record the information of Infrared Automatic Counting Equipment collection and further be transferred to analytic system, and analytic system is analyzed the probability that insect may be broken out.
This trapper is merely able to gather the T/A information that insect enters trapper, is unfavorable for the kind of insect is identified and analyzed.
The utility model content
The utility model provides a kind of pest trap device, and this pest trap device can carry out the collection of quantity information and image information to the insect be entrapped, and is convenient to the value volume and range of product of insect is carried out to multianalysis.
A kind of pest trap device, comprise top cover, funnel seat, pest catcher and control module, between described funnel seat and pest catcher, being provided with only can be for the single passage only passed through one by one of insect, described channel side wall is provided with counting assembly and infrared induction minisize pick-up head, the quantity of described infrared induction minisize pick-up head is at least four, is located at the sustained height of passage and circumferentially is uniformly distributed along passage.
After the insect admission passage, be counted device counting once, and the infrared induction minisize pick-up head gathers image to the single insect that enters coverage, the image information of single insect is for being identified the kind of this insect.
For ease of insect is carried out to kind identification, described infrared induction minisize pick-up head is at least four, and all infrared induction minisize pick-up heads are located at the sustained height of passage and circumferentially are uniformly distributed along passage.Because the attitude of insect admission passage is unpredictable, a plurality of infrared induction minisize pick-up heads, when guaranteeing to photograph the insect full face, are convenient to capture the front and back photo of insect simultaneously, and its general image is gathered comprehensively.And the image information of the single insect of collection is sent to control module.
As preferably, the internal face of described passage is exasperate.Coarse inwall is conducive to slow down the creep speed of insect in passage, is convenient to infrared induction minisize pick-up head and counting assembly and is taken pictures and count.
For exempting from counting assembly to same insect repeat count, be provided with electrothermal ring in described passage, this electrothermal ring is positioned at the below of counting assembly.As preferably, the temperature of described electrothermal ring is 48～50 ℃.Electrothermal ring forms a high temperature ring in passage, and more than 48 ℃, is the fatal high temperature of general insect, and insect is avoided this humidity province by the light of nature, so can avoid same insect to come and go and creep in the induction zone of counting assembly, avoids repeat count.
Insect is just fallen in pest catcher after crossing this high-temperature region.Described pest catcher bottom is provided with the haftplatte of catching insect, and the haftplatte surface is equipped with pressure transducer, and the pest catcher top is provided with camera, and control module receives the signal of pressure transducer, and then controls camera work.Place pheromone attractant during use on haftplatte, whenever there being insect to arrive haftplatte, this pressure transducer just sends a signal to control module, and control module is controlled camera and taken pictures, image information to insect colony in pest catcher is gathered, and facilitates the user to check the insect pest situation.
Except the signal that is limited by pressure transducer, described camera also can independently arrange the time interval of taking pictures, and sends the image of collection to control module.
As preferably, described counting assembly is comprised of photoelectric sensor and counting circuit, described counting circuit connection control unit.Photoelectric sensor induction insect is also exported the low and high level signal, and described counting circuit receives this low and high level signal and is converted into pulse signal; Control module is converted to this pulse signal the quantity information of insect.
Control module is accepted and the insect information of storing can be sent in computing machine by interfaces such as USB, insect identification software in computing machine carries out kind identification according to the image information of single insect (image information of insect colony of take be with reference to) to insect, in conjunction with number of pest information, the insect pest situation is carried out to Real-Time Monitoring again.
The recognition methods of this insect classification software comprises the steps:
(1) sample training
1. the training sample of collecting insect is some, obtains image, and removes the background in image, only retains the insect image;
2. the insect image is carried out to gradation conversion, conversion formula is:
y=0.3r+0.59g+0.11b （1）；
Wherein, y means the gray-scale value after gray processing, and r means the value of red component in the insect image, and g means the value of insect image Green component, and b means the value of blue component in the insect image;
3. after gradation conversion, adopt the eigenwert of compressed sensing algorithm abstract image;
Take and be of a size of i*h as example (i is row, and h is row), the gray-scale value of each pixel of take builds gray matrix as element, folded with windrow, makes it become the vectorial p(p ∈ of a row R
1 * n, n=i * h);
P and random compressed sensing observing matrix multiply each other, and obtain the image feature value x(vector of training sample insect):
(2) pattern detection
The insect image information that computing machine and remote data center receive is test sample book; According in step (1) 2. method 3. obtain the image feature value of test sample book, recycle the kind that nearest neighbor algorithm is determined the test sample book insect;
Nearest neighbor algorithm comprises: calculate the distance between the image feature value of the image feature value of test sample book and training sample, computing formula is:
H
1The image feature value that means test sample book, h
2The image feature value that means training sample.
Find the instruction nearest with the image feature value of test sample book image feature value originally in the kind identification software, the insect type of this test sample book is identical with the insect type of this training sample;
If a class pest comprises a plurality of training samples, calculate the distance between the image feature value of the image feature value of test sample book and all training samples, and all distances are averaging, find the image feature value with the immediate training sample of mean distance, the insect type of this training sample is the insect type of test sample book again.
Described pest species identification software is applied to compressive sensing theory in obtaining of insect image feature value, adopts stochastic matrix to extract eigenwert, greatly reduces data dimension when having suppressed noise.
For realizing the remote monitoring to the insect pest situation, pest trap device of the present utility model comprises wireless transmitter module, and the information of control module count pick up device and the output of infrared induction minisize pick-up head, control wireless transmitter module and be transferred to remote data center.The information that in pest catcher, camera is exported also controlled unit receives and is transferred to remote data center by wireless transmitter module.
As preferably, described wireless transmitter module is the GPRS module.Dispose SIM card on this GPRS module, instruction note for receiving remote data center, and under the control of control module, the number of pest information of collection and image information are sent to remote data center with the form of note or multimedia message, by remote data center, carry out pest species identification and real-time remote monitoring.
For increasing the capture rate of insect, be provided with four foot supports between described top cover and funnel seat, the bottom surface of described top cover is equipped with trap lamp.Trap lamp is for attracting insect.
As preferably, the bottom of described pest catcher also is provided with at least three feets.Avoid described pest trap device make moist or corroded.
The utility model also provides a kind of insect remote identification supervisory system, comprises trap and remote data center, and described trap is pest trap device described in the utility model.Described remote data center is with the pest species identification software, and as preferably, described remote data center is mobile phone or PC.
Described insect remote identification supervisory system triggers with note, remote data center is to sending an instruction note " 111 " on the SIM card on the GPRS module, control module controls infrared induction minisize pick-up head, counting assembly, camera collection relevant information, control the GPRS module after collection completes pest-related information is sent to remote data center, the mailbox that the multimedia message receiving end of remote data center is mobile phone or PC with the form of multimedia message.
Compared with prior art, the beneficial effects of the utility model are embodied in:
Pest trap device utilization of the present utility model only is arranged on can gather at least four infrared induction minisize pick-up heads in the single passage only passed through one by one of insect the image information of single insect, utilize the image information of camera collection insect colony, also insect is counted, be conducive to the value volume and range of product of insect be carried out to multianalysis, effective monitoring insect pest situation.
The accompanying drawing explanation
The structural representation that Fig. 1 is a kind of pest trap device of the utility model;
The structural representation that Fig. 2 is passage place in Fig. 1;
The structured flowchart that Fig. 3 is a kind of insect remote identification of the utility model supervisory system;
The workflow diagram that Fig. 4 is a kind of insect remote identification of the utility model supervisory system.
Embodiment
As shown in Figure 1, a kind of pest trap device of the utility model, comprise top cover 1, funnel seat 2, pest catcher 3 and control module 6, be mounted with the power supply 11 of whole pest trap device in top cover 1, top cover 1 has four foot supports 14 to be connected with funnel seat 2, the bottom surface of top cover 1 is equipped with trap lamp 12, and between funnel seat 2 and pest catcher 3, being provided with only can be for the single passage 4 only passed through one by one of insect.The bottom of pest catcher 3 also is provided with three feets 31.Avoid pest trap device to make moist or corroded.
As seen from Figure 2, passage 4 sidewalls are provided with trough type photoelectric sensor 9 and infrared induction minisize pick-up head 8.In this embodiment, the quantity of infrared induction minisize pick-up head 8 is four, is located at the sustained height of passage 4 and circumferentially is uniformly distributed along passage 4.
The internal face of passage 4 is exasperate.So can slow down the creep speed of insect in passage 4, be convenient to the image information that infrared induction minisize pick-up head 8 is captured single insect.
After infrared induction minisize pick-up head 8 is captured the image information of single insect, insect continues to climb downwards, trough type photoelectric sensor 9 induction insects are also exported the low and high level signal, this low and high level signal is received and is converted to pulse signal by the single-chip microcomputer counting circuit 7 be connected with trough type photoelectric sensor 9, and control module 6 receives this pulse signal and is converted into the quantity information of insect.Single-chip microcomputer counting circuit 7 is placed in the square box 21 of funnel seat 2 sidewalls.
For exempting from 9 pairs of same insect repeat counts of trough type photoelectric sensor, be provided with electrothermal ring 13 in passage 4, this electrothermal ring 13 is positioned at the below of trough type photoelectric sensor 9.The temperature of electrothermal ring 13 is 48～50 ℃.Electrothermal ring 13 is at high temperature ring of the interior formation of passage 4, and more than 48 ℃, is the fatal high temperature of general insect, and insect is avoided this humidity province by the light of nature, so can avoid same insect to come and go and creep in the induction zone of trough type photoelectric sensor 9, avoids repeat count.
Insect is just fallen in pest catcher 3 after crossing this high-temperature region.Pest catcher 3 bottoms are provided with the haftplatte (omitting in figure) of catching insect, and the haftplatte surface is equipped with pressure transducer (omitting in figure), and pest catcher 3 tops are provided with camera 10, and control module 6 receives the signal of pressure transducer, and then control camera 10 work.
The recognition methods of this insect classification software comprises the steps:
(1) sample training
1. the training sample of collecting insect is some, obtains image, and removes the background in image, only retains the insect image;
2. the insect image is carried out to gradation conversion, conversion formula is:
y=0.3r+0.59g+0.11b （1）；
Wherein, y means the gray-scale value after gray processing, and r means the value of red component in the insect image, and g means the value of insect image Green component, and b means the value of blue component in the insect image;
3. after gradation conversion, adopt the eigenwert of compressed sensing algorithm abstract image;
Take and be of a size of i*h as example (i is row, and h is row), the gray-scale value of each pixel of take builds gray matrix as element, folded with windrow, makes it become the vectorial p(p ∈ of a row R
1 * n, n=i * h);
P and random compressed sensing observing matrix
Multiply each other, obtain the image feature value x(vector of training sample insect):
(2) pattern detection
The insect image information that computing machine and remote data center receive is test sample book; According in step (1) 2. method 3. obtain the image feature value of test sample book, recycle the kind that nearest neighbor algorithm is determined the test sample book insect;
Nearest neighbor algorithm comprises: calculate the distance between the image feature value of the image feature value of test sample book and training sample, computing formula is:
H
1The image feature value that means test sample book, h
2The image feature value that means training sample.
Find the image feature value of the training sample nearest with the image feature value of test sample book in the kind identification software, the insect type of this test sample book is identical with the insect type of this training sample;
If a class pest comprises a plurality of training samples, calculate the distance between the image feature value of the image feature value of test sample book and all training samples, and all distances are averaging, find the image feature value with the immediate training sample of mean distance, the insect type of this training sample is the insect type of test sample book again.
For realizing the remote monitoring to the insect pest situation, pest trap device of the present utility model comprises GPRS module 5, control module receives the information of single-chip microcomputer counting circuit 7, infrared induction minisize pick-up head 8 and camera 10 outputs, controls GPRS module 5 and is transferred to remote data center.
In this embodiment, GPRS module 5 also is placed in the square box 21 of funnel seat 2 sidewalls.Dispose SIM card on this GPRS module 5, instruction note for receiving remote data center, and under the control of control module 6, the number of pest information of collection and image information are sent to remote data center with the form of note or multimedia message, by remote data center, carry out pest species identification and real-time remote monitoring.
As shown in Figure 3, pest trap device of the present utility model and remote data center can form an insect remote identification supervisory system.As seen from Figure 4, the workflow of this insect remote identification supervisory system is:
Power-on 11, all hardware module starts, and at first control module 6 carries out initialization to hardware module, and then GPRS module 5 is started shooting and is inquired about the instruction note " 111 " that remote data center sends over; If inquire, this instruction note is sent to control module 6 by serial ports I, then control module 6 is controlled photoelectric sensor 9 and single-chip microcomputer counting circuit 7, infrared induction minisize pick-up head 8 and common camera 10 collection relevant informations by serial ports II and USB interface respectively; After collection completes, control module 6 sends the relevant AT instruction of multimedia message by serial ports I to GPRS module 5 again, the quantity information of insect and image information are sent to mobile phone, PC with the form of multimedia message (MMS information) by GPRS network and Internet network respectively, and the multimedia message receiving end is mobile phone and mailbox; Mobile phone is checked on-the-spot insect pest situation, and PC is identified pest species, and by all data recording storages.If GPRS module 5 does not inquire instruction note " 111 ", continue inquiry.
Claims (8)
1. a pest trap device, comprise top cover, funnel seat, pest catcher and control module, between described funnel seat and pest catcher, being provided with only can be for the single passage only passed through one by one of insect, it is characterized in that, described channel side wall is provided with counting assembly and infrared induction minisize pick-up head, the quantity of described infrared induction minisize pick-up head is at least four, is located at the sustained height of passage and circumferentially is uniformly distributed along passage.
2. pest trap device as claimed in claim 1, is characterized in that, the internal face of described passage is exasperate.
3. pest trap device as claimed in claim 1, is characterized in that, in described passage, is provided with electrothermal ring, and this electrothermal ring is positioned at the below of counting assembly.
4. pest trap device as claimed in claim 1, is characterized in that, described pest catcher bottom is provided with the haftplatte of catching insect, the haftplatte surface is equipped with pressure transducer, the pest catcher top is provided with camera, and control module receives the signal of pressure transducer, and then controls camera work.
5. pest trap device as claimed in claim 1, is characterized in that, described counting assembly is comprised of photoelectric sensor and counting circuit, described counting circuit connection control unit.
6. pest trap device as claimed in claim 1, is characterized in that, comprises wireless transmitter module, and the information of control module count pick up device and the output of infrared induction minisize pick-up head, control wireless transmitter module and be transferred to remote data center.
7. pest trap device as claimed in claim 1, is characterized in that, between described top cover and funnel seat, is provided with four foot supports, and the bottom surface of described top cover is equipped with trap lamp.
8. an insect remote identification supervisory system, comprise trap and remote data center, it is characterized in that, described trap is the arbitrary described pest trap device of claim 1～7.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104410812A (en) * | 2014-10-10 | 2015-03-11 | 江苏省农业科学院 | A greenhouse pest warning method based on Web Service |
| CN106527217A (en) * | 2015-09-15 | 2017-03-22 | 宁波高新区鹏博科技有限公司 | System for automatically acquiring insect pest situation monitoring information of crops |
| WO2017213531A1 (en) * | 2016-06-07 | 2017-12-14 | Pinheiro Pinto Sobreiro Luís Filipe | Machine for capturing, counting and monitoring insects |
| CN108935339A (en) * | 2018-07-23 | 2018-12-07 | 陕西省西安植物园 | Pest trapping classification observation device |
| CN109845547A (en) * | 2018-12-12 | 2019-06-07 | 安徽玉野建设工程有限公司 | A kind of garden pest insects monitoring method and large-scale vertical garden pest insects monitoring device |
| CN109984105A (en) * | 2018-12-29 | 2019-07-09 | 南京林业大学工程规划设计院有限公司 | A kind of intelligent monitoring system of Landscape Construction |
| WO2020028960A1 (en) * | 2018-08-06 | 2020-02-13 | Cosme Carvalho Ervilha Joelcio | Method for detection and remote, automatic and continuous counting of insect pests, with transmission of information by means of communication systems in unenclosed and enclosed areas |
| WO2020028962A1 (en) * | 2018-08-06 | 2020-02-13 | Cosme Carvalho Ervilha Joelcio | Device for automatic and continuous remote counting and detection of target pests and perimeter lepidoptera controller |
| CN112931445A (en) * | 2021-01-28 | 2021-06-11 | 华南农业大学 | Detection device, system and method for sensing quantity and area of tea garden pests based on laser |
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- 2013-06-09 CN CN2013203347096U patent/CN203324781U/en not_active Expired - Lifetime
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104410812A (en) * | 2014-10-10 | 2015-03-11 | 江苏省农业科学院 | A greenhouse pest warning method based on Web Service |
| CN106527217B (en) * | 2015-09-15 | 2019-10-11 | 宁波高新区鹏博科技有限公司 | A kind of crops Insect infestation monitoring information automatic acquisition system |
| CN106527217A (en) * | 2015-09-15 | 2017-03-22 | 宁波高新区鹏博科技有限公司 | System for automatically acquiring insect pest situation monitoring information of crops |
| WO2017213531A1 (en) * | 2016-06-07 | 2017-12-14 | Pinheiro Pinto Sobreiro Luís Filipe | Machine for capturing, counting and monitoring insects |
| US11039607B2 (en) | 2016-06-07 | 2021-06-22 | Luís Filipe PINHEIRO PINTO SOBREIRO | Machine for capturing, counting and monitoring insects |
| CN108935339A (en) * | 2018-07-23 | 2018-12-07 | 陕西省西安植物园 | Pest trapping classification observation device |
| CN108935339B (en) * | 2018-07-23 | 2020-06-30 | 陕西省西安植物园 | Insect catching and classifying observation device |
| WO2020028960A1 (en) * | 2018-08-06 | 2020-02-13 | Cosme Carvalho Ervilha Joelcio | Method for detection and remote, automatic and continuous counting of insect pests, with transmission of information by means of communication systems in unenclosed and enclosed areas |
| WO2020028962A1 (en) * | 2018-08-06 | 2020-02-13 | Cosme Carvalho Ervilha Joelcio | Device for automatic and continuous remote counting and detection of target pests and perimeter lepidoptera controller |
| CN109845547A (en) * | 2018-12-12 | 2019-06-07 | 安徽玉野建设工程有限公司 | A kind of garden pest insects monitoring method and large-scale vertical garden pest insects monitoring device |
| CN109984105A (en) * | 2018-12-29 | 2019-07-09 | 南京林业大学工程规划设计院有限公司 | A kind of intelligent monitoring system of Landscape Construction |
| CN112931445A (en) * | 2021-01-28 | 2021-06-11 | 华南农业大学 | Detection device, system and method for sensing quantity and area of tea garden pests based on laser |
| CN112931445B (en) * | 2021-01-28 | 2023-01-10 | 华南农业大学 | Detection device, system and method for sensing quantity and area of tea garden pests based on laser |
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