16142 results about "Animal science" patented technology

The invention discloses piggy creep feed containing composite flavone. The piggy creep feed is prepared from the following raw materials in parts by weight: 13 to 20 parts of expanded corn, 10 to 25 parts of corn, 6 to 13 parts of broken rice, 8 to 12 parts of flour, 8 to 15 parts of whey mist, 3 to 8 parts of soy protein concentrate, 5 to 10 parts of extruded soybean, 0.7 to 3 parts of soya-bean oil, 7 to 12 parts of 46.5-percent bean pulp, 2 to 5 parts of fish meal, 2 to 5 parts of plasma protein powder, 0.3 to 0.7 part of mountain flour, 0.5 to 1.0 part of calcium hydrophosphate, 0.05 to 0.5 part of lysine, 0.05 to 0.3 part of threonine, 0.1 to 0.3 part of sodium chloride, 0.1 to 0.8 part of compound flavone premix compounds, 0.15 to 0.3 part of zinc oxide, 0.03 to 0.06 part of calcium propionate, 0.02 to 0.04 part of ethoxyquin and 1.0 part of suckling pig premix compounds. The invention also discloses a preparation method. The intestinal tract health and the production performance of weaned pigs can be improved.

The present application relates to animal bifidobacterium lactis Ca360 and its application. The present application also provides the application of animal bifidobacterium lactis in promoting the absorption and transport of minerals, improving osteoporosis, iron deficiency anemia and zinc deficiency. The animal bifidobacterium lactis of the present application can promote the absorption and transport of minerals, improve osteoporosis, iron deficiency anemia and zinc deficiency.

The invention belongs to the technical field of computer vision and deep learning, and relates to a cultured fish intelligent feeding system based on multi-feature fusion and a control method thereof, and the system comprises an image acquisition module, a space-motion feature extraction module, a motion track feature extraction module, a feeding state recognition module, a feeding control module and a feedback adjustment module. Extracting a depth optical flow image reflecting fish school feeding state characteristics through a fish school real-time video stream; classifying the fish school feeding state image samples to form a space-motion optical flow feature map data set; meanwhile, fish swimming trails are extracted, and a swimming trail feature map data set is formed; and training is carried out to obtain an optimal model weight, real-time identification is realized, an identification result is transmitted to the feeding control module, the feeding state of a fish school after feeding is completed is evaluated, the feeding amount is adjusted, or a feeding decision is optimized. According to the invention, real-time, accurate and efficient identification and decision control of the feeding state of the fish school can be realized, and intelligent feeding is realized on a low-cost edge end computing platform.

The invention relates to the technical field of production monitoring control, and discloses a method and a system for monitoring production of eggs capable of reducing blood sugar based on fermented feed. The method comprises the following steps: detecting the hypoglycemic active components of the fermented feed through a multispectral sensor array to obtain spectral characteristic data; establishing a laying hen blood glucose metabolism correlation model by using a partial least squares regression algorithm; dynamically predicting the egg hypoglycemic index based on the incidence matrix and performing function grading; regulating and controlling formula parameters of the fermented feed in real time by adopting a particle swarm optimization algorithm; and carrying out production process quality tracing monitoring and abnormity early warning according to the optimized formula instruction. According to the method, the monitoring precision, the prediction accuracy and the quality stability of the production of the blood-sugar-reducing eggs are improved.

The invention relates to a product of an SNP (Single Nucleotide Polymorphism) molecular marker related to sow litter size character detection and application of the product. The SNP molecular marker comprises Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt The nucleotide sequence of the gene is shown as SEQ ID No.1, and the nucleotide sequence of the gene is shown as SEQ ID No.1. The product at least comprises an upstream primer and a downstream primer, the nucleotide sequence of the upstream primer is as shown in SEQ ID No.2, and the nucleotide sequence of the downstream primer is as shown in SEQ ID No.3. The SNP molecular marker provided by the invention can be used for breeding, breeding and evaluating multi-variety sows with high reproductive performance.

The invention provides a laying hen feeding scheme adjustment method and system based on moulting image recognition, and relates to the technical field of intelligent breeding, and the method comprises the steps: obtaining a multi-angle body surface image sequence synchronously collected by a plurality of laying hen individuals in a target chicken flock under a natural light condition; performing semantic segmentation according to the multi-angle body surface image sequence to obtain a feather contour segmentation map set; performing group feature joint extraction according to the feather contour segmentation map set to obtain a multi-dimensional feature tensor representing individual features and group distribution information at the same time; performing group state collaborative inference according to the multi-dimensional feature tensor to obtain a three-dimensional probability distribution vector; performing group nutrition demand mapping according to the three-dimensional probability distribution vector to obtain an optimal nutrition parameter combination suitable for the whole chicken flock; and generating a feeding scheme according to the optimal nutrition parameter combination to obtain a feeding instruction stream. The accuracy and adaptability of nutrition regulation and control in the moulting period are effectively improved.

The utility model discloses a differentiated zoned irrigation and fertilization system for seed corn, which relates to the technical field of agricultural drip irrigation and fertilization equipment and comprises a plurality of drip irrigation tape units, male parent irrigation branch pipes and female parent irrigation branch pipes. The drip irrigation tape unit comprises single male parent drip irrigation tapes, single female parent drip irrigation tapes and double female parent drip irrigation tapes, and the ratio of the number of the single male parent drip irrigation tapes to the number of the single female parent drip irrigation tapes to the number of the double female parent drip irrigation tapes is 1: 1: 3; the single male parent drip irrigation tape is connected with the male parent irrigation branch pipe, and the single female parent drip irrigation tape and the double female parent drip irrigation tape are connected with the female parent irrigation branch pipe; the male parent irrigation branch pipe and the female parent irrigation branch pipe are connected with an original farmland irrigation pipe network through a shunt valve, and a master control valve is arranged between the shunt valve and the original farmland irrigation pipe network; the water inlet ends of the male parent irrigation branch pipe and the female parent irrigation branch pipe are respectively provided with a control valve. The device can meet the water and fertilizer requirements of male parents and female parents respectively, the emergence rate and uniformity of the male parents and the female parents are improved, the seed yield and quality are improved, and the water and fertilizer utilization efficiency is improved.

The invention discloses a livestock and poultry health state intelligent evaluation method based on multi-sensor fusion and an AI prediction model, and belongs to the technical field of livestock breeding, and the method comprises the following steps: setting multiple types of sensors in a livestock and poultry breeding area, collecting multi-source data such as temperature, humidity, carbon dioxide concentration, ammonia gas concentration, illumination intensity, weight and current, and carrying out the analysis of the data; wherein the weight data is obtained through the weighing platform, and the current data is used for sensing the operation state of drinking, ingestion, ventilation or lighting equipment; various types of sensors such as temperature and humidity sensors, carbon dioxide sensors, ammonia gas sensors, illumination sensors, weight sensors and current sensors are deployed in livestock and poultry breeding areas, all-directional data acquisition of environments and behavior states is realized, and dynamic modeling and feature extraction of key behavior nodes are realized by introducing a deep neural network structure of a gating circulation unit and an attention mechanism.

The invention discloses an automatic cattle checking method and system based on two-dimensional panoramic vision, and belongs to the technical field of computer vision and intelligent breeding, and the method comprises the following steps: reasonably arranging a plurality of fixed cameras in a cattle farm area, obtaining the internal reference and distortion coefficient of each camera through employing a camera calibration technology, and obtaining the internal reference and distortion coefficient of each camera; performing real-time distortion correction on the collected video frames; on the basis of side-by-side splicing or homography matrix perspective transformation, all paths of corrected images are fused into a complete two-dimensional panoramic image, and a view blind area of a single camera is eliminated; calling a lightweight target detection model on the panorama, and extracting bounding boxes and confidence coefficients of all cattle at one time; sorting according to the confidence from high to low, performing IOU non-maximum suppression de-duplication on the detection frame, and ensuring that the same cattle only counts once in an overlapping region; and the whole process is completed through the edge computing node. According to the invention, efficient, real-time and accurate on-site cattle checking of a large-scale cattle farm can be realized.

The invention discloses a cattle feed additive. The cattle feed additive consists of the following raw materials in parts by weight: 4-16 parts of perilla frutescens, 2-20 parts of cyrtomium rhizomes, 10-30 parts of cod-liver oil, 2-10 parts of sodium selenite, 3-13 parts of Haixiao, 5-25 parts of radix polygalae, 2-12 parts of longan aril, 4-20 parts of Chinese yam rhizomes, 5-25 parts of vietnamese sophora roots, 3-17 parts of folium isatidis, 2-12 parts of endothelium corneum gigeriae galli, 4-16 parts of actinolitum brevifibrum, 2-12 parts of herba asari, 4-12 parts of origanum vulgare, 3-13 parts of Chinese pulsatilla roots, 4-16 parts of fleeceflower roots, 2-18 parts of radix achyranthis bidentatae, 1-9 parts of a bacillus natto agent, 2-10 parts of bacillus and 1-7 parts of active dry yeast. The cattle feed additive disclosed by the invention has the advantages of being rich in nutrition, capable of improving beef quality, increasing the survival rate of cattle and the like.

Disclosed is an Artificial Intelligence (AI)-based livestock management system and a livestock management method therefor. According to the inventive concept, it is possible to determine whether the animal has abnormal symptoms by learning the standard livestock stall management data and analyzing the body temperature information and behavior information of livestock from livestock image data obtained in real time from livestock such as cattle, thus giving the manager confidence.

The utility model discloses a kind of egg products marinating machine, it is related to marinated egg processing technical field, including rack, marinating jar is rotatably installed on the rack, the marinating jar is positive rotation when marinating processing and reverses when output;One end of the marinating jar is equipped with several circumferentially arranged egg outlet, the inner wall of the marinating jar is respectively equipped with egg outlet guide structure corresponding to each described egg outlet, the egg outlet guide structure is set to the reverse direction of the marinating jar in the direction of being away from the egg outlet direction, the egg outlet guide structure is equipped with the egg outlet of being opened towards the reverse direction of the marinating jar, the egg outlet guide structure when the marinating jar reverses guides the egg that is shovelled into to the corresponding egg outlet.The utility model marinating effect is good, output is not broken, beneficial to reduce loss and improve production efficiency.

The invention discloses a sheep coccidiosis parasitic ovum accurate detection method based on deep learning, and the method comprises the following steps: automatically collecting a sheep manure sample image, carrying out the noise removal and enhancement of the image, and guaranteeing the image quality; the preprocessed image is input into an automatic sheep coccidiosis parasitic ovum detection model for training, the training process comprises image segmentation, feature extraction and accurate recognition, and a deep learning model is used for automatically recognizing sheep coccidiosis parasitic ovum; performing infection density analysis according to the number of sheep coccidiosis parasitic ova output by the improved deep learning model, and evaluating the infection risk of the sheep flock; the detection result is visually displayed, detailed analysis reports including the number, type distribution and infection density data of sheep coccidiosis parasitic ova are generated, hours or even longer time needed by a traditional method is shortened, and high accuracy of the detection result is ensured.

The invention relates to a tobacco disease identification early warning method, device, equipment and medium, and relates to the technical field of disease identification, the method comprises the following steps: obtaining the planting time of tobacco in a target area, and determining the growth period of the tobacco in the target area based on the planting time; judging whether the current time period is in any time period type of the growth period of the tobacco or not; if yes, acquiring image information and environment information of the target area in the current time period based on a time period type and an acquisition mode corresponding to the current time period; determining at least one tobacco disease recognition model based on the current time period, and determining a disease recognition result of tobacco in the target area based on the image information, the environment information and each tobacco disease recognition model; and generating an early warning strategy of the current time period based on the disease identification result. The method has the technical effects that the planting time is reasonably determined, the types and grades of the tobacco diseases are accurately identified, and the tobacco diseases are early warned and prevented in time.

The invention discloses a caged laying duck head key feature detection method based on an improved yolov8 model in the technical field of computer vision, and the method comprises the steps: 1, collecting the image data of caged laying ducks in a poultry enterprise production base; step 2, performing data cleaning, image preprocessing and expert-assisted marking of target detection frames of different parts, including the head, the beak and the eyes, on the acquired image, and constructing a caged laying duck head key feature detection data set; and step 3, aiming at the image data of the caged laying ducks, firstly performing pixel removal on the caged laying duck main body shielding cage net, then complementing the removed pixels, and finally constructing a caged laying duck head key feature detection data set after data enhancement according to the mapping relation between the image and the label. The key feature parts of the head of the cage-rearing laying duck can be detected more quickly, and the detection accuracy is improved.

The invention provides a method for identifying abnormal behaviors and death states of chickens based on attitude angles, which comprises the following steps of: continuously acquiring three-axis attitude angle signals (namely a pitch angle Pitch, a yaw angle Yaw and a roll angle Roll) by using an inertial sensing device worn on the body surface of a chicken, constructing a low-frequency behavior track sequence, and identifying the abnormal behaviors and the death states of the chicken according to the low-frequency behavior track sequence; and through a set posture change threshold value, posture stability judgment, frequency distribution analysis and a posture imbalance recognition algorithm, whether the chicken is in the states of dysphoria, abnormally static, prostration, stiff head raising or death or not is judged. The method does not depend on acceleration or six-axis fusion signals, has the advantages of being low in power consumption, high in adaptability, easy and convenient to deploy and the like, and is suitable for continuous health monitoring and death early warning management of chicken individuals in a large-scale farm. The method has the characteristics of clear signal input boundary, accurate recognition mechanism, economical system deployment and the like, and the digital management efficiency and the animal welfare guarantee level of poultry breeding are remarkably improved.

The invention provides a multi-sensor cooperative stress-free three-dimensional body size measurement method and system for sheep, and belongs to the technical field of livestock breeding, and the method comprises the following steps: collecting the point cloud data of the sheep from multiple perspectives, and carrying out the preprocessing of the collected point cloud data; performing registration and three-dimensional reconstruction according to the preprocessed point cloud data to obtain a sheep three-dimensional point cloud model; performing point cloud repair and attitude correction on the three-dimensional point cloud model of the sheep to obtain a final three-dimensional point cloud model of the sheep; and inputting the three-dimensional point cloud model of the sheep into the trained deep learning model for semantic segmentation and key point detection, and measuring body size parameters of the sheep. According to the multi-sensor cooperative stress-free three-dimensional body size measurement method and system for the sheep, full-life-cycle automatic accurate measurement of body size parameters of the sheep is realized, so that manual intervention is reduced, the stress risk of the sheep is reduced, the measurement precision and efficiency are improved, and technical support is provided for intelligent breeding.

The embodiment of the invention discloses a feeding method and device capable of accurately regulating and controlling the feed intake of sows. The method comprises the following steps: identifying an individual identity through an electronic ear tag, and collecting backfat thickness, body condition score and weight data by using an inspection robot; dynamically calling a standard feeding curve based on the fetus number and the body condition score, and finely adjusting the target feed intake in combination with the body weight change trend; a quantitative or interactive feeding mode is adopted in the gestation period, feeding is carried out with different meals of wet mixed feed in the lactation period, and the feed-water ratio is dynamically adjusted; meanwhile, a data closed loop is constructed, a feeding strategy is optimized through big data analysis, and abnormal individuals are visualized. According to the scheme, precise self-adaptive regulation and control of the feeding behavior of the sow in the whole breeding cycle are achieved, and the feed efficiency and the breeding performance are remarkably improved.

The invention discloses an artificial breeding method of epinephelus fuscoguttatus and pink pterus coerulescens hybrid species, which comprises the following steps: screening healthy epinephelus fuscoguttatus as a female parent, screening healthy pink pterus coerulescens as a male parent, and carrying out enhanced breeding on the male parent and the female parent, the gonad maturation of the parent is promoted; the method comprises the following steps: collecting egg liquid of a female parent and semen of a male parent, inseminating to obtain a fertilized egg, incubating the fertilized egg to obtain a hybrid spot, performing authenticity identification on the hybrid spot by using one or more of sequences SEQ ID NO.1-SEQ ID NO.8, and determining that the hybrid spot inherits genetic information of the female parent and the male parent. The technical blank of crossbreeding of the pink pink bass as the parent grouper is filled, so that the hybrid obtained by hybridizing the epinephelus fuscoguttatus and the pink pink bass is reliable in authenticity, and inherits genetic information of male and female parents on the molecular level.

The utility model discloses an automatic egg picking robot which comprises a walking mechanism, a mechanical arm, an egg picking mechanism, an egg picking mechanism, an egg picking mechanism and an egg picking mechanism. The picking clamp comprises a cleaning part and an egg picking part; the image recognition mechanism comprises a processor and an image collector, and the image collector is connected with the processor; wherein the egg picking component and the sweeping component are arranged at the mounting end part of the mechanical arm, and the image collector is arranged on the mechanical arm; the processor is configured to control the sweeping component and the egg picking component to act according to image information collected by the image collector. Full automation of the process of picking up the duck eggs laid by the flat-fed breeding ducks is achieved, the labor intensity of workers is remarkably reduced, the working efficiency is improved, meanwhile, it is guaranteed that the egg laying environment is quiet and neat, and continuous production of the breeding ducks is facilitated.

A system toilet for a pet includes an excretion container, including a liquid-permeable bottom surface portion, that houses toilet litter, a tray, disposed below the excretion container, that houses an absorbent sheet that absorbs liquid having passed through the liquid-permeable bottom surface portion, a lower container that holds the tray, and an upper container disposed to cover an upper part of the excretion container and having an opening portion through which a pet enters and exits. The upper container includes a pair of side wall portions disposed to face each other on both sides in a width direction of the opening portion and extending in a front-rear direction, an upper wall portion disposed above the opening portion to bridge over the pair of side wall portions, a lower wall portion disposed below the opening portion, and a side wall guide portion.

The invention discloses a feed mixing preparation device based on a dairy cow feeding system, and relates to the technical field of mixing, and the feed mixing preparation device comprises a mixing device. According to the feed mixing preparation device based on the dairy cow feeding system, through the design of the mixing device, feed enters the mixing shell from a feeding pipe, a first motor controls a center rotating shaft to rotate, the center rotating shaft drives blades to rotate, one side of each blade is of a beveling structure, and the feed is crushed in the rotating process; and secondly, a second motor controls a scraping mechanism to rotate, so that the stirring effect of materials at the bottom of the equipment is improved, excessive precipitation of the materials at the bottom of the equipment is avoided, and the mixing efficiency and the mixing effect of the materials at the bottom of the equipment are improved. The feed mixing effect is prevented from being influenced, so that the feed mixing efficiency is improved, and the bottom feed is pushed to move towards the discharge valve through the rotating mechanism, so that feed retention is reduced, and the discharge speed is increased.

The invention discloses a grass carp marker release effect evaluation method, which specifically comprises the following steps: dividing released grass carps into large grass carps and small grass carps, implanting microsatellite markers into abdominal cavities of the large grass carps, and fixing external markers on dorsal fins of the small grass carps; the released grass carp is subjected to fin ray cutting sampling, and the age, the weight and the shape of the grass carp are recorded; constructing a sample genetic archive; recapturing the released groups; and identifying the recaptured individuals, and counting released individuals in the recaptured grass carp. The larger the recapture rate is, the better the enhancement and release effect is, so that the contribution of the enhancement and release of the grass carps to the ecological quantity of all the grass carps in the river is estimated, and the enhancement and release effect of the grass carps is determined. The method is beneficial to recovery of the number of the grass carps in the river, the releasing effect of the grass carps can be known, the releasing method is improved in time, and the method has great popularization value.

The invention relates to the technical field of genetic breeding, in particular to application of a molecular marker related to daily gain traits of sheep before weaning. The molecular marker is at least one of the following (1)-(2): (1) a nucleotide sequence as shown in SEQ ID NO.1, wherein the nucleotide sequence at the 101bp site is T or C; (2) a nucleotide sequence as shown in SEQ ID NO.3, wherein the nucleotide sequence at the 101bp site is T or C. The application refers to any one of the following (1) and (2): (1) identifying the daily gain of the sheep before weaning; and (2) the daily gain of the offspring of the sheep before weaning is improved. The screened molecular marker influencing the daily gain character of the sheep before weaning can be used for identifying the daily gain character of the sheep before weaning, and the daily gain of offspring before weaning can be improved by selecting a CC genotype individual as a male parent or a female parent.

The invention is suitable for the technical field of laying hen feed preparation, and particularly relates to a laying hen feed preparation method which comprises the following steps: acquiring nutritional ingredient data of various feed raw materials; dividing the nutritional ingredient data to obtain a first type of nutritional ingredient data of each raw material and a second type of nutritional ingredient data of each raw material; combining the first type of nutrition component data of each raw material according to the nutrition complementarity of each raw material to obtain combined nutrition data corresponding to the first type of nutrition component data; performing quantitative proportioning on the combined nutrition data to obtain a main ingredient group, and performing quantitative proportioning on the second type of nutrition component data of each raw material to obtain an auxiliary ingredient group; and preparing based on the main ingredient group and the auxiliary ingredient group to obtain the final formula. The preparation method of the laying hen feed provided by the invention can solve the technical problem that the calculated formula is optimal in theoretical cost, but the actual feeding effect is not optimal, so that the egg laying quality is low.

The utility model discloses a nursing system applied to young green-head diving ducks, which comprises a plurality of single-piece nets, connecting pieces, a first movable door and a soft cushion, the plurality of single-piece nets and the connecting pieces are assembled into a movable net cage, the plurality of single-piece nets and the connecting pieces are combined into a first stage net cage to form a first young duck activity space, and the first stage net cage is connected with the first stage net cage to form a second young duck activity space. The first movable door is arranged on the bottom side of the first-stage net cage, and a transverse bar is installed in the middle of the first-stage net cage. The multiple single-piece nets and the connecting pieces are combined into a second-stage net cage, a second chick activity space is formed, a second movable door is further formed in the bottom side of the second-stage net cage, the first movable door is communicated with the second movable door, and the second chick activity space is larger than the first chick activity space; by means of the structure, the problems that the teratogenesis rate, the death rate and the injury rate are high, weak young ducks cannot be effectively protected and recognized by groups, and the stress reaction is solved through the stepped swimming pool when existing green head diving duck feeding is carried out are solved.

The invention provides a yak healthy feeding optimization method and system based on machine learning. The yak healthy feeding optimization method comprises the steps of obtaining a basic data set; according to the basic data set, performing erucic acid metabolic pathway feature construction to obtain a feature set representing erucic acid mediated lipid metabolic pathway; according to the lipid metabolism path feature set, meat quality improvement effect quantification is carried out, and probability distribution of unsaturated fatty acid deposition efficiency is obtained; according to the probability distribution, feeding amount reverse deduction is carried out, and a high-erucic-acid rapeseed oil intake interval is obtained through calculation; health benefit balance is carried out according to a high-erucic acid rapeseed oil intake interval, and a stable feeding strategy is obtained; biological rationality verification is carried out according to a stable feeding strategy, the continuity of the mapping relation between the feeding amount and the meat quality index is analyzed based on the topological structure of the feature space, and a healthy yak feeding optimization scheme is obtained. The feeding precision, the meat quality improvement effect stability and the yak health guarantee level are improved.

The invention discloses a fish ingestion intensity intelligent evaluation and dynamic feeding system and method, and the method comprises the steps: obtaining a fish shoal ingestion image in real time through video monitoring, extracting a key frame through a Hash difference threshold algorithm, and carrying out the multi-dimensional data enhancement; a three-level fusion model fusing CNN local features, CoordAtt attention features and Transform global features is constructed, and lightweight and high-precision optimization of the model is realized in combination with a transfer learning strategy; according to the feeding intensity grade output by the model in real time, dynamic and accurate feeding control is carried out in combination with the fish biomass, feed waste is effectively reduced, the environmental adaptability of the system is improved, and precision and intelligentization of fish culture are achieved.

The invention discloses a sheep weight and size measuring system and method, and relates to the technical field of animal husbandry breeding intelligent management. Firstly, the invention discloses a sheep weight and body size measuring system, which comprises a PLC (Programmable Logic Controller), a computer, a channel module, a blocking module, an identity recognition module, an entrance module, an image acquisition module, a weighing module and a grouping module, wherein the PLC is in communication connection with the computer. Secondly, the invention discloses a method for measuring the weight and the body size of the sheep, and the method comprises the following steps: S1, driving the sheep into a guide channel at the entrance of the system, and arranging a queue; and S2, a worker starts a blocking module to communicate the recognition channel with the guide channel, and after the first sheep enters the recognition channel, the blocking module is started again to block the space between the recognition channel and the guide channel and block the next sheep. The device has the advantages of automation, high precision and non-contact, so that personal errors and sheep stress are reduced, and the working efficiency is improved.

A regional termite intelligent monitoring control killing method and system based on Internet of Things relates to the termite monitoring field, and the method comprises the following steps: determining a region with a concentration difference rate exceeding a first threshold value and a humidity change rate reaching a standard as a termite activity region, calculating a difference value ratio of adjacent sampling points according to concentration gradient data in continuous time periods, determining the moving direction and activity intensity of the termites; establishing a connection path for the activity points, calculating a path concentration progressive degree and a time sequence correlation value, determining the path with the highest progressive degree and the correlation value exceeding a second threshold value as a main activity path, calculating a concentration space distribution characteristic value and an activity intensity time accumulation value of each region, and determining the region with the maximum characteristic value and the highest accumulation value as a suspected nest group position; and generating a bait point layout instruction containing the coordinates. And receiving suspected position pheromone response data, if the concentration in the preset range reaches a second preset change condition, determining a nest group position, and generating a prevention and treatment instruction when the activity intensity reaches a period peak value. By implementing the method, the termite killing accuracy can be improved.