CN111134033A - Intelligent animal feeder and method and system thereof - Google Patents

Intelligent animal feeder and method and system thereof Download PDF

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Publication number
CN111134033A
CN111134033A CN201911359046.1A CN201911359046A CN111134033A CN 111134033 A CN111134033 A CN 111134033A CN 201911359046 A CN201911359046 A CN 201911359046A CN 111134033 A CN111134033 A CN 111134033A
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animal
pet
intelligent
feeding
feeder
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林俊雄
赵进
侯文锋
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Foshan Muj Information Technology Co ltd
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Foshan Muj Information Technology Co ltd
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    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K5/00—Feeding devices for stock or game ; Feeding wagons; Feeding stacks
    • A01K5/02—Automatic devices
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K29/00—Other apparatus for animal husbandry
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01K—ANIMAL HUSBANDRY; AVICULTURE; APICULTURE; PISCICULTURE; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
    • A01K5/00—Feeding devices for stock or game ; Feeding wagons; Feeding stacks
    • A01K5/02—Automatic devices
    • A01K5/0291—Automatic devices with timing mechanisms, e.g. pet feeders
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1365—Matching; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/18—Eye characteristics, e.g. of the iris
    • G06V40/197—Matching; Classification
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

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  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Environmental Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Animal Husbandry (AREA)
  • Birds (AREA)
  • Public Health (AREA)
  • General Health & Medical Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Human Computer Interaction (AREA)
  • Medical Informatics (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Biomedical Technology (AREA)
  • Pathology (AREA)
  • Ophthalmology & Optometry (AREA)
  • Epidemiology (AREA)
  • Primary Health Care (AREA)
  • Feeding And Watering For Cattle Raising And Animal Husbandry (AREA)

Abstract

The invention discloses an intelligent animal feeder, a method and a system thereof. The method comprises the following steps: a. establishing an animal file; b. playing the feeding prelude sound of the animal; c. collecting and identifying physiological and behavioral characteristics of animals; d. and c, combining the data obtained in the step c with big data analysis, and providing food for the target animal under the condition of meeting the food intake. The system comprises: at least two intelligent animal feeders are arranged, and the intelligent animal feeders can share data with each other. The intelligent animal feeder and the method thereof have the characteristics of health management, automatic identification of animal identity for feeding and convenience in use.

Description

Intelligent animal feeder and method and system thereof
Technical Field
The invention relates to the field of animal feeding, in particular to an intelligent animal feeder and a method and a system thereof.
Background
The food outlet of the hourglass type feeder utilizes the hourglass principle, and the food storage box is immediately supplemented after the food at the outlet is cleaned by animals. The feeder can not feed regularly and quantitatively, can not be used for a long time, and can only ensure the feeding of two or three days at most.
A mechanical automatic feeder is an automatic feeder which can open a feeding opening or a box cover at fixed time by using a mechanical timing device at an outlet on the basis of an hourglass, and the feeder can feed only once or twice without power and batteries.
An electronic automatic feeder is characterized in that on the basis of a mechanical type, an electronic device (an electronic alarm clock, a time relay, a PLC and the like) is used at a food outlet to control the food outlet to be opened and closed at regular time, or to push food into a food box or to push the food box to the outlet. The feeder needs to be driven by electricity or batteries and can be used for feeding food for a plurality of times at regular time and fixed amount. The dog food and the cat food have no reasonable feeding standard, and the animal is easy to become fat or thin.
Several problems exist with the above-described conventional automatic animal feeders: (1) the phenomena that dogs eat cat food and cats eat dog food occur, the dogs eating the cat food for a long time can cause unbalanced nutrition, and the cats eating the dog food for a long time can suffer from urinary system diseases or kidney and liver diseases and nyctalopia; (2) the dog food can not provide reasonable food intake for the animals according to the actual conditions of the exercise amount, the weight change, the physical and mental states and the like of the animals, particularly, the dogs have no satiety and do not control the calorie intake, and the animals are easy to become fat or thin and have unhealthy body types; (3) in animal housing or animal hospitals, the animals may have improper food intake in strange environments.
Disclosure of Invention
In order to overcome the defects of the background art, the invention provides an animal intelligent feeder and a method and a system thereof.
In order to achieve the purpose, the invention adopts the technical scheme that: an animal smart feeding method comprising:
a. establishing an animal file;
b. playing the feeding prelude sound of the animal;
c. collecting and identifying physiological and behavioral characteristics of animals;
d. and c, combining the data obtained in the step c with big data analysis, and providing food for the target animal under the condition of meeting the food intake.
Further, the step c is to collect at least one characteristic of fingerprint, palm print, face, iris, voice and gait of the animal and measure the weight of the animal, and identify the identity of the animal by biometric identification characteristic technology.
Further, the step c is specifically to collect the body temperature, the pupil and the iris of the animal and the voice characteristics, check at least one of the physical and mental states of the animal such as diseases, emotions and hunger degrees through big data and machine learning, and identify the identity of the animal through a biological identification characteristic technology.
Further, the step c is to collect at least one of fingerprint, palm print, face, iris, voice and gait of the animal and record the activity of the animal, and identify the animal by the biological identification characteristic technology.
Further, the big data analysis may reference scientific recommendations and may form a practical feeding regimen.
An animal intelligent feeder related to the animal intelligent feeding method comprises the following steps: the server and the feeder body, the voice playing module, the acquisition module and the recognition module which are associated with the server.
Further, the feeder main body is provided with a weighable hamper.
Furthermore, the acquisition module is at least provided with a weight scale connected with the server.
Further, the acquisition module at least comprises a weight scale connected with the server and a motion tag wirelessly connected with the server.
An animal smart feeding system comprising: at least two intelligent animal feeders are arranged, and the intelligent animal feeders can share data with each other.
The invention has the beneficial effects that: the intelligent animal feeder combines a traditional feeder and intelligent equipment, acquires and identifies the physiological and behavioral characteristics and the environmental characteristics of animals, learns the environmental temperature and humidity, the weight change of the animals, the hunger degree of the animals, the emotion of the animals, the diseases of the animals and the activity of the animals, performs operation and analysis according to the acquired and identified data, automatically adjusts the feeding formula and the feeding amount, and avoids the situation that the animals are hungry and thin or are stretched and fat; after feeding of one animal is finished, the animal can not be fed under the condition that the feeding is not met, and the animal can be fed without the feeding, so that malnutrition caused by uneven food struggle of the animal is avoided; by identifying the identity of the animal, the corresponding food is provided, and animal malnutrition caused by the fact that a cat eats dog food and a dog eats cat food can be avoided; no matter the animal is to be in the place of residence, parents, animal custody or animal hospital, can regularly and as required throw the food for the animal, avoided owner to forget to feed and let the animal hungry, also need not to reset and feed the scheme, facilitate the use.
Drawings
Fig. 1 is a schematic diagram of an animal intelligent feeding method.
Fig. 2 is a schematic diagram of a smart feeding method for pets.
Fig. 3 is a schematic view of the wireless connection of the structure of the intelligent animal feeder.
In the figure: 110-a feeder body, 111-a collection module, 112-a recognition module, 113-a voice playing module, 114-an automatic driving module, 120-a weighing hamper, 121-an automatic shielding door, 122-a weight sensor, 130-a weighing scale, 131-a palm print collector, 200-a cloud server, 300-a motion tag, 301-an acceleration sensor, 302-a positioning system and 400-a client.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other. The following is an example of pets and livestock for the purpose of explaining the present invention.
As shown in fig. 1 to 3, an animal smart feeder and a method and a system thereof are applied to pet feeding, and a pet smart feeding method as shown in fig. 2 includes:
step 110: establishing a pet file, and selecting or inputting the food consumption prelude sound and biological identification data of the target pet. The food-taking prelude sound can be conditioned reflex sound formed by a pet owner calling sound, a crib knocking sound, a food impacting crib sound and the like to a target pet, or the pet owner sends voice or video interactive calling to the pet; the biometric data may be a fingerprint, palm print, facial makeup, iris, voice, gait, etc., entered into one or more of which is used to authenticate the pet's identity, and may also utilize RFID (i.e., radio frequency identification, non-contact data communication between a reader and a tag).
Step 120: the pet food can be attracted to fetch food and collect data before playing the food-taking prelude sound of the pet, and the data can be attracted to collect before the pet without feeding.
Step 130: the method comprises the steps of collecting and identifying physiological and behavioral characteristics of the pet, collecting at least one characteristic of fingerprint, palm print, facial makeup, iris, voice and gait of the pet, and identifying the identity of the pet by a biological identification characteristic technology.
Step 140: according to the data obtained in the step 130 and combined with big data analysis, if the pet is identified as a dog under the condition of satisfying the feeding condition, providing dog food, and combining the big data analysis to provide reasonable feeding amount according to the health requirement of the dog; if the pet is identified as a cat, providing cat food, analyzing health requirements of the cat by combining big data to provide reasonable feeding amount, and not providing the pet food under the condition that the feeding condition is not met. The eating condition can be that the food is eaten according to time points, six-point breakfast, twelve-point Chinese meal and eighteen-point dinner can be set, and the food is not fed if the condition is not met.
In an embodiment, the step 130 is to collect the face of the pet and measure the weight of the pet, measure the weight of the pet each time and upload the weight to the server for storage and analysis, and perform identity screening of the pet through an image recognition model of the following steps: acquiring a current frame image and extracting characteristics; acquiring historical frame images and identification features of profiled pets; and determining the pet identity of the current frame image according to the feature coincidence degree of the corresponding positions in the current frame image and the historical frame image.
The big data analysis is at least to statistically analyze the correlation between the weight change of the pet and the food feeding amount of the pet, so that the feeding condition can be set as feeding according to the weight change, and three or more meals are fed in a day according to the weight change of the pet within a time period; besides the time point feeding, the pet food is fed according to the weight reduction of the pet in a certain time period, and the pet food feeding amount with corresponding energy is supplemented according to the weight reduction.
In an embodiment, the step 130 is to collect the body temperature, the pupil, the iris and the voice characteristics of the pet, check at least one of the physical and mental states of the pet through big data and machine learning, identify the identity of the pet through iris recognition and/or voiceprint recognition, determine the identity of the pet through a voiceprint recognition model, perform voiceprint recognition on the voiceprint of the target pet to obtain the voiceprint of the pet, and match the pet identity corresponding to the voiceprint of the target pet from the preset mapping relationship between the pet identity and the voiceprint. In another embodiment, troubleshooting the physical and mental state of the pet further includes collecting and analyzing physical and postural features of the pet. The body temperature characteristic can be measured by an infrared thermometer, the voice characteristic is obtained by analyzing vocal prints, the posture characteristic is obtained by detecting height and weight to establish the fat and thin degree, the posture characteristic is obtained by detecting behaviors such as snivel, ear movement, tail movement and the like, changes of irises and pupils are detected, the direct or indirect relation formed by the characteristics and the disease, emotion and hunger degree of the pet is obtained by machine learning and big data statistical analysis, for example, the body temperature, irises and pupils, voice, posture and posture are related to diseases, the snivel of cats and dogs is probably a cold, the continuous low-lying kays of pet dogs are continuously possibly sick, the nearly glaring nasal sounds are continuously possibly sick, and the treatment medicines can be automatically put into the sick pets; for example, clatter, iris and pupil, posture are related to emotion, and a pet dog may feel frightened by raising a tail; for example, the cry is related to the hunger level, the pet dog whims and is hungry, and the pet cat gives out a specific meow sound when hungry. Taking the example of checking the hunger degree of a pet, collecting the cry of the pet and weighing the surplus of the pet food feeding amount, inputting the cry and the surplus of the pet food feeding amount into a machine learning model, and outputting the hunger degree corresponding to the cry, wherein the machine learning model is a hunger perception model formed by mapping based on a cry sample set and a corresponding hunger degree sample set in advance, then setting feeding conditions to feed according to the hunger degree of the pet, if the pet cat is perceived to be in a hungry state, feeding according to a certain feeding condition, then detecting the surplus of the pet food feeding amount and supplementing food according to a detection result so as to realize automatic feeding satiety of the pet cat; if the pet dog is sensed to be in a hungry state, food supplement can be not needed after no food remains after the pet dog is fed according to certain feeding conditions; and if the pet dog or the pet cat is sensed to be in a satiety state, the pet dog or the pet cat does not eat the food or does not continue to eat the food. The influence of diseases, emotion and hunger degree on the pet intake is analyzed by combining big data and machine learning, and then the direct or indirect relation between the physical and mental states of the pet and the pet food feeding amount is analyzed in a statistical manner, and a mathematical model is established so as to properly adjust the feeding amount and times in the following process.
In one embodiment, the step 130 is to collect a palm print of the pet and record the activity of the pet, and identify the pet by a palm print identification feature technology, wherein the palm print identification can be provided on the weighing scale. The big data analysis is at least to statistically analyze the mutual relation between the activity of the pet, the weight variation of the pet and the pet food feeding amount, the pet is fed according to the activity and the weight variation of the pet, the weight variation rule of the pet is analyzed according to the weight variation and the activity of the pet in a time period, the consumption of the pet in a next time period is estimated, and the pet food feeding amount with corresponding energy is supplemented according to the predicted consumption.
In one embodiment, the step 130 further includes collecting the temperature and humidity of the environment, and the big data analysis includes statistically analyzing the relationship between the temperature and humidity of the environment, the disease of the pet, the emotion of the pet, the hunger degree of the pet, the activity of the pet, and the weight change of the pet with each other and the food feeding amount of the pet. Therefore, new eating conditions are established, and at least two groups of the food can be eaten according to the environmental temperature and humidity, the weight change of the pet, the hunger degree of the pet, the emotion of the pet, the disease of the pet and the activity of the pet.
In one embodiment, the big data analysis may introduce a scientific recommendation scheme from the cloud in combination with the physiological and behavioral characteristics of the pet to provide a scientifically recommended pet food feeding amount for the pet in the pup or in the growing period, wherein the scientific recommendation scheme may be based on the measured calorie content of different pet foods per cup of the american pet obesity prevention association, the daily required calorie consumption amount corresponding to the pet standard weight data, the calorie consumption amount of the pet during daily exercise, the pet variety statistics of the american pet clubs, and the average weight of the pet breeds, adult male and female pets, the average weight of the puppy defined through scientific research; the brand and variety of pet food prevail in the market, and the calorie content per gram of the corresponding pet food is increased; through scientific research, the daily calorie intake required to be supplemented relative to the variety, age and weight of the pet, which is recommended by the expert, and correspondingly, the daily pet food intake required to be supplemented relative to the variety, age and weight of the pet, which is recommended by the scientific research and the expert; furthermore, the influence of the environmental temperature and humidity, the diseases of the pet, the emotion of the pet and the hunger degree of the pet on the food feeding amount of the pet is considered in the scientific recommendation scheme. After the pet is subjected to the scientific feeding recommendation scheme to mature period, because the demand on part of growing nutrients is reduced after the pet is mature, external environmental factors such as environmental humidity, temperature and climate and the like and related habits such as activity, weight change, physiological and behavioral characteristic change, intake, physical and mental states of the pet are collected by feeding of the scientific recommendation scheme, direct or indirect connection between the pet and the food feeding amount of the pet is obtained through big data analysis, the theoretical intake of the pet can be estimated, and a set of practical feeding scheme is formed. In another embodiment, if the intelligent feeding method is started after the pet is grown up, the early stage of starting feeding is according to a scientific recommendation scheme, and since the early stage feeding is not clear of pet habits, the scientific recommendation scheme is adopted, and after regular feeding is obtained for a period of time, a practical feeding scheme is adopted.
In one embodiment, according to the theoretical intake amount analyzed by each situation, the pet food does not need to be put into the hamper at one time, the pet food is added in multiple times, and whether the pet food is continuously added or not can be selected according to the remaining condition and the physical and mental states of the pet by detecting the feeding amount of the pet food.
In one embodiment, the identity and the symptoms of the pet can be marked first, i.e., the case file of the newly added pet is marked, the intelligent feeder is pre-provided with the treatment medicine, and the corresponding treatment medicine is taken after the identity of the pet is identified in the feeding process.
A pet smart feeder associated with the pet smart feeding method, comprising: the server and the feeder body, the voice playing module, the acquisition module and the recognition module which are associated with the server. The server, the voice playing module, the collecting module and the identifying module are arranged on the feeder body, the server is provided with a machine learning model, the machine learning model can be applied to the intelligent feeding method for the pet, programming is realized on all steps and actions, such as a voiceprint identifying model, an image identifying model, a hunger perception model and the like, and the machine learning model can be used for identifying the identity of the pet and analyzing the physical and mental states of the pet, such as hunger degree, emotion and the like. In one embodiment, the server can be a cloud server, internet data, data collected from the environment of the feeder main body and the pet are applied to machine learning and big data analysis, an intelligent system is constructed, and different users jointly enable scientific recommendation schemes to be more complete. The voice playing module is used for playing the food-taking prelude sound and other voices. The acquisition module can be a camera, a recorder, a finger and palm print acquisition instrument, a sports collar, a thermometer, a hygrometer, a weighing scale and the like, records images, videos, audios, finger and palm prints and other biological identification data of the pet, and acquires the body temperature and activity of the pet, and the image and the temperature and humidity of the surrounding environment of the feeder main body. The identification module can realize the identification of the identity and the physical and mental states of the pet by mutually fusing a biological identification feature technology, a machine learning technology, a mobile internet technology and a big data technology. Further, the feeder main part is equipped with the autopilot module, can be used to the shift position and pursue the pet, and on the other hand still can be used to the simulation robot, and the autopilot module lets the feeder main part play with the pet through the motion of simulation robot, in addition, still can be through the client at any time remote control intelligent feeder, looks over the daily situation of pet through network video or photo, can also carry out interdynamic with the pet.
In one embodiment, the feeder body is provided with a weighable hamper, the weighable hamper is provided with a shielding door and a weight sensor which are connected with the server, and the weighable hamper can be used for detecting the feeding amount and the rest condition of pet food. An automatic shielding door is arranged above the weighing hamper, the weighing hamper is not opened under the condition that food taking is not met, when the weighing hamper is opened, the weighing hamper is rotated and replaced by a cat food groove if the pet cat is identified, and the weighing hamper is rotated and replaced by a dog food groove if the pet dog is identified; furthermore, the shielding door of the weighing hamper is transparent, so that the shielding door is not opened when the pet food in the hamper is seen, and the shielding door is used for attracting the pet to collect data; still further, the top of the hamper of can weighing and the place ahead of camera are equipped with an arched door, and when the pet forages, the outer sheltering from of arched door can order about the pet to walk to discern and gather other data in the arched door, conveniently discern the identity of pet and attract the pet to come the data acquisition.
In one embodiment, the collection module is provided with a weight scale connected with the server. The weighing hamper is positioned in front of the feeder main body, the weight scale is arranged in front of the weighing hamper and the arch, and the weight of the pet can be conveniently measured when the pet takes food or attracts to take food; in another implementation, the palm print collecting instrument can be arranged on a weight scale, so that the identity of a pet can be conveniently identified, and the palm print collecting instrument is suitable for primates such as chimpanzees, gorillas and the like and koala.
In an embodiment, the collection module is provided with a motion tag wirelessly connected with the server, and the motion tag can be a motion bell, a motion collar, a motion bracelet, a motion foot ring and other devices provided with an acceleration sensor and wireless communication, and can be used for recording motion information of the pet and uploading the activity of the pet to the server. Furthermore, the motion tag can be provided with a positioning system for tracking the position of the pet; still further, the motion tag may be provided with a radio frequency identification tag, which may be used for identification and data recording.
A pet smart feeding system comprising: at least two pet intelligent feeders are arranged, and the pet intelligent feeders can share data with each other. In one embodiment, the pet is raised in different places, such as a hostess place during traveling, a father and mother place during passing, and a place for residence during working, so that the same set of feeding scheme can be used without worrying about resetting and adjusting, and the eating disorder of the pet is avoided. In another embodiment, the data sharing of the intelligent feeders in the same or different places can make the disease certification more accurate and timely by means of big data, track the origin of the disease and stop the spread of the disease timely.
In one embodiment, data sharing is encrypted, data can be checked and shared only by logging in an account and a password, various feeding schemes and corresponding feeding result samples can be obtained, and a user selects a feeding scheme according to the feeding result samples so as to expect that a pet to be kept is similar to the feeding result samples, such as body size and weight.
Accordingly, the animal smart feeder, the pet smart feeding method and the pet smart feeding system can be applied to livestock breeding, and the pet smart feeder, the pet smart feeding method and the pet smart feeding system can be cited in the aspect of not conflicting with the pet breeding. In one embodiment, the development conditions of each individual livestock are different and the climates of different feeding places are different, the body fat rate, the body size and the body weight of the livestock such as pigs, cows, sheep and horses can be further controlled according to the favor of customers by adjusting the livestock grains and the feeding conditions of different individuals, the slaughtering time is delayed or advanced according to the supply and demand relationship of the market, the livestock cannot be fed under the condition that the feeding conditions are not met after the feeding of the livestock is finished, the livestock which is not fed can be fed, the malnutrition caused by the uneven feeding of the livestock is avoided, and the individuals with different growth conditions can be adjusted to be slaughtered in the same batch to meet various requirements of the customers.
Accordingly, the intelligent animal feeder, the intelligent pet feeding method and the intelligent pet feeding system are applied to zoo feeding, and the intelligent pet feeder, the intelligent pet feeding method and the intelligent pet feeding system can be cited in zoo feeding in the aspect of not conflicting with pet feeding. In one embodiment, the animal diet condition and the nutritional requirement of different growth stages are different, and the food of corresponding age bracket is provided by identifying the animal identity, so as to avoid animal malnutrition or dyspepsia, and on the other hand, the intelligent feeding is carried out on the beasts such as lions and tigers, so that the potential danger of feeding personnel is avoided.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (10)

1. An intelligent animal feeding method, comprising:
a. establishing an animal file;
b. playing the feeding prelude sound of the animal;
c. collecting and identifying physiological and behavioral characteristics of animals;
d. and c, combining the data obtained in the step c with big data analysis, and providing food for the target animal under the condition of meeting the food intake.
2. The intelligent animal feeding method of claim 1, wherein: and c, specifically, collecting at least one characteristic of fingerprint, palm print, facial appearance, iris, voice and gait of the animal, measuring the weight of the animal, and identifying the identity of the animal by a biological identification characteristic technology.
3. The intelligent animal feeding method of claim 1, wherein: and c, acquiring the body temperature, the pupil and the iris of the animal and the voice characteristics of the animal, checking at least one physical and mental state of the animal such as diseases, emotions and hunger degrees through big data and machine learning, and identifying the identity of the animal through a biological identification characteristic technology.
4. The intelligent animal feeding method of claim 2, wherein: and c, acquiring at least one of fingerprint, palm print, facial appearance, iris, voice and gait of the animal, recording the activity of the animal, and identifying the identity of the animal by a biological identification characteristic technology.
5. The intelligent animal feeding method of claim 1, wherein: the big data analysis may reference scientific recommendations and may form practical feeding regimens.
6. An animal intelligent feeder related to the animal intelligent feeding method of claims 1-5, characterized by comprising the following steps: the server and the feeder body, the voice playing module, the acquisition module and the recognition module which are associated with the server.
7. The animal intelligent feeder of claim 6, wherein: the feeder main body is provided with a weighing hamper.
8. The animal intelligent feeder of claim 6, wherein: the acquisition module is at least provided with a weight scale connected with the server.
9. The animal intelligent feeder of claim 6, wherein: the acquisition module at least comprises a weight scale connected with the server and a motion tag wirelessly connected with the server.
10. An animal intelligent feeding system, comprising: at least two intelligent animal feeders are arranged, and the intelligent animal feeders can share data with each other.
CN201911359046.1A 2019-12-25 2019-12-25 Intelligent animal feeder and method and system thereof Pending CN111134033A (en)

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Cited By (8)

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CN111466305A (en) * 2020-05-27 2020-07-31 电子科技大学中山学院 Pet feeding system based on pet collar
CN111837992A (en) * 2020-07-30 2020-10-30 武汉中畜智联科技有限公司 Timing feeding system of lactating sow feeding machine
CN112243868A (en) * 2020-10-22 2021-01-22 珠海格力电器股份有限公司 Equipment control method and device, electronic equipment and readable storage medium
CN112450120A (en) * 2020-11-26 2021-03-09 小佩网络科技（上海）有限公司 Pet weight recording method and device, pet toilet and medium
CN114303979A (en) * 2021-12-29 2022-04-12 齐鲁工业大学 Pet feeding method, system, storage medium and device based on OneM2M
CN115250939A (en) * 2022-06-14 2022-11-01 新瑞鹏宠物医疗集团有限公司 Pet hamper anti-misoperation method and device, electronic equipment and storage medium
CN115299366A (en) * 2022-06-21 2022-11-08 新瑞鹏宠物医疗集团有限公司 Intelligent feeding method and device, electronic equipment and storage medium
CN116530428A (en) * 2023-07-07 2023-08-04 四川省畜牧科学研究院 Sow feeding control system and method

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Publication number Priority date Publication date Assignee Title
CN111466305A (en) * 2020-05-27 2020-07-31 电子科技大学中山学院 Pet feeding system based on pet collar
CN111837992A (en) * 2020-07-30 2020-10-30 武汉中畜智联科技有限公司 Timing feeding system of lactating sow feeding machine
CN112243868A (en) * 2020-10-22 2021-01-22 珠海格力电器股份有限公司 Equipment control method and device, electronic equipment and readable storage medium
CN112450120A (en) * 2020-11-26 2021-03-09 小佩网络科技（上海）有限公司 Pet weight recording method and device, pet toilet and medium
CN114303979A (en) * 2021-12-29 2022-04-12 齐鲁工业大学 Pet feeding method, system, storage medium and device based on OneM2M
CN115250939A (en) * 2022-06-14 2022-11-01 新瑞鹏宠物医疗集团有限公司 Pet hamper anti-misoperation method and device, electronic equipment and storage medium
CN115250939B (en) * 2022-06-14 2024-01-05 新瑞鹏宠物医疗集团有限公司 Pet hamper anti-misfeeding method and device, electronic equipment and storage medium
CN115299366A (en) * 2022-06-21 2022-11-08 新瑞鹏宠物医疗集团有限公司 Intelligent feeding method and device, electronic equipment and storage medium
CN115299366B (en) * 2022-06-21 2024-02-13 新瑞鹏宠物医疗集团有限公司 Smart feeding method, smart feeding device, electronic equipment and storage medium
CN116530428A (en) * 2023-07-07 2023-08-04 四川省畜牧科学研究院 Sow feeding control system and method
CN116530428B (en) * 2023-07-07 2023-09-22 四川省畜牧科学研究院 Sow feeding control system and method

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