WO2021019457A2 - Estimation de poids de poulets à l'aide d'une vision artificielle 3d et d'une intelligence artificielle - Google Patents

Estimation de poids de poulets à l'aide d'une vision artificielle 3d et d'une intelligence artificielle Download PDF

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Publication number
WO2021019457A2
WO2021019457A2 PCT/IB2020/057147 IB2020057147W WO2021019457A2 WO 2021019457 A2 WO2021019457 A2 WO 2021019457A2 IB 2020057147 W IB2020057147 W IB 2020057147W WO 2021019457 A2 WO2021019457 A2 WO 2021019457A2
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WIPO (PCT)
Prior art keywords
weight
images
livestock
microcomputer
data
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PCT/IB2020/057147
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English (en)
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WO2021019457A3 (fr
Inventor
Mahender Pal SINGH
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Singh Mahender Pal
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Publication date
Application filed by Singh Mahender Pal filed Critical Singh Mahender Pal
Publication of WO2021019457A2 publication Critical patent/WO2021019457A2/fr
Publication of WO2021019457A3 publication Critical patent/WO2021019457A3/fr

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Classifications

    • 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
    • A01K45/00—Other aviculture appliances, e.g. devices for determining whether a bird is about to lay
    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/02—Agriculture; Fishing; Forestry; Mining
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/22—Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
    • G06V10/225—Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition based on a marking or identifier characterising the area
    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G17/00—Apparatus for or methods of weighing material of special form or property
    • G01G17/08—Apparatus for or methods of weighing material of special form or property for weighing livestock

Definitions

  • This invention generally relates to the field of livestock operation and specifically to the real time body weight estimation of livestock.
  • the feed conversion ratio is the amount of feed ingested by an animal which can be converted into one kilo of live weight.
  • feed efficiency is a major variable to determine the cost of a kilogram of poultry meat.
  • the Feed Conversion Ratio which varies depending on the type of production applied, is always a very helpful benchmark to determine the profitability of a farm. Should one aim to increase the revenue of their poultry enterprise, it is important to know how to improve the Feed Conversion Ratio and how to reduce the feed costs.
  • Farm operators constantly strive to minimize mortality and improve FCR by constantly making adjustments to farming practice and feed as livestock growth is highly sensitive to a number of controllable and uncontrollable factors.
  • body weight is an important parameter to understand and monitor the body composition of livestock and can shed light on any current or future unexpected performance issue in the farm.
  • the producers and sellers of animal products require to have information about the body composition of animals to track their efforts and subsequently producing leaner meat animals.
  • Animal nutritionists also need information about body composition to determine their dietary requirements and the amount of energy an animal eats is then captured as growth or other forms of production. Growth rate and metabolic response of a livestock population or poultry farm thus cannot be monitored and investigated without knowing the variations in the body weight of the animals.
  • the body weight information can be put to use immediately and necessary actions can be triggered to rectify any unwanted outcome.
  • poultry industry which can be further categorized as a Breeder Farm, Hatchery, Growth Farm, and Processing Plant
  • measurement of the body weight of the Broiler, Breeder or Layer birds is a critical input to ensure that the farm performance is as per the expectations.
  • body weight or growth rate is a desired input on a regular basis to ensure that the farm is performing as per the established growth standards and plan harvesting of the birds accordingly.
  • the present invention enables taking three-dimensional images of the chickens and convert the visual information into a highly accurate weight estimate using advanced image processing methods to extract features (predictors) from these images and neural network models.
  • a contour capturing device records the depth images at regular intervals and feeds to the AI engine.
  • the central processing unit in the device manages to provide the estimated weight data using advanced image processing methods and Neural Network models which is then transferred to servers through Wi-Fi module. All these components work together to provide an accurate weight estimate and also assist health assessment of the livestock.
  • the invention is developed to provide real time and on demand weight visibility for livestock through artificial intelligence and advanced image processing technologies.
  • a three-dimensional sensor device records the depth images as an input to the AI engine.
  • the AI engine estimates weight for every image processed using a variety of parameters and computations such as the minimum and maximum width, length of Broiler contour, height captured using depth images, convex volume, surface area etc.
  • the weight estimates computed on the device are recorded in a text file which is transferred to Cloud servers using the Wi-Fi connection.
  • the weight estimate data transferred to Cloud servers is further analyzed to generate practical KPIs and insights which can be accessed through computers/phones/tablets applications.
  • the growth rate/body weight is measured using the following two methods that are prevalent in the industry:
  • This method involves using a brooder to trap the chickens and manually weigh them using a weighing scale. Being a highly manual process, it depends heavily on the available manpower as well as the expertise and efficiency of the human resource and have limitations associated in the way it is carried out. Any excess or inefficient handling by farm hands also stresses the birds adversely, impacting their well-being and retarding their growth rate. As such, this method can only be applied on a periodic basis on a small sample to minimize human handling. Since it is done periodically there needs to be certain rules to be followed to increase the accuracy of this method;
  • This method involves using an automatic electronic platform weigher in the Broiler farms.
  • the drawbacks associated with this method are;
  • the system/method utilizes images of individual animals and determines the identity of a specific animal based on markers extracted from the image of the animal. These markers may then be used to characterize the state of the animal as to weight, health, and other parameters.
  • the system is configured to log these parameters in a temporal database that may be used to determine historical activity of the animal, including but not limited to activity relating to food and/or fluid intake. This historical record in conjunction with analysis of the animal state parameters is used to determine the animal health status and may also be used to determine whether the animal is ready for harvesting.
  • This invention utilizes images of individual animals and determines the identity of a specific animal based on markers extracted from the image of the animal, which is used to characterize the state of the animal as to weight, health, and other parameters.
  • the present invention utilizes artificial intelligence to provide real time weight estimation and health monitoring of the livestock.
  • the system is configured to determine livestock health data of livestock animals.
  • the livestock health data includes livestock health characteristic data indicative of a health characteristic of the corresponding livestock animal associated livestock identification data that uniquely identifies each livestock animal.
  • the livestock identification data is received by each livestock health sensor system from a livestock identification tag coupled to the corresponding livestock animal.
  • Each livestock health sensor system transmits the determined livestock health data to a livestock health monitoring server, which aggregates the livestock health data for each livestock animal and analyzes the health data to determine whether any abnormalities are present. If so, the livestock health monitoring server may control a livestock treatment device to provide treatment to the corresponding livestock animal on a per-animal basis.
  • a livestock health sensor system comprising a communication circuit to receive livestock identification data and a treatment device for the livestock in response to the determination of the requirement based on the captured health data.
  • the features of the presently claimed invention like the AI engine and the use of microcomputer to carry out image processing for the weight estimation is not present here.
  • the system/method is designed to calculate the weight of the dressed poultry by measuring only a change in the height of laser structured lights and a 2D geometric shape of the dressed poultry, thereby reducing the processing time for measuring the weight of the dressed poultry.
  • This invention deals with a dressed poultry weight calculating system method by measuring only a change in the height of laser structured lights and a 2D geometric shape of the dressed poultry. Since the client’s invention also deals with weight monitoring of livestock, there might be an overlap. Features like the capture of voice signature and use of artificial intelligence are missing over here.
  • the system comprises a monitoring center, a weight information collecting and sending device, a mobile information terminal, a wireless signal transceiver and a station marker, wherein the weight information collecting and sending device, the mobile information terminal and the station marker are wirelessly connected with the monitoring center through the wireless signal transceiver and the weight information collecting and sending device is arranged on feed mixing equipment.
  • the invention focusses on wireless integration and monitoring of information in a livestock feeding process.
  • the present invention utilizes artificial intelligence to provide real time weight estimation and health monitoring of the livestock.
  • the system comprises a random-measuring weight device and a feed consumption measuring device.
  • the weight random-measuring device is used for measuring weight data of an animal group dynamically and intelligently in real time and acquiring a group parameter of an average daily gain according to daily group weight difference.
  • the feed consumption measuring device is used for acquiring dynamic real-time feed consumption parameters.
  • the weight random measuring device and the feed consumption measuring device respectively send weight information and feed consumption information to a data processing unit through a transmission network, and the data processing unit sends processed data to a data receiving terminal.
  • the intelligent intensive livestock and poultry monitoring system and the intelligent intensive livestock and poultry monitoring method are capable of measuring maximum marginal income and real-time variation tendency of marginal cost dynamically and intelligently in real time and are extremely high in reliability and practicability.
  • the invention relates to an intelligent intensive livestock and poultry monitoring system and an intelligent intensive livestock and poultry monitoring method.
  • the present invention utilizes artificial intelligence to provide real time weight estimation and health monitoring of the livestock.
  • the method comprises: a camera and a sensor collecting data, when data collection is completed, transmitting the data to a single board computer, the single board computer integrating the data, and transmitting the integrated data to a C/S terminal of a local terminal to perform next-step processing; on the local terminal C/S, firstly performing living body identification on acquired RGB images, combined with depth point Cloud data of a depth camera, deducing a 3D point Cloud image, meanwhile uploading RGB and 3D point Cloud images, and individual information of living bodies and environment variable collected by the sensor to a Cloud server; the Cloud server cleaning and denoising the 3D point Cloud images according to the uploaded individual information and environment variable, after the 3D point Cloud images reach a standard, restoring volume to obtain living body volume, and calculating mass; returning an obtained living body mass result to the C/S terminal, if objection for error of mass exists, correcting errors by hand, after error correction, recording and uploading to the Cloud server.
  • the invention discloses a method for monitoring livestock breeding living body weight based on the internet of things.
  • the present invention utilizes artificial intelligence to provide real time weight estimation and health monitoring of the livestock.
  • the invention doesn’t include the feature of the present invention that executes the AI model on the single board computer on the device in the farm itself and not transmit the images to the local terminal for processing. This is a critical difference since the farms tend to be in remote locations with limited connectivity which will make it impossible to send images to Cloud for processing, failing which weight can’t be estimated.
  • the weight estimates are computed in the farm by the processor that is connected by wire to the 3D camera and the weight estimate is stored in a text file. This is a small size file that can be easily sent to Cloud even under limited connectivity conditions and at any time.
  • the main object of the invention is aimed at to estimate the weight/growth rate of a
  • a further object of the invention is to enable on-demand data collection and weight
  • a further object of the invention is to ensure large and random sample size without
  • a further object of the invention is to enable system to estimate weight on the device (edge computing). This is a critical capability since sending images over the Wi-Fi will necessitate very high bandwidth to connect with the remote system which is an infrastructure limitation as most farms tend to be located in remote areas. Furthermore, even if images can be transmitted it will limit how many images can be sent and it will take a long time to complete the transfer inserting long delays in delivering insights and alerts for decision making since timing is an important factor.
  • a further object of the invention is to enable assessment of Bird Weight Uniformity in real time which is a critical predictor of flock health and performance.
  • a further object of the invention is the development of a complete system used to manage the devices remotely from a central location. It is important for the device to be operating when required, maintain necessary RAM, storage along with sound internal connectivity. In addition, the device has to maintain a preset height from the ground for the AI engine to estimate weight accurately.
  • the current version of the device and the system are capable of ensuring that the system operations parameters are communicated, including self-reported height of the device, to the control tower for necessary follow up actions in case there is a disruption of service.
  • Bird Contour Capturing Device is a depth sensing camera (e.g. Microsoft Kinect).
  • Central Processing Unit is a microcomputer (e.g. Odroid processor).
  • Connectivity Device are Wi-Fi modules installed on the microcomputer that can send the processed data on the device, a text file, to external servers for further processing and reporting.
  • AI Artificial Intelligence
  • the system is capable of taking continuous images at any time or at predetermined intervals (that can be remotely changed as required) and the processor estimates the weight of the livestock from these images.
  • the estimated weight from the processed images is computed and sent to the servers and the end user can use the information as the case may be.
  • Our invention differs from the prior art devices by incorporating the following concepts:
  • the remote team can inform the ground team to intervene only when required.
  • It can be either installed at fixed locations or mounted on a mobile mechanism such as conveyor or a drone to increase the sample size without investing in too many devices.
  • Figure 1 describes the components inside the system.
  • Figure 2 describes the top view of the system.
  • Figure 3 describes the base sheet of the system on a scale of 1:5.
  • Figure 4 describes the top sheet of the system on a scale of 1 :5.
  • the livestock weight estimation and health monitoring system/method comprise the following units:
  • the livestock weight estimation and health monitoring system/method consist of a 3D sensor device, Kinect (or similar) which records depth images. Images are main input data to the system’s AI engine. Images are collected on regular intervals for each day.
  • the system uses a single board computer such as an Odroid processor on which the AI engine is installed.
  • Image processing algorithm extracts different weight descriptors - 2D and 3D features.
  • 2D features such as minimum and maximum width, length of Broiler contour and 3D features such as height captured using depth images, convex volume, surface area etc.
  • AI engine estimates weight for every image processed.
  • a Wi-Fi signal receiver module is installed on the microcomputer which connects the device to a Wi-Fi provider device.
  • the processed estimated weight data in the form of a text file is transferred to Cloud servers using the Wi-Fi connection.
  • the device is in constant communication with the central control tower for any operational action in case there is a device malfunction.
  • the system uses a set of hardware to acquire 3D images that are processed by a trained AI Network model to estimate weight and dimensions of the birds from these images.
  • a trained AI Network model to estimate weight and dimensions of the birds from these images.
  • Cloud based database application that receives the estimated weight of individual birds as a text file for further analytics such as average daily weight, variation in daily weight, growth trends in daily weight, feed conversion ratio, future prediction of weight etc.
  • Steps carried out automatically by the device in the farm edge computing device has a 3D Camera and a single board computer
  • Depth maps 1 of each individual chicken from the 3D Camera images are preprocessed to ensure that images are suitable for extracting selected features identified during AI engine training. This includes, but not limited to, removing birds that are not fully visible to the camera, overlapping bird images, removing images of the bird with spread wings as it contorts body contours, correction based on removal of the background disturbance caused by the litter that is present in most closed houses.
  • the engine also corrects for the height based on the position of the bird if it is sitting, crouching or standing.
  • a depth map is an image or image channel that contains information relating to the distance of the surfaces of scene objects from a viewpoint. 3.
  • selected features are extracted that include, but not limited to, measures of the Minor Ellipse Axis (width), Major Ellipse Axis (length), Ellipse Area (Surface Area), Inscribed Circle (another measurement of surface area), Height, that are identified by the AI Network model during training as the strongest predictor input for estimating weight.
  • Text file with estimated weight of each bird seen in each frame collected by the camera is sent to the Cloud via Wi-Fi connection for further processing. Steps carried out by the system in the Cloud after data is received from the device in each house:
  • Each device and house have a unique id number which is paired during installation to ensure 1-1 mapping of the device and the house at all times.
  • the estimated weight data of each chicken captured by the camera of each device in a particular house is sent as a text file via Wi-Fi to the application in the Cloud to be stored separately for further analysis of the performance of that particular house.
  • the device and the underlying methods can be trained and used for the Breeder and Layer farms in the Poultry, Aqua, Swine, Cattle and other livestock for enhancing farm performance using effective and timely weight estimation & predictions.
  • a device similar to the current embodiment can be used to acquire necessary images of the Breeder and Layer farm for estimating weight in real time.
  • the same could be done for Swine, Cattle and Aqua farms after making necessary adaptation of Image Acquisition device, Image Preprocessing engine and the AI Network model.
  • the overall approach remains identical.
  • contour capturing devices such Intel RealSense can replace the one used in the invention, to get bird’s contour features in order to estimate the weight.
  • the Kinect depth sensing camera is used in the current version.
  • any other microcomputer can be used in place of the Odroid processor used in the present version.
  • the entire wiring and circuit could be done on a chip/wafer.
  • the system can be used to capture multiple environment parameters in real time that can generate superior insights. These insights could highlight correlations and causations between anomalous weight performance and sensor readings for preventative measures to ensure good health and growth rate of the birds in the farm at a lower cost.

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Abstract

La présente invention concerne un système et un procédé d'estimation du poids de poulets à l'aide d'une technique de vision artificielle 3D dans laquelle : le dispositif de capture de contour d'oiseau est une caméra de détection de profondeur, l'unité de traitement centrale est un micro-ordinateur, le dispositif de connectivité est un module Wi-Fi qui peut envoyer des données à des serveurs externes. Des composants protecteurs et autres consistent en : un protecteur de surtension qui offre une protection contre les pointes de tension, un boîtier pour loger tous les autres composants et un câble pour se connecter à la source d'alimentation. Un moteur d'IA installé sur le micro-ordinateur embarqué estime le poids de poulets à partir des images 3D. Le système prend des images 3D continues et le processeur estime le poids à partir de ces images 3D. Les poids estimés sont sauvegardés sur le dispositif et envoyés à des serveurs à distance, par exemple, en nuage, pour générer et visualiser des rapports et des aperçus pour un partage avec des utilisateurs par l'intermédiaire d'une application logicielle.
PCT/IB2020/057147 2019-07-31 2020-07-29 Estimation de poids de poulets à l'aide d'une vision artificielle 3d et d'une intelligence artificielle WO2021019457A2 (fr)

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Cited By (4)

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CN112990014A (zh) * 2021-03-15 2021-06-18 深圳喜为智慧科技有限公司 一种猪体重估计方法、系统、设备及存储介质
CN113096178A (zh) * 2021-04-25 2021-07-09 中国农业大学 猪只体重的估测方法、装置、设备和存储介质
CN113627486A (zh) * 2021-07-12 2021-11-09 杨龙 一种牲畜估重方法、装置及存储介质
CN115968813A (zh) * 2021-10-15 2023-04-18 智逐科技股份有限公司 家禽健康监测系统及其方法

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012519277A (ja) * 2009-02-27 2012-08-23 ボディー サーフェイス トランスレーションズ， インコーポレイテッド 三次元表示を使用する物理パラメータの推定
DE102016201389A1 (de) * 2016-01-29 2017-08-03 Robert Bosch Gmbh Verfahren zu einer Erkennung von Objekten, insbesondere von dreidimensionalen Objekten

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112990014A (zh) * 2021-03-15 2021-06-18 深圳喜为智慧科技有限公司 一种猪体重估计方法、系统、设备及存储介质
CN113096178A (zh) * 2021-04-25 2021-07-09 中国农业大学 猪只体重的估测方法、装置、设备和存储介质
CN113627486A (zh) * 2021-07-12 2021-11-09 杨龙 一种牲畜估重方法、装置及存储介质
CN113627486B (zh) * 2021-07-12 2024-04-16 杨龙 一种牲畜估重方法、装置及存储介质
CN115968813A (zh) * 2021-10-15 2023-04-18 智逐科技股份有限公司 家禽健康监测系统及其方法

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