METHOD OF AUTOMATED ACQUISITION OF ANIMAL CONSUMPTION DATA AND BEHAVIOR DATA

专利摘要:
identification, measurement, monitoring and animal management system. a highly automated system and method for acquiring consumption and animal behavior data, comprising stations where consumable products are fed to animals. the stations being equipped with rfid equipment to read rfid tags in close proximity to the station and weighing devices to measure the weight of the consumables. the rfid equipment and the weighing device are connected to a computer that calculates the weight of the trough at specific times, using weight data collected before and after the specified time, to improve the accuracy of the weight measurement. the computer uses a "weighted mathematical filter technique" to assess the weight of the trough before and after a consumption event. the computer uses a method to split a reduction / increase in heavy material between the last tag to split a reduction / increase in heavy material between the last rfid tag seen and the next rfid tag that appears, providing the reduction / increase in material in less than a specified amount.
公开号:BR112013008147B1
申请号:R112013008147-3
申请日:2011-10-05
公开日:2021-03-23
发明作者:Camiel Huisma
申请人:Growsafe Systems, Ltd.；
IPC主号:

专利说明:

[0001] [0001] This Order claims the benefit of Provisional Order No. 61 / 390,803 deposited on October 7, 2010. Field of the Invention
[0002] [0002] This invention relates to an animal identification, measurement, monitoring and management system and a method of using it in an animal production environment and, more specifically, a system that is capable of being used with several transmitters for to monitor, automatically and continuously, the consumption and behavior of individual animals to predict and determine a variety of conditions related to health, performance, and production yield, enabling the determination of individual animal performance in different diets, response to medications, response to food supplements, response to minerals and trace minerals, response to growth-promoting substances, prediction of carcass quality and determination of greenhouse gas and manure excretion. Background of the Invention Radio frequency identification
[0003] [0003] During the past 40 years, however, radio frequency identification has been used to identify objects automatically. An example of a practical application of this technology has resulted in electronic identification of individual animals. The basic elements of such a system include a reader / transmitter, an antenna or a transponder. The reader / transmitter sends an electromagnetic wave through the antenna to the transponder which uses this energy to transmit a radio frequency signal back through the antenna to the reader / transmitter. Typically, the signal includes a unique identification code for each transponder. To monitor the activities of large herds or confined groups of animals, one must be able to monitor several transponders in a relatively small area. With currently available technology it is extremely difficult to read several transponders using a reader / transmitter.
[0004] [0004] If each of the several transponders uses the same frequency to transmit its unique identification code back to the reader / transmitter, a single reader / transmitter is unable to easily decipher each individual identification code. To make systems with several transponders operational, several readers / transmitters are required, which, in turn, make such a system expensive and will also reduce the area in which the transponders can be read simultaneously. Food intake measurement - previous generation of food intake measurement
[0005] [0005] A rudimentary way to measure individual food or water intake was to house animals individually and record consumption by manually measuring and recording the food supplied minus the refused or remaining food. This method is both labor-intensive and cost-prohibitive. Studies on both pigs and cattle have shown that animals housed individually alter their performance significantly from those fed in production environments.
[0006] [0006] The first generation of electronic feeders acted on the same principle as manual registration. These systems isolate an animal for an individual feed gate or stable. When the animal enters the stable the initial weight of the trough is registered and when the animal leaves the final weight of the trough is registered. The difference between the initial weight and the final weight is determined to equalize the food intake. Although a rough measurement of what food disappeared during the time the animal entered and left the feeding stall, this measurement does not take into account what happened accurately during the time period.
[0007] [0007] The methodology is further compromised when access to the trough is open at all times and RFID is used to identify the animal. RFID is position sensitive and therefore could require a variable amount of time to read, compromising the start of the event. Other aspects that complicate the use of RFID, particularly when measuring visitation by an individual animal to a trough, is that the RFID reading field often extends to one or more adjacent trough areas. Therefore, it is possible that when the animal has its head close to one side or the other of a feeding trough that the adjacent RFID antenna also reads the RFID tag of the adjacent animal, and this potentially creates reading / calculation problems.
[0008] [0008] These first generation systems should typically be housed in granaries that provide protection from wind and other environmental conditions, which add significantly to the measurement cost. On a windy day, for example, the wind or air pressure applied to the gutter often varies by 10 N. Such pressure variation becomes very problematic when trying to weigh a typical meal event food intake, usually around 800 grams .
[0009] [0009] In addition, birds, rodents, etc., and consumption of something from the food in the trough, and such food losses will lead to inaccurate food consumption determinations. In particular, studies have estimated that the food eaten by starlings, for example, can be as much as 6% to 12% of the food presented for animals.
[0010] [0010] It should be appreciated that little or no behavioral information is acquired through these first generation systems, activity between meals is not recorded. The effect of animal competition on feed intake behavior is not adequately measured, and feed rates are normally considered to be constant during a feeding event. In terms of behavioral measurement, perhaps the most limiting factor is that the equipment determines what a feeding event or meal event is, due to an animal visit being recorded by the equipment.
[0011] [0011] Another aspect that arises from the use of such equipment is that typical feeding behaviors are severely modified by the design of the measuring device itself. The animal can only be left to visit its specific food stall to record consumption. Or when two animals wish to enter the trough at the same time, none of the animals will gain access. To overcome the limitations of the system for reading several labels in close proximity, the system prevents access to food.
[0012] [0012] Several of these preceding generation systems do not include the method for taking into account the appearance of food in the trough. Some tried to take proper account of the appearance of food using deflectors that keep animals from the supports when gutters were filled. Animals were refused entry when food was replenished.
[0013] [0013] The first generation systems did not include the ability to audit or assess the accuracy of measurements. Several researchers have developed generalized and average statistical assumptions to overcome errors that occur in first generation systems. In scientific literature, incorrect data are usually adjusted per visit (for example, De Haer et al., 1992). Some studies correct measurement error by evaluating individual feed intake and tolerance factors based on those taken in group feeding studies. This circular reasoning does not improve measurement accuracy although data may fit what the researcher perceives to be true based on previous research on group adjustments. Background for measuring feeding behavior
[0014] [0014] In the early 1990s Growsafe Systems Ltd (“Growsafe”) developed a computerized data acquisition system that could identify and monitor ostrich chicks electronically. Puppies should visit the feeder approximately 500 times a day. When the chicks became sick, the feeding visitation behavior fell rapidly, declining to approximately 50 visits per day. This decline in visits could be observed as a trend over a very short period of time, usually within approximately 4-12 hours. In response to GrowSafe data triggers, bird flu experts developed treatment protocols that responded. Using GrowSafe technology and animal health treatment protocols that responded incorporated in it, the survival rate of the tested subjects improved from 8% to more than 90% (Anedotário Huisma 1993).
[0015] [0015] Previous findings in livestock research using GrowSafe technology have indicated similar previous predictive capabilities using animal behavior to identify diseases at an earlier point in time than otherwise possible. From 1993 to 2000 a significant body of work was compiled by researchers using first-generation GrowSafe behavior research technology that indicates that patterns of feeding behavior in sick and non-sick calves differ and could be measured (Basarab, 1996); and that the technology had the potential to identify sick animals before any visible disease symptoms could be detected (Quimby, 1999). Research has determined that the economic value of sick calves could be as much as $ 0.19 to $ 0.35 less per kg, than for healthy calves (Sowell, 1999).
[0016] [0016] The technological transition of a GrowSafe system that could measure a small bird confined in a controlled environment to a large animal in a livestock environment was extremely complex and required the adaptation and development of new electronics, wireless communication methods and data analysis and acquisition. Several of these methods are currently protected by patents granted or granted to GrowSafe Systems Ltd. Eating Behavior and Disease Identification
[0017] [0017] Researchers have traditionally observed behavioral changes as simple signs of debilitating effects of disease (Weary, 2009). Results of several key studies now indicate (1) disease behavior is a motivational state; (2) disease behavior is a well-organized adaptive response to infection; (3) cytokines produced by activated leukocytes induce disease behavior; and (4) cytokines transmit messages from the periphery to the brain using humoral and neural pathways (Johnson, 2002). During the past decade there has been a substantial shift in thinking about behavioral concepts related to animal health.
[0018] [0018] Identifying sick animals, earlier in the course of the disease, can be one of the most difficult jobs in livestock production. When treated earlier, most animals have an excellent chance of survival, however, if an animal is ill even for a few days, treatment regimens are less likely to be effective. Recognition of declining food intake can assist with the identification of sick animals. In recent years there has been a growing interest in disease behavioral indicators. A decrease or change in eating patterns is usually a symptom of sick individuals. The research demonstrated decreases in the carcass value of sick animals between animals that were not treated, and those that were treated once, twice and three times, respectively (Schneider, 2009). The value of diagnosis and rapid treatment of disease increases when cattle are sold based on the value (merit) of the carcass due to the negative effects of disease on the carcass's features (Larson 2005).
[0019] [0019] Several epidemiological studies have indicated that even with increased pharmaceutical use, the incidence of morbidity and mortality in livestock feedlot farms (fattening) has increased. Total deaths on livestock feedlots in 2003 increased by 69% when compared to those in 1994. Deaths from bovine respiratory disease (BRD) more than doubled (118%) during the same period of time (Loneragan, 2008).
[0020] [0020] Research indicates that the synchronization of initial BRD treatment is associated with performance and health outcomes (Babcock, 2009). The effectiveness of antimicrobials in the treatment of BRD depends primarily on early recognition and treatment (Apley, 2007, Cusack, 2003). BRD manifests its economic losses cumulatively, through the cost of treatment, the cost of lost production and loss due to death, thus emphasizing the importance of preventing and treating BRD as early as possible. Food Yield
[0021] [0021] For several years genetic selection programs have focused on the feature of production (output) with little attention given to production costs (inputs). This view has recently begun to change, and the yield of food conversion (that is, the amount of product per unit of food input) has been recognized as the most important.
[0022] [0022] Within any beef cattle operation, feed costs are undoubtedly the main concern, since they typically take into account approximately 60-65% of total production costs. Due to the high costs associated with food, increasing food yield was targeted as a means of improving the profitability of the meat industry. An assessment of food yield is the feed conversion ratio. Traditionally this was expressed as a food: gain ratio, but this led to the confusing result that a higher ratio meant lower income. Today, to overcome this problem, food conversions are often expressed as a gain: food relationship. Even so, results can be confusing, since these relationships are closely correlated to the animal's entry and gain rate (Carstens et al., 2004).
[0023] [0023] Two animals could have a similar gain: food ratio and still be very different in their food intake and gain rates. Conversely, the same animal in different entries could certainly have different gain: feed ratios even though the animal's genetics have not changed. Therefore, gain: food relationships have never been widely recognized as a criterion for genetic selection. Residual feed intake (RFI), defined as actual feed intake minus the expected feed intake of each animal, was first proposed as an alternative measurement of feed yield by Koch et al. (1963). It can be defined in other words as the difference between the actual food intake and the expected food requirements for maintaining body weight and for weight gain. In contrast to gain: food, intake of residual food is independent of growth and maturity patterns. Therefore, RFI should be a more sensitive and accurate measurement of food utilization, since it is based on energy input and energy requirements.
[0024] [0024] RFI is an individual animal record that takes attempts at feeding into account. Accurate measurements of the daily food consumed should be made as much as the average daily earned. Research has found that there is considerable variation in individual animal feed entries at the same time above and below what is expected or predicted based on size and growth. These findings coupled with the fact that individual animals of the same body weight require vastly different amounts of food for the same level of production instead establish the scientific basis for measuring RFI in beef cattle (Sainz et al., 2004). Reduction of Manure and GHG Emissions.
[0025] [0025] In relation to high RFI cattle, low RFI cattle have been shown to lay off less methane - a potent greenhouse gas (GHG). Scientific evidence indicates that a reduction in methane and manure production can be achieved through a low RFI, which is through a reduction in food intake (Arthur 2009). Animal welfare
[0026] [0026] Animal welfare is a complex aspect that includes important scientific, economic and ethical considerations. This aspect has the potential to impact profitability across the entire cargo and dairy chain if the end result of animal welfare initiatives requires the adoption of different farming practices or processing methods.
[0027] [0027] Early identification of disease, reduced tension in the farm field, behavioral measurement of the animal and an ability to monitor welfare and mitigate adverse conditions for individual animals is an important priority for animal welfare and research. Antimicrobial resistance
[0028] [0028] Current legislation was introduced in March 2009 at the U.S. House of representatives to prevent the use of antibiotics important to human health from being used non-therapeutically in animals. In North America, a ban on the use of antimicrobials for prophylaxis could result in a further increase in the incidence of clinical diseases, reduced performance and increased production costs. The beef cattle feedlot industry has not explored cost-effective alternatives for feed and production for the use of antimicrobials to prevent disease.
[0029] [0029] It is likely that in response to animal welfare and consumer demand that pharmaceutical products will be targeted at individuals who require treatment. Summary of the Invention
[0030] [0030] Therefore, it is an objective of the present invention to overcome the previously mentioned problems and disadvantages associated with the preceding technique. It is another objective to provide a highly automated, unconfined management system and method that allows continuous and selected measurement of the time of entry of animal consumption and behavior, and the determination and monitoring of healthy and sick animals and their performance without disrupting the animal's behavior typical within their usual environments that include the farm, confinement, dairy and / or pasture.
[0031] [0031] Another objective of the present invention is to provide a system that more accurately determines the entry of individual food from animals without errors that are introduced by any change in environmental conditions, in such a way that the system can be used in a greater variety feeding facilities.
[0032] [0032] Another objective of the present invention is to determine more precisely the weight of food within a food trough in both, at the beginning and at the end of an consumption event by an animal.
[0033] [0033] Yet another objective of the present invention is to provide a system that periodically audits and reports the measurement accuracy and performance of the system. Brief Description of Drawings
[0034] [0034] The invention will now be described by way of example with reference to the accompanying drawings, in which:
[0035] [0035] Figure 1 is a perspective view of the system components for identification, measurement, monitoring and management of animals.
[0036] [0036] Figure 2 is a side plan view of a consumption station of the system for identification, measurement, monitoring and management of animals according to figure 1;
[0037] [0037] Figure 3 is a frontal plan view of the consumption station of the system for identification, measurement, monitoring and management of animals according to figure 1;
[0038] [0038] Figure 4 is a graphical illustration of measured weight data collected over a period of time and includes noise caused by a variety of factors;
[0039] [0039] Figure 5 is a graphic illustration of filtered weight data, determined from the weight data measured using the innovative method;
[0040] [0040] Figure 6 is a graphical illustration of the consumption events of four different animals and the corresponding filtered weight data determined from the weight data measured using the innovative method;
[0041] [0041] Figure 7 is a detailed graphic illustration of circled portions VII of the graphic illustrations according to figures 5 and 6;
[0042] [0042] Figure 8 is a table of numerical data graphically illustrated in Figure 7;
[0043] [0043] Figure 9 is another table of data graphically illustrated in Figure 7; and
[0044] [0044] Figure 10 is yet another table of data graphically illustrated in Figure 7. Detailed Description of the Invention
[0045] [0045] Turning now to figure 1, a generic description relating to the various components of the present invention will now be discussed shortly. It generally comprises a consumption station 4 that includes a front panel 6 supported by a base structure 8. The front panel 6 is arranged so as to limit access to the food trough 10 in such a way that only one animal 12 at a time is capable of extend your head through the opening 14 in the front panel 6 and consume food from the food chute 10. As shown in a generic way in figure 1, the base structure 9 supports the front panels 6 and the food chute 10 in relation to the another while maintaining the food trough 10 in such a way that the weight of the food trough 10 can be measured consistently and consistently, and with minimal interference from animals 12.
[0046] [0046] As is conventional in the art, the opening 14 in the front panel 6 is defined by a pair of spaced apart vertical neck bars 16 and a pair of spaced apart horizontal neck bars 18 which are both spaced apart from each other another by a sufficient distance to allow a single animal 12 to extend its head through the opening 14 in the front panel 6 and feed from the respective food trough 10. Preferably the positions of at least one of the horizontal neck bars and / or vertical 16, 18 is adjustable to allow changing the size of opening 14 in the front panel 6 through which an animal 12 can insert its head to access and consume food contained within the food trough 10. Although opening 14 should be sized to allow only one animal 12 at a time to access the food trough 10, opening 14 should also be large enough to provide animal 12 with sufficient access and for, generally speaking, all the food contained within the food trough 10.
[0047] [0047] A rear section 20 of the front panel 6 is fixed to the base structure 8 by means of conventional hardware and in a conventional manner, and the base structure 8 is dimensioned to support a plurality of food troughs arranged in sequence 10. Each trough of food 10 is generally defined by a front wall 22 and an opposite rear wall 24, and a pair of opposite side walls 26, 28. The food troughs 10 are supported on the base structure 8 so that the food troughs 10 are arranged closely adjacent to each other, in series, so as to allow periodic replenishment of food within the food troughs 10 when desired and / or necessary. However, the food troughs 10 should not contact each other, as such contact will interfere with the determination of accurate weight measurement of the food contained within the respective food trough 10.
[0048] [0048] The base structure 8 supports a plurality of load cells 30 which directly support each other of the food troughs 10. and as is conventional in the art, they function as scales. According to the present invention, each of the respective food troughs 10 is supported by at least one load cell 30, for example, each food trough 10 is supported by a load cell located centrally or by means of a pair of opposite load cells 30, or by a load cell 30 that supports each corner of the food trough 10. Due to this configuration, the entire weight of each of the food troughs 10, as well as the food contained in them, is focused and completely supported by the respective load cells 30 to accurately determine the weight of the food contained within the food trough 10. Since the use of the load cells 30 to measure weight is generally known in the art, a further detailed discussion concerning the use of load cells 30 will not be provided here. An important feature of load cells 30 according to the present invention is that they should be configured to continuously monitor and measure the weight of the food trough 10, and transmit such weight measurements to a local collection device. and / or remote, for registration and analysis, as will be discussed in more detail below. The load cells 30 can be arranged in any way with respect to the food trough 10, as long as the weight of the food trough 10 rests on the load cells 30 for accurate measurements.
[0049] [0049] The food trough 10 is dimensioned to maintain a sufficient amount of food for the animal, for example, between 100 and 400 pounds of food, for example. It should be appreciated that the amount of food to be contained within each of the food troughs 10 is generally non-critical, as long as there is a sufficient amount of food to feed an animal 12 during a consumption event. Preferably each food trough 10 is sized to contain enough food to satisfy the food requirements of a number of animals 12 that consume the food for at least a portion of the day.
[0050] [0050] The base structure 8 also supports a control panel 32 that communicates with each of the load cells 30 either wirelessly or through conventional cabling not shown in detail, which is supported by the base structure 8. The weight that the food and associated food trough 10 apply to each of the load cells 30 is measured and transmitted to the control panel 32. Another detailed discussion regarding the collection and subsequent transmission of the measured weights collected by the control panel 32 will be discussed below .
[0051] [0051] The control panel 32 is coupled in order to communicate with a variety of RFID radio frequency identification equipment comprising an RFID antenna 34 which is typically embedded, for example, in a rim of the front wall 24 of the food trough 10 and / or one of the vertical and horizontal bars 16, 18 on the front panel 6. The actual location or placement of the RFID antenna 34 in relation to the associated food chute 10 and the front panel 6 is generally not critical since the RFID antenna 34 be positioned so as to receive only the unique identification signal information (code) of the animal 12 that extends its head through the opening 14 in the respective front panel 6 to consume food from the associated food trough 10, and not receive the signals of unique identification information from any other animal 12 specifically an animal 12 that eats from an adjacent food trough 10. In a similar manner to load cells 30, the antenna RFID 34 also communicates with the control panel 32 to provide current information relating to the unique identification information signal (code) of the animal 12 currently feeding on the associated food trough 10.
[0052] [0052] To facilitate tracking of each animal 12 to be monitored, each of the animals 12 that has access to any of the consumption stations 4 carries an RFID transponder 36 and each transponder 36, and thus each animal 12, is provided with a unique identification code. The RFID 36 transponder is generally located on the animal 12 in the vicinity of the neck, head or ear. As a result of such a configuration, when an animal 12 approaches one of the consumption stations 4 and accesses a food trough 10 extending its head through one of the openings 14 formed in one of the front panels 6, the RFID transponder 36 is brought to proximity sufficiently together with the RFID 34 antenna. Since the RFID 36 transponder is within the detection range of the RFID 34 antenna, for example, within a range of from 2 to 50 inches, for example, the RFID 34 antenna receives the signal (code) of unique identification information that is transmitted by the respective RFID 36 transponder. As noted above, this signal includes a unique code for the RFID transponder number that is associated with the animal 12 currently feeding from the food trough 10, so that the monitoring system of the present invention is able to monitor that consumption event, as well as any other event or activity of that animal 12. Once the signal exclusive is received by the RFID antenna 34, this signal is repeatedly transmitted to the control panel 32, so that each of the associated consumption events will be associated with that respective animal 12. That is, the time and duration that the animal 12 is in the respective food trough 10 it is determined with a reasonable level of precision, for example, the time that the animal 12 first extends its head through the opening 14 in one of the front panels 6 and started to feed from the respective food trough 10, the time that the animal 12 finally removed its head from the opening 14 in one of the front panels 6 and discontinued the feeding from the respective food trough 10 and the entire length of time that the animal's head was in close enough proximity to the respective food trough 10 is determined and recorded.
[0053] [0053] The control panel 32 comprises an electronic signal receiving and transmitting device 38. As discussed briefly above, the control panel 32 is arranged in a conventional manner to communicate with each of the load cells 30 and the RFID antenna. associated 34 for each of the consumption stations 4, in order to receive respective signals from each of those monitoring devices, so that the control panel 32 is informed of the respective animal 12 located in each of the consumption stations 4 , as well as the instant weight of the food contained within the associated food trough 10. The control panel 32 generally also includes a data storage unit (not separately labeled), for temporarily recording and storing the measured and collected weight and unique identification information signals (code) from load cells 30 and RFID antenna 34, as well as the corresponding time this information is collected gives. It is also possible that the control panel 32 may not have any separate data storage unit other than perhaps an internal memory. In this case, the control panel 32 simply collects and then retransmits all the collected weight and unique identification information (code) and time information collected from the load cells 30 and the associated RFID antenna 34 to a remote central processing computer 40 via a conventional transmission mechanism by wireless transmission or through conventional cabling (not shown). If the control panel 32 includes a storage unit (not separately labeled), the collected weight and unique identification information (code) from the load cells 34 and the RFID antenna 34 are temporarily stored for a period of time desired, for example, for a few minutes to possibly a day or more, but this information is eventually transmitted to the central processing computer 40 at some point in the desired time later. For example, the storage unit can collect data for a period of 24 hours and thereafter transmit all collected data to the central processing computer 40 at a selected time, for example, 12:00 am each night for processing and analysis by the central computer 40. Alternatively, the storage unit can collect data for a shorter period of time, for example, 2-8 hours, for example, and thereafter periodically transmit all collected data to the computer. central processing 40, at various times during the day.
[0054] [0054] The basic data that is collected, recorded and processed by the central processing computer 40 includes the total weight of the trough, which includes the food contained therein, as well as the unique identification information (code) of an RFID 36 transponder that is in proximity to the respective front panel 6 associated with the food trough 10 and the current moment. When the processing computer 40 receives this determined and transmitted information, this information is then stored in a suitable memory device, together with the associated time stamp information correlating the precise moment when this information was completed. In accordance with a preferred form of the present invention, system 2 collects and records the measured weight information as well as the unique identification information (code) of an RFID transponder 36 that is in close proximity to the respective front panel 6 associated with the rail of food 10 once every second of the day, so that 86,400 weight measurements are collected for each of the food troughs 10 each day. It should be appreciated that depending on a variety of factors it is possible that more or less data can be collected each day in relation to each of the food troughs 10.
[0055] [0055] By measuring the weight of the food trough every second or more for a period of 24 hours, and storing all this data collected in the main storage device of system 2, it is possible to analyze the weight data at a later point in time , and more precisely to calculate changes in the weight of the food contained within the food trough 10, as discussed in more detail below. An advantage of the methodology discussed here is that system 2 is not limited in determining the weight at a given point in time, but by historical and future data (limited by the future time we choose to calculate this data).
[0056] [0056] Coupling or arranging a plurality of consumption stations 4 together side by side in series with each other, as shown generically in figure 1, a number of animals 12 are capable of consuming food at the same time. This is beneficial for a number of obvious reasons. For example, when feeding a number of animals 12 from a single or a small number of consumption stations 4, the most dominant animals 12 within the group tend to prevent one or more of the less dominant animals 12 from feeding on a desired way. Thus, the number and duration of consumption events of an animal 12 can be affected by the number of consumption stations. The actual number of consumption stations 4 used by the production facility obviously depends on the number of animals 12 to be contained within a containment area, that is, the overall size of the enclosure in a confined area, as well as the number of animals 12 that understands the flock.
[0057] [0057] Despite the number of consumption stations 4 used by the production facility, it must be recognized that each of the consumption stations 4 comprises a completely separate food trough 10, supported by or a separate load cell 30, a set separate from load cells 30 which are completely separate and independent from the load cells 30 used by any of the other consumer stations 4. In addition, the front panel 6 has the corresponding RFID antenna 34 which is also separate and independent from the other RFID antennas 34 which are used by any adjacent consumption station 4, so that system 2 can accurately identify which animal 12 is feeding from which feed troughs 10 at any given point in time. Despite the mechanism used to collect and record the unique identification information (code) of an RFID 36 transponder, the food trough weight information and the current moment, it is critical to correlate the unique identification information (code) with the data current weights that are measured and collected from the specific set of load cells (30), as well as the precise moment that both sets of data or information are being collected and recorded by the system 2.
[0058] [0058] As mentioned above, the data collected and recorded are generically analyzed at some point in the later time, for example, at night or some other convenient time. According to the present invention, analyzing the data may include the use of a weighted filtering technique. Figures 4 and 5 show a sample of the weight data as recorded over the course of approximately a half hour period. Figure 4 shows the data collected and recorded (pre-processed data) that includes the measured weight and the moment at which the measured weight was collected and recorded. Although figure 4 shows the data collected and recorded (pre-processed data) before any filtration technique is applied, figure 5 shows the data collected and recorded (refined or filtered data) after the filtering technique is applied. As shown in figure 4, the pre-processed data includes a number of sharp points, each of which represents either a sharp increase or a sharp decrease in the measured weight of the food trough 10 at some point in time. Such sharp points can result, for example, from an animal 12 by forcing its muzzle, nose and / or mouth into the food contained within the food trough 10. This force temporarily increases the measured weight of the food and the respective food trough. food 10, which is detected by the respective load cells 30. Other erroneous weight measurements can be introduced by feeding the animal 12 fodder that has not been well chopped or otherwise processed. In this situation the pressure of the snout in the food is substantially different from when an animal 12 is consuming corn flakes for example. Fodder creates a "feed weight profile" of very little pressure over very long durations when the animal 12 typically does not remove its food head from the food trough 10 while chewing and consuming the forage. In comparison, steamed corn flakes have a 'feed weight profile' with distinct bites of short duration. The collected and recorded data (pre-processed data) can also be negatively influenced depending on the direction of the pressure. In the case of forage, the animal 12 is able to exert a negative pressure on the food trough 10 when the animal 12 bites and raises a mouth full of forage from the trough 10, since the forage intermingles with itself. Thus, from the collected and recorded data (pre-processed data) (figure 4) it is easily evident that an inaccurate food trough measurement or measured weight can be detected if the measurement is obtained when this additional force is being applied to the trough of food 10. If system 2 is to use pre-processed data such as the measured weight of the food contained within one of the food troughs 10 at the beginning of a consumption event which is typical in the prior art systems, then a inaccurate initial measured weight can be used to determine the amount of food being consumed by an animal 12 during a consumption event. For example, the weight measured in the food trough 10 recorded at the beginning of a consumption event could correspond to a peak of one or several points shown in figure 4. It should be appreciated that the large points illustrated in figure 4 can represent as much as a 2.5 kg change in the measured weight of the food contained within one of the associated food troughs 10 during the course of less than a minute or for example (see figure 4 at approximately 9: 28: 30). Clearly, such a large change in weight measured over such a short span of time is not possible. However, prior art systems could possibly detect and use the wrong information from such a tip as an initial measured weight of food or as a final measured weight of food. This could lead to highly inaccurate and / or unrealistic food consumption rates and is believed to be quite prevalent with the use of currently known management systems. It is possible to conclude, using the known methods of calculating changes in the measured weight of the food trough 10, that during a single consumption event an animal 12 consumed 2.5 kg of food during the time span of just a few minutes, which is highly unlikely and unrealistic. It is also conceivable to determine that an animal 12, during a consumption event, has added food to the food trough 10 which is also highly unlikely. These inaccuracies observed in determining changes in the measured weight of the food contained within the food trough 10 according to the systems of the prior art are overcome in the present invention and discussed in more detail below.
[0059] [0059] Figure 5 shows the same weight regression measured for time as that of figure 4, however the weight data for this regression are more precisely delineated using the innovative method according to the present invention. It is obvious to see that the tips described above or inaccuracies associated with the pre-processed data for the collected and recorded measured weights are removed, in such a way that it is possible to more accurately calculate differences in the weight of the food trough 10 over a desired period of time , and thus more accurately calculate the amount of food actually being consumed by an animal 12 during a consumption event.
[0060] [0060] The weighted filter of the present invention uses statistics such as regression and averaging to calculate weights and / or the resolution of measurements that are dramatically more accurate than those achieved by any of the known techniques, which typically include a “floor of noise ”(a noise floor is generically created by changes in weight caused by environmental conditions).
[0061] [0061] With the innovative method, at specified time intervals, the measured and collected measured weights are filtered with a weighted filter to create precise start and end weights for use in determining food consumption during each recorded consumption event. That is, a consumption event is typically considered to coincide with the amount of time that a specific animal 12 is present in the respective food trough 10, as determined by the receipt of RFID signals that contain the animal's unique identification information (code). The weighted filter comprises a duration factor, a specified amount of time before and after a real moment that the processing computer 40 uses to determine an accurate weight, and a mathematical methodology to describe the most accurate weight that is representative for that length of time, based on the subset of preprocessed data.
[0062] [0062] Typical known methods of improving the accuracy of measured weight data while weight measurements are being collected and recorded, are performed by averaging several samples (weights measured over a length of time). One of the problems encountered while averaging the measured weight of a food trough 10, is that an animal generically applies significant force to a food while making a bite as discussed above. These inaccurate measurements are included when calculating the average measured weight and as such the calculated measured weight of the food is significantly distorted.
[0063] [0063] There are several mathematical methodologies that can be used to eradicate the error. The weighted filter of the invention uses a practical and simple way of limiting inaccurate measured weights, which includes the use of numerous weight measurements. Each set of these measured weights is classified and arranged from the lowest weight value to the highest weight value in a respective system, and then from each system a specific index is used to determine the filtered measured weight. appropriate. Other preferred modalities of the weighted filter may use the process of collecting, selecting and arranging the systems as described above, and then selecting a subset from that system and finally specifying a specific position within the data subset. The measured weight value at this specified position will be the appropriate filtered measured weight. Another preferred modality of the weighted filter includes the process of collecting, selecting and arranging the system as described above, and then eliminating a number of measured weight values in the system and then averaging the rest of the measured weight values, with the value of average measured weight with the measured filtered weight being appropriate. Yet another preferred modality of the weighted filter includes the process of collecting, selecting and arranging the systems as described above, and then averaging the measured weight values in the system and then eliminating all measured weight values that are outside of a deviation. pattern chosen from the mean, after which the remaining system of measured weight values is averaged. Another preferred modality of the weighted filter includes the process of collecting, selecting and arranging the systems as described above, and then selecting and regressing the system subset and then using a specified system index to specify the appropriate measured filtrate weight.
[0064] [0064] To illustrate a preferred way of processing measured weight data, figure 7 shows a graphic illustration of weight measured over approximately a 15 to 20 second time period, as circled in figures 4 and 5 and labeled 7. Although the weight of the food trough 10 is measured continuously, in-line filtering of pre-processed data (measured weights MW) the measured weights MW can be collected and recorded at specific time intervals instead of a continuous basis, as discussed above . For example, the measured MW weights can be recorded every tenth of a second, half a second, or as in the example illustrated below, once every second. In this example illustrated in figure 7, the measured weights MW such as those illustrated graphically in figure 4 are represented by squares that are connected by a solid line. As can be seen in figure 7, the graph of the measured weights MW includes a large tip approximately at the point in time T5 (9:12:09). This tip represents an increase of approximately 0.6 kg in the weight of the food that lasts for less than 2 seconds.
[0065] [0065] The precise filtered weights FW (appropriate filtered measured weight) as processed in this modality taken as an example, such as those illustrated graphically in figure 5, are represented by filled black dots that are connected by a dashed line. As seen in figures 5 and 7, processing the measured MW weights in the manner described here, the unreasonable inaccurate measured weights MW as the measured weight MW at the point in time T5 (9:12:09) in figures 4 and 7, which typically introduce significant errors in the prior art methods, can be eliminated. Figures 8, 9 and 10 include the numerical data represented in Figure 7. The first time column in Figures 8, 9, 10 represents the moments at which the measured MW weights were recorded and stored and includes the points in time (T1-T6 ) in which the weight of the food trough 10 in kg was measured and recorded. The time span as illustrated in this example stretches from approximately 9:12:00 to approximately 9:12:15, thus representing the measured MW weights of the food trough 10 as recorded every second for a period of 15 seconds. The second MW measured weight column in Figures 8, 9, 10 lists the MW measured weights as recorded during the 15 second time interval. The next six columns in each of Figures 8, 9 and 19 only help to demonstrate a process of filtering measured MW weights and determining accurate filtered weights FW and should be seen only as an example of such a process.
[0066] [0066] In this example to determine the accurate filtered weight FW at the point in time T1 (9:12:05), a set 11 of measured MW weights is collected. This set is shown in the third column of figure 8 and includes the measured weights MW that were recorded starting from 5 seconds before the time point T1 to 5 seconds after the time point T1 or, in other words, this set includes the measured weights MW that were recorded during the time span from 9:12:00 to 9:12:10. The third column of figure 8 lists the set of measured MW weights that will be considered in the process to determine the precise filtered weight FW at the point in time T1. Then the set of 11 MW measured weights is arranged in order from the lowest MW measured weight value to the highest MW measured value and listed in the fourth column of figure 8. Finally, the fourth MW value of measured weight the lowest of the ordered set of MW values of measured weight is chosen as the precise filtered weight FW. Thus, the precise filtered weight FW for the time point T1 (9:12:05) is equal to 47,875 kilograms and is shown in the fifth column of figure 8.
[0067] [0067] To determine the precise filtered weight FW at a point in time T2 (9:12:06), another set of eleven measured MW weights is collected. This set includes the measured MW weights that were recorded starting 5 seconds before the T2 time point to 5 seconds after the T2 time point or, in other words, this set includes the MW measured weights that were recorded since 9:12:01 until 9:12:11. The set of measured MW weights considered to determine the precise filtered weight FW at time point T2 are listed in the sixth column of figure 8. Next, the set of eleven measured MW weights is arranged from the value of the measured MW most low to the highest measured weight MW value and listed in the seventh column of figure 8. Finally, the fourth lowest measured weight value MW of the ordered set of MW measured weight MW values is chosen as the precise filtered weight FW. Thus, the precise filtered weight FW for the time point T2 9:12:06 is equal to 47,875 kg and is shown in the eighth column of figure 8.
[0068] [0068] In the manner described above with respect to the points at time T1 and T2, to determine the precise filtered weight FW at the point in time T3 9:12: 07, a set of eleven measured weights MW was collected again. This set includes the measured MW weights that were recorded starting 5 seconds before the T3 time point to 5 seconds after the T3 time point or, in other words, this set includes the MW measured weights that were recorded since 9:12:02 until 9:12:12. The set of measured MW weights considered to determine the accurate filtered weight FW at time point T3 is listed in the third column of figure 9. Then the set of eleven measured MW weights is arranged from the lowest measured MW value to the MW measured weight value the highest and listed in the fourth column of figure 9. Finally, the lowest MW measured value of the ordered set of MW measured weight values is chosen as the precise filtered weight FW. Thus, the precise filtered weight FW for the T3 9:12: 07 time point is 47,875 kg and is shown in the fifth column of figure 9.
[0069] [0069] To determine the precise filtered weight FW at a point in time T4 9:12:08, a set of eleven measured MW weights is collected again. This set includes the measured MW weights that were recorded starting 5 seconds before the T4 time point to 5 seconds after the T4 time point, or in other words, this set includes the MW measured weights that were recorded since 9:12:03 until 9:12:13. The set of measured weights MW considered to determine the precise filtered weight FW at the point in time T4 is listed in the sixth column of figure 9. Then the set of 11 measured weights MW w is arranged from the value of the lowest measured weight MW up to the highest measured MW weight value and listed in the seventh column of figure 9. Finally, the lowest lowest MW measured value of the ordered set of MW measured weight values is chosen as the accurate filtered weight FW. Thus, the precise filtered weight FW for the time point T4 9:12:08 is equal to 47.80 kg and is listed in the eighth column of figure 9.
[0070] [0070] The precise filtered weights FW at points in time T5 and T6 are determined in the manner as described above with respect to points in time T1, T2, T3 and T4 and for the sake of brevity the same will not be discussed further. However, the MW measured weight sets, the ordered list of MW measured weight values from low to high and the corresponding accurate filtered weights FW can be seen in the columns in figure 10. To summarize, the precise filtered weight FW for the time point T5 9:12:09 is equal to 47.80 kg and likewise an accurate filtered weight FW for the time point T6 9:12:10 is equal to 47.80 kg.
[0071] [0071] The precise filtered weights FW from each of the points in time T1-T6 are graphically illustrated in figure 7 by the filled black dots that are connected by a dashed line. As indicated above, figure 5 is a graphical illustration of the accurate filtered weights FW over an approximate period of time of 30 minutes. By filtering the measured MW weights and determining and plotting the precise filtered weights FW the trough weights can be clearly illustrated without the inaccuracies often associated with such data in known methods.
[0072] [0072] Other mathematical formulas that include rewrites, minimums, maximums, standard deviations plus the minimum, can also be used to obtain the most accurate weighted filter.
[0073] [0073] As discussed above, the basic purpose of the weighted filter is to filter or remove inaccurate abnormal weight measurements such as measurement recorded at a time when a force is being applied to the food trough 10, such as when animal 12 pushes its snout for food, to consume food. The type of food being consumed (for example, fodder, silage, water or minerals, for example) and environmental conditions (for example, wind, rain or unit, for example) can also have an influence on which weighted filter will be the most appropriate and will work best.
[0074] [0074] The methodology used to determine which weighted filter to use with the method is an interactive process that applies a number of different weighted filters and compares the outputs of these weighted filters against the sum of all feeding events and the total amount of food supplied for a pre-set time interval, as well as the amount of food that appears or disappears when no transponder 36 is being read (the intermediate feed interval information). The accuracy for selecting the best suitable weighted filter is also dependent on the speed of the processing computer 40, the time interval (typically a 24 hour time period) and the amount of time available for the processing computer 40 to perform desired calculations .
[0075] [0075] Numerous factors must be considered when selecting which weighted filter to use with the method. Some of these are the desired extent and accuracy of the determined weight measurement and the allowable length of time to calculate the desired weight measurement. For example, increasing the length of time from which the sample is derived provides a more accurate filtered weight measurement, however, it also increases the amount of time taken by the computer to calculate the final weight measurement. That is, this reduces the responsiveness of the weighing device. On the other hand, decreasing the time frame from which the sample is derived, provides a less accurate filtered weight measurement, however this also decreases the amount of time taken to calculate the accurate filtered weight measurement. That is, it reduces the ability to minimize error by introducing factors such as influences from the animal and / or wind.
[0076] [0076] The typical field in which RFID transponder 36 can be read is shown diagrammatically in figure 2 as a shaded area or region 42 and is typically known as a transponder reading area. Since the transponder reading area may possibly also extend to an adjacent food trough 10, there is a possibility that the RFID transponder 36 of an animal 12 can be read intentionally by the RFID antenna 34 associated with the adjacent food trough 10 in addition to being read by the RFID antenna 34 of the food trough 10 from which the animal 12 is consuming food. However, this typically does not occur when there is an animal 12 consuming food from the adjacent chute, since the RFID transponder 36 of the animal 12 that is consuming food will drown out the RFID transponder signal from animal 12 in the adjacent food chute 10, due to the remote signals being generally weaker.
[0077] [0077] To greatly reduce, if not eliminate, the occurrence of such incorrect detection, system 2 of the invention uses a specified time frame, (typically a period of time when transponder 36 has been read on a fairly consistent basis), and the location of the consumption event for all RFID observations.
[0078] [0078] Since RFID 36 transponders are typically position sensitive, such that the reading range can be dramatically reduced if the RFID 36 transponder is located in a minimally favorable position, it should take more than a few seconds before the RFID tag or signal is actually read by the system 2. Occasionally the first measured weight data collected and recorded by the control panel 32 coincides with the animal 12 that is putting its muzzle on the food and applying force on the load cells 30 that support the associated food trough 10. Therefore, using the measured weight collected by system 2 at the point in time when RFID 36 transponder is actually read as a starting weight for the consumption event can, in some cases, severely compromise the data. To reduce the effect of such occurrences, the method of the present invention uses the precise filtered weight FW which was determined by the weighted filter at a point in time between the last registration of a previous animal 12 and the first RFID signal of registration of the new animal 12 as the final weight for the previous animal 12 and the starting weight for the new animal 12 that can be used to calculate the amount of food consumed by the animals 12.
[0079] [0079] However, a possible disadvantage regarding this methodology is that the possible disappearance of any food (such as food that is possibly consumed by birds or rodents) from the food trough 10, between the time when the previous animal 12 left the food trough 10 and the moment when a new animal 12 arrived at the food trough 10, it should be considered in some way. Assuming that the error is relatively small, the present invention proposes to use the precise filtered weight FW as calculated by the filtering technique described earlier at a point in time that is halfway between the last RFID record of the previous animal 12 and the first RFID record of the new animal 12. However, it should be appreciated that the use of this method is not without problems, since it is possible that one or more animals 12 inside the corral have either lost their RFID 36 transponder or have an RFID 36 transponder that is defective or is not operating properly.
[0080] [0080] To compensate for this potential problem, system 2 according to the invention calculates a weight difference between the precise filtered weight FW of the food trough 10 including the food at the exact point in time when the previous animal 12 left the respective food trough 10, and the precise filtered weight FW of food trough 10 including the food at the exact point in time when the new animal 12 arrived at food trough 10. If this weight difference exceeds a certain threshold, system 2 will admit that the missing food was consumed by a rodent, a bird and / or an animal, with a lost or malfunctioning RFID 36 transponder, and thus use both these precise FW filtered weights as the subsequent start and end weights of the respective consumption event. The threshold amounts of the weight difference preferably range from approximately 250 to approximately 750 g, more preferably between approximately 400 to approximately 600 g, and more preferably 500 g.
[0081] [0081] When determining precise start and end weights for a consumption event, system 2 performs a verification and auditing procedure. This procedure considers food that is “either removed from” or possibly supplied to the chute between recorded consumption events. The disappearance of or the appearance of any food in the food trough 10 is recognized by changes in the precise filtered weight FW of the food trough 10 including the food, while no animal 12 is detected as being present in, and feeding from, the food trough. food 10. As previously discussed, these weight changes can be caused by any number of factors such as changes in environmental conditions such as wind or humidity, the consumption of food by a rodent, a bird and / or an animal, with an RFID transponder 36 lost or malfunctioning. Unlike data inaccuracies introduced when animal 12 places its muzzle on food and is typically seen graphically as sharp points in measured weight regressions, such as those discussed above and seen in Figure 4, weight changes caused by factors such as changes in Environmental conditions can be seen in the graphical illustration of the filtered data as decreases in the weight of the food between consumption events (figure 6).
[0082] [0082] The verification and auditing procedure includes consideration of missing food accounted for which is in the inverse relationship between the sum of all unaccounted food missing divided by all accounted food missing is expressed as a percentage. The present invention adds up all the disappearance of unaccounted food (the disappearance of food that was above a certain weight value between the previous animal 12 that leaves or leaves the food trough 10 and the appearance of the new animal 12 in the food trough 10) and divides this sum by a sum of disappearance of food counted from all consumption events. This number is expressed as a percentage and recorded as the disappearance of unaccounted-for food.
[0083] [0083] Another consideration in the verification and auditing procedure is provided for the supply of accounted food, that is, the inverse relationship between the sum of all unaccounted food appearance / / all accounted food disappearance, also expressed as a percentage.
[0084] [0084] Providing consideration for impromptu food and fraudulent management, system 2 records the length of time that trough 10 has been empty during the day and how much food has been left at trough 10 each day.
[0085] [0085] To confirm whether or not the innovative system 10 is operating properly throughout the day, an audit routine calculates the ratio of the number of weight measurements collected and recorded during a given period of time divided by the number of measurements weight that should have been collected and recorded during that same period of time. For example, if weight measurements were collected and recorded once every second, this should result in a total of 86,400 measurements being collected and recorded over the course of a 24 hour time period. Thus, the result of this calculation for a system 2 working properly is 1, for example, 86,400 weight measurements / 86,400 weight measurements, and a result of less than 1 should indicate a system working improperly.
[0086] [0086] System 2 according to the present invention, is able to determine if too much food has been placed in the gutter 10. Excess food placed in the gutter 10 can spill over the ground, or it can be consumed by animals without the animals 12 putting their heads through opening 10. According to this determination, system 2 records a percentage of the day that the trough was superseded with food, adding the amount of time that the weight of the trough was above a certain limit. This limit is variable depending on the type of food placed in the trough 12 and is determined considering the specific weight of the food and the size and capacity of the food trough 10.
[0087] [0087] It is possible to confirm that RFID 36 transponders are being read correctly by system 2. To verify that RFID 36 transponders are being read properly, system 2 calculates the RFID reading ratio collected and recorded by consumption event for each food trough 10. A consumption event can be determined by passing a certain amount of time from a previous consumption event, without the presence of any animal 12 in the food trough 10. Typically if animals 12 are absent from the food trough 10 for a period of time typically in the range of 500 seconds to 100 seconds or approximately 300 seconds, it could be determined that a consumption event has ended.
[0088] [0088] Figure 6 shows a graphical illustration of the weight of the food trough including the weight of the food, as determined with the mathematical weighted filter technique, over a period of time as described above. Four different symbols, that is, circles, squares, crosses and triangles are outlined in this figure and each symbol represents a distinct animal 12 as identified by the animal's unique RFID 36 transponder. Each grouping of the different symbols over a period of time is indicative of the length of time that the animal 12 was feeding on the respective food trough 10 or, in other words, represents the duration of the consumption event for that specific animal 12. For example , the time period from time point B to F represents a consumption of an animal 12 identified by squares, and the time period from time point G to D represents a consumption of the next animal 12 identified by crosses. The graph in figure 6 illustrates four different consumption events of varying time durations. As would be expected, the weight of the food trough 10, specifically the food contained within the food trough 10, noticeably decreases during each of the four consumption events.
[0089] [0089] Between each of the consumption events there is a duration of time where the system 2 does not detect any animal 12 as feeding in the respective food trough 10 (no unique identification information (code) is being read and, therefore, none food is presumably being consumed during such a period of time. Due to the absence of animals 12 during these periods of time, one could normally expect the weight of the food trough 10 to be substantially constant, however, as shown in figure 6, weight measurements may vary somewhat due to the fact that the unique identification information (code) of an RFID 36 transponder could not be read immediately due to the position that the RFID 36 transponder is not favorable for transmitting the unique identification information (code ) for the RFID antenna 34. As noted earlier, there are a number of reasons why the measured weight of food within a food trough 10 may change air, even though the amount of food contained within the trough 10 actually remains the same. As briefly discussed above, when food and / or food trough 10 are exposed or subjected to changes in environmental conditions, for example, it is common for these changes in time or environmental conditions to change the actual measured weight of the food contained within the trough of food 10. For example, if the food was relatively dry when initially loaded into the food trough 10 and the relative humidity for the surrounding environment was relatively low, and the relative humidity in the area of the trough 10 gradually increases over the course of the day, it is quite possible that the actual weight of the food contained within the food troughs 10 will gradually increase when the normally dry food absorbs moisture. In addition, if precipitation were to fall into the trough during the course of the day, the weight of the food contained within the food trough 10 should also appear to increase. In addition, the inventors have observed that exposure of the food trough 10 to wind, for example, can affect the weight of the food trough 10. Wind has been observed to change the determined weight of the food trough 10 by up to a pound or so, for example . As a result, the wind can easily cause the weight of the food trough 10 including the food, or increase or decrease, depending on the wind speed and / or the direction of the wind acting on the food trough 10 being measured. .
[0090] [0090] Due to the possibility of changes in the measured weight of the food trough 10 occurring between consumption events, the innovative method for accurately measuring the weight of food consumed during a consumption event also includes a procedure to compensate for such environmental effects. This procedure is discussed below in relation to three different scenarios between four consumption events as shown in figure 6. For points in time and weights taken as an example they are used below to help further illustrate the three scenarios. It should be understood that points in time and weight are purely for illustrative purposes only, and do not represent actual points or weights.
[0091] [0091] Scenario 1 illustrates a change in weight between a first consumption event as indicated by the presence of a first animal 12 indicated by the circles, and a second consumption event as indicated by the presence of a second animal 12 indicated by the squares. The time difference between the first and second consumption events, that is, the time interval between the point in time A (the last detected reading of the RFID transponder 36 of the first animal 12) and the point in time B (the first reading detected from the transponder 36 of the second animal 12) is identified as the time difference AB. The difference in the weight of the food trough 10 at the time point A and the time point B is identified as the weight difference AB '. In this scenario the AB time difference is said to be less than an adjusted time limit value X, which could be in the range of 2,400 seconds to 1,200 seconds, or it should preferably be approximately 1,800 seconds for example, and the weight difference AB` it is said to be less than an adjusted weight limit value Y which could be in the range of 1,000 g to 100 g or could preferably be approximately 500 g. In this way, the selected weight that should be considered when calculating the weight of food consumed in the first and second consumption events or, in other words, the selected weight as the final weight of the first consumption event and the selected weight as the starting weight of the second consumption event is the weight of the trough at the point in time C, which is the point in time that is half the time difference AB.
[0092] [0092] To help further illustrate the above, the first consumption event will be considered to have ended at 12:00:00 (time point A) and the second consumption event will be considered to have started at 12:02: 00 ( point in time B), so the time difference AB in this example is 120 seconds. According to scenario 1, since the AB time difference and the AB weight difference are each smaller than the respective adjusted time and weight limit value`, the weight selected as the final weight of the first event consumption and the initial weight of the second consumption event is the weight at 12:01:00 (point in time C).
[0093] [0093] Scenario 2 illustrates a change in weight between a third consumption event as indicated by the presence of a third animal 12 indicated by crosses and a fourth consumption event as indicated by the presence of a fourth animal 12 indicated by triangles. The time difference between the third and fourth consumption events, that is, the time interval between the point in time D (the last detected reading from RFID transponder 36 of the third animal 12) and the point in time E (the first detected reading of RFID transponder 36 from fourth animal 12) is identified as the DE time difference. In this scenario the DE time difference is greater than an adjusted time limit value X that could be 1,800 seconds, for example. Due to the length of time between the third and fourth consumption events, there is an increased likelihood that due to changes in environmental conditions, such as a relatively significant change in temperature or change in the level of humidity, the food has either dried or absorbed. humidity, which can have a measurable influence on the weight of the food detected by the instrumentation. In view of this possibility, the final selected weight that should be considered when calculating the weight of food consumed during the third consumption event is the weight at the time of the last RFID reading of the third animal 12, that is, the point in time D. selected starting weight that should be considered when calculating the weight of food consumed during the fourth consumption event is the weight at the time of the first RFID reading for the fourth animal 12, that is, at the point in time E. Any weight difference between these two points in time D, E are referred to above as an unaccounted food disappearance.
[0094] [0094] To help further illustrate scenario 2, the third consumption event will be considered to have ended at 12:30:00 (time point D) and the weight of food at that time is considered to be 4,700 g. The fourth consumption event will be considered to have started at 1:05:00 (time point E) and the weight of food at that time is considered to be 4,500 g, so the DE time difference is 2100 seconds. According to scenario 2, since the time difference DE is greater than the adjusted time limit X, the weight selected as the final weight of the third consumption event is the weight of food at 12:30:00 ( point in time D) which is 4,700 g. The weight selected as the starting weight for the fourth consumption event is the food weight at 1:05:00 (point in time E) which is 4,500 g. In addition, in this example there should be a 200 g unaccounted food disappearance.
[0095] [0095] Scenario 3 illustrates a change in weight between the second consumption event as indicated by the presence of the second animal 12 indicated by squares, and a third consumption event as indicated by the presence of the third animal 12 indicated by crosses. The time difference between the second and third consumption events, that is, the time between the point in time F (which is the last detected reading of the RFID transponder 36 of the second animal 12) and the point in time G ( which is the first detected reading of the RFID transponder 36 of the third animal 12) and is identified with the FG time difference. The difference in weight of the food trough 10 between the time point F and the time point G is the weight difference FG´. In this scenario the FG time difference is less than an adjusted time limit value X that could be 1,800 seconds for example, however, the FG´ weight difference is greater than an adjusted weight limit value Y that could be 500 g , for example. The great difference in the weight of FG´ food between the second and third consumption events is indicative of the amount of food that was consumed by one or more rodents, birds and / or animals 12 with the loss or malfunction of the RFID transponder 36. In this scenario, the final selected weight that should be considered when calculating the weight of food consumed during the second consumption event is the weight at the time of the last RFID reading of the second animal 12, that is, at the point in time F. The starting weight selected that should be considered when calculating the weight of food consumed during the third consumption event is the weight at the time of the first RFID reading for the third animal 12, that is, at the point in time E. The FG´ weight difference is described above as an unaccounted for food disappearance.
[0096] [0096] To help better illustrate scenario 3, the second consumption event will be considered to have ended at 12:10:00 (point in time F) and the weight of food at that time is considered to be 6,000 g. The fourth consumption event will be considered to have started at 12:15:00 (point in time G) and the weight of food at that time is considered to be 5,400 g, so the time difference FG is 300 seconds and the weight difference FG ´ is 600 g. According to scenario 3, since the FG´ weight difference is greater than the adjusted weight limit value Y the weight selected as the final weight of the second consumption event is the food weight at 12:10:00 (point in time F) which is 6,000 g. The weight selected as the starting weight for the third consumption event is the food weight at 12:15:00 (time point G) which is 5,400 g. Also, in the example, the disappearance of 600 g food would not be accounted for.
[0097] [0097] Although calculating the weight of food consumed by an animal during a consumption event is known and relatively simple, it will be described for one of the consumption events in relation to the above scenarios. Generally, to calculate the weight of food consumed during a consumption event, the weight of food at the end of the consumption event (final weight) is subtracted from the weight of the food at the beginning of the consumption event (initial weight). In this way, using the weights given in the scenarios above as examples, the weight of food consumed by the third animal 12 indicated by crosses during the third consumption event is calculated by subtracting the weight of the food at time point D (4,700 g) from the weight of the food at time point G (5,400 g), that is, the weight of food consumed by the third animal 12 indicated by crosses during the third consumption event is equal to 700 g.
[0098] [0098] The moments and weights used in these examples to determine the durations of consumption events and the quantities of food or consumed or not counted, are specified for illustrative purposes only, and should not be considered to limit real times and weights used to determine durations of consumption events and the quantities of food consumed or not counted. The duration of consumption events and the length of time between consumption events, as well as the quantities of food consumed or not counted, should depend on numerous factors such as the type of animals that consume the food, the number of animals that can share the food. food, the number of food troughs available to the animals, to name a few.
[0099] [0099] Since certain changes can be made in the improved system and method described above, without departing from the scope of the invention involved here, it is projected that all the matter of the description above or shown in the accompanying drawings, should be interpreted simply as examples that illustrate, here, the inventive concept, and should not be imagined as limiting the invention.

权利要求:
Claims (23)
[0001]
Method of automated acquisition of animal consumption data characterized by the fact that it uses a system (2) that comprises a plurality of separate consumption stations (4), and each of the plurality of separate consumption stations (4) allowing consumption of food by only a single animal (12) at a time and each separate consumption station (4) comprising a unique consumption station identification and a respective feeding trough (10) to contain a desired amount of food, respective weighing device of food (30), to weigh the food contained within the respective food trough (10) and a respective radiofrequency identification detection antenna to detect identification data of the animal (12) consuming food at the respective consumption station (4) and system (2) still comprising at least one control panel (32) coupled to each of the respective radio frequency identification detection antennas, and to each of the the respective weighing devices (30) to receive data from them, and at least one control panel (32) that is coupled to a processing computer (40) to process the received data, the method comprising the steps of: periodically transmitting food weight measurement data from each of the respective food weighing devices (30) to the processing computer (40); periodically transmit to the processing computer (40) through the respective radio frequency identification detection antenna the respective identification of the consumption station and the animal identification data (12) of any animal located in the respective consumption station (4); collect and store food weight measurement data, animal identification data and consumption station identification data (4) together with timekeeping information, which indicates when each weight measurement data, animal identification data and the identification data of the consumption station (4) were collected; after collecting and storing the data, processing the stored food weight and time measurement data, the animal identification data and the identification data of the consumption station (4) for each of the respective consumption stations to determine each feeding event; for each given feed event average the food weight measurement data at a time when the given feed event starts, food weight measurement data before the given feed event started and weight measurement data from food after the determined feeding event has started, to calculate an initial weight of the food contained within the respective feeding chute (10) at the beginning of the determined feeding event; compile food weight measurement data at a time when the given feed event ends, food weight measurement data before the given feed event ended and food weight measurement data after the given feed event ended , to calculate a final weight of the food contained within the respective feeding chute (10) after the end of the determined feeding event and determine the amount of food consumed by each animal (12) during each determined feeding event by subtracting the initial weight of the food contained within the respective feeding chute (10) at the beginning of the feeding event determined from the final weight of the food contained within of the respective feed chute (10) after the end of the determined feed event.
[0002]
Method according to claim 1, characterized by the fact that it still comprises the step of periodically transmitting weight measurement data from each of the separate weighing devices (30) and identification data from each of the measuring antennas. separate detection modes, a plurality of times per minute.
[0003]
Method according to claim 2, characterized by the fact that it still comprises the step of periodically transmitting weight measurement data from each of the separate weighing devices (30) and identification data from each of the measuring antennas. detecting detectors once every second.
[0004]
Method according to claim 1, characterized by the fact that it still comprises the step of determining the amount of food consumed by each animal (12) during each determined feeding event, calculating the initial food weight and the final food weight of each feeding event determined using a weighted mathematical filter comprising a set of food weight measurement values.
[0005]
Method according to claim 4, characterized by the fact that it still comprises the step of arranging the set of food weight measurement values from the lowest value to the highest value and selecting a desired one from the arranged set of values measurement of food weight as a starting weight of the food or as the final weight of the food.
[0006]
Method according to claim 5, characterized by the fact that it still comprises the step of defining the final food weight of a first consumption event as the initial food weight of a second consumption event, if a range of the plurality of measurements of weight measured after the first consumption event and before the second consumption event is less than a threshold value.
[0007]
Method according to claim 1, characterized by the fact that it still comprises the step of using a value between 250 g to 750 g as the threshold value.
[0008]
Method according to claim 1, characterized by the fact that it still comprises the step of carrying out an audit procedure that takes into account any disappearance of food that is in an inverse relationship between a sum of all unaccounted food disappearances divided by all the disappearances of fed accounted for, expressed as a percentage.
[0009]
Method according to claim 1, characterized by the fact that it still comprises the step of performing an audit routine that calculates a ratio of a number of weight measurements calculated and recorded over a period of time divided by a number of weight measurements that should have been collected and recorded over the same period of time to determine that the method is working properly.
[0010]
Method according to claim 1, characterized by the fact that it still comprises the step of compensating for environmental effects by determining a time limit value between a moment of a first finished consumption event and a moment of a second started consumption event and if the time limit value is less than a threshold value of between 2,400 seconds to 1,200 seconds and select the final food weight of the first consumption and the initial food weight of the second consumption to be the same weight value and a weight value of fed between the moment the first consumer event ended and the moment the second consumer event started.
[0011]
Method according to claim 1, characterized by the fact that it still comprises the step of compensating for environmental effects by determining a time limit value between a moment of a first finished consumption event and a moment of a second started consumption event and if the time limit value is greater than a threshold value of between 2,400 seconds to 1,200 seconds, and to determine any difference in weight between the time of the first finished consumption event and the time of the second consumption event started as the disappearance of unaccounted food.
[0012]
Method according to claim 1, characterized by the fact that it still comprises the step of compensating for environmental effects to determine a time limit value between a moment of a first finished consumption event and a moment of a second started consumption event and if the time limit value is less than a time threshold value of between 2,400 seconds to 1,200 seconds and if a weight difference between the final food weight at the end of the first consumption event is an initial food weight at the beginning of the second consumption event is greater than a weight threshold value then determine the difference in weight as disappearance of unaccounted food.
[0013]
Method according to claim 1, characterized by the fact that it still comprises the step of connecting a plurality of radio frequency identification antennas to only a single radio frequency identification reader.
[0014]
Method for automatically acquiring animal consumption and behavior data characterized by the fact that it uses a system (2) that comprises at least one consumption station (4) in which consumables are temporarily stored for feeding to an animal (12 ), at least one consumer station (4) being equipped with the respective radio frequency identification equipment is a respective weighing device (30), the method comprising the steps of: measuring a weight of the consumables contained within the respective feed chute (10) of the consumption station (4); reading identification data from a radio frequency identification tag (36) associated with the animal (12) with the radio frequency identification equipment when the animal (12) is located in close proximity to the weighing device (30); couple the radio frequency identification equipment and the weighing device (30) to a computer (40) and transfer the measurement of the weight data from the weighing devices (30) and the identification data from the weight identification equipment radio frequency to the computer with time information; calculate, with the computer (40), an initial weight of the consumables at a time when a consumption event started by averaging the weight data marked with time at the time the consumption event started with the weight data marked with time , both, before and after the moment when the consumption event started; calculate, with the computer (40), a final weight of the consumables at a time when a consumption event ended by averaging the weight data marked with time at the time the consumption event ended with the weight data marked with time , both, before and after the moment when the consumption event ended; determine the amount of consumables consumed by each animal (12) during each determined consumption event, subtracting the initial weight of the consumables at the time the consumption event started from the final weight of the consumables at the time the consumption event ended.
[0015]
Method according to claim 14, characterized by the fact that it still comprises the step of connecting a plurality of radio frequency identification antennas to a radio frequency identification reader.
[0016]
Method according to claim 14, characterized by the fact that it still comprises the step of auditing, with a computer (40), the accuracy of the consumable weight measurements by calculating a total amount of material being added divided by a sum of all feeding events for a certain period of time.
[0017]
Method according to claim 16, characterized by the fact that it still comprises the step of calculating, with the computer (40), an ideal time base filter to use as the weighted mathematical filter technique for the certain period of time iterating over a base time to find a correct range for the disappearance of consumables.
[0018]
Method according to claim 14, characterized by the fact that it still comprises the step of calculating a consumable input during an observed feeding event by determining an initial consumable weight at the beginning of the observed feeding event by taking a filtered weight of the consumables in a first point in time halfway between the end of a preceding feed event and the start of the observed feed event and determining a final weight of the observed feed event by taking the filtered weight of the consumables at a second point in time midway between the first reading of an upcoming feeding event and a moment of the last reading of the observed feeding event; and validate the filtered weight of the consumables at the first and second points in time by taking the filtered weight of the consumables at the end of the previous feeding event and subtracting this from the filtered trough weight of the consumables at the beginning of the observed feeding event and when the value exceeds a quantity predetermined, the filtered weight of the consumables at the beginning of the observed feed event is used as an initial weight of the observed feed event to be measured.
[0019]
Method according to claim 16, characterized by the fact that it still comprises the step of calculating, with the computer (40), individual animal daily consumption (12) and dividing this for behavioral time events such as feeding frequency and duration and location of these feeding events and further dividing these feeding events into classes of behavioral events such as inverted duration and grazing frequency.
[0020]
Method according to claim 16, characterized by the fact that it still comprises the step of determining, with the computer (40), from the weight data and the identification data of at least one of an animal (12) that feeds first after feeding, an animal (12) that is moved from a feeding station during a feeding event, an animal (12) that takes precedence, a feeding speed during a feeding event, a bite size, a amount of pressure exerted on the feed chute (10) when taking a bite, duration of pressure exerted while taking a bite, frequency of bite removal during a feeding event, frequency patterns, pressure duration, inlet behavior and competitive.
[0021]
Method according to claim 16, characterized by the fact that it still comprises the step of automatically calculating a quantity of consumables supplied for each feeding station at a time when the feeding station was supplied with consumables.
[0022]
Method according to claim 16, characterized by the fact that it still comprises the step of automatically auditing the collected weight data by calculating a difference in the total quantity of consumables supplied minus a sum of all feeding events on a percentage basis and calculating a sum total of all consumable appearances or disappearances between the feed events on a percentage basis of the total quantity of consumables supplied and referring to the percentage as the counted feed disappearance.
[0023]
Method according to claim 16, characterized by the fact that it still comprises the step of automatically carrying out, with the computer (40), statistical process control on collected radio frequency identification samples, a resonant voltage of radio frequency identification antenna and a number of weight samples collected.

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同族专利:

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公开号 | 公开日

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BR112013008147A2|2016-08-09|

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CA2813361A1|2012-04-12|

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US20120089340A1|2012-04-12|

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WO2012046124A1|2012-04-12|

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CA2813361C|2016-05-10|

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US8930148B2|2015-01-06|

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法律状态:
2018-12-26| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|

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2020-10-27| B06A| Notification to applicant to reply to the report for non-patentability or inadequacy of the application [chapter 6.1 patent gazette]|

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2021-01-12| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|

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2021-03-23| B16A| Patent or certificate of addition of invention granted|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 05/10/2011, OBSERVADAS AS CONDICOES LEGAIS. |

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