US20210407018A1 - Farm-sensing system and calibration method of sensor data thereof - Google Patents
Farm-sensing system and calibration method of sensor data thereof Download PDFInfo
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- US20210407018A1 US20210407018A1 US17/113,704 US202017113704A US2021407018A1 US 20210407018 A1 US20210407018 A1 US 20210407018A1 US 202017113704 A US202017113704 A US 202017113704A US 2021407018 A1 US2021407018 A1 US 2021407018A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Mining
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D18/00—Testing or calibrating apparatus or arrangements provided for in groups G01D1/00 - G01D15/00
- G01D18/008—Testing or calibrating apparatus or arrangements provided for in groups G01D1/00 - G01D15/00 with calibration coefficients stored in memory
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
Abstract
A farm sensing system is provided. The farm sensing system includes a cloud server, a sensing apparatus, and a computer device. The sensing apparatus is configured to be connected to a specific sensor disposed on a farm. The computer device is configured to obtain specific sensor data generated by the specific sensor through the cloud server. In response to there being potential failure of the specific sensor, the sensing apparatus enters a sensor-calibration mode. In response to a reference sensor being connected to the sensing apparatus, the sensing apparatus builds a calibration table by periodically receiving specific sensor data and reference sensor data, and executes a finite-state machine to perform a calibration procedure on each entry in the calibration table. In response to the number of consecutive hits of the one-to-one correspondence in a specific entry in the calibration table reaching a predetermined number N, the finite-state machine stops the calibration procedure and determines that the specific entry is calibratable.
Description
- This application claims priority of Taiwan Patent Application No. 109121973, filed on Jun. 30, 2020, the entirety of which is incorporated by reference herein.
- The present invention relates in general to sensor apparatuses, and, in particular, to a farm-sensing system and a calibration method of sensor data thereof.
- For various applications of the Internet of Things (IoT), different types of sensors will be widely installed where needed. Because many smart applications of the Internet of Things often cause inaccurate sensor data due to failure, aging or interference of the installed sensor, sensor calibration is a very important issue, especially in applications for setting sensors outdoors, such as smart agriculture. Because the application of smart agriculture requires many different types of sensors to be installed on a farm (including in outdoor environments), if some of these sensors fails or ages, and the resulting sensor data is inaccurate, resulting in inappropriate local spraying of water, pesticides or fertilizers on the farm and thus causing agricultural damage.
- Therefore, there is need for a farm-sensing system and a calibration method of sensor data thereof to solve the above problems.
- In an exemplary embodiment, a farm sensing system is provided. The farm sensing system includes a cloud server, a sensing apparatus, and a computer device. The sensing apparatus is connected to a specific sensor disposed in a farm, wherein the specific sensor is configured to detect environmental information about the farm to generate corresponding specific sensor data. The computer device is configured to obtain the specific sensor data generated by the specific sensor from the sensing apparatus through the cloud server. In response to the computer device determining that there is potential failure of the specific sensor according to the specific sensor data, the computer device transmits a calibration command to the sensing apparatus through the cloud server to control the sensing apparatus to enter a sensor-calibration mode. In response to a reference sensor of the same type as the specific sensor being connected to the sensing apparatus, the sensing apparatus establishing a calibration table by continuously and periodically receiving the specific sensor data and reference sensor data respectively from the specific sensor and the reference sensor, wherein each entry in the calibration table records one-to-one correspondence between the specific sensor data and the reference sensor data. The sensing apparatus executes a finite-state machine to perform a calibration procedure on each entry in the calibration table, wherein in response to the number of consecutive hits of the one-to-one correspondence between the specific sensor data and reference sensor data stored in a specific entry in the calibration table reaching a predetermined number N, the finite-state machine stops the calibration procedure of the specific entry and determines that the specific entry is calibratable.
- In some embodiments, in response to a number of consecutive misses of the one-to-one correspondence between the specific sensor data and reference sensor data stored in the specific entry in the calibration table reaching the predetermined number N, the finite-state machine stops the calibration procedure of the specific entry and determines that the specific entry is not calibratable. In some embodiments, the predetermined number N is equal to 2.
- In some embodiments, when the finite-state machine determines that the specific entry is not calibratable, the sensing apparatus determines that the specific sensor has failed and transmits a sensor-failure message to the computer device to notify, a farm administrator to replace the specific sensor.
- In some embodiments, when the sensing apparatus determines that each entry in the calibration table is calibratable, the sensing apparatus calibrates the specific sensor data generated by the specific sensor using the calibration table, and transmits the calibrated specific sensor data to the computer device through the cloud server.
- In another exemplary embodiment, a calibration method of sensor data, for use in a farm sensing system is provided. The farm sensing system includes: a cloud server, a sensing apparatus, and a computer device. The sensing apparatus is connected to a specific sensor disposed in a farm, and the specific sensor detects environmental information about the farm to generate corresponding specific sensor data. The method includes the following steps: obtaining, by the computer device, the specific sensor data generated by the specific sensor from the sensing apparatus through the cloud server; in response to determining that there is potential failure of the specific sensor according to the sensor data, transmitting, by the computer device, a calibration command to the sensing apparatus through the cloud server to control the sensing apparatus to enter a sensor-calibration mode; in response to a reference sensor of the same type as the specific sensor being connected to the sensing apparatus, building, by the sensing apparatus, a calibration table by periodically receiving the specific sensor data and reference sensor data respectively from the specific sensor and the reference sensor, wherein each entry in the calibration table records one-to-one correspondence between the specific sensor data and the reference sensor data executing, by the sensing apparatus, a finite-state machine to perform a calibration procedure on each entry in the calibration table; and in response to the number of consecutive hits of the one-to-one correspondence between the specific sensor data and reference sensor data stored in a specific entry in the calibration table reaching a predetermined number N, stopping, by the finite-state machine, the calibration procedure of the specific entry and determines that the specific entry is calibratable.
- In some embodiments, the method further includes: in response to a number of consecutive misses of the one-to-one correspondence between the specific sensor data and reference sensor data stored in the specific entry in the calibration table reaching the predetermined number N, stopping, by the finite-state machine, the calibration procedure of the specific entry and determines that the specific entry is not calibratable. In some embodiments, the predetermined number N is 2.
- In some embodiments, the method further includes: when the finite-state machine determines that the specific entry is not calibratable, determining, by the sensing apparatus, that the specific sensor fails and transmits and sensor-failure message to the computer device to notify a farm administrator to replace that specific sensor.
- In some embodiments, the method further includes the following steps: when the sensing apparatus determines that each entry in the calibration table is calibratable, calibrating, by the sensing apparatus, the specific sensor data generated by the specific sensor using the calibration table, and transmits the calibrated specific sensor data to the computer device through the cloud server.
- The present invention can be more fully understood by reading the subsequent detailed description and examples with references made to the accompanying drawings, wherein:
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FIG. 1 is a diagram of a farming-sensing system in accordance with an embodiment of the invention; -
FIG. 2 is a diagram of communication between the sensor apparatus and cloud server in accordance with an embodiment of the invention; -
FIGS. 3A-3C are diagrams of different finite-state machines in accordance with an embodiment of the invention; -
FIG. 4A is a diagram of relationships between the probability of successful calibration and a number of entries in the calibration table for FSM1 and FSM2 in accordance with an embodiment of the invention; -
FIG. 4B is a diagram of relationships between the probability of calibration failure and a number of entries in the calibration table for FSM1 and FSM2 in accordance with an embodiment of the invention; -
FIG. 5 is a flow chart of a calibration method of sensor data in accordance with an embodiment of the invention. - The following description is made for the purpose of illustrating the general principles of the invention and should not be taken in a limiting sense. The scope of the invention is best determined by reference to the appended claims.
- It must be understood that the words “including”, “including” and other words used in this specification are used to indicate the existence of specific technical features, values, method steps, operations, elements and/or components, but not It is not excluded that more technical features, values, method steps, job processing, elements, components, or any combination of the above can be added.
- Words such as “first”, “second”, and “third” used in the claims are used to modify the elements in the claims, and are not used to indicate that there is an order of priority, antecedent relationship, or It is an element that precedes another element, or the chronological order of execution of method steps, which is only used to distinguish elements with the same name.
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FIG. 1 is a diagram of a farming-sensing system in accordance with an embodiment of the invention. - The farm-
sensing system 100 may include asensing section 110, acloud server 120, anactuator 130, and acomputer device 140, wherein thesensing section 110,actuator 130, andcomputer device 140 may be electrically connected to thecloud server 120. Thesensing section 110 is configured to detect various environmental information about a farm to generate sensor data of different types. - In an embodiment, the sensing section s 110 may include a
sensing apparatus 111, a plurality ofsensors 1601 to 160N, and asensor 115. In addition, the sensing apparatus 11 may include acontroller 113, avolatile memory 1131, anon-volatile memory 1132, and a plurality ofsensor interfaces 1121 to 112N and 114. Each sensor among thesensors 1601 to 160N, for example, may be connected to the sensing apparatus 11 via the corresponding sensor interface among thesensor interface 1121 to 112N, and thesensor 115 can be connected to thesensing apparatus 111 via thesensor interface 114. Thecontroller 113 may be a central-processing unit (CPU), a general-purpose processor, or a microcontroller, but the invention is not limited thereto. - For example, the
sensors 1601 to 160N can be disposed outside thesensing apparatus 111, and thesensors 1601 to 160N may be sensors for detecting different types of information about the farm. Thesensors 1601 to 160N may include but is not limited to temperature sensors, ultraviolet (UV) sensors, humidity sensors, carbon dioxide (CO2) sensors, atmosphere-pressure sensors, soil-humidity sensors, soil-temperature sensors, soil-conductivity sensors, soil-PH sensors, wherein the soil-humidity sensors, soil-temperature sensors, soil-conductivity sensors, soil-PH sensors can be collectively regarded as soil sensors. It should be noted that the number of sensors of each type is not limited to one, and the user may arrange different numbers of sensors for each type of sensor data according to the size of the farm and the actual situation. For example, the user may set humidity sensors and soil sensors in different corners of the farm to more accurately determine the environmental information about different locations on the farm. In addition, thesensing apparatus 111 further includes arain gauge 116 and ananemometer 117, wherein the rain gauge andanemometer 117 can be disposed inside the housing (not shown) of thesensing apparatus 111 to detect the rainfall and wind speed of the farm. - Specifically, the
sensing apparatus 111 may include avolatile memory 1131 and anon-volatile memory 1132. Thevolatile memory 1131, for example, may be a dynamic random access memory (DRAM) or a static random access memory (SRAM), but the invention is not limited thereto. Thenon-volatile memory 1132 may be a hard-disk drive (HDD), a solid-state disk (SSD), a flash memory, or a read-only memory (ROM), but the invention is not limited thereto. Thenon-volatile memory 1132 is configured to store a device application (DA) 1133 and a sensor application (SA) 1134. - The
device application 1133 may support Hyper-text Transfer Protocol Secure (HTTPS) and Message Queuing Telemetry Transport (MQTT) standards for IoT communication, thereby communicating with the could server 120. The sensor application is configured to perform a calibration mechanism of the sensors, such as building a calibration table to calibrate the original sensor data. Thecontroller 113 of thesensing apparatus 111 may load thedevice application 1133 andsensor application 1134 from thenon-volatile memory 1132 to thevolatile memory 1131 for execution. - The
controller 113, for example, may receive corresponding original sensor data from thesensors 1601 to 160N,rain gauge 116, andanemometer 117. Thesensor application 1134 executed by thecontroller 113 may perform a calibration of the original sensor data from each sensor, and thedevice application 1133 may transmit the calibrated sensor data to thecloud server 120 through wired or wireless transmission using the HTTPS and MQTT protocols. - The
cloud server 120 is configured to receive various environmental information from the farm detected by thesensing section 110, and perform one or more artificial-intelligence (AI) models to determine whether to transmit an actuation command to the actuation-control device 131 to control thefarm actuators 150 to 160 to perform corresponding actions on the farm. In addition, thecloud server 120 also serves as a communication bridge between thesensing apparatus 111, actuation-control device 131, and thecomputer device 140. That is, thecomputer device 140 transmits control commands or calibration commands to the actuation-control device 131 or thesensing apparatus 111 through thecloud server 120, and the sensor data obtained by thesensing apparatus 111 is also sent to thecomputer device 140 through thecloud server 120. - In an embodiment, the
actuation section 130 may include an actuation-control device 131 and a plurality offarm actuators 150 to 156, wherein thefarm actuators control device 131 may include acontroller 133, avolatile memory 1331, and anon-volatile memory 1334. Thecontroller 133 may be a central-processing unit (CPU), a general-purpose processor, or a microcontroller, but the invention is not limited thereto. Thevolatile memory 1331, for example, may be a dynamic random access memory (DRAM) or a static random access memory (SRAM), but the invention is not limited thereto. Thenon-volatile memory 1332 may be a hard-disk drive (HDD), a solid-state disk (SSD), a flash memory, or a read-only memory (ROM), but the invention is not limited thereto. Thenon-volatile memory 1332 is configured to store anactuator application 1334. Thecontroller 133 of the actuation-control device 131 may load theactuator application 1334 from thenon-volatile memory 1332 to thevolatile memory 1331 for execution. - The farm actuators 150 to 156 are connected to the actuation-
control device 131, and thecontroller 133 of the actuation-control device 131 may control thefarm actuators 150 to 156 to perform corresponding actions on the farm according to the actuation commands from thecloud server 120, such as spraying water, insect repellent, fertilizer, or activating the insect-repellent light. - The
computer device 140 may be a personal computer or an electronic portable device (e.g., a smartphone or a tablet PC). For convenience of description, in the following embodiments, thecomputer device 140 is described by taking a smartphone as an example. Thecomputer device 140 can communicate with thecloud server 120 and transmit data using a wireless communication protocol, where the wireless communication protocol includes, for example, third generation (3G), fourth generation (4G), fifth generation (5G) Wi-Fi, long-term evolution (LTE), near-field communication (NFC), Bluetooth, low-power wide-area network (LPWAN), LoRaWAN, Sigfox, NB-IoT, etc., but the invention is not limited thereto. - As depicted in
FIG. 1 , thecomputer device 140 can execute a monitoring program (not shown) to display a web-basedmonitoring interface 143 on thedisplay screen 142, and the monitoring program can transfer the sensor data that is received by thecomputer device 140 from thesensing section 110 through thecloud server 120 on themonitoring interface 143. - In an embodiment, the
computer device 140 may perform homogeneous tests, heterogeneous tests, or a combination thereof on some types of thesensors 1601 to 160N according to the received sensor data to determine whether there is a potential failure of a sensor in thesensing section 110. Thecomputer device 140 may display a warning message on themonitoring interface 143, and transmit a failure-notification message to thecloud server 120 upon determining that there is a potential failure of a sensor, so that thecloud server 120 transmits a calibration command to thesensing apparatus 111 to control thesensing apparatus 111 to enter a sensor-calibration mode from a normal mode. - For example, the homogenous tests performed by the
computer device 140 refers to the data analysis of the sensor data generated by the sensors of the same type in the same farm, thereby determining whether there is a potential failure of any sensor of the same type. Taking atmosphere-pressure sensors, temperature sensors, humidity sensors, and CO2 sensors as examples, in theory, the sensor data generated by multiple sensors of the same type disposed in the same farm are highly correlated from each other. If the error between the sensor data generated by a specific senor and the sensor data generated by other sensors of the same type is too large (e.g., greater than a standard deviation, not limited), thecomputer device 140 can determine that there is a potential failure of the specific sensor. - In addition, if the locations and altitudes of different farms are very different, the sensor data detected by the various types of sensors in the farms at different locations will theoretically be different. That is, in addition to comparing the sensor data of the sensors of the same type in the same farm, the
computer device 140 can also compare the sensor data of the sensors of the same type in farms at different locations. Besides, if only one set of thesensing section 110 is disposed in the same farm, thecomputer device 140 can obtain weather information from the nearest government weather station, and compare the obtained weather information with the sensor data of the corresponding sensors in thesensing section 110 to determine whether there is a potential failure of any sensor. - The heterogeneous tests performed by the
computer device 140 require the cooperation of thesensors 1601 to 160N and thefarm actuators 150 to 156. For example, taking the soil-humidity sensor and the water dripper as an example, when the soil-humidity sensor and the water dripper are operating normally, thecomputer device 140 may calculate a delay time t between activation and deactivation of the water dripper. According to the histogram of the delay time t, thecomputer device 140 can derive a distribution for selecting a suitable delay time threshold T. When it is impossible to determine whether the soil-humidity sensor and the water dripper installed on the same farm are operating normally, thecomputer device 140 will continue to perform the interactive test of the soil-humidity sensor and the water dripper by measuring the delay time t. If the water dripper cannot be turned off within the delay time threshold T after being turned on, thecomputer device 140 will determine that a potential failure has occurred. - Specifically, when the sensor data of the soil-humidity sensor received by the
cloud server 120 from thesensing apparatus 111 indicates that the RH value of the farm soil is too low (e.g., lower than 45% RH), theactuator application 1334 performed by thecomputer device 140 may sent a control signal to the actuation-control device 131 through thecloud server 120 to control the water dripper to start watering. If the water dripper works normally, after a predetermined of time, the humidity of the farm soil should increase to a predetermined threshold (e.g., 45% RH). When the soil-humidity sensor detects that the soil humidity of the farm reaches the predetermined threshold within the delay time threshold T, thecomputer device 140 may determine that there is a potential failure of the soil-humidity sensor or the water dripper after receiving the sensor data of the soil-humidity sensor through thecloud server 120. Meanwhile, themonitoring interface 143 of thecomputer device 140 may display a warning message to notify the farmer, and sends a warning message to thecloud server 120 to indicate that a potential failure has occurred. -
FIG. 2 is a diagram of communication between the sensor apparatus and cloud server in accordance with an embodiment of the invention. - As depicted in
FIG. 2 , thedevice application 1133 andsensor application 1134 performed by thesensing apparatus 111 can be classified into sub-modules in the normal mode and the sensor-calibration mode. For example, the sensor application 134 may include sub-modules 1135 and 1136, and thedevice application 1133 may include sub-modules 1137, 1138, and 1139. The sub-modules 1137 and 138 may be input device features (IDFs), and can be respectively regarded as IDF X and IDF Cb channels. The IDF channels are different communication channels between thesensing apparatus 111 and thecloud server 120. For example, thesensing apparatus 111 can transmit the sensor data of the sensor Sz and Sw to thecloud server 120 respectively through the IDF X and IDF Cb channels. The sub-module 1139 may be output device feature that is used in the sensor-calibration mode. For example, the sub-module 1139 may receive the calibration request sent from thecomputer device 140 through thecloud server 140, and thus the sub-module 1139 can be regarded as the ODF Cb module. - In the normal mode, the sub-module 1135 of the
sensor application 1134 and the sub-module 1138 of thedevice application 1133 are not activated. When thesensing apparatus 111 is in the sensor-calibration mode, thecontroller 113 may activate the sub-module 1135 of thesensor application 1134 and the sub-modules 1138 and 1139 of thedevice application 1133. It should be noted that the sub-module 1136 of thesensor application 1134 and the sub-module 1137 of thedevice application 1133 are always active no matter whether thesensing apparatus 111 is in the normal mode or the sensor-calibration mode. - The sensor Sx refers to one of the
sensors 1601 to 160N connected to thesensing apparatus 111. In the normal mode, thesensors 1601 to 160N are connected to thesensing apparatus 111 and periodically detect the environmental information about the farm, but thesensor 115 is not connected to thesensing apparatus 111. The sensors of different types have different detection periods, and the user can adjust the detection period of each sensor or the period of thecontroller 111 capturing sensor data from each sensor according to actual conditions. The sensor data generated by the sensor Sx will be sent to the sub-module 1136 (e.g., can be regarded as SAx module), and the sub-module 1136 will process the sensor data, and send the processed sensor data to thecloud server 120 through the sub-module 1137. - It should be noted that, taking the temperature sensor as an example, if the temperature range detected by the temperature sensor is −40 degrees Celsius to 65 degrees Celsius. The temperature sensor may not be able to accurately detect the temperature in some temperature ranges due to damage or aging caused by being in an outdoor environment, defects in the sensor's manufacturing process, or interference during the detection process. These problems can also be regarded as a potential failure of the temperature sensor. A similar method can be used to determine whether there is a potential failure of sensors of other types.
- In the aforementioned embodiment, when the cloud server transmits a calibration command to the
sensing apparatus 111, thesensing apparatus 111 enters the sensor-calibration mode from the normal mode. Meanwhile, thecontroller 113 will activate the sub-module 1135 of thesensor application 1134 and the sub-module 1138 of thedevice application 1133. Before starting the sensor-data-calibration procedure, the sensor 115 (i.e., sensor Sw needs to be connected to thesensing apparatus 111 and placed next to the sensor Sx that has a potential failure to ensure that the environmental information detected by the sensors Sx and Sw is similar. Thesensor 115, for example, can be regarded as a standard sensor or a reference sensor. That is, thesensor 115 is a sensor that has been confirmed to work normally, so the accuracy of the sensor data generated by thesensor 115 is worthwhile trusted. - Given that Tx is the data value measured by the sensor Sx of entry X in the calibration table and the variable Vx is used to store the most recently received data from the sensor Sx, the sub-module 1136 of the
sensor application 1134 may execute the following pseudo code: - S1: Wait to receive a sample νx from Sx
S2: Vx←νx
S3: if (Tx(νx)=NIL), then Tx(νx)←x
S4: Send Tx(νx) to the IDF of Sx in the DA
S5: Go to step S1 - When starting to create the content in the entries of the calibration table, different values detected by the sensor Sx will be sequentially filled into the entries in the calibration table. For example, the first data is filled into
entry 1, and the second data is filled intoentry 2, and so on. In brief, the content of the calibration table is initially empty, and different values detected by the sensor Sx will be filled into each entry in the calibration table. It should be noted that step S1 to S5 will be executed continuously no matter whether or not thesensing apparatus 111 is in the sensor-calibration mode. That is, if the farm's environment changes greatly, the number of entries in the calibration table may increase. - In this embodiment, when the
sensing device 111 is in the sensor calibration mode, the sub-module 1135 of thesensor application 1134 may perform a calibration procedure, for example, to fill the standard (STD) field corresponding to each entry in the calibration table with the value detected by the sensor Sw. For example, thesensing apparatus 111 may use the same time period to simultaneously capture sensor data from the sensors Sw and Sx, where the sensor Sx can be regarded as a device under test (DUT), and the sensor Sw can be regarded as a standard sensor. Taking the temperature sensor as an example, if the DUT field of the first entry in the calibration table is 26.52 degrees Celsius and the temperature measured by the standard sensor Sw is 24.98 degrees Celsius, the value of 24.98 degrees Celsius will be filled into the STD field of the first entry. Similarly, if the DUT field of the second of the calibration table is 27.41 degrees Celsius and the temperature measured by the standard sensor SW is 25.79 degrees Celsius, the value of 24.98 degrees Celsius will be filled into the STD field of the second entry. By repeating the aforementioned steps, values in the STD field of each entry in the calibration table can be established, as shown in Table 1: -
TABLE 1 entry DUT(° C.) STD(° C.) 1 26.52 24.98 2 27.41 25.79 3 28.90 27.19 4 31.45 29.68 5 32.73 29.85 6 33.00 31.22 7 32.73 31.61 8 33.79 32.35 9 34.67 33.82 10 35.33 33.86 11 35.90 34.48 12 35.88 34.51 - In another embodiment, taking the humidity sensor as an example, if the DUT field of the first entry in the calibration table is 78.47% RH and the humidity measured by the standard sensor Sw is 77.24% RH, the value of 77.24% will be filled into the STD field of the first entry. Similarly, if the DUT field of the second of the calibration table is 77.31% and the humidity measured by the standard sensor Sw is 76.56%, the value of 76.56% will be filled into the STD field of the second entry. By repeating the aforementioned steps, values in the STD field of each entry in the calibration table can be established, as shown in Table 2:
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TABLE 2 entry DUT(%) STD(%) 1 78.47 77.24 2 77.31 76.56 3 72.41 72.29 4 63.63 64.31 5 57.47 58.80 6 58.28 58.67 7 50.80 52.58 8 51.06 52.16 9 46.56 45.85 10 45.86 47.69 11 45.07 46.92 12 43.71 46.09 - During the calibration procedure, the sensor Sx (i.e., DUT) may detect the same value that has been previously detected, so if the sensor Sx detects the same value, it will point to the same entry in the calibration table. Assuming that the entry Tx(vx) has previously been filled in with the corresponding standard value vW, if the sensor Sx detects the value vx and the sensor Sw detects the value vW, it Means that the Correspondence of the entry Tx(vx) hits. If the sensor Sx detects the value vx and the sensor Sw detects a value other than vW, it indicates that the correspondence of the entry Tx(vx) misses. The aforementioned calibration procedure is controlled by a finite-state machine (FSM), and the status of “hit” or “miss” of the correspondence is the input signal of the finite-state machine, and can control the state transition of the finite-state machine, as shown in
FIG. 3A . It should be noted that each sensor has a corresponding finite-state machine to calibrate the sensor data thereof. In some embodiments, the finite-state machine may be implemented by software codes. In some other embodiments, the finite-state machine may be implemented by a dedicated logic circuit. - In the embodiment, if the calibration message M=(s, id) is exchanged between the
sensing apparatus 111 and thecloud server 120 through the control channel and the calibration message is sent from thecloud server 120 to thesensing apparatus 111, it indicates the status M.s=R which is a calibration request. When the calibration request is sent from the sensing apparatus Ill to thecloud server 120, the status M.s=C indicates that the calibration procedure is successfully completed, and the status M.s=F indicates that the calibration procedure has failed. M.id represents the number of the sensor to be calibrated. The corresponding state of each entry Tx(v) in the calibration table Tx is denoted as Fx(v). Accordingly, the calibration procedure executed by the sub-module 1135 of thesensor application 1134 can be expressed by the following pseudo code; - W1: Wait to receive the calibration request message M=(R, id) from Channel ODF Cb
- W3: for (∀νϵTx) do {Fx(ν)←0}
W4: Wait to receive a value νw from Sw
W5: if Tx(Vx)=νW then Fx(Vx)+1 - else {Tx(Vx)←νW; Fx(Vx)←Fx(Vx)+1}
- W6: if(Fx(ν)=N) then {
W6a: Send the calibration failed message M=(F,X) to Channel IDF Cb; - Go to Step W1;}
- W6b: elseif(∀VϵTx, Fx(ν)=1) then {
- send the calibration complete message M=(C,X) to Channel IDF Cb;
-
- Go to Step W1;}
W6c: else Go to Step W4;
- Go to Step W1;}
- It should be noted that the steps S1 to S5 and step W1 to S6 are executed independently. The value Vx generated in step S2 and the execution time of step W4 are approximately the same. In an embodiment, even if the sensor Sx can be calibrated, since the sensor Sx may have a low probability of random errors, a miss may still occur during the calibration procedure. If the probability of miss is not 0, theoretically the finite-state machine in
FIG. 3A will eventually proceed to the state of Fx(v)=N, and step W6a may determine that the calibration procedure has failed. In this case, the computer device (or the cloud server 120) will notify the farmer that it is necessary to replace the hardware of the sensor that has been misjudged to be invalid, but the sensor Sx has not failed in fact, so it may cause unnecessary increase of costs. - In general, if the sensor Sx can be calibrated, step W6b will be executed to successfully complete the calibration procedure. For the finite-state machine FSM0 in
FIG. 3A , the only stable state is Fx(v)=N. In order to ensure that the state Fx(v)=1 is also a stable state, the finite-state machine FSM0 inFIG. 3A is changed to the finite-state machine FSM1 inFIG. 3B . Thus, after the calibration procedure is successfully completed, the flow is aborted in step W6b. The probability of successfully completing the calibration procedure and aborting is derived as follows. - Let the probability πi of occurrence of the i-th state of the finite-state machine FSM1 is Pr[Fx(v)=i], since
state 0 is a transient state, the probability of occurrence π0=0. Accordingly, the total probability of occurrence ofother states 1 to N is 1, which can be expressed by the equation (1): -
π1+π2+ . . . +πN=1 (1) - Let the probability of data hit Pr(hit)=p and the probability of data miss Pr(miss)=1−p, then equation (2) can be obtained:
-
π1 =pπ 1 +pπ 2 + . . . +pπ N =p (2) - For 1<n<N, equations (3) and (4) can be obtained:
-
πn=(1−p)πn−1 =p(1−p)n−1 (3) -
πN(1−p)πN−1+(1−p)πN=(1−p)N−1 (4) - Accordingly, if the sensor Sz can be calibrated, the sensor Sx has a probability p that can be successfully calibrated no matter whether the value N is selected. If the sensor Sx needs to be replaced, according to equation (4), the probability of replacing the sensor Sx is (1−p)N−1. In other words, if a larger value of N is selected, it will take a long time to perform the aforementioned calibration procedure before determining that the sensor Sx needs to be replaced. In a preferred embodiment, N=2 is selected to perform the aforementioned calibration procedure.
- For example, for each value of v, when the finite-state machine FSM1 in
FIG. 3B proceeds to state Fx(v)=1 or N, the calibration of this value of v may be suspended. Accordingly, the finite-state machine FSM1 may randomly stop when enteringstate 1 or N. With regard to the aforementioned random model, the probability that the calibration procedure stops at step W6b is expressed by equation (5): -
Pr[M.s=C]=P |Tx | (5) - For N=1, the probability that the calibration procedure stops at step W6a is expressed by equation (6):
-
Pr[M.s=F]=1−P |Tx | (6) - When the value of |TX| is very large, the probability of reaching step W6b (i.e., successfully completing the calibration procedure) is very low. Thus, it is necessary to increase the probability of successfully completing the calibration procedure in equation (5). Specifically, as shown in the finite-state machine FSM2 in
FIG. 3C , if there are two consecutive hits for a specific entry in the calibration table, the specific entry can be regarded as calibrated (or can be calibrated), and the finite-state machine FSM2 for this project entry will stop. Accordingly, the probability π3,n indicating that the probability that the finite-state machine FSM2 has visitedstate 1 for n times before proceeding tostate 3 can be expressed by equation (7): -
π3,n =p[p(1−p)]n−1 (7) - Thus, the probability that the finite-state machine FSM2 stops at
state 3 can be expressed by equation (8): -
- Similarly, the probability π4,n indicating that the probability that the finite-state machine FSM2 has visited
state 1 for n times before proceeding tostate 4 can be expressed by equation (9): -
π4,n=(1−p)2[p(1−p)]n−1 (9) - Thus, the probability that the finite-state machine FSM2 stops at
state 4 can be expressed by equation (10): -
- where equations (8) and (10) satisfy π3,n+π4,n=1.
- Therefore, for the finite-state machine FSM2, the probability of calibration completion and calibration failure can be respectively expressed by equations (11) and (12):
-
- For example, referring to the finite-state machine FSM2 in
FIG. 3C , if the correspondence between the DUT and STD sensor data in a specific entry is missed after the first hit, the finite-state machine FSM2 will enterstate 2. If the second hit occurs instate 2, the finite-state machine FSM2 will enterstate 1. When a third hit occurs instate 1, the finite-state machine FSM2 will enterstate 3 to determine that the specific entry is calibratable. If a miss occurs again instate 2, the finite-state machine FSM2 will enterstate 4 to determine that the specific entry is not calibratable and the sensor Sx (i.e., DUT) has failed. Briefly, if there are two consecutive misses for a specific entry in the calibration table Tx, the specific entry can be regarded as not calibratable. -
FIG. 4A is a diagram of relationships between the probability of successful calibration and the number of entries in the calibration table for FSM1 and FSM2 in accordance with an embodiment of the invention.FIG. 4B is a diagram of relationships between the probability of calibration failure and the number of entries in the calibration table for FSM1 and FSM2 in accordance with an embodiment of the invention. - Referring to
FIG. 2 andFIGS. 4A to 4B , in an embodiment, if the probability p that the sensor data of the sensor Sx can successfully hit is 0.999, the probability of successful calibration of the finite-state machine FSM1 will gradually decrease with the increment of the number of entries in the calibration table Tx. However, the probability of successful calibration of the finite-state machine FSM2 can be maintained at close to 1, as shown inFIG. 4A . If the sensor Sx has truly failed and needs to be replaced (e.g., probability p of a successful hit is 0.1),FIG. 4B shows the relationship between the probability of calibration failure and the number of entries in the calibration table for the finite-state machines FSM1 and FSM2. As depicted inFIG. 4B , if the number of entries in the calibration table Tx is greater than or equal to 5, the probability Pr[M.s=F] of determining failure of the sensor Sx is close to 1. - It can be understood that if the sensor Sx is calibratable, the finite-state machine FSM2 in
FIG. 3C can still successfully establish the calibration table. In addition, in comparison with the finite-state machine FSM1 inFIG. 3B , if the sensor Sx has truly failed and needs to be replaced, the calibration procedure of the finite-state machine FSM2 inFIG. 3C can be quickly stopped. It indicates that the finite-state machine FSM2 can quickly determine that the sensor Sx has failed. Specifically, when the sensing apparatus III determines that each entry in the calibration table is calibratable, thesensing apparatus 111 will use the calibratable entry in the calibration table to calibrate the sensor data generated by the sensor Sx and transmit the calibrated sensor data to thecomputer device 140 through thecloud server 120 without considering whether or not thesensing apparatus 111 is in the sensor-calibration mode. After the calibration of the sensor Sx is completed, the sensor Sw can be removed from the sensing apparatus by the farmer. However, if any entry in the calibration table is determined as not calibratable by the finite-state machine FSM2 (or FSM1), thesensing apparatus 111 determines that the sensor Sx has failed, and transmits a sensor-failure message to thecomputer device 140 to notify the manager of the farm (e.g., the farmer). -
FIG. 5 is a flow chart of a calibration method of sensor data in accordance with an embodiment of the invention. - Referring to
FIG. 1 andFIG. 5 , in step S510, thecomputer device 140 receives specific sensor data generated by a specific sensor (e.g., sensor 1601) from thesensing apparatus 111 through thecloud server 120. The specific sensor may be one of a temperature sensor, ultraviolet (UV) sensor, humidity sensor, carbon dioxide (CO2) sensor, atmosphere-pressure sensor, soil-humidity sensor, soil-temperature sensor, soil-conductivity sensor, and soil-PH sensors, but the invention is not limited thereto. - In step S520, in response to the
computer device 140 determining that there is a potential failure of the specific sensor according to the specific sensor data, thecomputer device 140 transmits a calibration command to thesensing apparatus 111 through the cloud server, so that thesensing apparatus 111 enters a sensor-calibration mode. For example, thecomputer device 140 may perform homogeneous tests, heterogeneous tests, or a combination thereof according to the received specific sensor data to determine whether there is a potential failure of a sensor in thesensing section 110, and the details can be referred to in the aforementioned embodiments. - In step S530, in response to a reference sensor of the same type with the specific sensor being connected to the
sensing apparatus 111, thesensing apparatus 111 continuously and periodically receives the specific sensor data and reference sensor data respectively from the specific sensor and the reference sensor to establish a calibration table, wherein each entry in the calibration table records one-to-one correspondence between the specific sensor data and the reference sensor data. - In step S540, a finite-state machine is executed to perform a calibration procedure on each entry in the calibration table. For example, the finite-state machine may be the finite-state machine FSM1 in
FIG. 3B or the finite-state machine FSM2 inFIG. 3C . - In step S550, in response to a number of consecutive hits of the correspondence between the specific sensor data and the reference sensor data of a specific entry in the calibration table reaching a predetermined number N, the finite-state machine stops the calibration procedure of the specific entry and determines that the specific entry is calibratable. According to the aforementioned embodiments, the predetermined number N is an integer greater than or equal to 2. In a preferred embodiment, the predetermined number N is equal to 2, but the invention is not limited thereto. One having ordinary skill in the art can adjust the value of the predetermined number N according to actual conditions.
- For example, as shown in
FIG. 3C , the finite-state machine FSM2 may includestate 0,state 1,state 2,state 3, andstate 4. It will always hit instate 0, and the finite-state machine FSM2 must enterstate 1. The state transition betweenstates 1 to 4 depends on the input (e.g., hit or miss) of the finite-state machine FSM2. If the correspondence between the reference sensor data and specific sensor data in the specific entry is missed after the first hit, the finite-state machine FSM2 will enterstate 2. If the second hit occurs instate 2, the finite-state machine FSM2 will enterstate 1. When a third hit occurs instate 1, the finite-state machine FSM2 will enterstate 3 to determine that the specific entry is calibratable. If a miss occurs again instate 2, the finite-state machine FSM2 will enterstate 4 to determine that the specific entry is not calibratable and the sensor Sa (i.e., DUT) has failed. - In view of the above, a farm-sensing system and a calibration method of sensor data thereof are provided. The farm-sensing system and the calibration method are capable of performing the calibration procedure on the sensor data of a specific sensor having a potential failure using the reference sensor while determining that there is a potential failure of the specific sensor. In addition, the finite-state machine in the calibration procedure can quickly and accurately determine whether the specific sensor is calibratable or has failed, so time cost can be saved and unnecessary replacement of sensor hardware can be avoided.
- While the invention has been described by way of example and in terms of the preferred embodiments, it should be understood that the invention is not limited to the disclosed embodiments. On the contrary, it is intended to cover various modifications and similar arrangements (as would be apparent to those skilled in the art). Therefore, the scope of the appended claims should be accorded the broadest interpretation so as to encompass all such modifications and similar arrangements.
Claims (10)
1. A farm sensing system, comprising:
a cloud server;
a sensing apparatus, connected to a specific sensor disposed in a farm, wherein the specific sensor is configured to detect environmental information about the farm to generate specific sensor data, and
a computer device, configured to obtain the specific sensor data generated by the specific sensor from the sensing apparatus through the cloud server,
wherein in response to the computer device determining that there is a potential failure of the specific sensor according to the obtained specific sensor data, the computer device transmits a calibration command to the sensing apparatus through the cloud server to control the sensing apparatus to enter a sensor-calibration mode,
wherein in response to a reference sensor of the same type as the specific sensor being connected to the sensing apparatus, the sensing apparatus establishes a calibration table by continuously and periodically receiving the specific sensor data and reference sensor data respectively from the specific sensor and the reference sensor, wherein each entry in the calibration table records one-to-one correspondence between the specific sensor data and the reference sensor data,
wherein the sensing apparatus executes a finite-state machine to perform a calibration procedure on each entry in the calibration table,
wherein in response to a number of consecutive hits of the one-to-one correspondence between the specific sensor data and reference sensor data stored in a specific entry in the calibration table reaching a predetermined number N, the finite-state machine stops the calibration procedure of the specific entry and determines that the specific entry is calibratable.
2. The farm sensing system as claimed in claim 1 , wherein in response to a number of consecutive misses of the one-to-one correspondence between the specific sensor data and the reference sensor data stored in the specific entry in the calibration table reaching the predetermined number N, the finite-state machine stops the calibration procedure of the specific entry and determines that the specific entry is not calibratable.
3. The farm sensing system as claimed in claim 2 , wherein the predetermined number N is 2.
4. The farm sensing system as claimed in claim 2 , wherein when the finite-state machine determines that the specific entry is not calibratable, the sensing apparatus determines that the specific sensor has failed, and transmits a sensor-failure message to the computer device to notify a manager of the farm to replace the specific sensor.
5. The farm sensing system as claimed in claim 2 , wherein when the sensing apparatus determines that each entry in the calibration table is calibratable, the sensing apparatus calibrates the specific sensor data generated by the specific sensor using the calibration table, and transmits the calibrated specific sensor data to the computer device through the cloud server.
6. A calibration method of sensor data, for use in a farm sensing system, wherein the farm sensing system comprises: a cloud server, a sensing apparatus, and a computer device, and the sensing apparatus is connected to a specific sensor disposed in a farm, and the specific sensor detects environmental information about the farm to generate corresponding specific sensor data, the method comprising:
obtaining, by the computer device, the specific sensor data generated by the specific sensor from the sensing apparatus through the cloud server,
in response to determining that there is a potential failure of the specific sensor according to the specific sensor data, transmitting, by the computer device, a calibration command to the sensing apparatus through the cloud server to control the sensing apparatus to enter a sensor-calibration mode;
in response to a reference sensor of the same type as the specific sensor being connected to the sensing apparatus, establishing, by the sensing apparatus, a calibration table by periodically receiving the specific sensor data and reference sensor data respectively from the specific sensor and the reference sensor, wherein each entry in the calibration table records one-to-one correspondence between the specific sensor data and the reference sensor data;
executing, by the sensing apparatus, a finite-state machine to perform a calibration procedure on each entry in the calibration table; and
in response to a number of consecutive hits of the one-to-one correspondence between the specific sensor data and reference sensor data stored in a specific entry in the calibration table reaching a predetermined number N, stopping, by the finite-state machine, the calibration procedure of the specific entry and determines that the specific entry is calibratable.
7. The calibration method as claimed in claim 6 , further comprising:
in response to a number of consecutive misses of the one-to-one correspondence between the specific sensor data and the reference sensor data stored in the specific entry in the calibration table reaching the predetermined number N, stopping, by the finite-state machine, the calibration procedure of the specific entry and determining that the specific entry is not calibratable.
8. The calibration method as claimed in claim 7 , wherein the predetermined number N is 2.
9. The calibration method as claimed in claim 7 , further comprising:
when the finite-state machine determines that the specific entry is not calibratable, determining, by the sensing apparatus, that the specific sensor has failed and transmitting a sensor-failure message to the computer device to notify a manager of the farm to replace the specific sensor.
10. The calibration method as claimed in claim 7 , further comprising:
when the sensing apparatus determines that each entry in the calibration table is calibratable, calibrating, by the sensing apparatus, the specific sensor data generated by the specific sensor using the calibration table, and transmitting the calibrated specific sensor data to the computer device through the cloud server.
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