System for delivering sprouts for hydroponic cultivation

Abstract

The present invention relates to a system for delivering sprouts for hydroponic cultivation. The system for delivering, to a consumer, a sprout product shipped from a production site producing sprouts for hydroponic cultivation comprises: an information collection unit for collecting information on the customer, order information, and delivery request date information; a delivery information collection unit for collecting environment information and delivery status, collected from a delivery device performing delivery from the production site to an address of the consumer; an optimal delivery route calculation unit for calculating an optimal delivery route from the production site to the address of the consumer and transmitting the optimal delivery route to a preset deliverer terminal and the delivery device; a normal delivery determination unit for determining whether normal delivery has been made, on the basis of the delivery request date and the information on the consumer, collected by the information collection unit, and the environment information and the delivery status, collected by the delivery information collection unit; and a compensation unit for providing a preset compensation to a deliverer and the consumer, on the basis of the delivery status including normal delivery, determined by the normal delivery determination unit.

Description

Hydroponic sprout delivery system

[0001] The present invention relates to a delivery system for hydroponic sprouts that require freshness maintenance, and more particularly, to a hydroponic sprout delivery system that maintains the freshness of hydroponic sprouts and delivers them to consumers on a date selected by the consumer through an optimal route.

[0002]

[0003] Hydroponics is a method of growing plants that are usually rooted in the ground in water, and is also called nutrient solution farming. When growing plants in coco peat or stone wool, which have a similar appearance to soil but do not contain nutrients, it is also called hydroponics. However, when growing plants whose initial habitat is water, such as aquatic plants, it is not called hydroponics.

[0004] As mentioned above, hydroponics, compared to conventional farming, uses nutrient solution and water efficiently to grow crops with a small amount of fertilizer, and the roots of the crops are directly exposed to the nutrient solution, improving nutrient absorption efficiency, thereby saving resources such as water and fertilizer required for crop productivity and growth.

[0005] In addition, compared to arable farming, techniques such as vertical farming can improve space utilization efficiency and minimize environmental pollution by recycling used water and nutrients, making sustainable agriculture possible.

[0006] In addition, it is possible to optimize crop growth and easily control the cultivation period by controlling temperature, humidity, and lighting regardless of the external environment and season by installing it indoors, and to produce high-quality crops through precise environmental management.

[0007] Meanwhile, in the case of hydroponic cultivation, the method of germinating and harvesting from seeds makes it difficult to know the health status of the crops in the seed state, and if the seeds contain pests or diseases, they can also cause damage to surrounding crops after germination. Therefore, crops are delivered in the form of sprouts, sterilized, and then cultivated in hydroponic facilities. As the number of hydroponic facilities increases, the practice of cultivating and delivering only sprouts for hydroponic cultivation is gradually increasing.

[0008] However, there are frequent cases where the freshness of the sprout-shaped crops decreases or their condition rapidly deteriorates and they die after being delivered to the hydroponic cultivation site through seed germination. This phenomenon occurs more frequently in proportion to the delivery distance, so hydroponic farmers are often forced to order sprouts from companies due to geographical and environmental factors that focus on delivery distance rather than price and quality.

[0009] Therefore, research is required on a hydroponic sprout delivery system that maintains freshness and delivers hydroponic sprouts to consumers through an optimal route.

[0010]

[0011] The purpose of the present invention is to deliver fresh sprout products on a delivery date set by a consumer by receiving data from a sensor that senses environmental information of a loading box loaded with sprout products in a delivery device and providing an optimal delivery route to a delivery person.

[0012] In addition, the purpose is to calculate the failure probability of the sensor that collects environmental information within the delivery device, and to perform repair, replacement, and inspection on sensors with a high failure probability to accurately determine the delivery status of sprout products.

[0013] In addition, the purpose is to objectively determine whether sprout products have deteriorated during the delivery process by calculating a delivery score that reflects the delivery request date entered by the consumer, the actual delivery date, the measurement values ​​of the measurement sensors in the delivery device, environmental information for maintaining the freshness of the delivered sprout products, average environmental information during the delivery period, and the failure probability of the measurement sensors.

[0014]

[0015] According to an embodiment of the present invention, a system for delivering sprout products shipped from a production site for producing sprouts for hydroponics to a consumer may include an information collection unit that collects consumer information, order information, and delivery request date information, a delivery information collection unit that collects environmental information and delivery status collected from a delivery device that performs delivery from the production site to the consumer's address, an optimal delivery route calculation unit that calculates an optimal delivery route from the production site to the consumer's address and transmits the calculated optimal delivery route to a preset delivery terminal and the delivery device, a normal delivery determination unit that determines whether delivery is normal based on the delivery request date collected by the information collection unit, the consumer's information, and the environmental information and delivery status collected by the delivery information collection unit, and a reward unit that provides preset rewards to the delivery person and the consumer based on the normal delivery status determined by the normal delivery determination unit.

[0016] In addition, the delivery information collection unit includes a loading sensor unit that collects the environmental information by providing a temperature measurement sensor, an oxygen concentration measurement sensor, a carbon dioxide concentration measurement sensor, and a humidity measurement sensor inside a loading box in which the sprout product is loaded in the delivery device, a monitoring unit that receives the sensing data collected by the loading sensor unit and transmits the environmental status to the preset delivery terminal, and the loading sensor unit includes a sensor information collection unit that collects the supply voltage, consumption current, and output voltage supplied to the measurement sensor, a sensor error measurement unit that extracts a comparison target time that is a time when a change rate of a measurement value of the sensing data exceeds a preset rate, and a data transmission unit that periodically transmits the comparison target time of the sensor error measurement unit to the monitoring unit, and the sensor error measurement unit can extract sensing data corresponding to n arbitrary times in the sensing data as comparison target times when there is no time exceeding the preset rate.

[0017] In addition, the sensor unit is provided with a comparison sensor as the same sensor within a preset radius from at least one of the temperature measurement sensor, the oxygen concentration measurement sensor, the carbon dioxide concentration measurement sensor, and the humidity measurement sensor, and the monitoring unit uses the sensing data collected from the measurement sensor and the comparison sensor and the comparison target time to calculate the sensor failure probability (S) according to the following [Mathematical Formula 1] TR ) is produced,

[0018] [Mathematical Formula 1]

[0019]

[0020] (Here, S TR is the probability of sensor failure, T ms1 is the measurement value of the measurement sensor at the first time, T ms2 is the measurement value of the measurement sensor at the second time, T ms3 is the measurement value of the measurement sensor at the third time, T msn is the measurement value of the measurement sensor at the nth time, T cst1is the measurement value of the comparison sensor at the first time, T cst2 is the measurement value of the comparison sensor at the second time, T cs3 is the measurement value of the comparison sensor at the third time, T csn is the measurement value of the comparison sensor at the nth time, T msav is the average measurement value of the measurement sensor, and SE means the efficiency deviation of the measurement sensor.)

[0021] The efficiency deviation (SE) of the above measurement sensor is calculated according to the following [Mathematical Formula 2],

[0022] [Equation 2]

[0023]

[0024] (Here, SE av is the average efficiency of the measuring sensor, SE i refers to the initial efficiency of the measuring sensor)

[0025] A hydroponic sprout delivery system characterized in that the average efficiency of the above measurement sensor is calculated according to the following [Mathematical Formula 3].

[0026] [Equation 3]

[0027]

[0028] (Here, W IN1 is the power supplied to the measurement sensor at the first time, W OUT1 The power measured when the measurement value sensed by the measurement sensor at the first time is output as an electrical signal, W IN2 is the power supplied to the measurement sensor at the second time, W OUT2 The power measured when the measurement value sensed by the measurement sensor at the second time is output as an electrical signal, W INn is the power supplied to the measurement sensor at the nth time, W OUTn It means the power measured when the measurement value sensed by the measurement sensor at the nth time is output as an electrical signal.

[0029] In addition, the normal delivery judgment unit calculates a delivery score (D) according to the following [Mathematical Formula 4] in response to the environmental information collected during the delivery period from the time the sprout product is loaded onto the delivery device to the time delivery to the consumer is completed, the delivery request date information, and the delivery completion time. s ) is produced,

[0030] [Equation 4]

[0031]

[0032] (Here, D w is the delivery date weight, DD r is the actual delivery date, DD a is the delivery request date, S TR·T is the probability of failure of the temperature measurement sensor, O T·av The optimal delivery temperature for sprout products, M T·av is the average temperature during the delivery period, S TR·O is the probability of failure of the oxygen concentration measurement sensor, O O·av is the optimal oxygen concentration for delivery of sprout products, M O·av is the average oxygen concentration during the delivery period, S TR·C is the probability of failure of the carbon dioxide concentration measurement sensor, O C·av is the optimal carbon dioxide concentration for delivery of sprout products, M C·av is the average carbon dioxide concentration during the delivery period, S TR·H is the probability of failure of the humidity measurement sensor, O H·av The optimum humidity for delivery of sprout products, M H·av refers to the average humidity during the delivery period)

[0033] You can determine whether normal delivery has occurred based on the above delivery score.

[0034] In addition, the compensation unit may impose compensation or penalties on the delivery person and the consumer in response to the delivery score calculated by the normal delivery judgment unit.

[0035]

[0036] According to the present invention, by receiving data from a sensor that senses environmental information of a loading box loaded with sprout products in a delivery device and providing an optimal delivery route to a delivery person, sprout products with high freshness can be delivered on a delivery date set by a consumer.

[0037] In addition, by calculating the failure probability of the sensor that collects environmental information within the delivery device, it is possible to perform repairs, replacements, and inspections on sensors with a high failure probability to accurately determine the delivery status of sprout products.

[0038] In addition, by calculating a delivery score that reflects the delivery request date entered by the consumer, the actual delivery date, the measurement values ​​of the measurement sensors in the delivery device, environmental information for maintaining the freshness of the delivered sprout products, average environmental information during the delivery period, and the failure probability of the measurement sensors, it is possible to objectively determine whether the sprout products have deteriorated during the delivery process.

[0039]

[0040] FIG. 1 is a block diagram illustrating a sprout delivery system for hydroponic cultivation according to an embodiment of the present invention.

[0041] FIG. 2 is a drawing showing an intermediate block diagram of a delivery information collection unit in a hydroponic sprout delivery system according to an embodiment of the present invention.

[0042] FIG. 3 is a block diagram illustrating an intermediate block diagram of a loading sensor unit in a hydroponic sprout delivery system according to an embodiment of the present invention.

[0043]

[0044] Specific details, including the problems to be solved, means of solving them, and effects of the invention, are included in the embodiments and drawings described below. The advantages and features of the present invention, and methods for achieving them, will become clearer with reference to the embodiments described below in detail, along with the accompanying drawings.

[0045] The scope of the present invention is not limited to the embodiments described below, and various modifications may be made by a person having ordinary knowledge in the relevant technical field without departing from the technical spirit of the present invention.

[0046] Hereinafter, the sprout delivery system for hydroponic cultivation of the present invention is described in detail with reference to the attached drawings 1 to 3.

[0047] First, FIG. 1 is a block diagram of a hydroponic sprout delivery system according to an embodiment of the present invention, FIG. 2 is a block diagram of an intermediate block diagram of a delivery information collection unit in a hydroponic sprout delivery system according to an embodiment of the present invention, and FIG. 3 is a block diagram of an intermediate block diagram of a loading sensor unit in a hydroponic sprout delivery system according to an embodiment of the present invention.

[0048] Referring to FIG. 1, a hydroponic sprout delivery system (100) according to an embodiment of the present invention may include an information collection unit (110), a delivery information collection unit (120), an optimal delivery route calculation unit (130), a normal delivery determination unit (140), and a compensation unit (150).

[0049] The hydroponic sprout delivery system (100) of the present invention transmits shipment information and delivery information to a delivery person for sprout products shipped from a production site, and transmits and receives data on the delivery device, delivery status, and delivery status to and from the delivery person and the consumer until the delivery person delivers the shipped sprout products using the delivery device.

[0050] Here, the above-mentioned delivery person may mean a person who performs delivery by operating or driving a delivery device.

[0051] The above information collection unit (110) can collect consumer information, order information, and delivery request date information.

[0052] More specifically, the information collection unit (110) can collect personal information of the consumer required for order execution, such as the consumer's name, age, ID, payment details, payment method, payment card, purchase history, address, contact information, and email address.

[0053] In addition, the above order information may refer to detailed information on the hydroponic sprouts, seeds, products, order quantity, order frequency, and ordered products purchased by the consumer.

[0054] Meanwhile, the above delivery request date information allows the consumer to select a delivery date when ordering hydroponic sprouts through the information collection unit (110), but can designate a delivery request date a preset number of days after the order date based on the consumer's address.

[0055] For example, if the above-mentioned sprout production site for hydroponic cultivation is located in Uijeongbu-si, Gyeonggi-do, and a consumer with an address in Seo-gu, Busan orders ginseng sprouts for hydroponic cultivation on June 20, 2023 and enters a delivery request date, the delivery request date can only be entered as a date after June 23, 2023.

[0056] Through this, if the distance between the production site and the consumer's address is greater than a certain distance, realistically, the delivery date can be excluded in advance for which it is difficult to arrive within the deadline.

[0057] The above delivery information collection unit (120) can collect environmental information and delivery status collected from a delivery device that performs delivery from the production site to the consumer's address.

[0058] Here, the delivery device refers to a truck, ship, drone, etc. for delivering goods, and may further include a maintenance device in which sprout products are loaded and a certain environment can be maintained, a plurality of sensors for collecting environmental information within the loading box, and a device for monitoring this and transmitting and receiving sensing data to and from the maintenance device.

[0059] At this time, the detailed configuration of the delivery information collection unit (120) is described in more detail with reference to FIGS. 2 and 3.

[0060] Referring to FIG. 2, the delivery information collection unit (120) may include a loading sensor unit (121) and a monitoring unit (122).

[0061] The above loading sensor unit (121) can collect environmental information by providing a temperature measurement sensor, an oxygen concentration measurement sensor, a carbon dioxide concentration measurement sensor, and a humidity measurement sensor inside the loading box where sprout products are loaded in the delivery device.

[0062] Here, the environmental information may refer to measurement information collected from a temperature measurement sensor or humidity measurement sensor provided inside the loading box.

[0063] At this time, the loading sensor unit (121) may include a sensor information collection unit (121a), a sensor error measurement unit (121b), and a data transmission unit (121c) according to FIG. 3.

[0064] The above sensor information collection unit (121a) can collect the supply voltage, consumption current, and output voltage supplied to the above-mentioned measurement sensor.

[0065] More specifically, the load sensor unit (121) can collect the supply voltage, consumption current, and output voltage supplied from the power source by further providing a voltage measuring sensor on the power supply line and output line of the measuring sensor.

[0066] At this time, the above measurement sensor means one of the temperature measurement sensor, the harmful gas concentration measurement sensor, and the dust amount measurement sensor mentioned in the above loading sensor unit (121), and an identical sensor (a sensor of the same model) within a preset radius from the measurement sensor may be provided as a comparison sensor.

[0067] Here, the preset radius is ideally located within a radius of 10 mm to 500 mm from the center position of the measurement sensor, and it can be judged that the closer it is to the measurement sensor, the higher the accuracy when compared.

[0068] The above sensor error measurement unit (121b) can extract a comparison target time, which is a time when the rate of change in the measured value of the sensing data collected from the measurement sensor exceeds a preset rate.

[0069] Here, the preset ratio can be set to a ratio of 25% to 30%, and the setting can be changed from a minimum of 10% to a maximum of 90% depending on the type of measurement sensor and the surrounding environment.

[0070] In addition, the method for calculating the rate of change in the measured value of the sensing data is as follows: the measured value T measured at time t2 within the time range of the sensing data collected by the sensor information collection unit (121a) t2 t in a The measurement value T measured at time t1, which is a time interval t1 T is the value minus t1 After dividing the measurement value, multiplying it by 100 to obtain the absolute value, the rate of change in the measurement value can be calculated.

[0071] For example, if the time interval set by the system administrator is 2 seconds, the total measurement time from the start of operation of the current measurement sensor, the temperature sensor, to the end is 2000 seconds, and the measurement value measured at 1520 seconds is 21℃ and the measurement value measured at 1518 seconds is 31.6℃, the measurement value change rate can be calculated as approximately -50.47% (100*(21-2318.6) / 21). At this time, if the measurement value change rate ratio extracted as the comparison target time preset by the system administrator is at most 30%, 1518 seconds can be extracted as the comparison target time because the measurement value change rate exceeds 30%.

[0072] Meanwhile, if there is no time at which the rate of change in the measured value exceeds a preset rate and is therefore not extracted, the sensor error measurement unit (121b) can extract sensing data corresponding to n arbitrary times within the sensing data as comparison target times and transmit the extracted data to the monitoring unit (122).

[0073] Here, the method of extracting random n visual points within the sensing data can be performed using a program using a programming language, and the programming language can mean Python, Java, C language, C++, JavaScript, Go, Ruby, Swift, Kotlin, PHP, C# (C Sharp), etc.

[0074] For example, a method for extracting n random times from sensing data using Python can be done by setting the time range in which the sensor operates in the sensing data using the Random module and the Datetime module and then extracting n random times, or by using the Numpy module.

[0075] Additionally, another method for randomly extracting n time points within the sensing data is to apply the Fisher-Yates shuffle algorithm to the time range of the sensing data to randomly extract n time points within the sensing data.

[0076] Meanwhile, among the n points of time extracted from the above sensor error measurement unit (121b), n means a natural number that may vary depending on the operating environment set by the system administrator, and the meaning of the arbitrary point of time may mean a point of time extracted in a random format without regularity from the entire time collected from the sensing data.

[0077] The above data transmission unit (121c) can periodically transmit the comparison target time of the sensor error measurement unit (121b) to the monitoring unit (122).

[0078] In addition, the data transmission unit (121c) can transmit data including the supply voltage, consumption current, and output voltage of the measurement sensor collected by the sensor information collection unit (121a) to the monitoring unit (122).

[0079] Through the above process, the loading sensor unit (121) can transmit sensing data, which is a set of measurement values ​​collected from a plurality of measurement sensors, to the delivery terminal, and the system administrator can distinguish a section in which the change rate of the sensing data does not exceed a preset change rate in response to a set time interval as a 'standard state section', and distinguish a section in which the change rate exceeds the preset change rate as an 'abnormal state section'.

[0080] Here, when the 'abnormal state section' of the sensing data collected from the loading sensor unit (121) using the input device including the delivery terminal exceeds the maximum time range of the 'abnormal state section' set by the system administrator or the number of times the 'abnormal state section' has occurred exceeds a certain number of times, the process of the process in which the sensor is located, the system is temporarily stopped, the power is cut off, etc. can be set to be automatically performed. Through this, a quick response to the occurrence of an abnormal phenomenon can be performed.

[0081] In addition, the loading sensor unit (121) can use sensing data collected from a plurality of measurement sensors provided in the loading box included in the delivery device to transmit the environmental status inside the loading box to the monitoring unit (122) and a preset delivery terminal to determine the internal environment of the loading box.

[0082] Here, the above-described delivery terminal refers to an electronic device capable of wired or wireless communication, display, input and output, and may refer to a PC, laptop, smartphone, tablet PC, etc. that transmits and receives data with the loading box and monitoring unit (122).

[0083] In addition, depending on the system administrator settings, if the measured value is outside the upper and lower limits of the relative humidity measurement value set by the system administrator, it may be classified as an 'abnormal condition section'.

[0084] For example, when the average value of the relative humidity measured using a humidity measuring sensor located in a loading box in a delivery device that performs wireless communication with the hydroponic sprout delivery system (100) is 90 to 95%, and the system administrator sets the sensing data change rate setting value to 20%, and the sensing data measuring the relative humidity from 0 seconds to 46,800 seconds is used to classify it as a 'standard state section' or an 'abnormal state section', a section in which the change rate per second of the relative humidity exceeds 20%, which is the same value as the sensing data change rate setting value, can be classified as an 'abnormal state section', and a section in which the change rate per second is less than 20% can be classified as a 'standard state section'.

[0085] Meanwhile, under the above conditions, if the system administrator sets the upper limit of the relative humidity to 95% and the lower limit to 90%, and the relative humidity measured at 149 seconds is 72%, the relative humidity measured at 150 seconds is 91%, and the relative humidity measured at 151 seconds is 97%, the rate of change for the 149 to 150 second section can be calculated as approximately 26.38% (100*(91-72) / 72). At this time, the 149 to 150 second section can be classified as an 'abnormal state section' because the rate of change per second exceeds 20%. In addition, the rate of change per second for the above 150 to 151 second section is calculated as approximately 6.59% (100*(97-91) / 91), which means that the rate of change per second does not exceed 20%. However, since the relative humidity measurement value measured at 151 seconds exceeded 95%, which is the upper limit set by the system administrator, it can be classified as an 'abnormal condition section'.

[0086] In addition, the loading sensor unit (121) can further provide an infrared sensor in the loading box inside the delivery device or in the space where the sprout product is located, so as to sense whether the loading box is horizontal during the time it is delivered from the production site to the consumer, and extract only the time determined to be horizontal.

[0087] For example, the loading sensor unit (121) is configured to provide a reflective type infrared sensor in a space where a loading box is provided inside the delivery device, and the loading box is positioned to block or reflect the reflective type sensor. Then, a light emitting diode (LED) and an infrared receiver (Photodiode) are arranged so that infrared rays generated from the LED are reflected by an object and reach the infrared receiver, and the amount of reflected infrared rays is measured to determine changes in horizontal movement of the sprout product.

[0088] Meanwhile, in the case of sprout products for which the leveling of the sprout products is of high importance, a gyroscope sensor may be additionally installed in the delivery device to calculate in detail the change in inclination by time period for three axes during delivery from the production site to the consumer, and transmit the corresponding data to the delivery terminal or monitoring unit (122).

[0089] The above monitoring unit (122) can receive sensing data collected from the loading sensor unit (121) and transmit the environmental status to a preset delivery terminal.

[0090] Here, the above environmental condition may mean the current condition based on environmental information collected from measurement sensors provided in the loading sensor unit (121).

[0091] At this time, the current status may mean the status within the loading box, such as indicating it as good when the difference between the delivery environment (temperature, humidity, oxygen concentration, etc.) of the sprout products loaded in the loading box and the environmental information (temperature, humidity, oxygen concentration, etc.) of the loading box is sensed to be less than the standard value.

[0092] Meanwhile, the system administrator can set and change the settings for specifying the reference data value for indicating the above environmental status, whether to display a notification, and the notification display text corresponding to the reference data value.

[0093] In addition, the monitoring unit (122) uses the sensing data collected from the measurement sensor and the comparison sensor and the comparison target time to calculate the sensor failure probability (S) according to the following [Mathematical Formula 1]. TR ) can be produced.

[0094] [Mathematical Formula 1]

[0095]

[0096] (Here, S TR is the probability of sensor failure, T ms1 is the measurement value of the measurement sensor at the first time, T ms2 is the measurement value of the measurement sensor at the second time, Tms3 is the measurement value of the measurement sensor at the third time, T msn is the measurement value of the measurement sensor at the nth time, T cst1 is the measurement value of the comparison sensor at the first time, T cst2 is the measurement value of the comparison sensor at the second time, T cs3 is the measurement value of the comparison sensor at the third time, T csn is the measurement value of the comparison sensor at the nth time, T msav is the average measurement value of the measurement sensor, and SE means the efficiency deviation of the measurement sensor.)

[0097] At this time, the average efficiency (SE) of the above measurement sensor av ) can be calculated according to the following [Mathematical Formula 2].

[0098] [Equation 2]

[0099]

[0100] (Here, SE av is the average efficiency of the measuring sensor, SE i refers to the initial efficiency of the measuring sensor)

[0101] The average efficiency of the above measurement sensor can be calculated according to the following [Mathematical Formula 3].

[0102] [Equation 3]

[0103]

[0104] (Here, W IN1 is the power supplied to the measurement sensor at the first time, W OUT1 The power measured when the measurement value sensed by the measurement sensor at the first time is output as an electrical signal, W IN2 is the power supplied to the measurement sensor at the second time, W OUT2 The power measured when the measurement value sensed by the measurement sensor at the second time is output as an electrical signal, W INn is the power supplied to the measurement sensor at the nth time, W OUTn It means the power measured when the measurement value sensed by the measurement sensor at the nth time is output as an electrical signal.

[0105] At this time, the n time points mentioned in the above [Mathematical Formula 1] to [Mathematical Formula 3] may mean the number of multiple time points or randomly extracted time points at which the rate of change in the measured value of the sensing data extracted from the sensor error measurement unit (121b) exceeds a preset rate.

[0106] For example, in a state where a first temperature sensor provided as a measurement sensor in a loading box of a goods transport truck, which is the delivery device, and a second temperature sensor, which is the same model as the first temperature sensor and is provided as a comparison sensor within a radius of 10 mm, are provided, the input / output voltage of the first temperature sensor and the current consumption inside the measurement sensor can be displayed. At this time, when three times are extracted from the measurement sensor, and the voltages supplied during the extracted first to third times are 4.9 V, 5 V, and 5 V, and the measurement sensor is measured to consume currents of 1 mA, 0.9 mA, and 1.1 mA at the corresponding times and output as 10 mV, 9 mV, and 11 mV, the input power (W) supplied to the measurement sensor at the first time IN1 ) is 0.0049W (4.9V*0.001A), and the input power at the second time (W IN2 ) is 0.0045W (5V*0.0009A), and the input power at the third time point (W IN3 ) can be calculated as 0.0055W (5V*0.0011A). In addition, the output power (W) of the first time output from the measurement sensor out1 ) is 0.00001W (0.01V*0.001A), the output power of the second time (W OUT2- ) is 0.0000081W (0.009V*0.0009A), the output power of the third visual (W OUT3 ) can be calculated as 0.0000121W (0.011V*0.0011A). Using this, the average efficiency (SE) of the above measurement sensor av) can be calculated as approximately 0.2(100 / 3*(0.00001 / 0.0049+0.0000081 / 0.0045+0.0000121 / 0.0055)). At this time, the initial efficiency (SE) provided by the manufacturer of the measuring sensor being measured i ) is 0.2%, the efficiency deviation (SE) of the measuring sensor can be calculated as 0. Here, the average efficiency (SE) of the measuring sensor av ) is an efficient sensor the lower the output value is, and the higher the output value is than the initial efficiency, which is the efficiency calculated using the measurement values ​​collected from the manufacturer or initially measured, the higher the probability of failure in the electrical domain of the sensor. Meanwhile, the initial efficiency (SE) of the measurement sensor i ) is not provided, the initial efficiency (SE) is the efficiency measured before being placed in the above loader. i ) can be set and input to the monitoring unit (122).

[0107] In addition, in an environment where the temperature inside the loading box is set to be maintained at 22 degrees, sensing data according to the operation of the first temperature sensor provided in the loading box can be collected from 0 seconds to 28,800 seconds. At this time, when the average measurement value collected from the first temperature sensor is 22.5 degrees Celsius, and three random times are extracted from the sensing data of the first temperature sensor using a sensing data processing program, the measurement values ​​measured at each time can be extracted as 21 degrees Celsius (485 seconds), 22 degrees Celsius (1893 seconds), and 23 degrees Celsius (2021 seconds). Here, when the measurement values ​​measured at the same time and each time from the second temperature sensor that operates simultaneously with the first temperature sensor are 21.5 degrees Celsius (485 seconds), 23 degrees Celsius (1893 seconds), and 22.5 degrees Celsius (2021 seconds), the failure probability (S) of the first temperature sensor TR ) can be calculated. That is, the failure probability (S) of the first temperature sensor TR) can be calculated as approximately 2.96% (Min((|21-21.5|+|22-23|+|23-22.5|) / (3*22.5)*100+0), 100).

[0108] As another example, the monitoring unit (122) calculates the sensor failure probability (S) according to the following [Mathematical Formula 1-2], which reflects the weight according to the distance between the measurement sensor and the comparison sensor. TR ) can be produced.

[0109] [Equation 1-2]

[0110]

[0111] (Here, D v refers to the distance weighting of the measurement sensor and the comparison sensor)

[0112] At this time, the distance value weight (D-) of the above measurement sensor and comparison sensor v ) is applied in response to the weight set by the shipper, and the system administrator can freely change and apply the weight.

[0113] For example, if the measurement sensor and the comparison sensor are provided in the above-mentioned loading box as temperature measurement sensors of the same model, the distance weight (D) of the measurement sensor and the comparison sensor according to the distance (D) of the measurement sensor and the comparison sensor v ) can be calculated according to [Table 1] below.

[0114] [Table 1]

[0115]

[0116] At this time, the distance weight (D v ) is the same condition as the above example that does not reflect the distance weight (D v ) is the failure probability of the first temperature sensor (S TR ) can be calculated as approximately 2.96% (Min((|21-21.5|+|22-23|+|23-22.5|) / (3*22.5)*100+0), 100).

[0117] Through the above process, the monitoring unit (122) uses the sensing data collected from the load sensor unit (121) to determine the failure probability (S) of the sensor. TR ) can be produced.

[0118] In addition, the failure probability (S) calculated through the above monitoring unit (122) TR ) exceeds the preset ratio, a sensor failure notification, replacement notification, etc. can be transmitted to the preset delivery terminal.

[0119] Here, the failure probability (S TR ) can be set to 40% by default, and the system administrator can reset the ratio between 0 and 99% depending on the type and sensitivity of the sensor.

[0120] Referring again to Figure 1, the optimal delivery route calculation unit (130) can calculate the optimal delivery route from the production site to the consumer's address and transmit it to a preset delivery terminal and delivery device.

[0121] More specifically, the optimal delivery route calculation unit (130) can calculate the optimal delivery route using algorithm technology.

[0122] Here, the above algorithm technology may be Dijkstra's Algorithm, A Algorithm, Genetic Algorithm, Dynamic Programming, Combined Pickup and Delivery Problem, etc.

[0123] For example, when the optimal delivery route calculation unit (130) needs to calculate an optimal delivery route that reflects distance and real-time traffic information, it can calculate an optimal delivery route using an A algorithm that supports fast route search by utilizing a heuristic function and performs route modification reflecting distance, expected cost, and real-time traffic information, and transmit the result to the preset delivery terminal and delivery device.

[0124] The above normal delivery determination unit (140) can determine whether or not normal delivery has occurred based on the delivery request date and consumer information collected by the information collection unit (110), the environmental information collected by the delivery information collection unit (120), and whether or not delivery has occurred.

[0125] More specifically, the normal delivery judgment unit (140) calculates a delivery score (D) according to the following [Mathematical Formula 4] in response to the environmental information, delivery request date information, and delivery completion time collected during the delivery period from the time the sprout product is loaded into the delivery device to the time delivery to the consumer is completed. s ) can be produced.

[0126] [Equation 4]

[0127]

[0128] (Here, D w is the delivery date weight, DD r is the actual delivery date, DD a is the delivery request date, S TR·T is the probability of failure of the temperature measurement sensor, O T·av The optimal delivery temperature for sprout products, M T·av is the average temperature during the delivery period, S TR·O is the probability of failure of the oxygen concentration measurement sensor, O O·av is the optimal oxygen concentration for delivery of sprout products, M O·av is the average oxygen concentration during the delivery period, S TR·C is the probability of failure of the carbon dioxide concentration measurement sensor, O C·av is the optimal carbon dioxide concentration for delivery of sprout products, M C·avis the average carbon dioxide concentration during the delivery period, S TR·H is the probability of failure of the humidity measurement sensor, O H·av The optimum humidity for delivery of sprout products, M H·av refers to the average humidity during the delivery period)

[0129] For example, a consumer purchases hydroponic Redville sprouts on June 25, 2023, and requests delivery on the delivery date (DD a ) was set on July 1, 2023, and when the actual delivery was completed on July 2, 2023, when the Redville sprouts arrived at the consumer, the delivery person entered the actual delivery completion date into the terminal, and the delivery score (D s ) can be automatically calculated and displayed. Here, the delivery score (D s ) to calculate the delivery temperature, oxygen concentration, carbon dioxide concentration and humidity according to the delivery sprout product, and when the above Redville sprout product is determined, the delivery temperature (O) according to the manual T·av ) is 22℃, the optimal oxygen concentration for delivery (O O·av ) is 22%, and the delivery-appropriate carbon dioxide concentration (O C·av ) is 1150ppm, and the optimum humidity for delivery (O H·av ) is 60%, and the delivery date weighting (DD) w ) can be set to 3. In addition, the average temperature (M) inside the loading box of the delivery device loaded with Redville sprout products during the delivery period from the time of loading from the production site on July 1, 2023 until delivery to the consumer on July 2, 2023 T·av ) is 21.5℃, average oxygen concentration (M O·av ) was 22.1%, and the average carbon dioxide concentration (M C·av ) is 1200ppm, average humidity (M H·av ) is 58%, and the failure probability of the temperature measurement sensor (S) according to the above [Mathematical Formula 1] to [Mathematical Formula 1-2] TR·T ) is 3.5%, the probability of failure of the oxygen concentration measurement sensor (S TR·O) is 2.1%, the probability of failure of the carbon dioxide concentration measurement sensor (S TR·C ) is 3.1%, and the probability of failure of the humidity measurement sensor (S TR·H ) is 2.5%, the above delivery score (D s ) can be calculated as approximately 3.3(3*(2-1)+(3.5*0.5 / 22+2.1*0.1 / 22+3.1*50 / 1150+2.5*2 / 60)).

[0130] Through this, the normal delivery judgment unit (140) calculates the calculated delivery score (D s ) can be used to determine whether normal delivery has occurred.

[0131] Here, the normal delivery judgment unit (140) calculates the calculated delivery score (D s ) According to [Table 2], the delivery status can be judged as best, normal, suspected of spoilage, high probability of spoilage, undeliverable, etc.

[0132] [Table 2]

[0133]

[0134] At this time, if the range of the above [Table 2] is '0~40', the delivery score (D) is 0 or more and less than 40. s ) means, and the '40~120' item means a delivery score of 40 or more but less than 120 (D s ) means, and the '120~' item is 120 or more for delivery score (D s ) may mean that the result is produced.

[0135] Also, DD r -DD a =0 means that the delivery request date and the actual delivery date are the same, and DD r -DD a ≠0 means that there is a difference between the delivery request date and the actual delivery date, and it means that the actual delivery date is sent earlier or delayed from the delivery request date, but it can generally mean that it is delayed.

[0136] That is, the delivery score (D) of the Redville sprout product exemplified above s) is calculated as approximately 3.3, and when the normal delivery judgment unit (140) performs a judgment in response to the above [Table 2], the Redville sprout product can be judged as ‘good’.

[0137] Meanwhile, the delivery score (D) of the above [Table 2] s ) The scope and delivery status can be automatically applied to the delivery terminal by the system administrator freely changing the settings.

[0138] In addition, the delivery status classified according to the above [Table 2] is also transmitted to the consumer terminal, so that the consumer can check the current status and send a message or pop-up message to the delivery terminal to ask whether or not to receive the sprout product, and depending on the consumer's response, a delivery progress or delivery interruption notification can be sent.

[0139] The above compensation unit (150) can provide preset compensation to the delivery person and the consumer in response to whether the delivery is normal as determined by the normal delivery determination unit (140).

[0140] More specifically, the compensation unit (150) may impose compensation or a penalty on the delivery person and the consumer when the delivery score calculated by the normal delivery judgment unit (140) is below a preset standard.

[0141] For example, the compensation unit (150) may provide benefits such as awarding points, reducing fees, and improving reliability scores for each delivery unit if the delivery judgment criteria of the normal delivery judgment unit (140) are displayed according to the status in [Table 2], and if the delivery unit determines that the status is 'best' based on the delivery score, delivery request date, and actual delivery date when delivering the sprout product to the consumer, the compensation unit (150) may provide benefits such as awarding points, reducing fees, and improving reliability scores for each delivery unit. Conversely, if the delivery is made in a 'suspected spoilage or undeliverable' status, which is below 'normal', the compensation unit may impose penalties such as increasing fees and reducing reliability scores for the delivery unit. In this case, if the consumer who ordered the sprout product maintains the delivery of the sprout product as is, an 80% refund may be provided for sprout products determined to be 'suspected spoilage', and an amount equivalent to 110% of the order amount may be refunded for sprout products determined to be 'high probability of spoilage' to 'undeliverable', thereby providing compensation to the consumer.

[0142] Through the above process, the hydroponic sprout delivery system (100) provides hydroponic sprout products from the production site where hydroponic sprouts are manufactured and shipped to consumers of hydroponic farms or consumers who grow crops through small-scale hydroponics, and inputs environmental information corresponding to the sprout products into the loading compartment of a delivery device such as a vehicle (truck) or drone, and determines whether the environmental information is maintained during the delivery period to determine whether the delivery is performed in a fresh state, and can display the status on the terminals of the delivery person and the consumer. In addition, the reliability of the sensing data can be improved by including a configuration that calculates the failure probability of the sensor by adding an identical sensor within a certain distance of an environmental information measuring sensor provided in a loaded space. Through this, a delivery score is calculated, and the delivery status is judged based on the calculated delivery score. If the delivery status is judged to be above the 'normal' level, a reward such as a reduced fee or a reliability score can be paid to the delivery person, and if the opposite is true, a penalty can be imposed. Also, if the consumer receives the sprout product with a level below 'normal', the system (100) provides a refund based on the order amount, thereby inducing both the consumer and the delivery person to improve their satisfaction and sense of duty regarding the delivery of the sprout product.

[0143] According to one embodiment of the present invention, by receiving data from a sensor that senses environmental information of a loading box loaded with sprout products in a delivery device and providing an optimal delivery route to a delivery person, sprout products with high freshness can be delivered on a delivery date set by a consumer.

[0144] In addition, by calculating the failure probability of the sensor that collects environmental information within the delivery device, it is possible to perform repairs, replacements, and inspections on sensors with a high failure probability to accurately determine the delivery status of sprout products.

[0145] In addition, by calculating a delivery score that reflects the delivery request date entered by the consumer, the actual delivery date, the measurement values ​​of the measurement sensors in the delivery device, environmental information for maintaining the freshness of the delivered sprout products, average environmental information during the delivery period, and the failure probability of the measurement sensors, it is possible to objectively determine whether the sprout products have deteriorated during the delivery process.

[0146] Although the embodiments of the present invention have been described with limited examples and drawings, the embodiments of the present invention are not limited to the embodiments described above, and various modifications and variations are possible based on this description by those skilled in the art to which the present invention pertains. Therefore, the embodiments of the present invention should be understood solely by the scope of the claims set forth below, and all equivalent or equivalent modifications thereof are deemed to fall within the scope of the present invention.

[0147]

[0148] 100: Hydroponic Sprout Delivery System

[0149] 110: Information Collection Department

[0150] 120: Delivery Information Collection Department

[0151] 121: Loading sensor section

[0152] 121a: Sensor information collection unit

[0153] 121b: Sensor error measurement unit

[0154] 121c: Data transmission section

[0155] 122: Monitoring Department

[0156] 130: Optimal delivery route calculation section

[0157] 140: Normal delivery judgment department

[0158] 150: Compensation Department

Claims

1. In a system that delivers sprout products shipped from a production site that produces sprouts for hydroponic cultivation to consumers, Information collection unit that collects the above consumer information, order information, and delivery request date information; A delivery information collection unit that collects environmental information and delivery status collected from a delivery device that performs delivery from the above production site to the above consumer's address; An optimal delivery route calculation unit that calculates an optimal delivery route from the above production site to the above consumer's address and transmits the calculated route to a preset delivery terminal and the above delivery device; A normal delivery judgment unit that judges whether or not normal delivery has occurred based on the delivery request date collected from the information collection unit, the consumer information, the environmental information collected from the delivery information collection unit, and the delivery status; and A compensation department that provides preset compensation to the delivery person and the consumer in response to whether or not the normal delivery has been determined by the above normal delivery judgment department; A hydroponic sprout delivery system characterized by including:

2. In paragraph 1, The above delivery information collection department, A loading sensor unit that collects the environmental information by providing a temperature measuring sensor, an oxygen concentration measuring sensor, a carbon dioxide concentration measuring sensor, and a humidity measuring sensor inside a loading box in which the sprout product is loaded within the delivery device; A monitoring unit that receives sensing data collected from the above loading sensor unit and transmits the environmental status to the preset delivery terminal; Including, The above loading sensor part, A sensor information collection unit that collects the supply voltage, consumption current, and output voltage supplied to the above measurement sensor; A sensor error measurement unit that extracts a comparison target time, which is a time when the rate of change in the measured value of the sensing data exceeds a preset rate; and A data transmission unit that periodically transmits the comparison target time of the above sensor error measurement unit to the above monitoring unit; Includes, The above sensor error measurement unit, A hydroponic sprout delivery system characterized in that, if there is no time exceeding the above-mentioned preset ratio, sensing data corresponding to n random times in the sensing data is extracted as a time to be compared.

3. In paragraph 2, The above sensor part, A comparison sensor is provided with an identical sensor within a preset radius from at least one of the temperature measurement sensor, oxygen concentration measurement sensor, carbon dioxide concentration measurement sensor, and humidity measurement sensor. The above monitoring unit, Using the sensing data collected from the above measurement sensor and the comparison sensor and the comparison target time, the sensor failure probability (S) is calculated according to the following [Mathematical Formula 1] TR ) is produced, [Mathematical Formula 1] (Here, S TR is the probability of sensor failure, T ms1 is the measurement value of the measurement sensor at the first time, T ms2 is the measurement value of the measurement sensor at the second time, T ms3 is the measurement value of the measurement sensor at the third time, T msn is the measurement value of the measurement sensor at the nth time, T cst1 is the measurement value of the comparison sensor at the first time, T cst2 is the measurement value of the comparison sensor at the second time, T cs3 is the measurement value of the comparison sensor at the third time, T csn is the measurement value of the comparison sensor at the nth time, T msav is the average measurement value of the measurement sensor, and SE means the efficiency deviation of the measurement sensor.) The efficiency deviation (SE) of the above measurement sensor is calculated according to the following [Mathematical Formula 2], [Equation 2] (Here, SE av is the average efficiency of the measuring sensor, SE i refers to the initial efficiency of the measuring sensor) A hydroponic sprout delivery system characterized in that the average efficiency of the above measurement sensor is calculated according to the following [Mathematical Formula 3]. [Equation 3] (Here, W IN1 is the power supplied to the measurement sensor at the first time, W OUT1 The power measured when the measurement value sensed by the measurement sensor at the first time is output as an electrical signal, W IN2 is the power supplied to the measurement sensor at the second time, W OUT2 The power measured when the measurement value sensed by the measurement sensor at the second time is output as an electrical signal, W INn is the power supplied to the measurement sensor at the nth time, W OUTn It means the power measured when the measurement value sensed by the measurement sensor at the nth time is output as an electrical signal.

4. In paragraph 3, The above normal delivery judgment department is, The delivery score (D) is calculated according to the following [Mathematical Formula 4] in response to the environmental information collected during the delivery period from the time the above sprout product is loaded onto the delivery device to the time delivery to the above consumer is completed, the delivery request date information, and the delivery completion time. s ) is produced, [Equation 4] (Here, D w is the delivery date weight, DD r is the actual delivery date, DD a is the delivery request date, S TR·T is the probability of failure of the temperature measurement sensor, O T·av The optimal delivery temperature for sprout products, M T·av is the average temperature during the delivery period, S TR·O is the probability of failure of the oxygen concentration measurement sensor, O O·av is the optimal oxygen concentration for delivery of sprout products, M O·av is the average oxygen concentration during the delivery period, S TR·C is the probability of failure of the carbon dioxide concentration measurement sensor, O C·av is the optimal carbon dioxide concentration for delivery of sprout products, M C·av is the average carbon dioxide concentration during the delivery period, S TR·H is the probability of failure of the humidity measurement sensor, O H·av The optimum humidity for delivery of sprout products, M H·av refers to the average humidity during the delivery period) A hydroponic sprout delivery system that determines whether delivery is normal based on the above delivery score.

5. In paragraph 4, The above compensation department, A hydroponic sprout delivery system that imposes compensation or penalties on the delivery person and the consumer in response to the delivery score calculated by the above normal delivery judgment unit.

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