JP7718792B2 - Cargo handling system, cargo handling management program, and cargo handling management method - Google Patents

Description

The present invention relates to a cargo handling system that uses forklifts, and a cargo handling management program and cargo handling management method used in the system.

Fruit and vegetables are harvested, placed in boxes, and transported by truck, and then transported to a sorting machine by forklift. Conventionally, sorting machines are known that measure and sort fruit size, weight, sugar content, etc. using various sensors and image processing technology. For example, Patent Document 1 discloses a method of irradiating fruit with light containing near-infrared rays, capturing an image of the reflected light, and using the generated image to detect blemishes on the fruit that cannot be detected under visible light.

However, the condition of the fruits and vegetables can vary from box to box, and some fruits and vegetables in certain boxes may have many scratches or be in a state of advanced deterioration. It is preferable for such fruits and vegetables in such boxes to be prioritized and then sorted by a sorting machine before being shipped, but without the use of the sensors and image processing technology described above, scratches and deterioration often cannot be detected. As a result, the shipment of fruits and vegetables that should be shipped earlier can be delayed.

JP 2012-147279 A

The problem that this invention aims to solve is to provide a loading and unloading system that can preliminarily sort fruits and vegetables into containers before they are unloaded by a forklift.

In order to solve the above problems, the cargo handling system according to the present invention comprises:
A cargo handling system including a plurality of containers placed in a predetermined area and a forklift for handling the containers,
an unmanned aerial vehicle having an infrared camera, which takes an image of a cargo box with the infrared camera before cargo handling to generate a cargo image;
and a cargo handling determination unit that determines the cargo placement location and/or cargo handling order of the cargo boxes based on the cargo image.

The cargo handling system preferably comprises:
The cargo handling determination unit has a score output unit that analyzes the cargo image and outputs a score, and determines a cargo placement location and/or a cargo handling order based on the score output by the score output unit.

The cargo handling system includes, for example:
The contents of the container are fruits and vegetables,
The score output unit analyzes the images of the fruits and vegetables and outputs the degree of damage to the fruits and vegetables as a score.

The cargo handling system includes, for example:
The contents of the container are fruits and vegetables,
The score output unit analyzes the package image and outputs the degree of internal quality as a score.

The cargo handling system includes, for example:
An identifier relating to the contents of the packing box is displayed on the surface of the packing box, and the identifier is covered with a material that is permeable to near-infrared rays to prevent the packing box from shifting.
The infrared camera captures the identifier through the cargo protection material,
The loading/unloading determination unit determines the loading location and/or loading order of the boxes based on the information contained in the identifiers.

The cargo handling system preferably comprises:
Further provided with a notification unit,
The notification unit notifies the operator of the forklift of the loading location and/or loading order determined by the loading/unloading determination unit.

In order to solve the above problems, the cargo handling management program according to the present invention comprises:
a forklift that loads and unloads boxes placed in a predetermined location;
an unmanned aerial vehicle having an infrared camera, which takes an image of the contents of a cargo box with the infrared camera before cargo handling to generate a cargo image;
A cargo handling management program used in a cargo handling system including a computer having an arithmetic unit and a storage unit,
The cargo handling management program is installed on the computer.
a score output unit that analyzes the package image and outputs a score;
The score output unit is operated as a loading/unloading determination unit that determines the loading location and/or loading order of the packing boxes based on the scores output by the score output unit.

In order to solve the above problems, the cargo handling management method according to the present invention comprises:
A cargo handling management method used in a cargo handling system including a cargo box placed in a predetermined area, a forklift that handles the cargo box, an unmanned aerial vehicle having an infrared camera, and a cargo handling determination unit,
Taking an image of the cargo box with an infrared camera before handling and generating a cargo image;
The loading and unloading process includes determining, by a loading and unloading determination unit, the loading and unloading locations and/or the loading and unloading order of the boxes based on the load image.

The loading and unloading system of the present invention can preliminarily sort fruits and vegetables into containers before they are unloaded by a forklift.

1 is a schematic front view of a cargo handling system according to a first embodiment of the present invention. FIG. 2 is a schematic plan view of the cargo handling system shown in FIG. 1 . FIG. 2 is a block diagram of the cargo handling system shown in FIG. 1 . FIG. 1 is a perspective view showing an unmanned aerial vehicle capturing an image of a shipping box. A shows a view of the fruit and vegetables under visible light, and B shows a portion of a load image generated by a near-infrared camera. FIG. 2 is a flow chart showing the flow of cargo handling work in the cargo handling system according to the first embodiment. FIG. 4 is a schematic front view of a cargo handling system according to a second embodiment of the present invention. FIG. 8 is a block diagram of the cargo handling system shown in FIG. 7. FIG. 1 is a perspective view showing an unmanned aerial vehicle capturing an image of a shipping box. 1 shows a load image generated by a near-infrared camera. FIG. 10 is a flow chart showing the flow of cargo handling work in the cargo handling system according to the second embodiment.

First Embodiment
First, a first embodiment of a cargo handling system, cargo handling management program, and cargo handling management method according to the present invention will be described with reference to Figures 1 to 6. Figure 1 is a schematic front view of a cargo handling system S according to the first embodiment of the present invention, and Figure 2 is a schematic plan view of the cargo handling system S. Figure 3 is a block diagram of the cargo handling system S. As shown in Figure 2, a first area E1, a second area E2, and a third area E3 are set within a facility according to this embodiment.

As shown in Figures 1 and 2, the cargo handling system S comprises a truck T, an unmanned aerial vehicle 1, a forklift 2, and a management device 3. In this embodiment, the "predetermined area" of the present invention is the loading platform of the truck T, and the multiple cargo boxes B managed by the cargo handling system S are multiple cargo boxes B transported by the truck T. However, these are merely examples, and the "predetermined area" of the present invention and the cargo boxes B managed by the cargo handling system S are not particularly limited. For example, the cargo handling system S may target cargo boxes B that have been transported by the truck T and are waiting in a specific waiting area.

Furthermore, the cargo handling system S is not particularly limited in the number of unmanned aerial vehicles 1 and forklifts 2. The contents of the cargo box B in this embodiment are apples, but this is just one example, and there is no particular limit as long as the infrared camera 15 can be used to score scratches D and internal quality.

<Unmanned Aerial Vehicles>
The unmanned aerial vehicle 1 is a so-called drone and has a main body 10 (see FIG. 4), four propellers 11 (see FIG. 4) arranged on each of the four sides of the main body 10, and a power unit 12 (see FIG. 3) that rotates the propellers 11. The unmanned aerial vehicle 1 is configured to be able to fly and hover using the propellers 11. The unmanned aerial vehicle 1 is also configured to be able to communicate with a management device 3.

As shown in Figure 3, the unmanned aerial vehicle 1 further has a flight position detection unit 13, a cargo position detection unit 14, an infrared camera 15, and an aerial vehicle control unit 16.

The flight position detection unit 13 has known sensors such as a GPS sensor and an ultrasonic sensor, and uses these sensors to detect the position of the unmanned aerial vehicle 1.

The cargo position detection unit 14 has a camera and an analysis unit. The camera takes an image of the cargo bed of the truck T to generate a cargo bed image, and the analysis unit analyzes the generated cargo bed image to detect the position of the cargo box B. Note that the configuration of the cargo position detection unit 14 is not limited to this; for example, the cargo position detection unit 14 may be configured with two-dimensional LiDAR or three-dimensional LiDAR, which may be used to detect the position of the cargo box B.

The infrared camera 15 is located at the bottom of the main body 10 (see Figure 4). The infrared camera 15 is capable of sensing near-infrared light, and as shown in Figure 4, captures the position of the cargo box B detected by the cargo position detection unit 14 to generate a cargo image. The infrared camera 15 may be configured as a multi-wavelength spectroscopic camera that is also capable of capturing visible light. In this case, the infrared camera 15 may function as the camera for the cargo position detection unit 14.

As shown in Figure 4, all or at least a portion of the top of the shipping box B is open, allowing the contents to be imaged by the infrared camera 15. Alternatively, at least a portion of the shipping box B may be configured to be transparent to near-infrared light, thereby allowing the contents of the shipping box B to be imaged using near-infrared light.

Figure 5A shows a view of fruit or vegetable F under visible light, and Figure 5B shows a portion of a package image generated by a near-infrared camera. As shown in Figure 5A, flaws D on fruit or vegetable F that are not visible under visible light are visible in the package image as shown in Figure 5B.

The unmanned aerial vehicle 1 may further include a near-infrared irradiation unit that is composed of an LED or the like and emits near-infrared light. In this case, the near-infrared irradiation unit irradiates near-infrared light at the position of the cargo box B detected by the cargo position detection unit 14. The infrared camera 15 then scans the near-infrared light reflected by the contents of the cargo box B to generate a cargo image.

Naturally, near-infrared light is not only reflected from the surface of an object, but also penetrates and reflects through the object to a certain extent. Therefore, by adjusting the amount and angle of near-infrared light irradiation, the infrared camera 15 can capture images of the contents of fruit or vegetable F within a range that allows for measurement of blemishes D and internal quality (sweetness, sourness, starch content, discoloration, cavities, etc.).

Based on flight commands from the management device 3, which will be explained later, the aircraft control unit 16 controls the power unit 12 to move the unmanned aircraft 1 to above the loading platform, then controls the cargo position detection unit 14 to detect the position of the cargo boxes B, and controls the infrared camera 15 to generate cargo images corresponding to each cargo box B. The generated cargo images are sent to the management device 3 along with the position information of the corresponding cargo box B.

<Forklift>
As shown in Figures 1 and 2, in this embodiment, the forklift 2 is an unmanned forklift that travels and performs loading and unloading operations autonomously. The forklift 2 has wheels, a vehicle body, forks, and a lifting device 20 (see Figure 3). The forklift 2 is configured so that the forks can be raised and lowered by the lifting device 20, and the forks lift and lower cargo boxes B. The forklift 2 is also configured so that it can communicate with the management device 3.

As shown in FIG. 3, the forklift 2 further includes a vehicle position detection unit 21, a drive unit 22, and a vehicle control unit 23.

The vehicle position detection unit 21 detects the position of the forklift 2 using known sensors such as a GPS sensor or laser sensor. The drive unit 22 drives the wheels and changes direction.

Based on the cargo handling command from the management device 3, the vehicle control unit 23 controls the drive unit 22 to drive the wheels and move the forklift 2 to the commanded position. Furthermore, when the forklift 2 arrives at the commanded position, the vehicle control unit 23 controls the lifting device 20 to raise and lower the cargo box B.

<Management device>
The management device 3 includes a computer, which includes a storage device and an arithmetic unit. The storage device stores a cargo handling management program of the present invention. The cargo handling management program causes the computer to operate as an aircraft command unit 31, a score output unit 32, a cargo handling determination unit 33, and a cargo handling command unit 34, all of which will be described later.

As shown in FIG. 3, the management device 3 has, as its functional configuration, a memory unit 30, an aircraft command unit 31, a score output unit 32, a cargo handling determination unit 33, and a cargo handling command unit 34.

The memory unit 30 stores the position of the bed of a truck T parked in a specified truck area TE. The memory unit 30 also stores the positions of the first, second, and third areas E1, E2, and E3.

When truck T arrives at truck area TE, the aircraft command unit 31 sends a flight command to unmanned aerial vehicle 1, including the location of the loading platform, so that unmanned aerial vehicle 1 flies to the loading platform of truck T.

The score output unit 32 analyzes each package image received from the unmanned aerial vehicle 1 and outputs a score. In this embodiment, the score output unit 32 outputs the degree of damage D to the fruit or vegetable F as a score.

The score output unit 32 is a trained model using deep learning, and has been trained in advance using training data in which a large number of package images are used as input data and a score corresponding to each package image is used as output data. When package images are input, the score output unit 32 is configured to output the degree of damage D on the fruits and vegetables F as a score. As a result, the score output unit 32 outputs a score corresponding to the degree of damage D on the fruits and vegetables F in each package box B. In this embodiment, the score is between 0 and 1.0, and the higher the degree of damage D, the higher the score output unit 32 outputs. The degree of damage D may be based on all or any of the depth, size, and number of damage D per package box B.

The loading and unloading determination unit 33 determines the loading location and/or loading order of multiple shipping boxes B based on the scores output by the score output unit 32. In this embodiment, the loading and unloading determination unit 33 determines the loading location and loading order based on the scores. Regarding the loading location, the loading and unloading determination unit 33 designates the loading location of shipping boxes B with a score of 0 to less than 0.4 as the first area E1, the loading location of shipping boxes B with a score of 0.4 to less than 0.8 as the second area E2, and the loading location of shipping boxes B with a score of 0.8 to 1.0 as the third area E3. Regarding the loading order, the loading and unloading determination unit 33 determines the loading order of multiple shipping boxes B so that loading is performed earliest in descending order of the scores.

The loading command unit 34 transmits loading commands to the forklift 2, including the loading order for multiple boxes B, the location of each box B, and the storage location corresponding to each box B.

<Load handling system operation>
Next, the operation of the cargo handling system S according to the first embodiment will be explained again with reference to the flow chart of FIG.

(1) First, when a truck T carrying multiple shipping boxes B arrives (see S1 in Figure 6), the management device 3 sends a flight command to the unmanned aerial vehicle 1 (see S2 in Figure 6).

(2) The unmanned aerial vehicle 1 moves to the location of the loading platform in accordance with the flight command (see S3 in Figure 6), detects the location of the loading box B (see S4 in Figure 6), and captures an image of the loading box B to generate a loading image (see S5 in Figure 6). The generated loading image and the location of the corresponding loading box B are sent to the management device 3 (see S6 in Figure 6).

(3) The management device 3 outputs a score corresponding to each shipping box B based on the received shipping image (see S7 in Figure 6), and determines the placement location and placement order for each shipping box B based on the score (see S8 in Figure 6).

(4) Next, the management device 3 sends a loading command to the forklift 2, which command includes the loading order for the multiple boxes B, the location of each box B, and the storage location corresponding to each box B (see S9 in Figure 6).

(5) The forklift 2 performs the loading and unloading operation in accordance with the received loading and unloading command (see S10 in Figure 6).

As described above, the cargo handling system S according to the first embodiment uses the unmanned aerial vehicle 1 to capture images of each container B beforehand prior to cargo handling operations, and the management device 3 can preliminarily sort the fruits and vegetables F for each container B. This allows the cargo handling system S to feed the fruits and vegetables F from the container B that should be prioritized into the sorter in order, thereby preventing delays in the shipment of fruits and vegetables F that should be shipped first.

Second Embodiment
Next, a second embodiment of the cargo handling system according to the present invention will be described with reference to Figures 7 to 11. Note that the description of the same configuration as in the first embodiment may be omitted.

Figure 7 is a schematic front view of the cargo handling system S according to this embodiment. As shown in Figure 7, the cargo handling system S includes a truck T, an unmanned aerial vehicle 1, a forklift 2, and a management device 3. Multiple cargo boxes B are placed on the loading platform of the truck T.

Packing boxes B, grouped into four, are surrounded horizontally by anti-shift material P, which prevents the boxes from shifting during transport. The anti-shift material P is made of a material that is transparent to near-infrared rays. Identifiers C, which will be explained later, are printed or affixed to multiple packing boxes B. These identifiers C are covered by the anti-shift material P and are configured so that they cannot be recognized under visible light unless the anti-shift material P is removed. Furthermore, these identifiers C are made of a material that is opaque to near-infrared rays.

As shown in Figures 7 and 8, the unmanned aerial vehicle 1 and forklift 2 have the same configuration as in the first embodiment.

As shown in FIG. 9, the infrared camera 15 captures an image of a set of cargo boxes B containing cargo collapse prevention material P and generates a cargo image. As in the first embodiment, the generated cargo image is sent to the management device 3 along with the position information of the corresponding cargo boxes B.

Figure 10 shows a package image generated by the infrared camera 15. As shown in Figure 10, the anti-shift material P transmits near-infrared light, but the identifier C does not. Therefore, the identifier C, which was covered by the anti-shift material P, can be recognized in the package image even if the anti-shift material P is not removed. The identifier C is composed of a known code such as a one-dimensional code or a two-dimensional code, and contains information related to the contents of the package B.

<Management device>
The management device 3 has the same hardware configuration as in the first embodiment and includes a computer. A cargo handling management program according to the second embodiment is stored in the storage device. The cargo handling management program causes the computer to operate as an aircraft command unit 31, a cargo handling determination unit 33, a cargo handling command unit 34, and an identifier reading unit 35, all of which will be described later.

As shown in FIG. 8, the management device 3 has, as its functional configuration, a memory unit 30, an aircraft command unit 31, a cargo handling determination unit 33, a cargo handling command unit 34, and an identifier reading unit 35.

As in the first embodiment, the memory unit 30 stores the position of the bed of a truck T parked in a specified truck area TE. The memory unit 30 also stores information about the contents of the shipping box B in advance, linking it with information about the identifier C. Information about the contents of the shipping box B includes, for example, but is not limited to, the type of contents in the shipping box B, the expiration date of the contents, and the storage location.

As in the first embodiment, when truck T arrives at truck area TE, the aircraft command unit 31 transmits a flight command, including the position of the loading platform, to unmanned aircraft 1 so that unmanned aircraft 1 flies to the loading platform of truck T.

The identifier reading unit 35 references the load image, recognizes the identifier C contained in the load image, reads the information of the identifier C, and acquires the information of the identifier C. The identifier reading unit 35 transmits the acquired information to the load handling determination unit 33.

The loading/unloading determination unit 33 receives information from the memory unit 30 regarding the contents of the container B corresponding to the information on the identifier C received from the identifier reading unit 35, and determines the loading location and loading order for the corresponding container B based on that information.

As in the first embodiment, the loading and unloading command unit 34 transmits loading and unloading commands to the forklift 2, including the loading order for multiple boxes B, the position of each box B, and the storage location corresponding to each box B.

As in the first embodiment, the forklift 2 performs loading and unloading operations based on the received loading and unloading command.

<Load handling system operation>
Next, the operation of the cargo handling system S according to the second embodiment will be described again with reference to the flow chart of FIG.

(1) First, when a truck T carrying multiple shipping boxes B arrives (see S1 in Figure 11), the management device 3 sends a flight command to the unmanned aerial vehicle 1 (see S2 in Figure 11).

(2) The unmanned aerial vehicle 1 moves to the location of the loading platform in accordance with the flight command (see S3 in Figure 11), detects the location of the loading box B (see S4 in Figure 11), and captures an image of the loading box B to generate a loading image (see S5 in Figure 11). The generated loading image and the location of the corresponding loading box B are sent to the management device 3 (see S6 in Figure 11).

(3) The management device 3 obtains the identifier C information corresponding to each shipping box B based on the received package image (see S7 in Figure 11), and determines the placement location and placement order for each shipping box B based on the information about the contents of the shipping box B corresponding to the identifier C information (see S8 in Figure 11).

(4) Next, the management device 3 sends a loading command to the forklift 2, which command includes the loading order for the multiple boxes B, the location of each box B, and the storage location corresponding to each box B (see S9 in Figure 11).

(5) The forklift 2 performs the loading and unloading operation in accordance with the received loading and unloading command (see S10 in Figure 11).

As described above, the cargo handling system S according to the second embodiment uses the unmanned aerial vehicle 1 to capture images of each cargo box B beforehand prior to cargo handling operations, and the management device 3 acquires identifier C information to determine the location and order in which each cargo box B will be placed. Furthermore, the cargo handling system S can acquire identifier C information without removing the anti-shift material P from the cargo box B by capturing an image of the identifier C covered by the anti-shift material P using the infrared camera 15. Therefore, even if the identifier C information is intentionally hidden, for example, the cargo handling system S according to this embodiment can acquire identifier C information while hiding the identifier C.

The cargo handling system S, cargo handling management program, and cargo handling management method according to the above embodiment of the present invention have been described above, but the cargo handling system, cargo handling management program, and cargo handling management method according to the present invention are not limited to the above embodiment. For example, the cargo handling system, cargo handling management program, and cargo handling management method according to the present invention may be implemented using the following modifications, or may be implemented by appropriately combining the following modifications.

<Modification>
The infrared irradiation unit may be disposed inside the wing of the truck T. In this case, the infrared irradiation unit is configured to irradiate near-infrared rays toward the cargo box B below when the wing of the truck T is opened. In this case, the unmanned aerial vehicle 1 does not need to have an infrared irradiation unit.

- The forklift 2 may be a manned forklift 2. In this case, the unmanned aerial vehicle 1 or the forklift 2 may further have an alarm device that notifies the driver of the forklift 2 of the loading location and loading order of each box B. The alarm device may be, for example, a speaker provided on the unmanned aerial vehicle 1 or a monitor provided on the forklift 2, and is not particularly limited.

- The waiting position of the unmanned aerial vehicle 1 is not particularly limited. For example, the unmanned aerial vehicle 1 may be configured to wait inside the truck T, and when the truck T arrives at the truck area TE, fly over and take an image of the shipping box B.

- To prevent sunlight from interfering with the generation of appropriate infrared cargo images, the wings of the winged vehicle may be configured to block sunlight, for example. In this case, the angle of the wings of the winged vehicle may be configured to be adjustable. Alternatively, the unmanned aerial vehicle 1 may be configured to detect the position of each cargo box B and capture an image of each cargo box B after entering the interior of the winged vehicle and closing the wings while confined within the winged vehicle.

The score output unit 32 may be configured to output the degree of damage D of the fruit or vegetable F as a score based on its internal quality (sweetness, sourness, starch content, discoloration, hollowness, etc.). In this case, the score output unit 32 may further be configured to perform supervised learning in advance using training data in which multiple load images are input data and scores related to the internal quality corresponding to each load image are output data. When a load image is input, the score output unit 32 outputs the internal quality of the fruit or vegetable F as a score. As a result, the score output unit 32 outputs a score corresponding to the internal quality of the fruit or vegetable F in each load box B. In this case, the load handling determination unit 33 determines the load handling order and storage location of the multiple load boxes B based on the scores corresponding to the internal quality of the fruit or vegetable F.

- The angle at which the infrared camera 15 captures the contents is not particularly limited in the first and second embodiments.

B Cargo box C Identifier E1 First area E2 Second area E3 Third area D Damage F Fruits and vegetables P Cargo collapse prevention material S Cargo handling system T Truck TE Truck area 1 Unmanned aerial vehicle 10 Main body 11 Propeller 12 Power unit 13 Flight position detection unit 14 Cargo position detection unit 15 Infrared camera 16 Aerial vehicle control unit 2 Forklift 20 Lifting device 21 Vehicle position detection unit 22 Drive unit 23 Vehicle control unit 3 Management device 30 Memory unit 31 Aerial vehicle command unit 32 Score output unit 33 Cargo handling determination unit 34 Cargo handling command unit 35 Identifier reading unit

Claims (7)

A cargo handling system including a plurality of containers placed in a predetermined area and a forklift for handling the containers,
an unmanned aerial vehicle having an infrared camera, which takes an image of the cargo box with the infrared camera before cargo handling to generate a cargo image;
a loading/unloading determination unit that determines a loading location and/or a loading order of the packing boxes based on the packing image,
The loading and unloading determination unit has a score output unit that analyzes the loading image and outputs a score, and the loading and unloading system determines the loading location and/or the loading and unloading order based on the score output by the score output unit. The contents of the packing box are fruits and vegetables,
The cargo handling system according to claim 1 , wherein the score output unit analyzes the cargo image and outputs a score indicating the degree of damage to the fruit or vegetable. The contents of the packing box are fruits and vegetables,
The cargo handling system according to claim 1 , wherein the score output unit analyzes the cargo image and outputs the degree of internal quality as a score. A cargo handling system including a plurality of containers placed in a predetermined area and a forklift for handling the containers,
an unmanned aerial vehicle having an infrared camera, which takes an image of the cargo box with the infrared camera before cargo handling to generate a cargo image;
a loading/unloading determination unit that determines a loading location and/or a loading order of the packing boxes based on the packing image,
An identifier relating to the contents of the packing box is displayed on the surface of the packing box, and the identifier is covered with a cargo collapse prevention material that is permeable to near-infrared rays,
The infrared camera captures an image of the identifier through the load-preventing material,
The loading/unloading determination unit is a loading /unloading system that determines the loading location and/or the loading order of the packing boxes based on the information contained in the identifier. A cargo handling system including a plurality of containers placed in a predetermined area and a forklift for handling the containers,
an unmanned aerial vehicle having an infrared camera, which takes an image of the cargo box with the infrared camera before cargo handling to generate a cargo image;
a loading/unloading determination unit that determines a loading location and/or a loading order of the packing boxes based on the packing image;
a notification unit,
The notification unit notifies the operator of the forklift of the loading location and/or the loading order determined by the loading determination unit. a forklift that loads and unloads boxes placed in a predetermined location;
an unmanned aerial vehicle having an infrared camera, which takes an image of the contents of the packing box with the infrared camera before loading and unloading and generates a packing image;
A cargo handling management program used in a cargo handling system including a computer having an arithmetic unit and a storage unit,
The cargo handling management program is installed on the computer.
a score output unit that analyzes the package image and outputs a score;
A cargo handling management program that operates as a cargo handling determination unit that determines the loading location and/or loading order of the packing boxes based on the scores output by the score output unit. A cargo handling management method used in a cargo handling system including a cargo box placed in a predetermined area, a forklift that handles the cargo box, an unmanned aerial vehicle having an infrared camera, and a cargo handling determination unit having a score output unit ,
Taking an image of the packing box with the infrared camera before handling and generating a packing image;
The score output unit analyzes the package image and outputs a score;
and determining, by the loading decision unit , the loading location and/or the loading order of the packing boxes based on the scores output by the score output unit .