Logistics base unmanned monitoring system

Abstract

To efficiently determine a cause of a logistics business accident such as an accident of work or the like at the time of arrival, warehousing, and sorting in an automated logistics base of transportation business.SOLUTION: A system is configured by a cloud server, a WEB server, a camera facility, a sensor facility, a determination function, and various terminals, to determine a cause of a logistics business accident such as an accident of work or the like at the time of arrival, warehousing, and sorting at a logistics base. The system is configured to: send, as information, the identified cause of the accident to a responsible person and a remote monitoring person / worker; improve a point of the cause of the accident; and utilize a logistics base unmanned monitoring system for quick work restoration.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to an unattended monitoring system for a logistics base, such as receiving, warehousing, and sorting operations at a logistics base.

Background Art

[0002] In a logistics base automated by an AGV (Automated Guided Vehicle) "unmanned transport vehicle" or the like, when the goods collapse or equipment such as a belt conveyor stops during receiving, warehousing, sorting operations, etc., it is important to acquire the situation with a camera image / video or a sensor and utilize it for improvement. If the goods collapse, it is necessary to find out the cause of the goods collapse. Just reporting the resulting image / video / sensor data is insufficient. Merely acquiring images / videos takes time to identify the corresponding cause location. Also, a large amount of storage is required for storing images / videos. For example, when the string cutting by a string cutting machine fails to be detected and equipment stops or the goods collapse in the next process, or when the occurrence of the goods collapse during AGV transportation and during the operation of a film winding machine cannot be detected and mis-shipment / other equipment stops occur, or when damage to a cardboard box occurs in the AGV area and the damaged part contacts the AGV and stops, etc., the cause may exist in a place different from where the stop or error is detected.

[0003] In this way, the working times and locations in an automated logistics base are diverse. Even if the location where the goods collapse has been found through images / videos, the cause of the goods collapse is not necessarily at the occurrence location. The goods may shift at a location before the occurrence location, resulting in the goods collapse at the occurrence location. Even if improvements are made to the occurrence location, it may not be a fundamental solution. That is, it is important to determine the cause of the goods collapse and identify the location where the cause occurs. Also, instant cause determination is required not only for preventing the goods collapse but also for preventing human accidents and arson.

[0004] In the above technical field, Patent Document 1 discloses a technique for more efficiently and accurately sorting packages. Further, Patent Document 2 discloses a package sorting system, a package sorting method, an information processing device, and its control technique. Patent Document 3 discloses a sorting station where packages or their storage containers are efficiently and accurately transferred, and an article distribution system incorporating the same.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0006] However, with the technologies described in the above documents, while it is possible to achieve improvements in efficiency and accuracy in sorting and the like, it is difficult to prevent accidents caused by complex reasons. Originally, a system should be constructed for the purpose of preventing recurrence of accidents and restoring operations in the shortest time by accurately determining the cause of an accident. By combining with other sensors like a drive recorder, or inputting images / videos from a camera that can be incorporated into an app and data from sensors into artificial intelligence, it becomes possible to determine the cause of an accident, identify the location corresponding to the cause of the accident, shorten the recovery time, and achieve efficient improvement. Therefore, there is a need to construct an integrated system for immediate determination, confirmation of the cause of an accident, and indication of improvement points by a cloud server, a WEB server, camera equipment, sensor equipment, a determination function, and various terminals.

[0007] An object of the present invention is to provide a technology for solving the above problems.

Means for Solving the Problems

[0008] Integrate and operate cloud servers, web servers, camera equipment, sensor equipment, judgment functions, and various terminals through an integrated system. The utilization of the convenience of cloud servers is optional, and the installation of web servers is operated in response to the number and continuity of workplaces. Camera equipment and sensor devices are installed at any appropriate location within the logistics base. The judgment function is composed of video / image recognition, artificial intelligence, etc. The various terminals are information terminals that can be carried, and are operated by administrators, remote monitors, workers, etc.

Advantages of the Invention

[0009] According to the system implementing the present invention, not only accidents during incoming goods, warehousing, sorting operations, etc. within the logistics base, but also artificial accidents and malfunctions of transportation devices can be instantly identified, so that recovery from accidents can be achieved in the shortest time. In addition, by accumulating a large amount of accident cause data, it becomes possible to discover improvement points and improve the equipment.

Brief Description of the Drawings

[0010]

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Modes for Carrying Out the Invention

[0011] The configuration of the present invention will be described below based on the attached drawings. In FIG. 1, 1 is a facility such as a logistics center, 2 is a WEB server, 3 is a camera built into the app, 4 is a temperature / humidity / acceleration / illuminance sensor, 5 is artificial intelligence, 6 is a database, 7 is a cloud server, 8 is an administrator terminal device, and 9 is a remote monitor / worker terminal device. In the facility 1 such as a logistics center, a WEB server 2, a camera built into the app 2, and a temperature / humidity / acceleration / illuminance sensor 3 are arranged. During operations such as incoming goods, warehousing, and sorting work in the logistics center and other facilities, image, video, and sensor data related to accidents such as equipment stoppage and cargo collapse at each work location are transmitted to the WEB server 2. The WEB server 2 transmits accident information to the cloud server 7, and the cloud server 7 inputs it to the artificial intelligence 5. At the same time, the cloud server 7 transmits the accident information to the administrator terminal device 8 and the remote monitor / worker terminal device 9. The WEB server 2 transmits and inputs the above accident information to the artificial intelligence 5 in the cloud server 7, analyzes the cause and determines the cause of the accident, creates countermeasures, and transmits them as a response report or the like to the administrator terminal device 8 and the remote monitor / worker terminal device 9. The artificial intelligence 5 stores the accident situation and cause in the database 6 for future learning.

[0012] The camera built into the app 2 and the temperature / humidity / acceleration / illuminance sensor 3 are equipped with means for transmitting accident data. The WEB server 2 is equipped with means for transmitting the accident information transmitted from the camera built into the app 2 and the temperature / humidity / acceleration / illuminance sensor 3 to the administrator terminal device 8, the remote monitor / worker terminal device 9, and the cloud server 7. The cloud server 7 is equipped with a database 6 for storing programs and related information and data such as the artificial intelligence 5 that operates the system. The artificial intelligence 5 is equipped with functions for determining the cause of the accident and formulating countermeasures by means of operations, searches, collations, outputs, displays, memories, and other processes for executing the program that operates the system. The cloud server 7 is equipped with means for user authentication of the administrator terminal device 8 and the remote monitor / worker terminal device 9 and for transmitting accident information.

[0013] The facilities such as the logistics center 1 can be indoor or outdoor, and can be located at multiple locations as desired. The WEB server 2 can be installed close to the facilities such as the logistics center 1 or remotely. The cloud server 7 is used according to the characteristics of the data to be stored and the presence or absence of connection with other external systems. The in-app camera 2, temperature / humidity / acceleration / illuminance sensor 3 are installed at appropriate locations in the facilities such as the logistics center 1 according to the monitoring targets and management contents. The administrator terminal device 8 and the remote monitor / worker terminal device 9 have different functions according to whether they are for administrators or remote monitors / workers, and the accessible information and data levels.

[0014] The in-app camera 2 has the same function as a drive recorder and constantly records videos. After recording for several hours, the recording is overwritten. When an abnormal image is received, the application built into the camera determines that an accident has occurred, extracts videos of any time before and after the accident, and transmits accident information such as video data and camera placement information to the WEB server 2.

[0015] The temperature / humidity / acceleration / illuminance sensor 3 constantly detects the temperature, humidity, vibration due to earthquakes, etc. at the installed location, and when abnormal values occur, it transmits the abnormal values and the sensor information to the WEB server 2.

[0016] When the WEB server 2 receives abnormal data from the in-app camera 2 and the temperature / humidity / acceleration / illuminance sensor 3, it creates an accident report, etc. based on the extracted accident data, and sends it to the administrator terminal device 8 and the remote monitor / worker terminal device 9 by email, SMS, etc. At the same time, it transmits the accident data to the cloud server 7.

[0017] The cloud server 7 inputs the received accident data into the artificial intelligence 5, and the artificial intelligence 5 analyzes the accident cause and identifies the accident cause. After identifying the accident cause, it formulates accident countermeasures, creates a countermeasure report, etc., and sends it to the administrator terminal device 8 and the remote monitor / worker terminal device 9 by email, SMS, etc.

[0018] Managers, remote monitors, and workers improve the accident causes of facilities such as logistics centers based on accident reports received from the WEB server 2 and accident countermeasure reports received from the cloud server 7, and promote the popularization of processes during incoming goods, warehousing, sorting operations, etc.

[0019] <Embodiment 1> [Wireless Communication] There are many shelters and complex machinery in facilities such as logistics bases. Under the conditions of this facility, it is necessary to build a large-scale network that enables long-distance communication while suppressing the minimum data and power consumption. In the present invention, LoRaWAN (Long Range Wide Area Network), which can connect many devices, is selected and used. FIG. 4 shows a comparison diagram of LoRaWAN and other wireless communication standards. FIG. 5 shows a performance comparison table of LoRaWAN and other wireless communication standards. However, the wireless communication standard used in the present invention is not limited to LoRaWAN.

[0020] [Camera] An example of the camera used in the system of the present invention is shown in FIG. 6. The camera uses Vieueka (manufactured by Panasonic). Vieueka is an IoT camera with a built-in CPU, and the image analysis application in the camera can be linked with the artificial intelligence of the cloud server, enabling rapid and minimum data analysis. However, the camera used in the present invention is not limited to Vieueka. Since a large number of cameras can be connected by the LoRaWAN gateway, it is preferable to arrange the cameras so that there are no dead spots as much as possible.

[0021] [Sensor] FIG. 7 shows examples of a temperature and humidity sensor, an acceleration sensor, and an illuminance sensor. As shown in FIG. 8, each sensor is connected to the LoRaWAN gateway and transmits data to the cloud server through a router.

[0022] The present invention aims to determine the cause of accidents during incoming, warehousing, sorting, etc. based on abnormal data from cameras and sensors, and to recover from accidents. However, it does not limit the determination data to only abnormal data from cameras and sensors. There are many devices in the logistics base, such as AGVs (Automated Guided Vehicles) "automatic guided vehicles", belt conveyors, string cutters, seismographs, fire alarms, etc. It is also possible to capture stop signals and abnormal signals from these devices into the system and construct a comprehensive unmanned monitoring system for the logistics base.

[0023] The following will be described based on generalized term examples. The administrator terminal device 8 and the remote monitor / worker terminal device 9 are preferably mobile terminals, such as smartphones or any other. The terminal device and the cloud server 7 are equipped with means (functions) for transmitting and receiving the relevant information (including various data hereinafter). For example, matters to be confirmed such as the personal authentication and authority of the person carrying the terminal (administrator, operator, etc.) are transmitted and received to each other for checking. The artificial intelligence 5 is configured and operated by the currently mainstream deep learning type artificial intelligence, but is not limited to this function and configuration. The artificial intelligence 5 analyzes the cause of the sorting accident by learning abnormal data, creates a countermeasure report, etc., and transmits it from the cloud server 7 to each terminal device.

Industrial Applicability

[0024] The present invention is an effective system for detecting abnormalities and analyzing the cause of cargo collapse in automated logistics bases, whether unmanned or manned, and has potential for use in applications other than logistics bases. For example, it can be effectively used for detecting abnormalities and analyzing the cause of abnormalities in product assembly / manufacturing lines, food manufacturing lines, unmanned stores, etc.

Explanation of Signs

[0025] 1 Facilities such as logistics bases 2 WEB server 3 In-app camera 4 Temperature, Humidity, Acceleration, and Illuminance Sensor 5 Artificial Intelligence 6 Database 7 Cloud Server 8 Administrator Terminal Device 9 Remote Monitor and Operator Terminal Device

Claims

【Claim 1】 A logistics base unmanned monitoring system for accidents such as equipment stoppage and abnormality detection in the sorting operation of a logistics base, a terminal operated by the person in charge, remote monitor, and worker of the logistics base, cameras and sensors installed in the logistics base, a WEB server that receives data from the cameras and sensors, an artificial intelligence and a database that process accident cause analysis from the data, a cloud server communicably connected to the terminal, characterized by comprising: The terminal includes: a receiving unit that receives abnormality detection and abnormality cause information in the work during the incoming, warehousing, sorting operation, etc. of the logistics base from the cloud server, a display unit that displays the abnormality detection and abnormality cause information, a transmission unit that transmits authentication information of the person in charge, remote monitor, and worker to the cloud server, and is provided with: The camera has: a function of constantly recording each facility of the logistics base as a video, an app function of transmitting videos of several seconds before and after when an abnormality occurs in the recorded video to the WEB server, a function of overwriting and recording after several hours when there is no abnormality in the recorded video, The sensor has: a function of recording data on acceleration such as temperature, humidity, and vibration of each facility of the logistics base, a function of transmitting abnormal data to the WEB server when an abnormality occurs in the recorded data, The artificial intelligence has a function of specifying an accident location from the abnormal video and abnormal data transmitted to the WEB server, a function of analyzing the accident cause from the accident location and specifying the accident cause corresponding location, a function of accumulating the abnormal data in the database and a function of learning the accumulated data, The cloud server has: an authentication unit that identifies authentication information of the person in charge, remote monitor, and worker, a function of transmitting abnormality detection and abnormality cause information to the person in charge, remote monitor, and worker by the authentication unit, and is provided with: A logistics base unmanned monitoring system characterized by the above.

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