Logistics business accident prediction system

Abstract

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

Description

Technical Field

[0001] The present invention relates to a logistics operation accident prediction system for predicting accidents such as incoming goods, warehousing, and sorting operations at a logistics base in the transportation industry.

Background Art

[0002] In a logistics base automated by AGV (Automated Guided Vehicle) "automated guided vehicle" etc., when the goods collapse or equipment such as a belt conveyor stops during incoming goods, 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 a goods collapse occurs, it is necessary to find out the cause of the goods collapse. Simply reporting the resulting image / video / sensor data is insufficient. Merely acquiring images / videos requires time to identify the corresponding cause location. Also, a large amount of storage is required for storing images / videos. For example, if the situation of a failed string cut by a string cutting machine cannot be detected and equipment stops or goods collapse occurs in the next process, or if the occurrence of 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 if damage to cardboard occurs in the AGV area and the damaged part contacts the AGV and stops, etc., the cause may exist in a location different from where the stop or error is detected.

[0003] In this way, the working times and working locations in an automated logistics base are diverse. Even if the location where the goods collapse has occurred can be found by 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 a goods collapse at the occurrence location. Even if improvements are made to the occurrence location, it may not be a fundamental solution. That is, prediction of goods collapse and identification of the location where the cause occurs are important. Also, prediction is necessary not only for 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. Patent Document 2 discloses a package sorting system, a package sorting method, an information processing device, and its control technology. Patent Document 3 discloses a sorting station where packages or their storage containers are efficiently and accurately transferred, and an article collection and 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 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 accidents and restoring operations in the shortest time by predicting accidents. 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, accident prediction, identification of the location corresponding to the accident prediction, and efficient improvement become possible. Detecting abnormal data at this causative location and performing accident prediction that can prevent subsequent accidents such as package collapse is important. Therefore, it is required to construct an integrated system including a cloud server, a WEB server, camera equipment, sensor equipment, an accident prediction function, and immediate determination, confirmation of accident prediction, and instructions for improvement points by various terminals.

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

Means for Solving the Problems

[0008] A cloud server, a WEB server, camera equipment, sensor equipment, an accident prediction function, and various terminals are operated by an integrated system. The utilization of the convenience of the cloud server is optional, and the installation of the WEB server is operated in response to the number and continuity of workplaces. The camera equipment and sensor equipment are installed at any appropriate location within the logistics base. The accident prediction 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 / operators, etc.

Effects of the Invention

[0009] According to the system implementing the present invention, not only accidents during incoming goods, warehousing, and sorting within the logistics base, but also artificial accidents and malfunctions of transportation devices can be predicted, so accidents can be prevented. In addition, by accumulating a large amount of accident prediction data, it becomes possible to discover improvement points and improve the equipment.

Brief Explanation of the Drawings

[0010]

Figure 1

Figure 2

Embodiments for Carrying Out the Invention

[0011] Hereinafter, embodiments of the present invention will be described based on the accompanying drawings. In FIG. 1, 1 is a facility such as a logistics center, 2 is a WEB server, 3 is a camera with an 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 / operator terminal device. In facilities such as logistics center 1, a web server 2, an in-app camera 2, and temperature / humidity / acceleration / illuminance sensors 3 are arranged, and image, video, and sensor data related to equipment abnormalities, cargo collapses, etc. from each work location during incoming goods, warehousing, and sorting in the logistics center and other facilities are sent to the web server 2. The web server 2 sends the accident prediction to the cloud server 7, and the cloud server 7 inputs it to the artificial intelligence 5. At the same time, the accident prediction is sent to the administrator terminal device 8 and the remote monitor / worker terminal device 9. The web server 2 makes the above accident prediction by sending / inputting it to the artificial intelligence 5 in the cloud server 7, creates countermeasures, and sends them as a response report, etc. to the administrator terminal device 8 and the remote monitor / worker terminal device 9. The artificial intelligence 5 stores the accident prediction data in the database 6 for future learning.

[0012] The in-app camera 2 and the temperature / humidity / acceleration / illuminance sensors 3 are equipped with means for sending abnormal data, and the web server 2 is equipped with means for sending the abnormal notifications sent from the in-app camera 2 and the temperature / humidity / acceleration / illuminance sensors 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 such as the artificial intelligence 5 that operates this system, related information, and data. The artificial intelligence 5 has a function of making accident predictions and formulating countermeasures by means of operations, searches, collations, outputs, displays, storages, 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 sending accident predictions.

[0013] The logistics center and other facilities 1 can be indoor, outdoor, and can be located at multiple locations arbitrarily. There are examples where the web server 2 is close to the logistics center and other facilities 1 and examples where it is installed remotely. The cloud server 7 is used according to the characteristics of the data to be stored and the presence or absence of connection to other external systems. The in-app camera 2, temperature / humidity / acceleration / illuminance sensor 3 are installed at appropriate locations in facilities such as logistics centers according to the monitoring targets and management contents. The administrator terminal device 8 and the remote monitor / worker terminal device 9 have different functions depending on whether they are for administrators or remote monitors / workers, and factors such as 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 detected, the application built into the camera determines that an abnormality has occurred, extracts videos for any time before and after the occurrence of the abnormality, and transmits the video data and abnormal data such as camera placement information to the WEB server 2.

[0015] The temperature / humidity / acceleration / illuminance sensor 3 constantly detects vibrations caused by temperature, humidity, earthquakes, etc. at the installed location. When abnormal values occur, the abnormal values and the sensor information of occurrence are transmitted 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 prediction report based on the extracted abnormal data and sends it to the administrator terminal device 8 and the remote monitor / worker terminal device 9 via email, SMS, etc. At the same time, it transmits the abnormal data to the cloud server 7.

[0017] The cloud server 7 inputs the received abnormal data into the artificial intelligence 5. The artificial intelligence 5 performs accident prediction analysis to identify accident predictions. After identifying the accident prediction, it formulates accident response measures, creates a response measure report, etc., and sends it to the administrator terminal device 8 and the remote monitor / worker terminal device 9 via email, SMS, etc.

[0018] Administrators and remote monitors / workers correct the malfunctions of facilities such as logistics centers based on the accident prediction reports received from the cloud server 7 and improve the processes during receiving, warehousing, and sorting.

[0019] The present invention aims to predict logistics operation accidents based on abnormal data from cameras and sensors and prevent accidents during incoming goods, warehousing, and sorting. 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 AGV (Automated Guided Vehicle) "automatic guided vehicle", belt conveyor, string cutter, seismometer, fire alarm, etc. It is also possible to incorporate abnormal signals from these devices into the system and construct a comprehensive logistics operation accident prediction system.

[0020] 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 said 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 constituted and operated by the currently mainstream deep learning type artificial intelligence, but is not limited to this function and configuration. The artificial intelligence 5 learns abnormal data to predict accidents during incoming goods, warehousing, and sorting, creates accident prediction reports, etc., and transmits them from the cloud server 7 to each terminal device.

Industrial Applicability

[0021] The present invention is an effective system for detecting abnormalities and preventing cargo collapses in automated logistics bases, but it also has potential for use in applications other than logistics bases. For example, it can be effectively used for detecting abnormalities and predicting accidents in product assembly / manufacturing lines, food manufacturing lines, unmanned stores, etc.

Explanation of Signs

[0022] 1 Facilities such as logistics bases 2 WEB server 3 Camera built into the app 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 business accident prediction system for detecting equipment stoppages and abnormalities during the operations of receiving, warehousing, and sorting at a logistics base, comprising: terminals operated by the person in charge, remote monitors, and workers at the logistics base; cameras and sensors installed at the logistics base; a web server that receives data from the cameras and sensors; artificial intelligence and a database that process accident prediction analysis from the data; a cloud server communicably connected to the terminals; wherein: the terminal includes: a receiving unit that receives abnormality detection and abnormality cause information during the operations of receiving, warehousing, and sorting at 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 monitors, and workers to the cloud server; and is provided with: the camera includes: a function of constantly recording each facility at 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 includes: a function of recording data on the acceleration such as temperature, humidity, and vibration of each facility at 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 identifying the accident location from the abnormal video and abnormal data transmitted to the web server, a function of analyzing accident prediction from the accident location and identifying the accident prediction applicable location, a function of accumulating the abnormal data in the database and a function of learning the accumulated data; the cloud server includes: an authentication unit that identifies the authentication information of the person in charge, remote monitors, and workers; a function of transmitting abnormality detection and abnormality cause information to the person in charge, remote monitors, and workers by the authentication unit; and is provided with: A logistics business accident prediction system characterized by the above.

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