KR-20260066480-A - Research on cranes and equipment for port loading and unloading operations

Abstract

Smart crane and cargo handling equipment technology for port operations is a system that monitors the location and operational status of cargo handling equipment in real time through sensors and automatic control systems, and helps perform operations efficiently and safely by calculating the optimal route.

Inventors

• 추보람
• 안상현

Assignees

• 가야마린 주식회사

Dates

Publication Date

20260512

Application Date

20241104

Claims (1)

1. A system designed to increase the operational efficiency of cargo handling equipment and ensure safety, (a) A sensor module that monitors the location, operation status, and load of unloading equipment in real time; (b) A control unit that automatically calculates the optimal path and work sequence of the unloading equipment based on data collected from the sensor module above; (c) a driving module that controls the operation of the unloading equipment by executing an optimized work instruction generated by the above control unit; and (d) A smart crane and cargo handling equipment system including a network module that enables remote monitoring and control of the status and operation conditions of cargo handling equipment by connecting to a central management server via real-time data transmission.

Description

Research on cranes and equipment for port loading and unloading operations Computer vision and image recognition technologies utilize cameras and sensors mounted on smart cranes to recognize the location and shape of cargo, facilitating automatic unloading at precise locations. Machine learning algorithms learn the sizes and shapes of various cargo to determine the optimal unloading path. IoT and sensor networks monitor equipment status and the surrounding environment in real time via sensors, connecting them to enable operators to receive real-time data. By monitoring various information such as location, weight, vibration, and temperature, they support accident prevention and preventive maintenance of equipment. The AI-based automatic control system uses AI to enable the crane to autonomously locate cargo and set optimal unloading routes and movements, thereby improving work speed. This automatic control system works in conjunction with remote control options to support safe operation for workers. Autonomous driving and unmanned transport systems connect Automated Guided Vehicles (AGVs) or Autonomous Mobile Robots (AMRs) with cranes to safely transport unloaded cargo to warehouses or move it to loading areas. Synchronization with cranes increases the speed and accuracy of logistics operations. A Digital Twin allows for the simulation of operating conditions in a virtual environment and the establishment of optimal operational strategies through the digital replication of actual cranes and cargo handling systems. This enables the analysis of operational efficiency and allows for rapid response in the event of problems. Predictive maintenance and monitoring systems are technologies that continuously monitor the condition of equipment to plan maintenance before failures occur. They utilize AI and machine learning to analyze data patterns and optimize equipment lifespan and performance. GPS and RTLS (Real-Time Location System) utilize GPS or real-time location tracking systems to track the location of cargo and cranes, optimizing material flow and operation speed. This technology enables precise location tracking and synchronization within the work site. Energy efficiency and eco-friendly power systems facilitate the efficient use of electricity by introducing eco-friendly equipment, such as electric cranes, and applying energy recovery systems. Battery and power recovery technologies reduce operating costs and carbon emissions. It has evolved in response to the continuously increasing demands for efficiency, safety, cost reduction, and environmental protection in port cargo handling operations. These background technologies aim to manage the complex processes of port cargo handling more sophisticatedly by enabling the automation of port logistics, data-driven operations, and the remote monitoring and control of equipment. The key inventive background technologies are as follows: First, conventional port cargo handling operations have primarily relied on manual labor or machinery. However, as large-scale ports continuously handle cargo of various sizes and weights, the need to improve efficiency through automation technology has increased. To address this, the introduction of autonomous cargo handling equipment and Automated Guided Vehicles (AGVs) utilizing AI and IoT has begun to attract attention. Secondly, as it became crucial to accurately detect the size, shape, and location of cargo to ensure safe and rapid unloading, cargo identification technology using cameras and sensors was introduced. Along with this, image recognition systems utilizing machine learning and deep learning technologies were installed on cranes, enabling operators to recognize cargo in real time and respond quickly. Thirdly, the importance of remote control has emerged as port cargo handling operations can be physically dangerous. Accordingly, various sensors and remote control systems, such as wireless communication, GPS, and RTLS (Real-time Location System), have been introduced, enabling operators to safely operate cranes or monitor cargo handling operations from a remote location. Fourth, since port equipment operates for extended periods, breakdowns pose a problem by causing work delays and increased costs. To prevent this, Predictive Maintenance technology has been developed that collects equipment status data via sensors and utilizes AI and machine learning to predict failures in advance. This aims to extend equipment lifespan and reduce operating costs. Fifth, digital twins create virtual equipment models identical to actual equipment, enabling the simulation of cargo handling operations. This allows operators to test equipment operation in advance and establish optimized operational strategies. Digital twins provide a method to enhance the efficiency of port operations and respond quickly to problems when they arise. Finally, driven by global carbon emission regulations and demands for eco-friendliness, technologies that enh