Excavator–truck operations, characterized by their repetitive excavation and loading tasks, present a prime candidate for automation. While numerous studies have aimed to automate the earthworks, practical implementations remain scarce. This research introduces a task component design focused on excavator–truck operation planning to improve the functionality of an earthwork automation system. To address this, fundamental task primitives necessary for executing excavation tasks were engineered, and a web-based system was developed to automate the generation of work plans for both point and trench excavation through algorithmic processes. Additionally, a JSON-based protocol was introduced to facilitate efficient integration with other subsystems. Field tests were conducted to validate the effectiveness of the newly developed algorithm and protocol within the broader context of earthwork automation systems. The results demonstrated the successful implementation of the task components, confirming their operational viability and seamless integration into the existing earthwork automation framework.

Currently, earthworks expenses, which account for a large portion of civil engineering work, are managed by hand or offline, such as invoices. However, such manual management can lead to human errors and poor management and manipulation of records, resulting in difficult situations that cause disputes between the client, construction company, partner company, and equipment technicians. In addition, a system that can transparently manage sand and soil is needed as illegal cases occur frequently, such as randomly bringing in rocks and soil at construction sites or unauthorized discharge and landfill of defective soil. In this paper, we want to use a Web-GIS-based smart invoice system to secure transparency and efficiency in bringing in external soil, identify the operation path and time of construction equipment with a GPS-based transport management system, and analyze the details by comparing contract details and big data. In addition, we intend to contribute to improving safety management by raising awareness of safety accidents through inspection and regulation of speeding vehicles using smart invoices. By calculating the optimal number of Sato equipment, we intend to increase system productivity by minimizing idle time of equipment and to summarize improvements by deriving smart invoice problems.