# 1241 / Study On Classification Of Excavated Soil Using Internal Sensor Data Of Hydraulic Excavator ## Authors Naoki Morisawa, Masaya Imanishi, Masaki Yanagishita, Teiichirou Chiba, Hiroshi Yamamoto, Takeshi Hashimoto, and Daisuke Endo {% hint style="info" %} Paper presented at ISTVS 2024 | 21st International and 12th Asia-Pacific Regional Conference of the ISTVS\ Keywords: Soil Classification; ICT; Hydraulic Excavator; Internal sensor; Automation\ {% endhint %} ## Abstract In these days, construction sites are facing workforce shortages caused by declining labor and lack of young workers. Therefore, “Improve Productivity” is very important. Automation and autonomy of construction machinery is one of the solutions. As above, ICT hydraulic excavators and bulldozers are widely used in many sites, but the scope of the application is limited. In particularly, automated digging in hydraulic excavators still has many difficulties in actual use. The root cause is needed to the complicated operation during digging affected by the soil conditions. Since the soil conditions change anytime, if the operation is not adjusted to match to them, the efficiency will be decreased significantly. In other words, to achieve automated digging, the machine must recognize variation of soil conditions first. While digging, the operator has been sensing the machine's response affected by the soil conditions to consider it and adjusting machine operation simultaneously. In other words, human senses were used to recognized soil conditions to perform efficient operations. In that case, we thought that if we could replace human senses with internal sensors of the machine, the machine could recognize the soil conditions by itself. In this study, based on this hypothesis, we conducted measuring sensor data during digging in various soil conditions (e.g. hardness, materials…). The test results indicated that the soil hardness measured by simplified N-value meter, has a high correlation with the work efficiency and bucket tooth speed calculated from internal sensor data. This implicated that the sensor data from the excavator can be used to be determine soil conditions. In addition, there is a possibility that machine could recognize soil conditions by itself. *** Full paper purchase: \ ISTVS members receive three complimentary papers per year: --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://2024.istvs.org/submissions/papers/1241.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.