PURPOSES : The driver's ability to make a commitment has resulted in excessive force and a lack of commitment. To solve this problem, we are developing an algorithm that analyzes resolution in real-time by introducing IoT and informs drivers of the completion of compaction. METHODS : Real-time compaction was analyzed by installing accelerometers on the rollers. To evaluate the algorithms, we conducted an apparent density test.
RESULTS : The algorithm data and apparent density test data showed similar trends. This means that the proposed algorithms are sufficiently reliable. However, a lack of data samples and the fact that only data prior to completion of the commitment were analyzed may indicate a lack of reliability.
CONCLUSIONS : In subsequent studies, the number of samples will be increased and the data after completion of the commitment analyzed to increase reliability. Introducing a tachometer will prevent the TVL from falling sharply when the direction of the rollers' progress changes. In addition, it is also planned to upgrade the algorithms by researching cases in which the algorithms did not produce satisfactory results owing to problems such as temperature and speed.

ABSTRACT
1. 서론
2. 가속도계 선정
3. 현장데이터 측정
4. 현장 데이터 분석 및 다짐도 추정 알고리즘 개발
    4.1. Auto-Spectrum
    4.2. 데이터 측정 결과
    4.3. 다짐도 추정 알고리즘 구성도
5. 알고리즘 신뢰도 평가
    5.1. 테스트베드
    5.2. 평가시험
    5.3. 평가시험 분석
    5.4. 상관분석
6. 결론 및 향후계획
REFERENCES

• 김건우(서울과학기술대학교 건설시스템공학과) | Kim Geonwoo
• 가현길(서울과학기술대학교 건설시스템공학과) | Ga Hyungil
• 문성호(서울과학기술대학교 건설시스템공학과) | Mun Sungho 교신저자