Measurement result of load cell and ultrasonic sensors (doi:10.34820/FK2/HZRCJI)

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Part 2: Study Description
Part 3: Data Files Description
Part 4: Variable Description
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Document Description

Citation

Title:

Measurement result of load cell and ultrasonic sensors

Identification Number:

doi:10.34820/FK2/HZRCJI

Distributor:

Telkom University Dataverse

Date of Distribution:

2022-03-22

Version:

1

Bibliographic Citation:

GUNAWAN, TEDI; HERNAWATI,ELIS; RIMA ADITYA,BAYU, 2022, "Measurement result of load cell and ultrasonic sensors", https://doi.org/10.34820/FK2/HZRCJI, Telkom University Dataverse, V1, UNF:6:7XSa2groDXBVtEYPw8O9ug== [fileUNF]

Study Description

Citation

Title:

Measurement result of load cell and ultrasonic sensors

Identification Number:

doi:10.34820/FK2/HZRCJI

Authoring Entity:

GUNAWAN, TEDI (Fakultas Imu Terapan, Applied Information Systems)

HERNAWATI,ELIS (Fakultas Imu Terapan, Applied Information Systems)

RIMA ADITYA,BAYU (Fakultas Imu Terapan, Applied Information Systems)

Distributor:

Telkom University Dataverse

Access Authority:

HERNAWATI, ELIS

Depositor:

HERNAWATI, ELIS

Date of Deposit:

2022-03-22

Study Scope

Keywords:

Computer and Information Science, load cell sensor,ultrasonic sensor

Abstract:

This dataset comes from the measurement results of plastic type waste in sensor-based smart trash cans. The sensor used is a load cell sensor to measure the weight of the waste and an ultrasonic sensor to measure the height of the waste. to measurements using a height sensor resulting in an average gap error of 0.08 cm. While the results of the comparison of measuring waste weight using a scale in kg compared to measuring waste weight using a weight sensor resulted in an average gap error of 0.03 kg. (2022-03-22)

Notes:

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Methodology and Processing

Sources Statement

Data Access

Notes:

CC0 Waiver

Other Study Description Materials

Related Publications

Citation

Identification Number:

DOI: 10.3844/jcssp.2021.1085.1092

Bibliographic Citation:

Anh Khoa, T., Phuc, C. H., Lam, P. D., Nhu, L. M. B., Trong, N. M., Phuong, N. T. H., ... & Duc, D. N. M. (2020). Waste management system using IoT-based machine learning in university. Wireless Communications and Mobile Computing, 2020. doi.org/10.1155/2020/6138637 Arief, M. F., & Gaol, F. L. (2017, June). Developing and Evaluating Prototype of Waste Volume Monitoring Using Internet of Things. In IOP Conference Series: Materials Science and Engineering (Vol. 215, No. 1, p. 012038). IOP Publishing. doi.org/10.1088/1757- 899X/215/1/012038 Doraipandian, M. (2020). IoT Framework for Smart Irrigation using Machine Learning Technique. doi.org/10.3844/jcssp.2020.355.363 Harith, M. Z. M. Z., Hossain, M. A., Ahmedy, I., Idris, M. Y. I., Soon, T. K., & Noor, R. M. (2020). Prototype Development of IoT Based Smart Waste Management System for Smart City. IOP Conference Series: Materials Science and Engineering, 884(1). doi.org/10.1088/1757-899X/884/1/012051 Hassan, H., Saad, F., Fazlin, N., & Aziz, A. (2018). Waste Monitoring System based on Internet-of Thing (IoT). Proceedings - 2018 IEEE Conference on Systems, Process and Control, ICSPC 2018, December, 187-192. doi.org/10.1109/SPC.2018.8704142 Kadry, S., Ramasamy, L. K., Mukhopadhyay, S. C., Islam, T., & Haigh, P. A. (2017). Garbage monitoring system using IoT Garbage monitoring system using IoT. doi.org/10.1088/1757-899X/263/4/042027 Mahajan, P. S. A., Kokane, A., Shewale, A., Shinde, M., & Ingale, S. (2017). Smart Waste Management System using IoT. International Journal of Advanced Engineering Research and Science, 4(4), 93-95. doi.org/10.22161/ijaers.4.4.12 Marliani, N. (2015). Pemanfaatan Limbah Rumah Tangga (Sampah Anorganik) Sebagai Bentuk Implementasi dari Pendidikan Lingkungan Hidup. Formatif: Jurnal Ilmiah Pendidikan MIPA, 4(2), 124-132. doi.org/10.30998/formatif.v4i2.146 Mustafa, M. R., & Ku Azir, K.N.F (2017). Smart Bin: Internet-of-Things Garbage Monitoring System. 01030, 1-4. doi.org/10.1051/matecconf/201714001030 Navghane, S. S., Killedar, M. S., & Rohokale, V. M. (2016). IoT Based Smart Garbage and Waste Collection Bin. International Journal of Advanced Research in Electronics and Communication Engineering, 5(5), 1576-1578. http://ijarece.org/wpcontent/uploads/2016/06/IJARECE-VOL-5-ISSUE- 5-1576-1578.pdf Saad, A. F., Ibrahim, M., Damanhuri, M., & Yusuf, N. I. (2019). Developing a Prototype for Sun Tracker System Based on IoT: Controlled by Mobile App and Online Database Monitoring. doi.org/10.3844/ajassp.2019.11.25 Sheng, T. J., Islam, M. S., Misran, N., Baharuddin, M. H., Arshad, H., Islam, M. R., Chowdhury, M. E. H., Rmili, H., & Islam, M. T. (2020). An Internet of Things Based Smart Waste Management System Using LoRa and Tensorflow Deep Learning Model. IEEE Access, 8, 148793-148811. doi.org/10.1109/ACCESS.2020.3016255 Wijaya, A. S., Zainuddin, Z., & Niswar, M. (2017). Design a smart waste bin for smart waste management. Proceedings of the 2017 5th International Conference on Instrumentation, Control, and Automation, ICA 2017, 62-66. doi.org/10.1109/ICA.2017.8068414 Ziouzios, D., & Dasygenis, M. (2019). A Smart Bin Implementation using LoRa. 2019 4th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), 1-4. doi.org/10.1109/SEEDA-CECNSM.2019.8908523 doi: ): 1085.1092 DOI: 10.3844/jcssp.2021.1085.1092

File Description--f4436

File: Tabel Pengukuran(3).xlsx

  • Number of cases: 42

  • No. of variables per record: 12

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Variable Description

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