IoT based Credit Payment Management (MCP) Monitoring System for the Caterpillar 305.5E2 Excavator

DOI

10.2991/978-94-6463-364-1_41How to use a DOI?

Keywords

heavy equipment; credit payment management; ESP32; Blynk IoT; McpPay

Abstract

In heavy equipment sales, mainly by credit payment, leasing company or owner gives customer the trust to use heavy equipment or machines and pay off the credit by the project income they are working on. Agreement between the two parties is generally implemented as a contract involving day-to-day working hours, workplace limits, and service and maintenance periods. To monitor the condition of the machine while it is operating in the field, the owner generally communicates with the customer by telephone. This method has proven to be less effective, particularly when customers are dishonest. The Credit Payment Management System (MCP) is developed to allow the owner supervising the machine exploitation. The system consists of hardware and software, where the hardware main components are ESP32, GSM, GPS, and relays modules, while the software consists of the host program on ESP32, the application program on the mobile phone connected to Blynk IoT, and the McpPay application on the computer connected with the host program on ESP32. Evaluation after implementation shows that the system can serve its purpose. The position of the machine can be detected on the map. It will be automatically turned down when it is brought outside the contract area. Also, the machine will be shut down if the payment has not been made. In addition, owner and customer can expect maintenance due to the working hours reported by the machine. If the machine shut down, the customer may ask the owner to activate the machine when the agreement is reached.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Faisal Backrie
AU  - Prihadi Murdiyat
AU  - Verra Aullia
PY  - 2024
DA  - 2024/02/17
TI  - IoT based Credit Payment Management (MCP) Monitoring System for the Caterpillar 305.5E2 Excavator
BT  - Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)
PB  - Atlantis Press
SP  - 435
EP  - 448
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-364-1_41
DO  - 10.2991/978-94-6463-364-1_41
ID  - Backrie2024
ER  -