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IoT-Based LPG Level Sensor for Domestic Stationary Tanks with Data Sharing to a Filling Plant to Optimize Distribution Routes

Author

Listed:
  • Roberto Morales-Caporal

    (Instituto Tecnológico de Apizaco, Tecnológico Nacional de México, Av. Instituto Tecnológico s/n, Apizaco C.P. 90300, Mexico)

  • Rodolfo Eleazar Pérez-Loaiza

    (Instituto Tecnológico de Apizaco, Tecnológico Nacional de México, Av. Instituto Tecnológico s/n, Apizaco C.P. 90300, Mexico)

  • Edmundo Bonilla-Huerta

    (Instituto Tecnológico de Apizaco, Tecnológico Nacional de México, Av. Instituto Tecnológico s/n, Apizaco C.P. 90300, Mexico)

  • Julio Hernández-Pérez

    (Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Luis Enrique Erro No. 1, San Andrés Cholula C.P. 72840, Mexico)

  • José de Jesús Rangel-Magdaleno

    (Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Luis Enrique Erro No. 1, San Andrés Cholula C.P. 72840, Mexico)

Abstract

This research presents the design and implementation of an Internet of Things (IoT)-based solution to measure the percentage of Liquefied Petroleum Gas (LPG) inside domestic stationary tanks. The IoT-based sensor, in addition to displaying the percentage of the LPG level in the tank to the user through a mobile application (app), has the advantage of simultaneously sharing the acquired data with an LPG filling plant via the Internet. The design process and calculations for the selection of the electronic components of the IoT-based sensor are presented. The methodology for obtaining and calibrating the measurement of the tank filling percentage from the magnetic level measurement system is explained in detail. The operation of the developed software, and the communication protocols used are also explained so that the data can be queried both in the user’s app and on the gas company’s web platform safely. The use of the Clark and Wright savings algorithm is proposed to sufficiently optimize the distribution routes that tank trucks should follow when serving different home refill requests from customers located in different places in a city. The experimental results confirm the functionality and viability of the hardware and software developed. In addition, by having the precise location of the tank, the generation of optimized gas refill routes for thirty customers using the heuristic algorithm and a visualization of them on Google Maps is demonstrated. This can lead to competitive advantages for home gas distribution companies.

Suggested Citation

  • Roberto Morales-Caporal & Rodolfo Eleazar Pérez-Loaiza & Edmundo Bonilla-Huerta & Julio Hernández-Pérez & José de Jesús Rangel-Magdaleno, 2024. "IoT-Based LPG Level Sensor for Domestic Stationary Tanks with Data Sharing to a Filling Plant to Optimize Distribution Routes," Future Internet, MDPI, vol. 16(12), pages 1-26, December.
    • Handle: RePEc:gam:jftint:v:16:y:2024:i:12:p:479-:d:1549536
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    References listed on IDEAS

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    1. Shih-Che Lo, 2022. "A Particle Swarm Optimization Approach to Solve the Vehicle Routing Problem with Cross-Docking and Carbon Emissions Reduction in Logistics Management," Logistics, MDPI, vol. 6(3), pages 1-15, September.
    2. Dingding Qi & Yingjun Zhao & Zhengjun Wang & Wei Wang & Li Pi & Longyue Li, 2024. "Joint Approach for Vehicle Routing Problems Based on Genetic Algorithm and Graph Convolutional Network," Mathematics, MDPI, vol. 12(19), pages 1-18, October.
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