An AI-integrated IoT-based Self-Service Laundry Kiosk with Mobile Application


Kusrini Kusrini(1); Alva Hendi Muhammad(2*); Moch Farid Fauzi(3); Jeki Kuswanto(4); Bernadhed Bernadhed(5); Wiwi Widayani(6); Eko Pramono(7); Elik Hari Muktafin(8); Yossy Ariyanto(9);

(1) Universitas Amikom Yogyakarta
(2) Universitas Amikom Yogyakarta
(3) Universitas Amikom Yogyakarta
(4) Universitas Amikom Yogyakarta
(5) Universitas Amikom Yogyakarta
(6) Universitas Amikom Yogyakarta
(7) Universitas Amikom Yogyakarta
(8) Universitas Amikom Yogyakarta
(9) PT. Mataram Karya
(*) Corresponding Author

  

Abstract


This paper proposes KILAO, an IoT-based self-service laundry kiosk connected with a mobile application that aims to improve the laundry experience by improving user convenience and operational efficiency. This study aims to streamline the washing process using autonomous payment systems, real-time monitoring, and AI-based queue management, resulting in better resource utilization and higher user satisfaction. The development technique comprises identification and requirement gathering, development of both software and hardware prototypes, and evaluation of the prototype. In the requirement-gathering phase, the design of a kiosk machine that consists of hardware and software is defined by combining regular washing machines with IoT technologies for remote control and monitoring. We also developed a mobile application to engage with the kiosk machine. The kiosk simplifies the choice of laundry bundles and accepts various payment options, including cash, cashless transactions, and card-based purchases. The evaluation procedure of the prototype was conducted by using expert evaluations. They are from academics and industry professionals who verified the system’s effectiveness and market potential. The results have shown several unique selling features for KILAO. Extensive payment options and self-service operations were highlighted from the customer’s perspective as key benefits. From the seller’s perspective, its interoperability with traditional washing machines enables a low-cost shift to intelligent, self-service operations, eliminating the need for pricey coin-operated machines. Also, the automatic monitoring system that detects cycle completion can reduce waiting times and improve energy efficiency. In summary, KILAO presents a significant advancement in laundry automation by integrating IoT and AI. Moreover, the Gradient boosting algorithm forecasts waiting times and gives real-time information on machine availability, removing the need for physical queueing. The research demonstrates that KILAO’s capability to provide self-service laundry by providing a user-friendly mobile application can enhance user experience, operational efficiency, and energy utilization.


Keywords


Gradient Boosting; IoT; Laundry Automation; Self-Service Kiosk; Smart Laundry Kiosk.

  
  

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doi  https://doi.org/10.33096/ilkom.v16i3.2050.382-393 		  

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Copyright (c) 2024 Kusrini Kusrini, Alva Hendi Muhammad, Moch Farid Fauzi, Jeki Kuswanto, Bernadhed Bernadhed, Wiwi Widayani, Eko Pramono, Elik Hari Muktafin, Yossy Ariyanto

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