Iot based laundry services: an application of big data analytics, intelligent logistics management, and machine learning techniques

• Published in: International journal of production research Vol. 58; no. 17; pp. 5113 - 5131
• Main Authors: Liu, Chang, Feng, Yongfu, Lin, Dongtao, Wu, Liang, Guo, Min
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 01.09.2020; Taylor & Francis LLC
• Subjects: Analytics; Big Data; big data analytics; Business models; Customers; Data analysis; Electronic commerce; intelligent manufacturing systems; Internet of Things; Laundries; Logistics management; Machine learning; performance measures; Profitability; real time scheduling; Smartphones; Transport buildings, stations and terminals
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207543.2019.1677961

The authors propose an innovative Internet of Things (IoT) based E-commerce business model Cloud Laundry for mass scale laundry services. The model utilises big data analytics, intelligent logistics management, and machine learning techniques. Using GPS and real-time update of big data, it calculates the best transportation path and update and re-route the logistic terminals quickly and simultaneously. Cloud laundry intelligently and dynamically provides the best laundry solutions based on the current state spaces of the laundry terminals through the user's specifications and thus offers local hotel customers with convenient, efficient, and transparent laundry services. Taking advantage of the rapid development of the big data industry, user interest modelling, and information security and privacy considerations, cloud laundry uses smartphone terminal control and big data models to maintain customers' security needs. Different from the traditional laundry industry, cloud laundry companies have higher capital turnover, more liquidity, and stronger profitability. Therefore, this new generation of smart laundry business model could be of interest to not only academic researchers, but E-commerce entrepreneurs as well.