Applications of IoT-Enabled Smart Model: A Model For Enhancing Food Service Operation in Developing Countries
DOI:
https://doi.org/10.37385/jaets.v5i2.4937Keywords:
Internet of Things (IoT), Order Management Systems, QR Code, Restaurant, Food ServiceAbstract
The dining sector in developing countries faces numerous challenges, including inefficiencies in order handling, resource management, and ensuring food quality and customer privacy. Traditional methods often lead to delays, errors, and dissatisfaction. This paper proposes a quick-witted, intelligent order-handling system utilizing the Internet of Things (IoT) to address these challenges and enhance the overall dining experience. We present a comprehensive approach to developing and implementing an IoT-based automated order-handling system tailored to restaurants' specific needs and challenges in developing countries, highlighting the importance of technology in enhancing operational efficiency and customer satisfaction. The proposed automated secure order-handling system using IoT demonstrates significant potential for improving efficiency and customer satisfaction in the dining sector. By addressing common problems through advanced technology, this system offers a sustainable solution that enhances the dining experience while ensuring food orders' validity, quality, and privacy. We analyzed the potential impact of implementing such a system in developing countries, focusing on economic and operational benefits.
Downloads
References
Alt, R. (2021). Digital Transformation in the Restaurant Industry: Current Developments and Implications. Journal of Smart Tourism, 1(1), 69–74. https://doi.org/10.52255/smarttourism.2021.1.1.9
Aytaç, K., & Korçak, Ö. (2021). IoT based intelligence for proactive waste management in Quick Service Restaurants. Journal of Cleaner Production, 284. https://doi.org/10.1016/j.jclepro.2020.125401
Bellini, P., Nesi, P., & Pantaleo, G. (2022). IoT-Enabled Smart Cities: A Review of Concepts, Frameworks and Key Technologies. In Applied Sciences (Switzerland) (Vol. 12, Issue 3). MDPI. https://doi.org/10.3390/app12031607
Ben Ayed, R., & Hanana, M. (2021). Artificial Intelligence to Improve the Food and Agriculture Sector. In Journal of Food Quality (Vol. 2021). Hindawi Limited. https://doi.org/10.1155/2021/5584754
Ben-Daya, M., Hassini, E., Bahroun, Z., & Banimfreg, B. H. (2020). The role of internet of things in food supply chain quality management: A review. In Quality Management Journal (Vol. 28, Issue 1, pp. 17–40). American Society for Quality. https://doi.org/10.1080/10686967.2020.1838978
Berezina, K., Ciftci, O., & Cobanoglu, C. (2019). Robots, artifiial intelligence, and service automation in restaurants. In Robots, Artificial Intelligence and Service Automation in Travel, Tourism and Hospitality (pp. 185–219). Emerald Group Publishing Ltd. https://doi.org/10.1108/978-1-78756-687-320191010
Bhuiyan, M. N., Rahman, M. M., Billah, M. M., & Saha, D. (2021). Internet of things (IoT): A review of its enabling technologies in healthcare applications, standards protocols, security, and market opportunities. IEEE Internet of Things Journal, 8(13), 10474-10498.
Bhuiyan, M. N., Billah, M. M., Bhuiyan, F., Bhuiyan, M. A. R., Hasan, N., Rahman, M. M., ... & Niu, M. (2022). Design and implementation of a feasible model for the IoT based ubiquitous healthcare monitoring system for rural and urban areas. IEEE Access, 10, 91984-91997.
Bigliardi, B., Bottani, E., & Filippelli, S. (2022). A study on IoT application in the Food Industry using Keywords Analysis. Procedia Computer Science, 200, 1826–1835. https://doi.org/10.1016/j.procs.2022.01.383
Billah, M. M., Bhuiyan, M. N., & Akterujjaman, M. (2021). Unsupervised method of clustering and labeling of the online product based on reviews. International Journal of Modeling, Simulation, and Scientific Computing, 12(2). https://doi.org/10.1142/S1793962321500173
Blöcher, K., & Alt, R. (2021). AI and robotics in the European restaurant sector: Assessing potentials for process innovation in a high-contact service industry. Electronic Markets, 31(3), 529–551. https://doi.org/10.1007/s12525-020-00443-2
Chavan, S., Chaudhari, P., Gade, K., Sharma, K., M, S., & D.B., P. (2023). Next Generation Electronic Waiter: Wireless Menu Ordering & Serving Robot. International Conference on Edge Computing and Applications (ICECAA).
Chochiang, K., Ung, P., & Bunsaman, N. (2020). One Stop Restaurant Service Application. 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) .
Deng, B., Li, S., Zhang, B., Wang, F., Li, D., & Lin, H. (2019, October 22). Iot Intelligent Restaurant System Design. ACM International Conference Proceeding Series. https://doi.org/10.1145/3331453.3361284
Entreprene. (2023). An overview of the restaurant industry in Bangladesh. Retrieved from https://www.thestrategywatch.com/restaurant-industry-bangladesh/
Intal, L., Payas, J., Fernandez, L., & Domingo, B. (2020). Restaurant Information System (RIS) with QR Code to Improve Service Operations of Casual Fine Dining Restaurant. 7th International Conference on Industrial Engineering and Applications, 1054–1059.
Islam Jubaid, M. J., Haque Chowdhury, M. S., Islam, M., Joy, P. P., Ahmed Hmu, S. E., Abrar, F., Hossain, M. M., & Alam, J. (2023). Design And Construction of a Smart Restaurant Service Using Conveyor Belt. IEEE International Conference on Advances in Electronics, Communication, Computing and Intelligent Information Systems, ICAECIS 2023 - Proceedings, 265–270. https://doi.org/10.1109/ICAECIS58353.2023.10170087
Jeon, H. M., Sung, H. J., & Kim, H. Y. (2020). Customers’ acceptance intention of self-service technology of restaurant industry: expanding UTAUT with perceived risk and innovativeness. Service Business, 14(4), 533–551. https://doi.org/10.1007/s11628-020-00425-6
Kandasamy, A., Shanmugam, T., Theethan, D., & Palaniappan, G. (2023). Smart restaurant menu ordering system using Arduino. AIP Conf. Proc.
Khan, P. W., Byun, Y. C., & Park, N. (2020). IoT-blockchain enabled optimized provenance system for food industry 4.0 using advanced deep learning. Sensors (Switzerland), 20(10). https://doi.org/10.3390/s20102990
Khan, Y., Su’ud, M. B. M., Alam, M. M., Ahmad, S. F., Ahmad, A. Y. A. B., & Khan, N. (2023). Application of Internet of Things (IoT) in Sustainable Supply Chain Management. In Sustainability (Switzerland) (Vol. 15, Issue 1). MDPI. https://doi.org/10.3390/su15010694
Kocaman, E., & Türkmen, B. (2022). The Effects of Use of Restaurant Management Systems Perceived by the Personnel According to Their Demographic Characteristics. IGI Global.
Kodan, R., Parmar, P., & Pathania, S. (2020). Internet of Things for Food Sector: Status Quo and Projected Potential. In Food Reviews International (Vol. 36, Issue 6, pp. 584–600). Taylor and Francis Inc. https://doi.org/10.1080/87559129.2019.1657442
Kumar, I., Rawat, J., Mohd, N., & Husain, S. (2021). Opportunities of Artificial Intelligence and Machine Learning in the Food Industry. Journal of Food Quality, 2021. https://doi.org/10.1155/2021/4535567
Lee, C. H., Chen, C. H., & Lee, Y. C. (2020). Customer requirement-driven design method and computer-aided design system for supporting service innovation conceptualization handling. Advanced Engineering Informatics, 45. https://doi.org/10.1016/j.aei.2020.101117
Lee, Y. K. (2021). Transformation of the innovative and sustainable supply chain with upcoming real-time fashion systems. Sustainability (Switzerland), 13(3). https://doi.org/10.3390/SU13031081
Leung, R., & Loo, P. T. (2022). Co-creating interactive dining experiences via interconnected and interoperable smart technology. Asian Journal of Technology Innovation, 30(1), 45–67. https://doi.org/10.1080/19761597.2020.1822748
Li, J. (Justin), Bonn, M., Wang, J., & Cho, M. (2021). Food delivery application user segmentation in the mobile marketing world in China. Journal of the Asia Pacific Economy.
Marshall, L. (2023). Restaurant Management and Operations: A Tourism Virtual Experience. The Internet and Travel and Tourism Education.
Nagarajan, S. M., Deverajan, G. G., Chatterjee, P., Alnumay, W., & Muthukumaran, V. (2022). Integration of IoT based routing process for food supply chain management in sustainable smart cities. Sustainable Cities and Society, 76. https://doi.org/10.1016/j.scs.2021.103448
Paul, R., Bhandopia, R. R., Patil, R. D., Raut, D. J., & Gotmare, D. A. (2020). An Efficient Digital Ordering System for Restaurant. International Journal of Research in Engineering, Science and Management , 3(3), 391–395.
Qamar, T., Tariq, S., Aqeel, A., Jaffri, F., & Hussain, T. H. (2019). SMARTABLE-Digital Ordering System for Restaurant Using Android. 1st International Conference on Computational Sciences and Technologies.
Qian, J., Wu, W., Yu, Q., Ruiz-Garcia, L., Xiang, Y., Jiang, L., Shi, Y., Duan, Y., & Yang, P. (2020). Filling the trust gap of food safety in food trade between the EU and China: An interconnected conceptual traceability framework based on blockchain. Food and Energy Security, 9(4). https://doi.org/10.1002/fes3.249
Ravi, R., Amrutha, R., Amritha, E., Haneena.P, & Jaseena.T. (2019). An Android Based Restaurant Automation System with Touch Screen. International Conference on Inventive Systems and Control (ICISC 2019), 438–442.
Schmidt, A., Kabir, M. W. U., & Hoque, M. T. (2022). Machine Learning Based Restaurant Sales Forecasting. In Machine Learning and Knowledge Extraction (Vol. 4, Issue 1, pp. 105–130). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/make4010006
Singh, R., Sonje, R., Salkar, S., & Jadhav, A. (2022). Smart QR-based Restaurant Dine-in System with Sales Analysis. ITM Web of Conferences, 44, 03014. https://doi.org/10.1051/itmconf/20224403014
Taillon, B. J., & Huhmann, B. A. (2019). Strategic consequences of self-service technology evaluations. Journal of Strategic Marketing, 27(3), 268–279. https://doi.org/10.1080/0965254X.2017.1411387
Tanizaki, T., Hoshino, T., Shimmura, T., & Takenaka, T. (2020). Restaurants store management based on demand forecasting. Procedia CIRP, 88, 580–583. https://doi.org/10.1016/j.procir.2020.05.101
Trajkovska Petkoska, A., Daniloski, D., D’Cunha, N. M., Naumovski, N., & Broach, A. T. (2021). Edible packaging: Sustainable solutions and novel trends in food packaging. In Food Research International (Vol. 140). Elsevier Ltd. https://doi.org/10.1016/j.foodres.2020.109981
Varriale, V., Cammarano, A., Michelino, F., & Caputo, M. (2021). Sustainable supply chains with blockchain, IoT and RFID: A simulation on order management. Sustainability (Switzerland), 13(11). https://doi.org/10.3390/su13116372
Vemulapalli, G. (2023). Self-Service Analytics Implementation Strategies for Empowering Data Analysts. International Journal of Machine Learning and Artificial Intelligence. https://jmlai.in/
Wen, Z., Hu, S., De Clercq, D., Beck, M. B., Zhang, H., Zhang, H., Fei, F., & Liu, J. (2018). Design, implementation, and evaluation of an Internet of Things (IoT) network system for restaurant food waste management. Waste Management, 73, 26–38. https://doi.org/10.1016/j.wasman.2017.11.054
Yi, S., & Liu, X. (2020). Machine learning based customer sentiment analysis for recommending shoppers, shops based on customers’ review. Complex and Intelligent Systems, 6(3), 621–634. https://doi.org/10.1007/s40747-020-00155-2
Yost, E., Kizildag, M., & Ridderstaat, J. (2021). Financial recovery strategies for restaurants during COVID-19: Evidence from the US restaurant industry. Journal of Hospitality and Tourism Management, 47, 408–412. https://doi.org/10.1016/j.jhtm.2021.04.012
CITEDNESS IN SCOPUS
CITEDNESS IN WOS
