Development of voice-activated ordering using android application for restaurant

Loi, Ming Onn (2021) Development of voice-activated ordering using android application for restaurant. Project Report. Melaka, Malaysia, Universiti Teknikal Malaysia Melaka. (Submitted)

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Abstract

Lifestyle today is very challanging nowadays and thus saving time is one of the most important factor for every industry field, especially food and beverage service which mainly from restaurant. A crowded restaurant with a long queue to take order has cause problem to many customers as they wanted to have easier and faster way to make their order without waiting too long. Customer who just need simple and fast checkout order have difficulties to repeat browsing the menu as they needed to take longer time and increase their waiting time. The main objective of this research is to develop a simple and user-friendly system application for menu ordering system that can improve the customer usage by also implementing voice-recognition technology as a possible method for these targeted customers. The system will be also adding in a basic database to apply two-way communication between the system and data input by the users for data collection. The work scope of this project includes system design that will made by free prototyping and designing tools. The application of the menu ordering system will be also developed with AndroidOS platform with Extensible Markup Language (XML) and JAVA programming language. Then the voice-recognition technology which also using Google Speech-to-Text (STT) and its function is implemented and combined into the application. An data collection of result will be analysed based on the accuracy for the voice-recognition method and comparison of time taken between these the common traditional manual method versus voice ordering method. The methodology is involving free assisting tool such as StarUML Draw.io, Adobe XD that are used to illustrate the workflow, system cycle and also the Graphical User Interface (GUI) of the application. Then the the application is programmed and structure with the Android Studio that based on AndroidOS system’s native users that use other devices than computer. There is significant consistency on the comparison for the results, where its percentage accuracy between preliminary result and expected result only 10% difference, 1.9seconds of weighted mean in manual ordering and 3 seconds for voiceordering method, given that some of addition of extra features and improvement. Overall, the methodology has succeed in giving out the main required result from data collection and analysis and showing the potential of improvement on quality of menu ordering system is exist by implementing voice recognition method into it and improve restaurant operation.

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