A web app utilising backend rule-based decision-making in recommending location for food and beverage outlets with desired attributes for customers
Live demo of the application is deployed on Firebase, available at: https://fyp-calvinloh-190428332.web.app/.
Several video demonstrations of functioning web application and high-fidelity prototype is also attached to the submission of this project.
- Problem statement identified as shortfalls in current methods among F&B management.
- Project scope is in understanding customers motivations and location scouting for new outlets.
- Status quo involves the techniques used to gather customer desired attributes and optimal outlet location relies on mainly human intuition
- and limited information technology tools, as identified in literature review and requirement gathering.
The proposed web application seeks to gather customer’s motivations, distill into these distinct criteria as input into this information system. Thereafter, this project aims to use rule-based decision-making based on specific business rules and customer inputs. The output of rule engine is displayed on the web application as a map with markers of target customers frequented locations and feature tiles for each desired attribute your restaurant is recommended to provide.
The project is built using the following technologies, attribution to the various projects and authors are as follows:
- React
- Open-react-template
- Firebase
- Unsplash
- json-rules-engine
- json-forms
- mapbox-gl
- react-map-gl
- emailjs
- mui
- Semantic UI
- sweetalert2
- Nucleo
- All rights reserved. 2022. Calvin.
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Builds the app for production to the build folder.
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