Design and Implementation of an Android Nigerian Recipe Generating System

Faiza Babakano Jada*, Ishaq O. Oyefolahan**, Hussein A. Zubairu***, Stella O. Etuk****, Farida Suleiman*****
*, ****Assistant Lecturer, Department of Information and Media Technology, School of Information and Communication Technology, Federal University of Technology, Minna, Nigeria.
** Senior Lecturer, Department of Information and Media Technology, Federal University of Technology, Minna, Nigeria.
*** Lecturer, Department of Information and Media Technology, School of Information and Communication Technology, Federal University of Technology, Minna, Nigeria.
*****Graduate,Department of Information and Medi Technology, Federal University of Technology, Minna,Nigeria.
Periodicity:July - December'2018
DOI : https://doi.org/10.26634/jmt.5.2.15629

Abstract

Food is any edible substance that is expected to give nutritional value to the living body. It is required for vitality, development and counteractive action of disease and repair of body cells. Daily, individuals are confronted with lack of knowledge on what to cook, how to cook or what ingredients are available or unavailable for cooking. This could be as a result of various reasons and can result to other problems like overthinking, food repetition, ignorance of availability of ingredient and food wastage, thus, this system was developed to help eliminate or reduce these problems. The system generates possible Nigerian meals that can be prepared with available ingredients in stock. It was developed for Android devices and implemented using Android Studio, with Java as the programming language, XML for the interface and SQLite for the database. The system was deployed on forty user’s mobile devices for testing and got positive feedbacks. The system proved to be useful and satisfied its potential users.

Keywords

recipe generator; smart systems; Android applications; mobile applications

How to Cite this Article?

Jada, F. B., Oyefolahan, I. O., Zubairu, H. A., Etuk, S. O., & Suleiman, F. (2018). Design and Implementation of an Android Nigerian Recipe Generating System. i-manager’s Journal on Mobile Applications and Technologies, 5(2), 19-28. https://doi.org/10.26634/jmt.5.2.15629

References

[1]. Dandekar, R., Gadkari, S., Sadudia, M., Kamble, S. (2016). FOODIE: An Android application. International Journal for Research in Applied Scienceand Engineering Technology, 6(111), 550-555.
[2]. Darwin, I. F. (2012). Android Cookbook: Problems and Solutions for Android Developers. USA: O'Reilly Media Inc.
[3]. Freyne, J., Berkovsky, S., & Smith, G. (2011). Recipe recommendation: Accuracy and reasoning. In 19th International Conference on user Modeling, Adaptation, and Personalization (pp. 99-110).
[4]. Hans-Erik, E., Magnus, P., Brian, L., & David, F. (2004). UML™ 2 Toolkit. USA : Wiley Publishing.
[5]. Jagithyala, A. (2015). Recommending Recipe Based On Ingredients And User Reviews. In Proceedings of the 4th IEEE International Congress on Big Data, Application Track. (pp. 475-482).
[6]. Kuo, F. F., Li, C. T., Shan, M. K., & Lee, S. Y. (2012). Intelligent menu planning: Recommending set of recipes by ingredients. In Proceedings of the ACM Multimedia 2012 Workshop on Multimedia for Cooking and Eating Activities (pp. 1-6).
[7]. Maruyama, T., Kawano, Y., & Yanai, K. (2012). Real-time mobile recipe recommendation system using food ingredient recognition. In Proceedings of the 2nd ACM International Workshop on Interactive Multimedia on Mobile and Portable Devices (pp. 27-34).
[8]. Nedovic, V. (2013). Learning recipe ingredient space using generative probabilistic models. In Proceedings of Cooking with Computers Workshop (CwC) (Vol. 1, pp. 13- 18).
[9]. Schäfer, H., Groh, G., Schlichter, J. H., Kolossa, S., Daniel, H., Hecktor, R., & Greupner, T. (2015). Personalized Food Recommendation. Proceedings of the 2nd International Workshop on Decision Making and Recommender Systems (pp. 21-24).
[10]. Ueda, M., Asanuma, S., Miyawaki, Y., & Nakajima, S. (2014). Recipe recommendation method by considering the users preference and ingredient quantity of target recipe. In Proceedings of the International Multi-Conference of Engineers and Computer Scientists (Vol. 1).
[11]. Ueta, T., Iwakami, M., & Ito, T. (2011). A recipe recommendation system based on automatic nutrition information extraction. In International Conference on Knowledge Science, Engineering and Management (pp. 79-90).
[12]. Teng, C. Y., Lin, Y. R., & Adamic, L. A. (2012). Recipe recommendation using ingredient networks. In Proceedings of the 4th Annual ACM Web Science Conference (pp. 298-307).
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