Mushroom Diagnosis Assistance System Based on Machine Learning by Using Mobile Devices

  • Intisar Shadeed Al-Mejibli University of Information Technology and Communications IRAQ
  • Dhafar Hamed Abd Al-Maaref University College IRAQ
Keywords: Android, Decision Tree, Mushroom Determination, Mobile Device, Naive Bays.

Abstract

Picking the wild mushrooms from the wild and forests for food purpose or for fun has become a public issue within the last years because many types of mushrooms are poisonous. Proper determination of mushrooms is one of the key safety issues in picking activities of it, which is widely spread, in countries. This contribution proposes a novel approach to support determination of the mushrooms through using a proposed system with mobile devices.  Part of the proposed system is a mobile application that easily used by a user - mushroom picker. Hence, the mushroom type determination process can be performed at any location based on specific attributes of it. The mushroom type determination application runs on Android devices that are widely spread and inexpensive enough to enable wide exploitation by users.

This paper developed Mushroom Diagnosis Assistance System (MDAS) that can be used on a mobile phone. Two classifiers are used which are Naive Bays and Decision Tree to classify the mushroom types.  The proposed approach selects the most effective of the already known mushroom attributes, and then specify the mushroom type. The use of specific features in mushroom determination process achieved very accurate results.

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Published
2017-11-20
How to Cite
Shadeed Al-Mejibli, I., & Hamed Abd, D. (2017). Mushroom Diagnosis Assistance System Based on Machine Learning by Using Mobile Devices. Journal of Al-Qadisiyah for Computer Science and Mathematics, 9(2), Comp Page 103 - 113. https://doi.org/10.29304/jqcm.2017.9.2.319
Section
Math Articles