An Early Recommendation Tool to Enhance Medicinal Plant Growth based on GIS and Soil Data

Ayurvedic medicinal plants are in the spotlight, solving the major problem which is being arisen in the modern world. Ayurvedic plants are acquiring great attention in the prescription field owing to having fewer deadly effects on human life and being much less expensive than chemical-based medicines. Based on the available statistics many scientists have shown plenty of interest in the research of recognizing and nurturing medicinal plants. The serious concern is the extension of medicinal plants affecting the life of the needy. In this paper, a novel method is proposed to identify the geographical location and the best suitable soil type of the medicinal plant species in the region of Karnataka, India. The work targets on few vulnerable plants and employs the random forest algorithm (decision tree algorithm) for the recommendation of the medicinal plants based on the soil and GIS data. Hence, an appropriate and easy access solution for the real-time information on the Ayurvedic herbs of Karnataka. The expected outcome of the system is a recommendation tool to grow, conserve and enhance the knowledge of medicinal plants by using the decision tree algorithm, revealing the vital details of herbs such as conservation status, soil type, region name, geo-location and climate condition for the growth of the medicinal plants to help its stakeholders. The system helps to preserve the ancient and traditional medicinal knowledge by identifying the medicinal plants using decision tree based predictive model.