Publication Type:

Journal Article

Source:

Communications in Computer and Information Science, Springer Verlag, Volume 956, p.217-229 (2019)

ISBN:

9789811331428

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058296562&doi=10.1007%2f978-981-13-3143-5_19&partnerID=40&md5=c99c8bac757e54cf5b552ca41cb66d72

Keywords:

Artificial intelligence, Decision support systems, Generic system, Grouping keywords, Highly accurate, Plant disease, Preventive measures, Textual description, Web scrapings

Abstract:

<p>The significance of agriculture in India and the amount of damage to the sector due to plant diseases, calls for a system which can identify plant diseases accurately. Improper identification of diseases and taking wrong measures to prevent the disease will be cost inefficient and time consuming. There are highly accurate existing techniques to identify plant diseases but they are specific to a particular crop. In this project, a generic system is developed to identify plant diseases accurately based on textual description of plant diseases. Dataset containing description of diseases is created using the concept of web scraping. The dataset is preprocessed where, keywords are extracted, categorized and grouped to obtain the list of symptoms from the disease description. Based on the symptoms provided by the user to the system, plant disease is identified and the output is the identified disease along with preventive measures. © Springer Nature Singapore Pte Ltd. 2019.</p>

Notes:

cited By 0; Conference of 2nd International Conference on Advanced Informatics for Computing Research, ICAICR 2018 ; Conference Date: 14 July 2018 Through 15 July 2018; Conference Code:221649

Cite this Research Publication

S. P. Thandapani, Senthilkumar, S., and S. Priya, S., “Decision Support System for Plant Disease Identification”, Communications in Computer and Information Science, vol. 956, pp. 217-229, 2019.