Crop Disease Recognition in Smart Farming Using Deep learning Model

India is the second-largest producer of rice, wheat, sugarcane, groundnuts, vegetables, fruits, and cotton in the world. Plant diseases are the leading cause of crop loss. Farmers can boost their productivity by being aware of the state of their vegetable's health. Because of the food we eat daily, many people in our country suffer from chronic ailments due to the high dose of pesticides that not only kill insects but are also present in the vegetables, fruit or green leaves, and therefore indirectly becomes a gradual poisoning for the humans. The model Inception V3 is suggested. The original model relies on categorization convolutional neural networks that have been retrained using the transfer method.

[1] Introduction

Crop disease has been one of the most serious issues in the agricultural sector for decades. It has a direct influence on agricultural productivity, food safety, and property development. According to the Republic of India, agricultural losses are caused by illnesses, animals, and weeds. Squares are the world's second-largest country, producing between two-hundredths and four-hundredths of the global output of vegetables, food grains, and fruit[l],[2]. Global warming might increase agricultural losses through a large number of active fungi and insects in the near future. Farmers recognise traditional illnesses and constrained coaching at presumably significant mistake rates. Similarly, they would not have access to the newest knowledge on treatment for crop disease. Even after visual inspection, professionals still find substantial interrater variability and poor intraater replacement square measurement in line with detailed suggestions and standards [3]. Consequently, crop disease misdiagnosis and incorrect treatment methods commonly happen and may seriously impact agricultural productivity. Inaccurate chemical treatments may boost value and lead to pollution by inefficient and excessively large doses. The technology of scientific management is utilised.