Agriculture
is the main source of income for Indian citizens with about 60% of the
population depending upon agriculture which influences India’s economy. Crop selection
and disease management plays a crucial role in the farmer’s economy. Smart farming
systems help farmers to increase crop production through automated systems. Crop
diseases can be predicted by a comprehensive analysis system. Smart farming system
with Artificial Intelligence (AI) observes, and manages Internet of Things
(IoT) devices to detect crop diseases by visual symptoms. Smartphone-based AI
apps guide farmers for disease diagnosis, thus preventing yield loss. This
system will detect plant diseases present on the leaves and provide preventive
measures for the detected diseases. The plant leaf images are collected which
show symptoms of diseased and healthy plants under maintained conditions to
check for fungal, bacterial and viral diseases. Machine and Deep Learning can
help identify crop diseases based on collected images and datasets pertaining
to the crops segmented into Healthy and Diseased Crop. The IoT technology
implements specific systems at different levels to predict crop diseases
effectively. The different data is accessed easily from the centralized cloud
system. The crop diseases are managed with the use of high fungicides due to
this soil toxicity increase but this activity system will provide the best recommendations
for proper disease management. AI, Image processing, IoT, machine learning,
robotics, satellites, cloud computing technologies are improving farmers' crop management
practices.
Keywords: Crop diseases, Crop management, Deep learning, Image processing, Internet of things, Machine learning, Smart farming.
