Fawad Ali Shah¹, Habib Akbar¹, Abid Ali^2,3, Parveen Amna⁴, Maha Aljohani⁵, Eman A. Aldhahri⁶, Harun Jamil^7,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1385-1413, 2023, DOI:10.32604/csse.2023.036144

Abstract The detection of rice leaf disease is significant because, as an agricultural and rice exporter country, Pakistan needs to advance in production and lower the risk of diseases. In this rapid globalization era, information technology has increased. A sensing system is mandatory to detect rice diseases using Artificial Intelligence (AI). It is being adopted in all medical and plant sciences fields to access and measure the accuracy of results and detection while lowering the risk of diseases. Deep Neural Network (DNN) is a novel technique that will help detect disease present on a rice leave because DNN is also considered… More >

R. Sowmyalakshmi¹, T. Jayasankar^1,*, V. Ayyem Pillai², Kamalraj Subramaniyan³, Irina V. Pustokhina⁴, Denis A. Pustokhin⁵, K. Shankar⁶

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1751-1767, 2021, DOI:10.32604/cmc.2021.016825

Abstract Internet of Things (IoT) paves a new direction in the domain of smart farming and precision agriculture. Smart farming is an upgraded version of agriculture which is aimed at improving the cultivation practices and yield to a certain extent. In smart farming, IoT devices are linked among one another with new technologies to improve the agricultural practices. Smart farming makes use of IoT devices and contributes in effective decision making. Rice is the major food source in most of the countries. So, it becomes inevitable to detect rice plant diseases during early stages with the help of automated tools and… More >