AI Driven Greentech Innovation in Agriculture
Ajith Kumar. P
Department Of Electronics and
Communication
Panimalar Institute of Technology Chennai, India.
pajith597@gmail.com
Barath. S
Department Of Electronics and
Communication
Panimalar Institute of Technology Chennai, India.
btwinknights26@gmail.com
Gowtham. S
Department Of Electronics and
Communication
Panimalar Institute of Technology Chennai, India.
gowthamspartan0@gmail.com
Mr. D. GuruPandi, M.E.
Assistant Professor
Department Of Electronics and
Communication Engineering
Panimalar Institute of Technology
Chennai, India
gurupandi85@gmail.com
Dr. S. Sathiya Priya, M.E., Ph.D. Dr. V. Jeya Ramya, M.E., Ph.D.
Professor & HOD Associate Professor
Department Of Electronics and Department of Electronics and
Communication Engineering Communication Engineering
Panimalar Institute of Technology Panimalar Institute of Technology
Chennai, India Chennai, India
priya.anbunathan@gmail.com jeyaramyav@gmail.com
Abstract— Agriculture is a primary concern of every developing nation. But most of the processes involved in agricultural sector are still orthodox and inefficient. Though the technology is improving day by day, it is high time to incorporate technology innovations into the field of agriculture for better productivity and resource utilization. We propose an intelligent farming technology with the aid of Internet of Things (IoT) and Machine Learning to make various farming techniques smarter and efficient. Various sensors were deployed in the fields to remotely monitor the parameters of soil, water and air. The sensed information is fed to an Android app and it will process the data and alert the farmer if any unusual events occur. We are also using convolutional neural network for detecting various diseases affected by the plants. Experimental results validate that our model can be used for efficient utilization of agricultural resources like water and fertilizers and thereby improve the productivity and profit.
Keywords—Internet of Things, Smart farming, Machine Learning, Plant disease identification, IoT in Agriculture.
