Artificial Intelligence (AI) is now becoming a way of life in every aspect imaginable. Agriculture is also catching up with the benefits of using AI based techniques for telemetry, health monitoring, and control of plants growth factors.
Non-traditional farming techniques such as hydroponics, which is the practice of growing plants in a nutrient solution without soil, are becoming more common. It is the preferable option when compared to soil farming since it yields more in a short time span, requires less water and can be used all year long, so seasonal crops are no longer in scarcity. The process is exceptionally suitable for arid areas or places where soil is not fertile or not available such as deserts, etc. However, there are some limitations that it undergoes including root rot, overwatering and sensitivity to changes in the environment it is placed in. These problems can be overcome by keeping it in a controlled system that regulates any change that can affect the hydroponic plants.
Telemetry is referred to the term of measuring from a distance! In case of hydroponics, this refers to a complete system of remotely monitoring various parameters of a hydroponic system such as water flow, liquid levels, nutrient levels, temperature, pH and conductivity, etc… In this talk, the complete AI based plan for a pilot hydroponic system will be presented that utilizes the IoT (Internet of Things) infrastructure for sensor network and IoT cameras for monitoring leaves for quantification of health of the plants. The use of AI was realized at two levels in this architecture: (a) converting the existing knowledge of hydroponic ‘recipes’ from formulas and experiences into a feedback controller, and (b) plants’ health monitoring through classification of images of the leaves into health categories. While a more elaborative study is underway, the initial findings are very encouraging and we can estimate to see more AI-driven systems in future that can produce better crops in even lesser time.
Biography
Uvais Qidwai received his Ph. D(EE). from the University of Massachusetts–Dartmouth USA in 2001. He taught in the EECS Department at Tulane University in New Orleans USA as Assistant Professor, and was in-charge of the Robotics lab as well as a research member of Missile Defense Center, during June 2001 to June 2005. He lead the robotics teams to several IEEE Robotics contests in USA, supervised graduate students to develop a prototype robotic vehicle for DARPA Grand Challenge 2004-5, and developed several autonomous and semi-autonomous robotic solutions.
His current affiliation (since September 2005) is with the Department of Computer Science & Engineering at Qatar University, Qatar where he is a Professor of Computer Engineering at present. His research interests are focused in the Computer Engineering field and include the development of intelligent embedded systems and techniques applied to healthcare and industrial applications, Machine and Deep Learning applied to health informatics, and Robotics.
He is also the co-Founder of a start-up company, ‘QAI-Sol’, in USA focused on the use of advanced AI solutions for real-world applications.
He has participated in several government- and industry-funded projects in the United States, Saudi Arabia, Qatar, UAE, Singapore, Malaysia, and Pakistan. He has published over 150 papers in reputable journals and conference proceedings, and has been granted one US patents, and three more have been submitted.