Unmanned Aerial Systems in Agriculture

Edited by:   Dionysis Bochtis (Associate Professor Department of Engineering Faculty of Science and Technology Aarhus University Aarhus Denmark), Aristotelis C. Tagarakis (Researcher, Institute for Bio-economy and Agri-technology (iBO), Centre for Research and Technology Hellas (CERTH), Greece), Dimitrios Kateris (Adjunct Assistant Professor, Agriculture Engineering, Technological Educational Institute of Epirus, Greece)
Imprint:   Academic Press Inc
Country of Publication:   United Kingdom
Dimensions:   Height: 229mm,  Width: 152mm, 
Weight:   500g
ISBN:   9780323919401
ISBN 10:   0323919405
Pages:   302
Publication Date:   02 September 2023
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

Dionysis D. Bochtis is an associate professor in the Department of Engineering of Faculty of Science and Technology at Aarhus University, Denmark. He holds a PhD in fleet management in bio-production systems, a MSc in automation control, and a B.Sc. in exact sciences (physics). His primary research is industrial engineering focused on bio-production and related supply chain systems including activities related to fleet management for conventional and autonomous field machinery; field robots (high level control aspects including mission planning, path planning, and task allocation); supply chain management for bio-energy, bio-recourses, and argi-food; field logistics (scheduling, area coverage planning, and routing); and automation and decision support systems. He is well recognized internationally, holding executive positions in the key international associations promoting agricultural engineering. Dr. Aristotelis Tagarakis is a Researcher at the Institute for Bio-economy and Agri- technology (iBO/CERTH) with expertise in precision agriculture. Dr Tagarakis received MSc degree in “Automation in Irrigation, Farm Structures and Farm Mechanization” and PhD degree in “precision agriculture” form the University of Thessaly, Greece. In the framework of his PhD he worked as research scholar at Auburn University, Biosystems Engineering department AL, U.S.A., in the area of Precision Agriculture, variable rate fertilization and automated irrigation in maize. Also, he has been Postdoctoral Associate at Cornell University, N.Y., U.S.A., leading the precision agriculture program. Before joining the iBO he was senior researcher at the BioSense Institute in Serbia. He has significant research experience working at various national, European, and other international projects. His main research interests include precision agriculture, digital farming, farm management information systems, remote sensing, sensor networks in agriculture, agricultural engineering, and automations in agriculture. ?Dimitris Kateris is currently an ?Adjunct Assistant Professor in Agriculture Engineering at the Technological Educational Institute of Epirus. He received his Ph.D. degree in Agricultural Engineering from Aristotle University of Thessaloniki in 2015, for his dissertation on ""Intelligent system for fault diagnosis in agricultural tractor mechanical subsystems"" He also holds M.Sc. degree from the Aristotle University of Thessaloniki in 2006 and two bachelor degrees in Agricultural Engineering and Water Resources from Aristotle University of Thessaloniki (2006) and Technological Educational Institute of Thessaly (1999), respectively. From 2012 to 2015 was an Adjunct Lecturer at the Department of Agriculture Technology, Technological Instute of Epirus. From 2002 to 2011 was an Adjunct Lecturer in Agriculture Engineering at the Department of Biosystems Engineering, Technological Instute of Thessaly. He concentrates his scientific research in the areas of Agricultural Machinery, Nondestructive testing and evaluation, Fault diagnosis techniques in mechanical subsystems, Vibration Analysis, Acoustic Emission Analysis, Machine Condition Monitoring, Neural Networks (NN), Machinery and Power systems, Safety and Reliability in Agricultural Machinery, Automation and New Technologies in Agricultural Machinery, Status check using Neural Networks and Self-Organizing Maps, Support Vector Machines (SVM).