Mr. Lucas Franco | Precision agriculture | Best Researcher Award

Mr. Lucas Franco, Universidade Federal de São Carlos, Brazil

Lucas is a Senior Developer at iDtrust, specializing in financial solutions with technologies like Java, Python, AWS, and Agile methodologies. He holds a Master’s in Computer Science from UFSCar, focusing on AI-driven drone route optimization for precision agriculture. Lucas also has expertise in automation and data analysis, with experience in the agricultural and industrial sectors. He has worked on projects with Embrapa/Qualcomm and Inselli Engenharia & Ciência Aplicada, contributing to automation and intelligent systems development. Passionate about learning and research, he is skilled in programming, machine learning, and cloud computing. 💻🤖🚁

Publication Profile

Google Scholar

Education and Academic Background

Lucas Franco holds a Master’s degree in Computer Science from UFSCar (2017-2019), where he conducted research on optimizing drone routes for precision agriculture using AI, under the guidance of Prof. Dr. Edilson Kato. He earned his Bachelor’s degree in Computer Science from UniSeb (2012-2015) and a degree in Industrial Automation Technology from IFSP (2009-2011). Lucas also completed a technical course in Industrial Automation at CEFET in 2008. His academic background equips him with a strong foundation in computer science, automation, and innovative technology applications. 🚁🤖💡

Professional Experience

Lucas Franco is currently a Senior Developer at iDtrust (2018-present), creating financial solutions using Java, Python, AWS Cloud, and Agile Scrum methodology. From 2016 to 2018, he worked on the Embrapa/Qualcomm project, focusing on drone technology for precision agriculture, image processing, and system configuration. He also taught Digital Circuits at Domênico Technical School (2016). Between 2010-2016, Lucas worked as a Systems Analyst at Inselli Engenharia, conducting research in automation, gas leak detection, embedded systems, software testing, and database management. He also assisted in automation courses at IFSP. 🤖📊💻

Qualifications

Lucas Franco has strong qualifications in Computer Science, proficient in programming languages such as Java, Python, R, MATLAB/SCILAB, C/C++, and Delphi. He has experience with AWS Cloud services, machine learning, data processing, and SQL database management, alongside embedded system development in Linux. In Industrial Automation, he excels in research and development, PLC programming, instrumentation, communication protocols, and bench testing with industrial equipment. Personally, Lucas possesses strong logical reasoning, teamwork skills, interpersonal relationships, and a passion for self-learning, research, and knowledge sharing. He is always eager to contribute and enhance team knowledge. 🤖📚

Research Focus

Lucas dos Santos Franco’s research primarily focuses on drone technology and precision agriculture. His work explores flight path optimization for multirotor Unmanned Aerial Vehicles (UAVs) using Ant Colony Optimization (ACO), a metaheuristic algorithm, to enhance agricultural applications. This research aims to improve aerial coverage in farming practices, optimizing efficiency and reducing operational costs. Additionally, his expertise in machine learning, data processing, and cloud computing complements his research in automation, especially for systems involving UAVs, remote sensing, and georeferencing. His contributions support technological advancements in agriculture and automation. 🌾🤖📡

Publication Top Notes

Publication: “A method for planning multirotor Unmanned aerial vehicle flight paths to cover areas using the Ant Colony Optimization metaheuristic”
Cited by: ERR Kato, RS Inoue, L dos Santos Franco
Year: 2025
📚🌍

Ms. Mar Ariza-Sentís | Precision Agriculture Award | Young Scientist Award

Ms. Mar Ariza-Sentís, Wageningen Univresity & Research, Netherlands

Maria del Mar Ariza-Sentís, a Ph.D. candidate at Wageningen University, specializes in Geo-Information Science and is an AI expert for the FlexiGroBots project. 🤖 With a background in Agricultural and Food Engineering, she’s dedicated to reducing pesticide use through AI models detecting Botrytis cinerea in vineyards. Maria’s expertise spans UAV technology, Big Data, and geospatial analysis. 🌱 As an educator, she has taught courses and moderated MOOCs, contributing significantly to agricultural innovation. Maria’s research publications and conference presentations underscore her commitment to advancing precision agriculture. Beyond academia, she enjoys figure skating, martial arts, and playing the piano. 🎿🥋🎹

Publication Profile

Orcid

Google Scholar

Professional Background

Maria del Mar Ariza-Sentís is a Ph.D. candidate at Wageningen University, specializing in Geo-Information Science. 🎓 With a master’s degree from Wageningen and a bachelor’s from the University of Lleida, she’s earned recognition for her academic achievements. Maria’s expertise extends to AI and UAV technology, evident through her role as an AI expert for the FlexiGroBots project, aiming to reduce pesticide use in agriculture. 🌿 Her diverse professional experience includes internships, teaching positions, and contributions to academic research, highlighting her commitment to advancing agricultural innovation.

Education and Awards

Maria’s dedication to continuous learning is evident through her complementary education, including a EU Drone license and qualifications in phytosanitary product handling. 🛩️ Her academic excellence has been recognized through numerous honors and awards, reflecting her commitment to excellence in research and academia.

Research Focus

Maria del Mar Ariza-Sentís’s research primarily focuses on the application of unmanned aerial vehicles (UAVs) and AI technologies in precision agriculture, with a specific emphasis on vineyard management. 🌱 Her work spans various areas, including object detection and tracking in precision farming, mapping spatial variability of diseases like Botrytis bunch rot, and optimizing crop management practices through UAV-based data analysis. 🚜 Maria’s innovative research contributes to sustainable agriculture by providing insights into crop health, yield prediction, and resource optimization, ultimately enhancing agricultural efficiency and minimizing environmental impact. 🌾