Sensor technologies and ‘Internet of Things’ (IoT) approaches are understood to hold great promise for agricultural research for development, yet researchers may have a difficult time navigating a diverse and complex array of service providers, technologies, and approaches. In order to begin to address this bottleneck, the CGIAR Platform for Big Data in Agriculture conducted an end-to-end design process for selecting services, software platforms, data transmission solutions, and the sensors themselves in light of requirements gathered from crop breeders and agronomists.

The design incorporated input from researchers at the Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), and the CGIAR Excellence in Breeding Platform to arrive at an IoT network design centered on the Alliance of Bioversity International and CIAT research campus in Palmira, Colombia. The resulting IoT pilot will help in the data collection from crops and environmental variables and in its integration with the analyses and services undertaken by the research teams with the high-throughput phenotyping and data-driven agronomy teams of CIAT, and with the ambition of providing a reference architecture that can meet cross-cutting research infrastructure needs identified across CGIAR centers and the wider research community.

Presenter

Dr. Jairo Alejandro Gómez

Senior Researcher

Research Group in Spatial Economics (RiSE), Department of Mathematical Sciences, EAFIT University

Dr. Jairo Alejandro Gómez received a Ph.D. in Engineering from the Australian Centre for Field Robotics (ACFR) at the University of Sydney (Australia) in 2011. He completed his studies in Electronic Engineering at Universidad del Valle (Colombia), receiving the best graduate award in 2005. Between 2016 and 2018 he worked as a Postdoctoral Research Fellow at the Center of Excellence and Adoption on the Internet of Things (CEA-IoT) in Colombia, leading the research line in agro-industry and environment. In 2018, he joined the PEAK Urban project as a Postdoctoral Researcher within the Research group in Spatial Economics (RiSE) at EAFIT University (Colombia), where he is leading a project to model the urban footprint growth in Latin American cities by combining machine learning algorithms with satellite imagery. Gómez has worked as a lecturer at Universidad de San Buenaventura, Universidad Autónoma de Occidente, and Pontificia Universidad Javeriana in Cali (Colombia). His research interests include computer vision, machine learning, robotics, and the Internet of Things, focusing on the development of intelligent products and services. He is a professional member of the Institute of Electrical and Electronics Engineers (IEEE), the Robotics and Automation Society (RAS), and the Association for Computing Machinery (ACM).