Topic: Machine Learning
The Startup Life: Meet R2-Weed2
October 9, 2019 at 7:00pm
Technology-driven agricultural experimentation. Iterative product testing. Validated machine learning. Pivot. Pivot. Pivot. Welcome to the ag-tech startup world of Teric Greenan and Nexus Robotics .
With Nexus Robotics , Teric is applying Artificial Intelligence to building a reliable and cost-effective way to produce crops. Their autonomous robot R2-Weed2 is capable of cutting and spraying weeds, fertilizing crops, and collect data about growing conditions. Teric will talk about his team’s start up journey, and the amazing technological innovations they are applying to revolutionize agriculture as we know it.
Teric Greenan
Teric grew up in Halifax, Nova Scotia. He ran a small vegetable farm in Lunenburg County, Nova Scotia for three years. He observed there were a lot of repetitive tasks on farms that were consuming farmers’ resources. These repetitive tasks seemed like good candidates to be automated. After talking with other vegetable farmers, it became clear that weeding was a massive problem that could be solved by a robot. In May of 2017, Teric founded Nexus Robotics with his close friend who is a computer engineer, Jad Tawil. Teric’s experience on the farm has been valuable for guiding product development at Nexus.
Forecasting: Using Machine Learning Techniques in Energy, Environment and Agriculture
January 10, 2017 at 7:00pm
Dr Daniel Silver will review a series of projects undertaken by the Acadia Institute for Data Analytics . These amazing projects can estimate crop yield from smart phone images, do solar energy forecasting, manage building energy, determine stream flow rate and aquifer recharge prediction, sales forecasting, and classifying objects in UAV agriculture field images.
Many of these problems utilize high resolution observed and forecasted weather, high definition and multi-spectral digital images, and 5 minute through 60 minute data flow rates. These projects use a variety of machine learning methods. Come learn about standard neural networks, random forests, more advanced deep and recurrent neural networks, as well as transfer learning.
Acadia Institute for Data Analytics
Rural Canada feeds our nation literally, economically, and environmentally. It provides the food, fiber, minerals, water and other bio-resources and natural resources on which our country depends and the arteries of transportation by which they are delivered. Digital technologies and data analytics can help us shape how we work with these resources and their impact on our local communities and our planet.
Mission
To advance knowledge in data analytics through collaborative and interdisciplinary research, education and outreach and to foster the ethical application and commercialization of data analytic solutions to challenges facing industry, government and society in rural Canada. The institute will initially focus on agriculture, food production, the environment, and green energy.
Dr Daniel Silver
Dr. Daniel L. Silver is the Director of the Acadia Institute for Data Analytics . He is also a Professor in and currently the Acting-Director of the Jodrey School of Computer Science at Acadia University. His areas of research and application are machine learning, data mining, and data analytics. His expertise is in Lifelong Machine Learning and Transfer Learning. He has published over 65 scientific papers and has co-chaired or been part of program committees for a number of national and international conferences, seminars and workshops on data mining and machine learning. He was the President of the Canadian Artificial Intelligence Association (CAIAC) from 2009-11. In 2011, he received the Science Champion Award from the Nova Scotia Discovery Center for his work on youth robotics and the advancement of STEM education. In December, 2014, he became an Honorary Colonel in the RCAF attached to 14 Wing Software Engineering Squadron, in Greenwood, NS. In June of 2016, was awarded Canadian AI’s Distinguished Service Award. Danny has over 30 years of experience in information technology, project management and business administration. Since 1993, he has worked on machine learning and data mining projects in the private and public sector providing situation analysis and problem definition, project management and guidance, and data mining services.
Matt Hall
I make stuff happen at Agile*, an independent geoscience idea factory in Canada.
We build awesome knowledge engines for organizations (mostly wikis), and we hone our skills in subsurface science… We have most recently been working on geothermal reservoir description. I’ve worked the Montney tight gas of Alberta and BC, frontier exploration in the Canadian Beaufort Sea, the Athabasca oil sands, the Norwegian North Sea. I also worked in software for several years, as an advocate of integrated volume visualization and interpretation and viz room pilot.
Nexus Robotics
Nexus Robotics is a Nova Scotian technology startup, developing autonomous robotic solutions for Agriculture using machine learning. Nexus provides farmers with a reliable and cost-effective way to produce crops. The Nexus Robotics team created an autonomous machine called R2-Weed2, which uses a camera system to differentiate between weeds and crops. The machine will be capable of cutting and spraying weeds, as well as able to fertilize crops and collect data about the crop and growing conditions.
PrecisionHawk
PrecisionHawk is the leading provider of aerial data and safety platforms for drones. The Lancaster is PrecisionHawk’s fixed-wing, autonomous drone built to collect the highest quality terrestrial data using a host of integrated sensors including visual, thermal, LiDAR, multispectral and hyperspectral. PrecisionHawk houses three divisions that support its mission: DataMapper aerial mapping and analysis software, TerraServer satellite imagery and LATAS (Low Altitude Traffic and Airspace Safety).