Topic: Dr Daniel Silver
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.
Ag + Tech = Innovation
February 12, 2019 at 7:00pm
Agriculture globally is a 12 trillion dollar annual industry ripe for technology startups looking to bring new hi-tech innovations to market. Where does digital technology and agriculture meet, and what are the opportunities?
Gary Morton (Morton Horticultural Associates, Annapolis Valley Chamber of Commerce Agriculture Committee) will discuss this exciting technology space, and the over $160,000 (cash and in-kind services) that the AVCC has awarded locally to spark agriculture innovation. Dr. Danny Silver (Acadia Institute for Data Analytics) will look at the opportunities around ag. and the field of data analytics. Finally, we will also explore the locally grown startup FoodByte, and how they are making big waves in the ag. tech space.
State of Computer Science Education
February 13, 2018 at 7:00pm
With an estimated 218,000 new skilled ICT workers needed in Canada by 2020 to meet the short term demands of our digital economy, focus on our educational system to address this challenge is paramount. The profound lack of diversity within the digital tech economy further complicates the response required. With changes in our provincial educational pipeline well under way, we are still early on in deploying a comprehensive response.
Join our panel discussion focused on defining challenges and solutions for Computer Science education today.
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.
Jodrey School of Computer Science
The Jodrey School of Computer Science prepares students for today’s ever changing world of technology in a unique, fully mobile computing environment. Students develop a thorough understanding of computer systems software, modern software design methods and computer systems software.
Students in all degree programs complete a self-directed project during the course of their studies. This provides students with the opportunity to work closely with professors and to apply knowledge acquired through experiment and real-life application. Many students work on projects that end up in the public domain as open-source applications, free for everyone to download. Some students complete research work that becomes an integral part of their supervisor’s research, leading to publications in conferences and journals.