Canada is one of the largest canola producing countries. The industry contributes about $20 billion revenue to the Canadian economy. Currently, canola farmers rely on the weather forecast (temperature, moisture, etc.) to decide whether to apply a fungicide. As the Internet-of-Things and sensor technologies get more advanced, farmers are deserved to have better technologies for intelligent farming. In this project, we propose the design of Internet-of-Things devices to monitor Sclerotinia sclerotiorum, a deadly airborne spore for canola.
Genetic engineering has proven to be a useful approach for gene therapy and transformation of value-added agricultural plants. However, the current available technologies suffer from several limitations. These include relative low delivery efficiency with difficult-to-deliver cells or complex constructs and limit freedom-to-operate. Considering advances have been made in the applications of nanotechnology to life science and plant biology, particularly in the realm of gene editing technology, improving delivery efficiency is urgently needed.
This project studies efficient online optimization algorithms for large-scale data transfer among data centers in a geographically-distributed cloud system, as well as their SDN (Software Defined Networking)-facilitated implementation. Big data analytics, content distribution, and various web applications (social networking, search engine) have become dominating applications on today's cloud platforms.