RESEARCH
Agri-Food Supply Chain Management
With the upsurge of data-driven models, and modern (computationally intensive) optimization techniques, there is an evident opportunity to improve the efficiency of operation for Agri-food systems. Current models for supply chain in the Agri-food literature, are mainly based on linear models used to maximize revenue. In this program, we expand this approach by allowing the integration of linear and non-linear models. We also introduce means to account for variations depending on the attention given to product quality, degradation, logistic possibilities like storing conditions at different stages, and different type of customers.
Products:
Products:
- Rethinking the Modeling of Ag-Food Production and Supply Chain. A novel framework. Under revision at International Journal of Production Economics. Jorge Barrera, Ratna Suthar, Jasmeet Judge.
- Modeling Water and Energy Use in Florida Tomato Postharvest Operations. Under preparation. Ratna Suthar, Jorge Barrera, Jasmeet Judge.
Big Data and Wireless Sensor Networks
The University of Florida is a major public, land-grant institution stablished in Gainesville FL. With approximately 2000 acres, including 448 acres of conservation land and open water bodies[1]. UF campus is constituted by a combination of protected and human intervened landscapes, which are regularly watched by the university’s Lakes, Vegetation and Landscape Committee[2] and other groups.
In this project, we look to implement an monitoring system across campus to help us study the landscape conditions with high spatial and time granularity. We will develop a Wireless Sensor Network with several monitoring stations to study soil and water conditions across campus. This project will also be the backbone for a more ample set of environmental data services, such as air quality, radiation, and micro climates.
With the recent advances on wireless sensors (WSN) technology and Data sciences, we can develop a pilot program to understand the landscape dynamics (soil, water and environment) in our campus. This project will be complementary to other projects relating to biodiversity on campus and environmental effects of human developed landscapes.
Currently we count with a pilot project using wireless humidity sensors in residential landscapes, and we have acquired a web server for data rich portals, which is hosted in the UF high performance-computing center. By developing the network of monitoring stations and integrating it to our existing resources, we can implement a portal for exploring the environmental conditions on campus.
[1] http://www.facilities.ufl.edu/library/prjdocs/00042854.pdf
[2] http://fora.aa.ufl.edu/University/JointCommittees/Lakes-Vegetation-And-Landscaping-Committee
In this project, we look to implement an monitoring system across campus to help us study the landscape conditions with high spatial and time granularity. We will develop a Wireless Sensor Network with several monitoring stations to study soil and water conditions across campus. This project will also be the backbone for a more ample set of environmental data services, such as air quality, radiation, and micro climates.
With the recent advances on wireless sensors (WSN) technology and Data sciences, we can develop a pilot program to understand the landscape dynamics (soil, water and environment) in our campus. This project will be complementary to other projects relating to biodiversity on campus and environmental effects of human developed landscapes.
Currently we count with a pilot project using wireless humidity sensors in residential landscapes, and we have acquired a web server for data rich portals, which is hosted in the UF high performance-computing center. By developing the network of monitoring stations and integrating it to our existing resources, we can implement a portal for exploring the environmental conditions on campus.
[1] http://www.facilities.ufl.edu/library/prjdocs/00042854.pdf
[2] http://fora.aa.ufl.edu/University/JointCommittees/Lakes-Vegetation-And-Landscaping-Committee