camera-traps
The Camera Traps application is both a simulator and IoT device software for utilizing machine learning on the edge in field research. The first implementation specializes in applying computer vision (detection and classification) to wildlife images for animal ecology studies. Two operational modes are supported (1) an input dataset of images to act as the images that would be generated an IoT camera device or (2) an input video file that would be captured by a camera which is then processed by an image detecting plugin that saves frames with motion in them; it uses these images to drive the simulation.
CT Controller
The ctcontroller tool can be used to manage the provisioning and releasing of edge hardware as well as running and shutting down the camera-traps application.
Harvest
Harvest is a tool designed to allow multiple types of stake holders in the digital agriculture space further their own unique goals from research to increases of the bottom line. Harvest allows for the creation of pipelines where users can preprocess their data, train models on HPC resources, infer on models to get insights on farm fields, and some visualizations to give an at a glance understand of what is happening on the field.
Ilúvatar
Ilúvatar is an open Serverless platform built with the goal of jumpstarting and streamlining FaaS research.
Plug-N-Play Speech Interfaces v1.0
Speech is the new essential fuel for human-computer interaction. With the current trend of
The Cetus Project
Cetus Source to Source compiler improvements are being done at the University of Delaware. In this release, we release cetus base plus an static profiling feature and the instructions to use it.