Research Projects
Production Data Analysis
Constrained Resource Scheduling (CORES)
Constrained Resource Scheduling (CORES)
Cardinal Creek was instrumental in the development of a modern integration and reporting tool-friendly, data exposure mechanism for AspenTech AORA.
This effort (ultimately purchased by AspenTech for inclusion in the AORA product) allows for unprecedented end-user analysis opportunities of daily production data. Several research projects have spun off from this effort - the most notable is using AI as a predictor of production 'health' and daily balance numbers.
Constrained Resource Scheduling (CORES)
Constrained Resource Scheduling (CORES)
Constrained Resource Scheduling (CORES)
With business analysis support from the University of Calgary, Cumming School of Medicine, Cardinal Creek undertook a 2-year research project to investigate using technology to generate medical resident schedules.
The COnstrained REsource Scheduling system (CORES) consisted of the development of a computer algorithm that leverages two key technologies: Genetic Programming and Symmetrical Multi-Processing. These technologies combined made the creation of 'feasible' medical schedules an iterative process, versus the traditional 'submit-and-wait' paradigm.
This project generated several academic papers (the main one here) that were submitted into the public domain and was the subject of a presentation at Flinder's University in Adelaide, Australia.
Mesh Networking for Telemetry Data
Constrained Resource Scheduling (CORES)
Mesh Networking for Telemetry Data
The advent of low-power, application-specific, integrated circuitry that contains a complete wireless network protocol stack has been a game changer in data telemetry collection and storage.
To make matters even more interesting is the acknowledgement by hardware vendors of the importance of device security in their products. Modern IoT hardware contains tightly coupled security, like Trusted Platform Modules - right on the chip, not in software!
Work is on-going to develop an Internet of Things (IoT) proof-of-concept using these low-cost devices to collect and deliver geographically distributed sensor data - all while minimizing the need for supporting infrastructure.