Centre for Sensors and System Integration

Purpose
To reduce the need for continuous human monitoring of mining haul-truck fleet through the creation of an autonomous drone including real-time data acquisition, predictive analytics, visualization and data-informed decision making on operational readiness.

Funding
Alberta Innovates, Government of Alberta (Major Innovation Fund)

Expected Completion Date
March 2025

Project Overview
We have developed an automated system to determine of operational readiness of autonomous mining trucks. The developed drone system includes several onboard sensors for detection of engine fluid levels, multiple pole-mount cameras for 360-degrees overview of vehicle(s), and a sensor equipped robot for undercarriage inspection. We established reliable communications between an on-site server with sensors and cameras through mesh network(s). LiDAR-based navigation was designed for robot missions and its sustainable operations ensured through precision docking and wireless charging.

The prototype has been deployed in mining operations where automated inspections are completed on autonomous trucks during their fueling cycles. A custom frontend/backend user interface has been implemented for operation of the integrated inspection system by an operator from a remote location reducing the need for human intervention particularly in inclement weather conditions.

Future/Ongoing Work
Further work is ongoing for real-time monitoring of vehicle status during mining operations. Predictive maintenance algorithms through real-time sensor-data analytics and computer vision are being developed. Increased safety, reliability, operational efficiency, and cost reduction are expected as project outcomes.

Vision- and Lidar-Based Autonomous Docking and Recharging of a Mobile Robot for Machine Tending in Autonomous Manufacturing Environments
Feiyu Jia, Misha Afaq, Ben Ripka, Quamrul Huda and Rafiq Ahmad. 2023
Applied Sciences

LED based systems for remote sensing of liquid levels in automotive fluid tanks
Quamrul Huda, Chelsea Ragbir, Matthew Hart, Andrew Anderson-Serson, Ben Ripka, Alberto L. Cevallos, Anas Ahmed, Dan Priestley. 2023
Proceedings of SPIE

Purpose
During bitumen processing, insufficient flow of slurry leads to deposition of coarse sand particles in hydrotransport lines, termed 'sanding' which can lead to blockages. This project aims to develop a method for detection of sand bed formation in hydrotransport lines using real-time predictive analytics on sensor data.

Expected Completion Date
January 2027

Project Overview
Currently, there is a lack of reliable early warning systems for sanding events and partial or total plugging events can cost millions of dollars per incident.

This project analyzes the feasibility of SANDtrac^TM, a sonar-based velocity profiler that provides velocity at multiple depths of pipeline cross-section, for detection of sanding events. The key element of our study is the interpretation of its one-year deployment data. Methods have been developed and tested for the removal of noise, harmonics, outliers, and other unwanted signals from sensor data, followed by comprehensive understanding, modeling, and analysis of sanding events.

Future/Ongoing Work
A machine learning model will be developed and trained using one year deployment and historical data to detect sanding events. Developed methods will significantly reduce the use of energy and water during the bitumen extraction process.

Purpose
Real-time monitoring of bison health status in wintertime through sensors and cameras with a self sustainable solar-wind hybrid power system   

Completion Date
December, 2023

Project Overview
Assessment of productive performance and other traits in commercial bison farms are challenging due to difficulties of safely herding and handling the animals. Automated remote assessment systems can allow information collection and decision-making. In collaboration with Lakeland College, NAIT CSSI has developed a bison monitoring unit for real-time monitoring of bison body weight through a walk-over-weight scale, along with visual and thermal imaging capabilities. A weather station was integrated for environmental data collection. An integrated data acquisition and control unit with cellular connectivity was developed to upload data and images to a cloud platform. A hybrid wind/solar system was developed and integrated to energize the unit for standalone operations. This hybrid configuration compliment each other to support load demand in Alberta wintertime conditions. The developed system represents a technological breakthrough for the Canadian bison industry and increase the capacity of producers in collecting data from a variety of production settings.
 

Hybrid Wind-Solar Energy System for Remote Locations In Northern Alberta
Muhammad Burhan, Yuri Montanholi, Quamrul Huda. 2023
Applied Research Results in Vocational Education and Training

Purpose
Development of a field deployable microwave imaging system that can detect metals and rocks buried under oilsand ores on a conveyer belt and generate real-time imaging for crusher protection.

Funding
Natural Sciences and Engineering Research Council (NSERC)

Completion Date
July 2024

Project Overview
We have developed a prototype system that is field-deployable in Alberta weather conditions for detection of rocks and metals during ore processing in upstream oilsands facilities. The work was conducted in collaboration with our industry and academic partners. The system utilizes ultra-wideband synthetic aperture radar technology to detect objects buried in the oil sands within a depth of 1 meter. Under the present project, a linear power supply and regulation module, a precision pulse repetition frequency (PRF) signal module, a radio frequency (RF) signal switching module, and a data acquisition system has been designed and implemented. Software integration for the system has been implemented for remote operation and monitoring of the system. The electronic control system and the transmitter/receiver antennas have been designed on IP67 standards for all-season outdoor deployment in mining environment.