University of Calgary
UofC Navigation


The MMSS team is involved in three main research areas:

  • Investigate the theory and techniques that are critical to the development of cost-effective M2G systems.
  • Use the resulting methods and procedures to enhance and develop innovative M2G applications.
  • Advance real-time M2G geo-computing.


    1. New Processing Techniques for M2G Systems

    The cost of navigation sensors make up nearly half the cost of a M2Gsystem, and therefore one of the objectives of this research is to reduce cost while maintaining accuracy. This can be achieved through the use of emergent low-cost MEMS sensors.  However, these sensors are not very accurate and therefore specialized processing techniques will be required to reduce the sensor noise, thus enhancing system accuracy without increasing cost.  This is the first research activity under this topic. 

    The application of estimation theory, digital signal processing, parametric and non-parametric data fusion techniques (including Kalman filtering, fuzzy logic, neural networks, etc.) in the development of advanced sensor integration techniques and sensor management will be the second research activity under this topic.

    M2Gsystems integrate navigation sensors with sensors that can be used to determine the positions of points remotely.  The sensors that are used for the remote position determination are predominantly photographic sensors, however, laser rangefinders or laser scanners are other examples of remote sensors.  Remote sensors typically generate huge amounts of data; this data becomes unmanageable without automated feature extraction techniques and algorithms.  Object detection and identification algorithms that will lead to the development of automated feature extraction techniques will be the third research activity under this topic.

    Real-time mapping applications, such as fighting forest fires, can be achieved through implementation of M2Gsystems providing the information necessary to combat such disasters in a timely manner.  This type of application requires reliable, real-time processing and the integration of wireless communications devices and navigation sensors. The introduction of real-time processing and the integration of wireless communications is the fourth research activity under this topic. 

    In the following, details will be given on some of the research activities carried out under this topic:

    (1)     Investigating the design of filtering techniques for band-limiting sensor noise:

    A first avenue of work is to improve existing sensor systems, for example, through the use of advanced signal processing methods, software and hardware. Results of the work in this direction are integrated in many of the M2G systems which are developed by the research team.

    (2)     Studying the applicability of Artificial Neural Network for Navigation Sensor Integration:

    Most of the present navigation sensors integration techniques are based on the Kalman filtering estimation procedure.  Although Kalman filtering represents one of the best solutions for multi-sensors integration, it still has some drawbacks in terms of stability, computation load, immunity to noise effects and observability.  Artificial Neural Networks (ANN) is a powerful tool for solving nonlinear problems that involve mapping input data to certain output data without necessarily having any prior knowledge of the mathematical process involved.  This research investigate the utilization of multi-layer neural networks for sensors integration.  In addition, this research address the impact of the different learning algorithms on positioning accuracy.

    (3)     Developing advanced feature extraction techniques from imaging sensors of M2G systems:

     Advanced techniques such as neural networks and snake models are currently under development to automate feature extraction and automatic object recognition from M2G system data.  However, two unique features of M2G-generated data make the automation of object recognition and measuring procedures feasible, and possibly more efficient and robust:

    • images have unknown exterior orientation parameters, and
    • the image sequences are along a known path.

    The research group utilize information and communication technology to investigate three aspects: geometric modeling and processing; multiple data fusion; and integrated object reconstruction and recognition.

    2.  Enhanced and Innovative Applications for M2G Systems

    This research investigates the deployment of existing technologies together with the processing techniques developed in the previous topic to achieve cost-effective innovative solutions.  The following provides an overview of some of these M2G systems:

    Cost Effective Vehicular Navigation and Safety System:

    The development of a MEMS-based integrated vehicular navigation and guidance system is the main objective in this research area.  Such a system is realized by integrating GPS chips and several MEMS-based inertial measurement units (IMU) on a single integrated circuit (IC) board.  Such systems will not only have the potential to be used as highly reliable navigation and safety systems, giving position, velocity, and altitude with high accuracy, but also as geo-referencing systems for various M2G systems that integrate imaging sensors (optical or digital cameras, laser scanners, multi-spectral scanners) for mapping applications.

    Environmental Impact Assessment and Management System:

    Increased environmental awareness to issues such as forest harvesting with the ultimate goal of achieving sustainable development has exacerbated the development of tools for environmental impact assessment and forest management using satellite imagery as a basic data source.  However, experience has shown that the spatial resolution (i.e. the pixel size or footprint of the smallest element in the satellite image on the terrain surface) is typically inadequate. The goal of this research is the development of a new airborne M2G system that integrates multi-spectral scanner with navigation sensors (for georeferencing purposes).  Such a system offer higher spatial resolution for the detection of critical features which are typically not discernable on satellite imagery; flexible coverage of user-definable project areas; and reduced influence of cloud cover since typical flights can be flown below the cloud ceiling.

    Endangered Species Tracking System:

    Recent outbreaks of animal disease, illegal-poaching activities have highlighted the importance of monitoring the movement and well being of our endangered species.  The development of low-cost geo-location modules that can be attached to the animal and the deployment of portable geo-mode monitoring stations that can scan barcodes attached to the animals and deliver this information to a base station will be investigated.  The software platform that integrates this geospatial information together with animal information to provide an effective tool for monitoring and management will be developed.  This platform technology could be utilized in other commercial applications such as fleet management, vehicle theft detection and recovery, etc.

    3.  Real-time M2G Geo-Computing

    The goal of this research in the area of real-time geo-computing is to develop tools and techniques that simplify the acquisition, retrieval and maintenance of spatial information in real time.  These tools and techniques will be first developed through innovative applications with a harvesting lessons learned process that leads to the development of a real-time geo-computing platform.  The following summarizes the proposed applications that will be investigated. 

    Real-Time Utilities Management:

     "Call before you dig" has long been the tagline for utilities protection services and organizations charged with ensuring that underground electric, communications, gas, sanitary sewer, and water facilities are not hit and damaged during new construction or maintenance of adjacent facilities.  Nevertheless, underground utilities continue to fall victim to the backhoe because municipal public works officials (as well as plant managers in large organizations responsible for their own utility systems) face the challenge of locating, mapping, and maintaining maps and records for underground utilities.

    This part of the resaerch will be directed towards the development of real-time M2G system for locating, mapping, and updating geo-spatial information of elements in the field.  The system marries GPS and GIS technologies, producing a pen-based GPS-integrated system that is "field-to-finish":  After utility lines are located via painting or staking, GPS surveyors collect underground line locations and associated attributes and map them directly into the GIS while in the field. The result is a complete, accurate, immediately updated GIS of underground utilities.

    Intelligent Structural Monitoring and Damage Detection:

    Canadian civil infrastructure assets have an estimated value in excess of US$12 trillion; the long service life of these structures necessitates periodic maintenance.  Proactive structural monitoring of civil infrastructure is cost-effective since it reduces costs associated with maintenance and replacement.  An effectual structural health monitoring system should report accurate, real-time loading conditions, detect when damage occurs in the structure and potentially inform the end user of the location and nature of this damage.  The goal of this research is to develop an intelligent structural performance monitoring system that is low-cost and requires minimum expert intervention using artificial intelligent techniques, MEMS based inertial sensors and wireless communication techniques.  The potential result of this research will be commercially viable intelligent structural monitoring systems and techniques that will provide notice of maintenance on a per-need basis, potentially reducing the cost of maintenance for these assets.  While it is difficult to assess the exact economic impact at this time, the potential could be millions of dollars per year in cost savings, and possibly the creation of a new industry dedicated to structural monitoring.

    Forest-Protection, Fire Hazard Categorization & Resource Allocation: 

    Forests affect our natural economy and livelihood.  Canada has a land mass of 997 million hectares, of which 418 million hectares is forested, representing about 10 per cent of the world's forests. Fifty-six per cent of Canada's forest is commercially productive, contributing in excess of $50 billion to the economy annually.  However, fire emergence, plant blight, illegal cutting and unlawful cultivation, endanger our forests.  If we cannot prevent and control these factors, the development of our forests will be threatened leading to increased water and soil erosion.

    'Fire hazard categorization' is vital for emergency planning in order to minimize loss of forests, lives and property.  Recording hazard levels help in understanding the spatial distribution of fire susceptible and vulnerable areas, assisting in the 'Allocation' and 'Mobilization' of dynamic resources.  In-situ field surveys are usually carried out to determine fire hazard categories. Although reasonably accurate, this method of classifying hazards is time consuming, not very accurate and most importantly does not permit spatial analysis.  This research will focus on two areas:

    a) Airborne Reporting System:

    Accurate and up to date map information on a forest fire is crucial, enabling ground crews, water bombers and helicopters to mount an effective initial attack. To date, this information is collected by airborne surveillance with a spotter aircraft flying a pre-assigned route, using navigation charts with a navigator observing the forests and looking for smoke.  The data (radio-based) exchanged between the aircraft and the land-based Forest Fire Information System (FFIS) could overload the air radio network, contributing to heavy pilot/navigator workloads.  A system that integrates imaging sensors (Infrared and Thermal Infrared Cameras) with real-time navigation technologies (Wide Area Differential GPS (WADGPS) and low cost Inertial Navigation System (INS)) will be developed.  The use of infrared/thermal infrared cameras, which sense the heat emitted in the form of infrared radiation, will enable early detection and location of forest fires that could not be sensed by the human eye.  In addition, the cameras will provide accurate images of the fire in reduced visibility due to haze, smoke or darkness.

    b) Land Reporting System:

     In this research, a M2G system for the forest ranger will be developed.  The system equips the forest ranger with radio interphone, GPS receiver and a portable Laser gun.  The forest ranger's route will be recorded by the GPS receiver, allowing the ranger to key in different codes when he/she comes across various forest disasters.  In case of fire emergence, the radio interphone can be used to report to the rescue center and transmit the coordinates of fire location and its boundary, which are identified by Laser gun.  The control system in the rescue center will compute the area and overlay the fire position on a digital map.  When fire-fighting teams arrive at the scene, digital video is used to shoot images of the fire and its development; the images are transmitted to the rescue center using an Instrumentation, Scientific and Medical (ISM) BAND Microwave Radio System.