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ECE491/599 - Real World Reasoning Mobile Sensor Networks (Section 36362/36951)

Course Information


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    This is an experimental special topic course discussing how to reason the real world through a group of mobile sensors, or how to collaborate with each other to achieve a better understanding of the real world.

    This sounds like a big topic, but we'll narrow it down to one special area inspired by the behavior of ant colony, path finding through collaborative processing and obstacle avoidance through collaborative processing. In ant society, a shortest path between a nest and a food source can be found by each ant laying pheromone on its way to attract other ants. The more the pheromone, the more reinforced the path.

    This sounds like a very difficult problem. Indeed, it is. But we'll take a babystep toward this area, obstacle avoidance on the road. That is, a sensor should avoid any obstacles encountered by other sensor nodes through collaborative processing. To add an engineering flavor to the course, you are going to build the mobile sensor node yourself.


    The course is developed into three phases,
    • lectures on computer vision
    • lectures on collaborative processing, and
    • projects.

    Syllabus will be posted later today


    The course is offered at three different levels, 491 for undergraduate, 599 for M.S., and 692 for Ph.D. The lectures are the same, but the project requirement is very different.
    • ECE491:
      • Build the mobile sensor node. A starting kit will be provided to each group. It shouldn't take you more than a month to build it.
      • Each sensor node is able to recognize obstacles (including the shape, size of the obstacle)
      • Final report (assembled from milestone reports) and demo
      • One midterm exam
    • ECE599:
      • Build the mobile sensor node
      • Each sensor node is able to recognize obstacles
      • Each sensor should be able to inform its neighbors about the position of the obstacles
      • Final report and demo
      • One midterm exam


        You should have programming, image processing, computer networking (for graduate students) and hardware background.

Last updated 01/13/05