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      • HARVEST
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      SMART SENSOR AND TRACKING SYSTEM FOR UNDERGROUND MINING

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      ZHANG-THESIS-2016.pdf (4.808Mb)
      Date
      2016-06-23
      Author
      Zhang, Xuechao 1991-
      Type
      Thesis
      Degree Level
      Masters
      Metadata
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      Abstract
      The thesis predominantly discusses a smart sensor and tracking system for under- ground mining, as developed by the author. The tracking system is developed by two steps, the rst of which involves nding an e cient way to measure the distance, and the second of which involves localizing the positions of each miner in real-time. For the rst step, a Received Signal Strength Indicator (RSSI) is used to measure the distance between two points by indicating the amount of energy lost during the transmission. Due to environmental and human factors, errors exist when using RSSI to measure distance. Three methods are taken to reduce the error: Gaussian distribution, statistical average and preset points. It can be observed that the average error between actual distance and measured distance is only 0.1145 meters using the proposed model. In regards to the localization, the "3-point localization method" is considered rst. With the proposed method, the result of the localization is improved by 0.6 meters, as compared to the "2-point localization method". The transmission method for the project is then discussed. After comparing sev- eral transmission protocols in the market, ZigBee was chosen for the signal trans- mission. With the Zigbee protocol, up to 65000 nodes can be connected, which are suitable for many miners using the system at the same time. The power supply for the ZigBee protocol is only 1mW for each unit, thus potentially saving a great amount of energy during the transmission. To render the tracking system more powerful, two smart sensors are installed: an MQ-2 sensor and a temperature sensor. The MQ-2 sensor is used to detect the harmful gas and smoke. In the event that the sensor's detected value is beyond the threshold, it will provide a warning for the supervisor on the ground.
      Degree
      Master of Science (M.Sc.)
      Department
      Electrical and Computer Engineering
      Program
      Electrical Engineering
      Supervisor
      Khan, Wahid
      Committee
      Chen, Li; Johanson, Robert; Oguocha, Ike
      Copyright Date
      June 2016
      URI
      http://hdl.handle.net/10388/7304
      Subject
      Tracking
      Smart Sensor
      Underground mining
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