Repository logo
 

SMART SENSOR AND TRACKING SYSTEM FOR UNDERGROUND MINING

Date

2016-06-23

Journal Title

Journal ISSN

Volume Title

Publisher

ORCID

Type

Thesis

Degree Level

Masters

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.

Description

Keywords

Tracking, Smart Sensor, Underground mining

Citation

Degree

Master of Science (M.Sc.)

Department

Electrical and Computer Engineering

Program

Electrical Engineering

Part Of

item.page.relation.ispartofseries

DOI

item.page.identifier.pmid

item.page.identifier.pmcid