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  • 标题:Wireless Sensor Network Surveillance on Forest Illegal Mining using 'Planned Behaviour Abortion Tower': Analytical Modelling
  • 作者:Eric Opoku Osei ; James B. Hayfron-Acquah ; Michael Asante
  • 期刊名称:International Journal of Computer Networks and Applications (IJCNA)
  • 电子版ISSN:2395-0455
  • 出版年度:2018
  • 卷号:V-5-I-4
  • 页码:52-60
  • 语种:English
  • 出版社:EverScience Publications
  • 摘要:The USAID report on climate change vulnerability and adaptation in Ghana confirmed the impact of recent explosion of illegal gold mining in forest reserves and in river body. Government of Ghana responded to such wake-up call in deploying military combatants against perpetrators operating at day and midnight hours when drones are ineffective to monitor. We aimed at wireless sensor network (WSN) deployment to compliment military efforts for real time remote sensing. A conceptual framework on WSN technology is proposed based on expert view gathered from Delphi technique data analysis. A close textual reading of illegal mining editorial and the primary evidence of climate change impact from water shortage due to river body pollution with cyanide chemical in Ghana are key input factors for this technology-based conceptual exploration. Positive analytical feedback from the 'Delphi' suggests that we can apply this conceptual framework to all environmental case studies in which technology-based security protocols are good compliments to abort human intention towards certain behavior. The comparative discussion on the use of Drones, Satellite and WSN showed that the latter is: economical to deploy, energy efficient for continuous operational availability and reliable data sensing at midnight mining compared to drones' image processing power at night to track manual mining excavations. This study gives a starting point for uptake investigation in WSN deployment for surveillance on illegal mining; hence the findings may have limitations such as subjectivity of expert view. This conceptual framework is a recommendation to urgent national issue and thus it is relevant having real-world implementation for testing the human behavioral assumptions.
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