AUTOMATIC DATA COLLECTION DESIGN FOR REAL-TIME DETECTION OF OIL-SPILLAGE DISASTERS IN NIGERIA
DOI:
https://doi.org/10.4314/njt.281.129Keywords:
Data collection, wireless networks, detection, neural networks, oil-spillsAbstract
Oil-spillage disaster is a phenomenon that has thrived and come to stay especially in the Niger Delta region in Nigeria where crude oil is produced both on-shored and off-shored resulting in the loss of billions of crude oils and corresponding loss of income every year. Such disasters can occur at any point within the entire oil-pipeline topology, which is geographically dispersed across the country spanning from the extreme south-south through south-east and south-west to the north central. A major cause of oil spillage disaster is oil-pipeline vandalism, which has recently become one of the primary means of defrauding the Nation by oil bunkers and even angry youths of the host communities. Currently in Nigeria oil spillage disaster is monitored manually under the auspices of the National Emergency Management Agency (NEMA) and involves huge human labor as gathering of useful data has proven to be difficult and untimely using traditional data collection methods given the peculiarity of the operational terrain. An automated data collection design (ADCD) for real-time data collection on oil spillages in the on-shore, mangrove, thick forest and off-shore areas of the Nation offers the much needed solution. This paper examined some current procedures for data collection and highlighted inherent pitfalls. It further presented a robust architecture and model for real-time detection of oil-spillage and discussed incorporated contemporary technological requirements. The major advantages and disadvantages of the proposed system were also discussed.Downloads
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