Fuel Consumption Monitoring through COPERT Model—A Case Study for Urban Sustainability

Muhammad Ali, Muhammad Daud Kamal, Ali Tahir and Salman Atif
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Muhammad Ali: Institute of Geographical Information Systems, National University of Sciences and Technology, Islamabad 44000, Pakistan
Muhammad Daud Kamal: Institute of Geographical Information Systems, National University of Sciences and Technology, Islamabad 44000, Pakistan
Ali Tahir: Institute of Geographical Information Systems, National University of Sciences and Technology, Islamabad 44000, Pakistan
Salman Atif: Institute of Geographical Information Systems, National University of Sciences and Technology, Islamabad 44000, Pakistan

Sustainability, 2021, vol. 13, issue 21, 1-12

Abstract: Trackers installed in vehicles gives insights into many useful information and predict future mobility patterns and other aspects related to vehicles movement which can be used for smart and sustainable cities planning. A novel approach is used with the COPERT model to estimate fuel consumption on a huge dataset collected over a period of one year. Since the data size is enormous, Apache Spark, a big data analytical framework is used for performance gains while estimating vehicle fuel consumption with the lowest latency possible. The research presents peak and off-peak hours fuel consumption’s in three major cities, i.e., Karachi, Lahore and Islamabad. The results can assist smart city professionals to plan alternative trip routes, avoid traffic congestion in order to save fuel and time, and protect against urban pollution for effective smart city planning. The research will be a step towards Industry 5.0 by combining sustainable disruptive technologies.

Keywords: COPERT; Global Positioning System (GPS); fuel consumption; apache spark; big data; spatio-temporal queries (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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