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Related Experiment Video

Updated: Feb 22, 2026

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

DISPAQ: Distributed Profitable-Area Query from Big Taxi Trip Data.

Fadhilah Kurnia Putri¹, Giltae Song², Joonho Kwon³

¹Department of Big Data, Pusan National University, Busan 46241, Korea. fadhilahkp@pusan.ac.kr.

Sensors (Basel, Switzerland)

|September 27, 2017

Summary

Taxi drivers can find more passengers using the new Distributed Profitable-Area Query (DISPAQ) system. This system analyzes big taxi trip data to identify profitable areas, boosting driver efficiency and earnings.

Keywords:

GPS sensors PQ-index Z-skyline big data distributed processing profitable areas taxi trip data

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Last Updated: Feb 22, 2026

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Area of Science:

Data Science
Transportation Systems
Database Systems

Background:

Taxi drivers face challenges in efficiently locating passengers to maximize profits.
Internet of Things (IoT) technology offers opportunities to analyze transportation data for improved services.

Purpose of the Study:

To propose a novel query processing system, DISPAQ, for identifying profitable areas for taxi drivers.
To enhance the efficiency and scalability of processing large volumes of taxi trip data.

Main Methods:

Developed a Distributed Profitable-Area Query (DISPAQ) system using Apache Spark and MongoDB.
Implemented a profitable-area query index (PQ-index) for efficient candidate area identification.
Utilized a Z-Skyline algorithm with local Z-Skyline optimization for refining profitable areas.

Main Results:

DISPAQ efficiently identifies profitable areas by querying taxi trip data.
The Z-Skyline algorithm and local optimization significantly improve query processing performance.
Extensive evaluations demonstrate the system's scalability and efficiency on real-world datasets.

Conclusions:

DISPAQ provides a scalable and efficient solution for processing profitable-area queries on big taxi trip data.
The proposed system can help taxi drivers increase profits by guiding them to high-potential areas.