Fuzzy Hot Spot Identification for Big Data: An Initial Approach

Triguero, Isaac; Tickle, Rebecca; Figueredo, Grazziela P.; Mesgarpour, Mohammad; Ozcan, Ender; John, Robert I.

Abstract

Hot spot identification problems are present across a wide range of areas, such as transportation, health care and energy. Hot spots are locations where a certain type of event occurs with high frequency. A recent big data approach is capable of identifying hot spots in a dynamic manner, through the processing of large volumes of sensor data arriving as a stream. However, the method may produce imprecise results due to its crisp interpretation of hot spot locations and reliance on a fixed hot spot radius value. This paper presents an initial approach to addressing this shortcoming through incorporating the concept of fuzzy hot spots into the process. Experimental results on large real-world transportation datasets demonstrate the improved way in which this approach handles uncertainty in the definition of hot spots, and highlight promising future research areas for further application of fuzzy systems to the hot spot identification problem.

Citation

Triguero, I., Tickle, R., Figueredo, G. P., Mesgarpour, M., Ozcan, E., & John, R. I. (2019, June). Fuzzy Hot Spot Identification for Big Data: An Initial Approach. Presented at 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
• Start Date: Jun 23, 2019
• End Date: Jun 26, 2019
• Acceptance Date: Mar 7, 2019
• Online Publication Date: Oct 11, 2019
• Publication Date: 2019-06
• Deposit Date: Nov 5, 2019
• Publicly Available Date: Nov 5, 2019
• Publisher: Institute of Electrical and Electronics Engineers
• Series ISSN: 1558-4739
• Book Title: 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
• ISBN: 978-1-5386-1729-8
• DOI: https://doi.org/10.1109/FUZZ-IEEE.2019.8858979
• Public URL: https://nottingham-repository.worktribe.com/output/3059289
• Publisher URL: https://ieeexplore.ieee.org/document/8858979
• Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
• Contract Date: Nov 5, 2019