SYSTEM FOR ANALYZING MOVEMENTS OF PERSONS WITHIN ROOMS
DOI:
https://doi.org/10.24867/14BE22MicicKeywords:
HDFS, Spark, Big data, KafkaAbstract
In this paper, we present the system for processing and analyzing data about person movement within rooms. The main focus is on a distributed and scalable architecture which enables development of these processing and analysis. There are several data processing algorithms which were implemented regarding number of people inside rooms, space utilization, percentage utilization, calculation of predefined periods of time and finding the most common movement pattern. Apart from data processing, visualization module is also implemented. For implementation Apache Spark, Kafka, HDFS, Flask and VueJS were used.
References
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[2] Krumm, J., Harris, S., Meyers, B., Brumitt, B., Hale, M., & Shafer, S. (2000, July). Multi-camera multi-person tracking for easyliving. In Proceedings Third IEEE International Workshop on Visual Surveillance (pp. 3-10). IEEE.
[3] Garg, N. (2013). Apache kafka. Packt Publishing Ltd.
[4] Chambers, B., & Zaharia, M. (2018). Spark: The definitive guide: Big data processing made simple. " O'Reilly Media, Inc.".
[5] Shvachko, K., Kuang, H., Radia, S., & Chansler, R. (2010, May). The hadoop distributed file system. In 2010 IEEE 26th symposium on mass storage systems and technologies (MSST) (pp. 1-10). Ieee.
[6] Chodorow, K. (2013). MongoDB: the definitive guide: powerful and scalable data storage. " O'Reilly Media, Inc.".
[7] Vogel, P., Klooster, T., Andrikopoulos, V., & Lungu, M. (2017, September). A low-effort analytics platform for visualizing evolving Flask-based Python web services. In 2017 IEEE Working Conference on Software Visualization (VISSOFT) (pp. 109-113). IEEE.
[8] Nelson, B. (2018). Getting to Know Vue. js. Berkeley, CA: Apress. https://doi. org/10.1007/978-1-4842-3781-6.
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Published
2021-09-09
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Section
Electrotechnical and Computer Engineering
