A Comparative Study of the Different Features Engineering Techniques Based on the Sensor Used in Footstep Identification and Analysis Using the Floor-Based Approach
Iskandar, A., Alfonse, M., roushdy, M., El-Horabty, E. (2023). A Comparative Study of the Different Features Engineering Techniques Based on the Sensor Used in Footstep Identification and Analysis Using the Floor-Based Approach. EKB Journal Management System, 23(4), 66-95. doi: 10.21608/ijicis.2023.249378.1307
Ayman Adel Moner Iskandar; Marco Alfonse; mohamed roushdy; El-Sayed M. El-Horabty. "A Comparative Study of the Different Features Engineering Techniques Based on the Sensor Used in Footstep Identification and Analysis Using the Floor-Based Approach". EKB Journal Management System, 23, 4, 2023, 66-95. doi: 10.21608/ijicis.2023.249378.1307
Iskandar, A., Alfonse, M., roushdy, M., El-Horabty, E. (2023). 'A Comparative Study of the Different Features Engineering Techniques Based on the Sensor Used in Footstep Identification and Analysis Using the Floor-Based Approach', EKB Journal Management System, 23(4), pp. 66-95. doi: 10.21608/ijicis.2023.249378.1307
Iskandar, A., Alfonse, M., roushdy, M., El-Horabty, E. A Comparative Study of the Different Features Engineering Techniques Based on the Sensor Used in Footstep Identification and Analysis Using the Floor-Based Approach. EKB Journal Management System, 2023; 23(4): 66-95. doi: 10.21608/ijicis.2023.249378.1307

A Comparative Study of the Different Features Engineering Techniques Based on the Sensor Used in Footstep Identification and Analysis Using the Floor-Based Approach

International Journal of Intelligent Computing and Information Sciences
Volume 23, Issue 4, December 2023, Page 66-95  XML PDF (506.48 K)
Document Type: Original Article
DOI: 10.21608/ijicis.2023.249378.1307
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Authors
Ayman Adel Moner Iskandar email orcid 1; Marco Alfonseorcid 2; mohamed roushdyorcid 1; El-Sayed M. El-Horabtyorcid 3
1Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt.
2Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt
3Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University
Abstract
Humans can be recognized by their distinctive walking patterns, which have been established using a variety of techniques, including the use of sensors. Footstep recognition, which analyzes the distinctive characteristics of a person's footsteps, can be applied in a range of scenarios, including security, criminal investigations, human behavior security applications, and healthcare for monitoring and analyzing gait abnormalities. This paper discusses the most recent work on footstep analysis and identification systems in terms of using the floor-based approach. It explains the various artificial intelligence methods as well as the machine learning and deep learning algorithms applied to the recognition and analysis of footsteps, the various feature engineering techniques applied to each type of sensor, the affection of the engineered features on the footstep identification and analysis systems, and the best suitable features for each type of sensor and application, which provide researchers in this domain with an appropriate grounding in footstep identification and analysis utilizing the floor-based technique.
Keywords
Footstep Identification and Analysis; Machine learning; Pattern recognition; Deep Learning; Pressure Sensor
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