Artificial Intelligence Based Emergency Identification Computer System
The use of Artificial Intelligence is currently being observed in many areas of life. In addition to assisting in intellectual work, solving complex computational problems, or analyzing various types of data, the aforementioned techniques can also be applied in the process of providing security to p...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Lublin University of Technology
2024-04-01
|
| Series: | Advances in Sciences and Technology |
| Subjects: | |
| Online Access: | http://www.astrj.com/Artificial-Intelligence-Based-Emergency-Identification-Computer-System,184343,0,2.html |
| _version_ | 1797263500151619584 |
|---|---|
| author | Diana Velychko Halyna Osukhivska Yuri Palaniza Nadiia Lutsyk Łukasz Sobaszek |
| author_facet | Diana Velychko Halyna Osukhivska Yuri Palaniza Nadiia Lutsyk Łukasz Sobaszek |
| author_sort | Diana Velychko |
| collection | DOAJ |
| description | The use of Artificial Intelligence is currently being observed in many areas of life. In addition to assisting in intellectual work, solving complex computational problems, or analyzing various types of data, the aforementioned techniques can also be applied in the process of providing security to people. The paper proposes an emergency identification system based on Artificial Intelligence that aims to provide timely detection and notification of dangerous situations. The proposed solution consider the position of a person "hands up" as an emergency situation that will indicate a potential danger for a person. Because people in the face of potential danger are mostly forced to raise their hands up and this pose attracts attention, emphasizes the emotional reaction to certain events and is usually used as a sign of risk or as a means of subjugation. The system should recognize the pose of a person, detect it, and consequently inform about the threat. In this paper, an AI based emergency identification system was proposed to detect the human pose "hands up" for emergency identification using the PoseNet Machine Learning Model. The assumption consists that the utilization only of 6 key points made allows reducing the computing resources of the system since the conclusion is made taking into account a smaller amount of data. For the study, a dataset of 1510 images was created for training an Artificial Intelligence model, and the decisions were verified. Supervised Machine Learning methods are used to classify the definition of an emergency. Alternative methods: Support Vector Machine, Logistic Regression, Naïve Bayes Classifier, Discriminant Analysis Classifier, and K-nearest Neighbours Classifier based on the accuracy were evaluated. Overall, the paper presents a comprehensive and innovative approach to emergency identification for quick response to them using the proposed system. |
| first_indexed | 2024-04-25T00:13:59Z |
| format | Article |
| id | doaj.art-f194b0f56a7149d891ece7e180d0f683 |
| institution | Directory Open Access Journal |
| issn | 2080-4075 2299-8624 |
| language | English |
| last_indexed | 2024-04-25T00:13:59Z |
| publishDate | 2024-04-01 |
| publisher | Lublin University of Technology |
| record_format | Article |
| series | Advances in Sciences and Technology |
| spelling | doaj.art-f194b0f56a7149d891ece7e180d0f6832024-03-13T07:59:59ZengLublin University of TechnologyAdvances in Sciences and Technology2080-40752299-86242024-04-0118229630410.12913/22998624/184343184343Artificial Intelligence Based Emergency Identification Computer SystemDiana Velychko0https://orcid.org/0000-0001-7635-1761Halyna Osukhivska1https://orcid.org/0000-0003-0132-1378Yuri Palaniza2https://orcid.org/0000-0002-8710-953XNadiia Lutsyk3https://orcid.org/0000-0002-0361-6471Łukasz Sobaszek4https://orcid.org/0000-0003-1298-2438Computer Systems and Networks Department, Faculty of Computer Information Systems and Software Engineering, Ternopil Ivan Puluj National Technical University, Ternopil, UkraineComputer Systems and Networks Department, Faculty of Computer Information Systems and Software Engineering, Ternopil Ivan Puluj National Technical University, Ternopil, UkraineDepartment of Radio Engineering Systems, Faculty of Applied Information Technologies and Electrical Engineering, Ternopil Ivan Puluj National Technical University, Ternopil, UkraineComputer Systems and Networks Department, Faculty of Computer Information Systems and Software Engineering, Ternopil Ivan Puluj National Technical University, Ternopil, UkraineDepartment of Information Technology Lublin, Faculty of Mathematics and Information Technology, University of Technology, Lublin, PolandThe use of Artificial Intelligence is currently being observed in many areas of life. In addition to assisting in intellectual work, solving complex computational problems, or analyzing various types of data, the aforementioned techniques can also be applied in the process of providing security to people. The paper proposes an emergency identification system based on Artificial Intelligence that aims to provide timely detection and notification of dangerous situations. The proposed solution consider the position of a person "hands up" as an emergency situation that will indicate a potential danger for a person. Because people in the face of potential danger are mostly forced to raise their hands up and this pose attracts attention, emphasizes the emotional reaction to certain events and is usually used as a sign of risk or as a means of subjugation. The system should recognize the pose of a person, detect it, and consequently inform about the threat. In this paper, an AI based emergency identification system was proposed to detect the human pose "hands up" for emergency identification using the PoseNet Machine Learning Model. The assumption consists that the utilization only of 6 key points made allows reducing the computing resources of the system since the conclusion is made taking into account a smaller amount of data. For the study, a dataset of 1510 images was created for training an Artificial Intelligence model, and the decisions were verified. Supervised Machine Learning methods are used to classify the definition of an emergency. Alternative methods: Support Vector Machine, Logistic Regression, Naïve Bayes Classifier, Discriminant Analysis Classifier, and K-nearest Neighbours Classifier based on the accuracy were evaluated. Overall, the paper presents a comprehensive and innovative approach to emergency identification for quick response to them using the proposed system.http://www.astrj.com/Artificial-Intelligence-Based-Emergency-Identification-Computer-System,184343,0,2.htmlartificial intelligencedeep learningdetectionemergency systemcomputer system |
| spellingShingle | Diana Velychko Halyna Osukhivska Yuri Palaniza Nadiia Lutsyk Łukasz Sobaszek Artificial Intelligence Based Emergency Identification Computer System Advances in Sciences and Technology artificial intelligence deep learning detection emergency system computer system |
| title | Artificial Intelligence Based Emergency Identification Computer System |
| title_full | Artificial Intelligence Based Emergency Identification Computer System |
| title_fullStr | Artificial Intelligence Based Emergency Identification Computer System |
| title_full_unstemmed | Artificial Intelligence Based Emergency Identification Computer System |
| title_short | Artificial Intelligence Based Emergency Identification Computer System |
| title_sort | artificial intelligence based emergency identification computer system |
| topic | artificial intelligence deep learning detection emergency system computer system |
| url | http://www.astrj.com/Artificial-Intelligence-Based-Emergency-Identification-Computer-System,184343,0,2.html |
| work_keys_str_mv | AT dianavelychko artificialintelligencebasedemergencyidentificationcomputersystem AT halynaosukhivska artificialintelligencebasedemergencyidentificationcomputersystem AT yuripalaniza artificialintelligencebasedemergencyidentificationcomputersystem AT nadiialutsyk artificialintelligencebasedemergencyidentificationcomputersystem AT łukaszsobaszek artificialintelligencebasedemergencyidentificationcomputersystem |