Automatic Fall Detection And Alert System For Home Safety
Abstract
Falls are a regular issue for the elderly and the disabled, and they can result in serious injuries or even death. We have created fall detection systems that use image processing methods to quickly identify falls in order to solve this problem. The device employs a camera to take pictures or videos of the person it is watching, then analyses the images to determine whether a fall has occurred. The photos are analyzed to see if a fall has occurred using image processing techniques like object recognition, motion analysis, and background subtraction. To ensure quick assistance, the system then notifies a carer or emergency contact. The use of image processing in a fall detection system offers a potentially effective way to address the issue of falls among the elderly and disabled. It offers an efficient, trustworthy, and affordable substitute for conventional fall detection techniques and can significantly increase the safety and well-being of people who need it most.
Keywords:
K Nearest Neighbor, MVC, Gaussian mixture model (GMM), Fall motion mixture model (FMMM)Published
Issue
Section
License
Copyright (c) 2023 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Sandra Saji, Melbin Mathew, Angel Mariya S, Amrutha Mugesh, Jincy Lukose, MACHINE LEARNING FOR DETECTION AND PREDICTION OF TOMATO LEAF DISEASES , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Abhijith J, Athul Krishna S, Amarthyag P, Angela Rose Baby, Mekha Jose, CATARACT DETECTION USING DIGITAL CAMERA IMAGES , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Tom Kurian, Ektha P S, Chethana Raj T, Diona Joseph, Annu Mary Abraham, Intelligent Disease Prediction in Hydroponic Systems Using Machine Learning , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Selin Sam, Ameen Shouketh, Eby Jo, Jithin Russel, Joyal Anto, Muhammed Nihal K, Animal Detection Using Footprint , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Elisabeth Thomas, Chris Joseph, Eva Mary Regi, Haby.S. Mathews, Irin Alex , PIMS: Public Issue Management System , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Prayag Suresh, Sneha Susan Alex, Rojan Varghese, Thomas Zacharias, Shiney Thomas, Survey of Strabismus Detection Techniques , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Jefrin Siby Mathew, Joyal Joseph, Roshik George, Tinu Rose Thottungal , Honey Joseph, Multiple Disease Detection using Machine Learning , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Devika R Nilackal, Resmara S, Greeshma R, Griesh R, Joice P Abraham, Najma Najeeb, Shehanas K Salim, CARDAMOM PLANT DISEASE DETECTION USING ROBOT , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Harinaranayana Bobi, Irene Elizabeth , Fathima Ishana K.M, Delin Raj, Honey Joseph, CureVeda:Personalized Ayurvedic Remedies Powered by AI with Expert Consultation , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Adams Mathew, Adithya Sanil, Akhil J Medackal, Nikhil J Medackal, Dyni Thomas, A Literature Review on IMAGE FORGERY DETECTION , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
You may also start an advanced similarity search for this article.
