Authors :
Mandeep Singh; Punnay Raheja; Shweta Sharma; Lakshay Sharma
Volume/Issue :
Volume 9 - 2024, Issue 12 - December
Google Scholar :
https://tinyurl.com/3rfvxa27
Scribd :
https://tinyurl.com/nnv93v2r
DOI :
https://doi.org/10.5281/zenodo.14505637
Abstract :
Linking every aspect of our lives could have
immediate positive effects on society. A basic gadget can
be included in the phrase "Internet of Things" if we give
it "computational intelligence" and connect it to the
network. In addition, improving features of the
fundamental design, the "smart" gadget is typically
portable and a option that is more affordable, effective,
and has the potential to grow in functionality over time.
IoT is changing our houses to better meet each person's
needs and desires.
The goal of our IoT-based fall detection system
project for smart home environments is still similar to
this, but it has more room to grow in terms of usefulness.
Not only would this gadget sound an alarm in the event
that an elderly person sustains injuries from falls but can
also be applied to identify costly things that fall when
being similar to stores that keep opulent and high-end
merchandise on display for customers. Additionally, this
prototype can be incorporated to learn popular
interaction models. nowadays days in IoT devices, like
video monitoring and voice help.
Keywords :
IoT, Fall Detection, Video Monitoring, Sensor Integration.
References :
- V. Hoang, J. W. Lee, M. J. Piran, and C. Park, "Advances in Skeleton-Based Fall Detection in RGB Videos: From Handcrafted to Deep Learning Approaches," IEEE Access, vol. 11, pp. 92322–92352, 2023. https://doi.org/10.1109/access.2023.3307138
- A. Y. Alaoui, S. El Fkihi, and R. O. H. Thami, "Fall Detection for Elderly People Using the Variation of Key Points of Human Skeleton," IEEE Access, vol. 7, pp. 154786-154795,2019. doi: 10.1109/ACCESS.2019.2946522.
- C. Kittiyanpunya, P. Chomdee, A. Boonpoonga, and D. Torrungrueng, "Millimeter-Wave Radar-Based Elderly Fall Detection Fed by One-Dimensional Point Cloud and Doppler," IEEE Access, vol. 11, pp. 76269-76283, 2023. doi: 10.1109/ACCESS.2023.3297512.
- S. Li, "Fall Detection With Wrist-Worn Watch by Observations in Statistics of Acceleration," IEEE Access, vol. 11, pp. 19567-19578, 2023, doi: 10.1109/ACCESS.2023.3249191.
- Espressif Systems, "ESP8266 Overview." [Online]. Available: https://www.espressif.com/en/products/hardware/esp8266ex/overview
- SunFounder, "MPU6050 Documentation," [Online]. Available: https://docs.sunfounder.com/projects/ultimate-sensor-kit/en/latest/components_basic/05-component_mpu6050.html
- P. Robots, "The MPU6050 Explained," Programming Robots. [Online]. Available: https://mjwhite8119.github.io/Robots/mpu6050
- S. Santos & R. Santos, "Arduino Guide for MPU-6050 Accelerometer and Gyroscope," Random Nerd Tutorials. [Online]. Available: https://randomnerdtutorials.com/arduino-mpu-6050-accelerometer-gyroscope
- M. Fezari & A. Al Dahoud, "Integrated Development Environment (IDE) for Arduino," 2018.
- Arduino, "Software," [Online]. Available: https://www.arduino.cc/en/software
- S. Vorapojpisut, "A lightweight framework of home automation systems based on the IFTTT model," Journal of Software, vol. 10, no. 12, pp. 1343-1350, 2015. https://doi.org/10.17706/jsw.10.12.1343-1350
- V. Kanade, "Understanding the meaning of IFTTT, its working, and alternatives," Spiceworks Inc., Aug. 31, 2023. [Online]. Available: https://www.spiceworks.com/tech/tech-general/articles/what-is-ifttt/
- M. A. Sarwar, B. Chea, M. Widjaja, and W. Saadeh, "An AI-Based Approach for Accurate Fall Detection and Prediction Using Wearable Sensors," in 2024 IEEE 67th International Midwest Symposium on Circuits and Systems (MWSCAS), Springfield, MA, USA, 2024, pp. 118–121. doi: 10.1109/MWSCAS60917.2024.10658849.
- D. Giuffrida, G. Benetti, D. De Martini, and T. Facchinetti, "Fall Detection with Supervised Machine Learning Using Wearable Sensors," in 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), Helsinki, Finland, 2019, pp. 253–259. doi: 10.1109/INDIN41052.2019.8972246.
- B. -S. Lin et al., "Fall Detection System with Artificial Intelligence-Based Edge Computing," IEEE Access, vol. 10, pp. 4328–4339, 2022. doi: 10.1109/ACCESS.2021.3140164.
- A. Aldousari, M. Alotaibi, F. Khajah, A. Jaafar, M. Alshebli, and H. Kanj, "A Wearable IoT-Based Healthcare Monitoring System for Elderly People," in 2023 5th International Conference on Bioengineering for Smart Technologies (BioSMART), Paris, France, 2023, pp. 1–4. doi: 10.1109/BioSMART58455.2023.10162041.
Linking every aspect of our lives could have
immediate positive effects on society. A basic gadget can
be included in the phrase "Internet of Things" if we give
it "computational intelligence" and connect it to the
network. In addition, improving features of the
fundamental design, the "smart" gadget is typically
portable and a option that is more affordable, effective,
and has the potential to grow in functionality over time.
IoT is changing our houses to better meet each person's
needs and desires.
The goal of our IoT-based fall detection system
project for smart home environments is still similar to
this, but it has more room to grow in terms of usefulness.
Not only would this gadget sound an alarm in the event
that an elderly person sustains injuries from falls but can
also be applied to identify costly things that fall when
being similar to stores that keep opulent and high-end
merchandise on display for customers. Additionally, this
prototype can be incorporated to learn popular
interaction models. nowadays days in IoT devices, like
video monitoring and voice help.
Keywords :
IoT, Fall Detection, Video Monitoring, Sensor Integration.