1. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
Development of a Home Surveillance Vehicle Using
Arduino
Reporter ： Siao-Dawn Tsai
Date : 112.06.02
Author: Chuin-Mu Wang, Shao-Wei Chu , Jiaren Lim,Siao-Dawn Tsai
2. NCUT Department of Computer Science and Information Engineering
Outline
Introduction
1
Method
2
- Model Training
- Dataset Preparation and Explaination
- Arduino Car
- Function List
- Vehicle Operation
- OpenPose’s Technique
Model
3
Experiment and Result
4
- Background
- Questions
- Purposed
Conclusions
5
2
4. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
Background
4
• In recent years, Taiwan has made significant advancements in
healthcare, resulting in longer life expectancy. The population is living
longer and a decline in birth rates, leading to a higher proportion of
elderly individuals.
• Advancements in technology have introduced various new
applications, such as microprocessors in embedded systems and the
utilization of deep learning in image recognition. These technologies
not only enhance convenience but also improve quality of life and
safety.
5. NCUT Department of Computer Science and Information Engineering
• With the aging population, home care has become increasingly significant,
yet the existing healthcare and long-term care services cannot meet the
growing demand.
• Elderly individuals who live alone or lack caregiver support may face the
following crises : Accidental falls, Sudden medical emergencies, Home
safety issues, etc.
Questions
5
6. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
Propose
6
• Arduino serves as the control center for monitoring vehicles, processing and
transmitting diverse data and image information.
• Develop a system that utilizes deep learning and image recognition to
identify accidents and achieve comprehensive monitoring.
• Leverage the low power consumption, small size, and ease of programming
of Arduino to enhance the efficiency and safety of home care.
7. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
NCUT Department of Computer Science and Information Engineering
Method
7
8. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
8
Arduino Car
•Arduino MEGA for vehicle control and transmission.
•3D print the vehicle body using PLA material.
•Utilize GA12-N20 gear motor for vehicle movement.
•OV7670 camera module for image acquisition.
•Integrate ESP Arduino Wi-Fi module.
9. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
9
Function List
•Remote control: Enable remote control of the vehicle's movement to
reach the person in need through a mobile phone or computer.
•Environmental monitoring: Monitor the environmental conditions, such
as temperature, humidity, and smoke, to detect abnormalities promptly.
11. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
OpenPose’s Techniques
•OpenPose comprises a feature extraction network and a keypoint detection
network.
•The feature extraction network utilizes convolutional layers, pooling layers, and
batch normalization layers to capture spatial and semantic information from the
image.
•The keypoint detection network consists of keypoint position detection and
keypoint correlation detection branches, employing convolutional neural
networks to detect keypoints' positions and relationships.
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12. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
NCUT Department of Computer Science and Information Engineering
Model
12
13. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
13
Model Training
End
Start OpenPose
Train Model
Model
Picture
Label
File
Dataset
Pretraining
Weight
14. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
14
Dataset Preparation and Explanation
• The source pictures are taken manually and dataset from online and the amount of pictures is
shown in Table.
Class 3
Images 5200
Split Ratio（Train, Test） 7 : 3
Quantity of Images and Classes
15. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
NCUT Department of Computer Science and Information Engineering
Experiment and Result
15
16. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
NCUT Department of Computer Science and Information Engineering
Motion Recognition Steps
16
18. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
NCUT Department of Computer Science and Information Engineering
Conclusions
18
19. Multimedia Application Lab
NCUT Department of Computer Science and Information Engineering
19
Conclusions
• This paper proposes to use image recognition to assist the long-term care. Compared with
the current mainstream safety devices, it can not only prevent the elders from accidents, but
also assist in checking the status of surrounding house area.
• The model trained in this experiment initially used 5,200 images, which were split into a
training set of approximately 3,640 images and a testing set of approximately 1,560 images.
The fall, walking, and sitting positions each accounted for one-third of the dataset, and the
overall accuracy was 0.96.
