scholarly journals A 2-D Motion Detection Model for Low-Cost Embedded Reconfigurable I/O Devices

2005 ◽  
Vol 52 (8) ◽  
pp. 1443-1449 ◽  
Author(s):  
A. Dollas ◽  
S. Sotiropoulos ◽  
K. Papademetriou
Keyword(s):  
Motion Detection ◽  
Low Cost ◽  
Detection Model

Control System of Powered Wheelchairs Based on Tongue Motion Detection

2016 ◽  
Vol 8 (4) ◽  
pp. 60-75
Author(s):  
Liao Lu ◽  
Ping Yi Deng ◽  
Ying Wu ◽  
Jie Jun Bai ◽  
Yun Xiao Zhang ◽  
...  
Keyword(s):  
Control System ◽  
Motion Control ◽  
Intelligent Control ◽  
Motion Detection ◽  
Potential Application ◽  
Low Cost ◽  
Control Mode ◽  
Powered Wheelchair ◽  
Embedded Controller ◽  
Tongue Motion

A new intelligent powered wheelchair is urgently needed for the individuals with tetraplegia and similar impairments who are unable to use the standard joystick. Based on the tongue motion detection, a new control system is introduced in this paper which is helpful for users to operate powered wheelchair efficiently and easily. This article introduces two control modes, including tongue motion control mode and infrared control mode. Wherein the infrared control mode mainly use the infrared controller. The tongue motion can be detected with several vibration film sheets that were embedded in the headset and a standard analog signal can be generated with embedded controller to control the wheelchair. The tongue motion drive system integrated into headset was developed and the control of the wheelchair has been tested moving along the designed route. Preliminary results show that the system is simple and convenient to control powered wheelchair with low cost, which has potential application in intelligent control domain.

scholarly journals Intact Detection of Highly Occluded Immature Tomatoes on Plants Using Deep Learning Techniques

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2984
Author(s):  
Yue Mu ◽  
Tai-Shen Chen ◽  
Seishi Ninomiya ◽  
Wei Guo
Keyword(s):  
Deep Learning ◽  
Low Cost ◽  
Yield Prediction ◽  
Learning Approaches ◽  
Size Estimation ◽  
Detection Model ◽  
Lighting Conditions ◽  
Learning Techniques ◽  
Location Map ◽  
Tomato Detection

Automatic detection of intact tomatoes on plants is highly expected for low-cost and optimal management in tomato farming. Mature tomato detection has been wildly studied, while immature tomato detection, especially when occluded with leaves, is difficult to perform using traditional image analysis, which is more important for long-term yield prediction. Therefore, tomato detection that can generalize well in real tomato cultivation scenes and is robust to issues such as fruit occlusion and variable lighting conditions is highly desired. In this study, we build a tomato detection model to automatically detect intact green tomatoes regardless of occlusions or fruit growth stage using deep learning approaches. The tomato detection model used faster region-based convolutional neural network (R-CNN) with Resnet-101 and transfer learned from the Common Objects in Context (COCO) dataset. The detection on test dataset achieved high average precision of 87.83% (intersection over union ≥ 0.5) and showed a high accuracy of tomato counting (R2 = 0.87). In addition, all the detected boxes were merged into one image to compile the tomato location map and estimate their size along one row in the greenhouse. By tomato detection, counting, location and size estimation, this method shows great potential for ripeness and yield prediction.

scholarly journals A Smart IoT Device for Detecting and Responding to Earthquakes

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1546 ◽  
Author(s):  
Jangsoo Lee ◽  
Irshad Khan ◽  
Seonhwa Choi ◽  
Young-Woo Kwon
Keyword(s):  
Low Cost ◽  
Warning System ◽  
Acceleration Sensor ◽  
Earthquake Early Warning System ◽  
Detection Model ◽  
Earthquake Detection ◽  
Warning Message ◽  
Acceleration Sensors ◽  
Learning Technique ◽  
Noise Data

The advancement of hardware and software technologies makes it possible to use smartphones or Internet of things for monitoring environments in realtime. In recent years, much effort has been made to develop a smartphone based earthquake early warning system, where low-cost acceleration sensors inside a smartphones are used for capturing earthquake signals. However, because a smartphone comes with a powerful CPU, spacious memory, and several sensors, it is waste of such resources to use it only for detecting earthquakes. Furthermore, because a smartphone is mostly in use during the daytime, the acquired data cannot be used for detecting earthquakes due to human activities. Therefore, in this article, we introduce a stand-alone device equipped with a low-cost acceleration sensor and least computing resources to detect earthquakes. To that end, we first select an appropriate acceleration sensor by assessing the performance and accuracy of four different sensors. Then, we design and develop an earthquake alert device. To detect earthquakes, we employ a simple machine learning technique which trains an earthquake detection model with daily motions, noise data recorded in buildings, and earthquakes recorded in the past. Furthermore, we evaluate the four acceleration sensors by recording two realistic earthquakes on a shake-table. In the experiments, the results show that the developed earthquake alert device can successfully detect earthquakes and send a warning message to nearby devices, thereby enabling proactive responses to earthquakes.

System Design and Implementation of a Transient-Motion-Powered IoT Sensor Node

2020 ◽  
Author(s):  
Xin Li ◽  
Hong Tang ◽  
Junrui Liang
Keyword(s):  
Wireless Communication ◽  
Embedded System ◽  
Motion Detection ◽  
Sensor Node ◽  
Low Cost ◽  
Successful Implementation ◽  
Interface Circuit ◽  
Transient Motion ◽  
Communication Module ◽  
Self Powered

Abstract In this paper, we introduce ViPSN-E: a transient-motion-powered IoT sensor node. It carries out motion detection and wireless communication by making good use of the energy harvested from an instantaneous motion. In our design, a piezo-magneto-elastic structure, which is composed of a low-cost piezoelectric cantilever and a pair of magnets, is used to induce a plucking excitation and power generation under a transient and one-way movement. An energy management circuit, which is composed of a self-powered synchronized switch harvesting on inductor (SP-SSHI) interface circuit and a voltage regulator is utilized for efficient energy conversion. Through the sophisticated collaboration between mechatronic design and computer program, the motion information can also be identified and sent out by a wireless communication module. The cyber-electromechanical synergy among mechanical dynamics, power conditioning circuit, and the low-power embedded system is emphasized towards the successful implementation of such a motion-powered IoT device. The prototyped ViPSN-E has done a good job by making good use of the energy associated with each transient plucking motion. With only one plucking excitation, the system can realize motion detection and several rounds of wire-less transmission. The study on ViPSN-E provides valuable guidance towards the self-powered ubiquitous motion-sensing systems.

Highly sensitive and stretchable strain sensors based on chopped carbon fibers sandwiched between silicone rubber layers for human motion detections

2019 ◽  
Vol 54 (3) ◽  
pp. 423-434 ◽  
Author(s):  
MB Azizkhani ◽  
Sh Rastgordani ◽  
A. Pourkamali Anaraki ◽  
J Kadkhodapour ◽  
B Shirkavand Hadavand
Keyword(s):  
Carbon Fibers ◽  
Motion Detection ◽  
Silicone Rubber ◽  
Low Cost ◽  
High Sensitivity ◽  
Human Motion ◽  
Strain Sensors ◽  
Body Motion ◽  
Gauge Factor ◽  
Human Motion Detection

Tuning the electromechanical performance in piezoresistive composite strain sensors is primarily attained through appropriately employing the materials system and the fabrication process. High sensitivity along with flexibility in the strain sensing devices needs to be met according to the application (e.g. human motion detection, health and sports monitoring). In this paper, a highly stretchable and sensitive strain sensor with a low-cost fabrication is proposed which is acquired by embedding the chopped carbon fibers sandwiched in between silicone rubber layers. The electrical and mechanical features of the sensor were characterized through stretch/release loading tests where a considerably high sensitivity (the gauge factor about 100) was observed with very low hysteresis. This implies high strain reversibility (i.e. full recovery in each cycle) over 700 loading cycles. Moreover, the sensors exhibited ultra-high stretchability (up to ∼300% elongation) in addition to a low stiffness meaning minimal mechanical effects induced by the sensor for sensitive human motion monitoring applications including large and small deformations. The results suggest the promising capability of the present sensor in reflecting the human body motion detection.

A scene-adaptive motion detection model based on machine learning and data clustering

2013 ◽  
Vol 74 (8) ◽  
pp. 2821-2839 ◽  
Author(s):  
Tao Hu ◽  
Minghui Zheng ◽  
Jun Li ◽  
Li Zhu ◽  
Jia Hu
Keyword(s):  
Machine Learning ◽  
Motion Detection ◽  
Data Clustering ◽  
Detection Model ◽  
Model Based ◽  
Adaptive Motion

DESIGN OF SMARTSCHOOL WEBCAM SECURITY SYSTEM USING RASPBERRY PI WITH MOTION DETECTION IN SMK PGRI SUKODADI

JOURNAL ASRO ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 202
Author(s):  
Firman Yudianto ◽  
Fajar Annas Susanto
Keyword(s):  
Motion Detection ◽  
Industry 4.0 ◽  
Low Cost ◽  
Security System ◽  
Educational Institutions ◽  
Raspberry Pi ◽  
File Size ◽  
Moving Image ◽  
Moving Images ◽  
Web Camera

Currently a low cost security system is needed and easy to apply especially at educational institutions that willimplement smart school and industry 4.0. Needed devices are raspberry pi and web camera. Raspberry pi willonly save moving images taken from the web camera. Because by storing an image whose file size is not toolarge will ease the performance of the server. In this study, a design for the raspberry pi based motion detectionsystem will be applied at SMK PGRI Sukodadi Lamongan Regency which has not have security system. Thissystem will save the file in the form of an image that will be put together into a moving image that looks like avideo that will displayed in a LED monitor.Keywords: smart school, motion detection, moving image.

scholarly journals Arching Detection Method of Slab Track in High-Speed Railway Based on Track Geometry Data

2020 ◽  
Vol 10 (19) ◽  
pp. 6799
Author(s):  
Zhuoran Ma ◽  
Liang Gao ◽  
Yanglong Zhong ◽  
Shuai Ma ◽  
Bolun An
Keyword(s):  
High Speed ◽  
Large Scale ◽  
Detection Method ◽  
Low Cost ◽  
Detection Methods ◽  
Data Conversion ◽  
Track Geometry ◽  
Slab Track ◽  
Detection Model ◽  
Characteristics Analysis

During the long-term service of slab track, various external factors (such as complicated temperature) can result in a series of slab damages. Among them, slab arching changes the structural mechanical properties, deteriorates the track geometry conditions, and even threatens the operation of trains. Therefore, it is necessary to detect slab arching accurately to achieve effective maintenance. However, the current damage detection methods cannot satisfy high accuracy and low cost simultaneously, making it difficult to achieve large-scale and efficient arching detection. To this end, this paper proposed a vision-based arching detection method using track geometry data. The main works include: (1) data nonlinear deviation correction and arching characteristics analysis; (2) data conversion and augmentation; (3) design and experiments of convolutional neural network- based detection model. The results show that the proposed method can detect arching damages effectively, and the F1-score reaches 98.4%. By balancing the sample size of each pattern, the performance can be further improved. Moreover, the method outperforms the plain deep learning network. In practice, the proposed method can be employed to detect slab arching and help to make maintenance plans. The method can also be applied to the data-based detection of other structural damages and has broad prospects.

Sign in / Sign up

Export Citation Format

Share Document