scholarly journals MTouch: An Automatic Fault Detection System for Desktop FFF 3D Printers Using a Contact Sensor

2021 ◽  
Author(s):  
Samuel Aidala ◽  
Zachary Eichenberger ◽  
Nickolas Chan ◽  
Kyle Wilkinson ◽  
Chinedum Okwudire
Keyword(s):  
Detection System ◽  
Low Cost ◽  
Raspberry Pi ◽  
Ambient Conditions ◽  
Fused Filament Fabrication ◽  
Hall Effect Sensor ◽  
Cost System ◽  
Contact Probe ◽  
3D Printers ◽  
Contact Sensor

Desktop fused filament fabrication (FFF) 3D printers have been growing in popularity among hobbyist and professional users as a prototyping and low-volume manufacturing tool. One issue these printers face is the inability to determine when a defect has occurred rendering the print unusable. Several techniques have been proposed to detect such defects but many of these approaches are tailored to one specific fault (e.g., filament runout/jam), use expensive hardware such as laser distance sensors, and/or use machine vision algorithms which are sensitive to ambient conditions, and hence can be unreliable. This paper proposes a versatile, reliable, and low-cost system, named MTouch, to detect millimeter-scale defects that tend to make prints unusable. At the core of MTouch is an actuated contact probe designed using a low-power solenoid, magnet, and hall effect sensor. This sensor is used to check for the presence, or absence, of the printed object at specific locations. The MTouch probe demonstrated 100% reliability, which was significantly higher than the 74% reliability achieved using a commercially available contact probe (the BLTouch). Additionally, an algorithm was developed to automatically detect common print failures such as layer shifting, bed separation, and filament runout using the MTouch probe. The algorithm was implemented on a Raspberry Pi mini-computer via an Octoprint plug-in. In head-to-head testing against a commercially available print defect detection system (The Spaghetti Detective), the MTouch was able to detect faults 44% faster on average while only increasing the print time by 8.49%. In addition, MTouch was able to detect faults The Spaghetti Detective was unable to identify such as layer shifting and filament runout/jam.

Face recognition in an intelligent door lock with ResNet model based on deep learning

2021 ◽  
pp. 1-11
Author(s):  
Suphawimon Phawinee ◽  
Jing-Fang Cai ◽  
Zhe-Yu Guo ◽  
Hao-Ze Zheng ◽  
Guan-Chen Chen
Keyword(s):  
Face Recognition ◽  
Detection System ◽  
Low Cost ◽  
Ease Of Use ◽  
Raspberry Pi ◽  
Training Methods ◽  
Graphics Recognition ◽  
Face Images ◽  
The Face ◽  
Door Lock

Internet of Things is considerably increasing the levels of convenience at homes. The smart door lock is an entry product for smart homes. This work used Raspberry Pi, because of its low cost, as the main control board to apply face recognition technology to a door lock. The installation of the control sensing module with the GPIO expansion function of Raspberry Pi also improved the antitheft mechanism of the door lock. For ease of use, a mobile application (hereafter, app) was developed for users to upload their face images for processing. The app sends the images to Firebase and then the program downloads the images and captures the face as a training set. The face detection system was designed on the basis of machine learning and equipped with a Haar built-in OpenCV graphics recognition program. The system used four training methods: convolutional neural network, VGG-16, VGG-19, and ResNet50. After the training process, the program could recognize the user’s face to open the door lock. A prototype was constructed that could control the door lock and the antitheft system and stream real-time images from the camera to the app.

scholarly journals Low Cost System for Laboratory-based Course in IT Education using Raspberry Pi

2020 ◽  
Author(s):  
Tae-Hoon Kim ◽  
Ricardo Calix ◽  
Dhruvkumar Patel
Keyword(s):  
Low Cost ◽  
Raspberry Pi ◽  
Cost System ◽  
It Education

Advanced Surface System for Central Venous Catheter Insertion Training

2020 ◽  
Author(s):  
Dailen Brown ◽  
Haroula Tzamaras ◽  
Jessica M. Gonzalez-Vargas ◽  
Scarlett Miller ◽  
Jason Moore
Keyword(s):  
Sensor Array ◽  
Low Cost ◽  
Venous Catheter ◽  
Maximum Deviation ◽  
Central Venous ◽  
Insertion Depth ◽  
Hall Effect Sensor ◽  
Cost System ◽  
Venous Catheterization ◽  
Measured Position

Abstract An advanced surface for Central Venous Catheterization (CVC) training and evaluation was designed using sensorization techniques, including the use of a hall effect sensor array to measure the insertion depth of a catheter. The sensor array was tested for accuracy in both static and dynamic scenarios, and was found to be sufficiently accurate; measuring position with an accuracy of ±1.1 mm on average. The highest deviations in measured positions were located at the extreme ends of the array where calculations rely on only a single sensor. The maximum deviation in measured position was found to be 3.5 mm. This low-cost system of catheter measurement has the potential to improve feedback and assessment of CVC training.

scholarly journals Individualized tracking of self-directed motor learning in group-housed mice performing a skilled lever positioning task in the home cage

2018 ◽  
Vol 119 (1) ◽  
pp. 337-346 ◽  
Author(s):  
Gergely Silasi ◽  
Jamie D. Boyd ◽  
Federico Bolanos ◽  
Jeff M. LeDue ◽  
Stephen H. Scott ◽  
...  
Keyword(s):  
Motor Learning ◽  
Radio Frequency Identification ◽  
Home Cage ◽  
Low Cost ◽  
Motor Task ◽  
Training Group ◽  
Cortical Reorganization ◽  
Raspberry Pi ◽  
Internet Connection ◽  
Cost System

Skilled forelimb function in mice is traditionally studied through behavioral paradigms that require extensive training by investigators and are limited by the number of trials individual animals are able to perform within a supervised session. We developed a skilled lever positioning task that mice can perform within their home cage. The task requires mice to use their forelimb to precisely hold a lever mounted on a rotary encoder within a rewarded position to dispense a water reward. A Raspberry Pi microcomputer is used to record lever position during trials and to control task parameters, thus making this low-footprint apparatus ideal for use within animal housing facilities. Custom Python software automatically increments task difficulty by requiring a longer hold duration, or a more accurate hold position, to dispense a reward. The performance of individual animals within group-housed mice is tracked through radio-frequency identification implants, and data stored on the microcomputer may be accessed remotely through an active internet connection. Mice continuously engage in the task for over 2.5 mo and perform ~500 trials/24 h. Mice required ~15,000 trials to learn to hold the lever within a 10° range for 1.5 s and were able to further refine movement accuracy by limiting their error to a 5° range within each trial. These results demonstrate the feasibility of autonomously training group-housed mice on a forelimb motor task. This paradigm may be used in the future to assess functional recovery after injury or cortical reorganization induced by self-directed motor learning. NEW & NOTEWORTHY We developed a low-cost system for fully autonomous training of group-housed mice on a forelimb motor task. We demonstrate the feasibility of tracking both end-point, as well as kinematic performance of individual mice, with each performing thousands of trials over 2.5 mo. The task is run and controlled by a Raspberry Pi microcomputer, which allows for cages to be monitored remotely through an active internet connection.

scholarly journals Effects of Filament Diameter Tolerances in Fused Filament Fabrication

2016 ◽  
Vol 2 (1) ◽  
pp. 44-47 ◽  
Author(s):  
Carolina Cardona ◽  
Abigail H Curdes ◽  
Aaron J Isaacs
Keyword(s):  
3D Printing ◽  
Low Cost ◽  
Acrylonitrile Butadiene Styrene ◽  
Fused Filament Fabrication ◽  
Important Indicator ◽  
Extrusion Rate ◽  
Filament Diameter ◽  
Printing Quality ◽  
3D Printers ◽  
And Control

Fused filament fabrication (FFF) is one of the most popular additive manufacturing (3D printing) technologies due to the growing availability of low-cost desktop 3D printers and the relatively low cost of the thermoplastic filament used in the 3D printing process. Commercial filament suppliers, 3D printer manufacturers, and end-users regard filament diameter tolerance as an important indicator of the 3D printing quality. Irregular filament diameter affects the flow rate during the filament extrusion, which causes poor surface quality, extruder jams, irregular gaps in-between individual extrusions, and/or excessive overlap, which eventually results in failed 3D prints. Despite the important role of the diameter consistency in the FFF process, few studies have addressed the required tolerance level to achieve highest 3D printing quality. The objective of this work is to develop the testing methods to measure the filament tolerance and control the filament fabrication process. A pellet-based extruder is utilized to fabricate acrylonitrile butadiene styrene (ABS) filament using a nozzle of 1.75 mm in diameter. Temperature and extrusion rate are controlled parameters. An optical comparator and an array of digital calipers are used to measure the filament diameter. The results demonstrate that it is possible to achieve high diameter consistency and low tolerances (0.01mm) at low extrusion temperature (180 °C) and low extrusion rate (10 in/min). 

scholarly journals Development of Smart Vehicle Security and Entertainment System (SSES) using Raspberry Pi

2020 ◽  
Vol 9 (3) ◽  
pp. 4077-4083 ◽  
Keyword(s):  
Low Cost ◽  
Cost Effective ◽  
Security System ◽  
Local Network ◽  
Raspberry Pi ◽  
Main Concept ◽  
Embedded Devices ◽  
Vehicle Owner ◽  
Cost System ◽  
Vehicle Security

This paper deals with development of a Vehicle Security and Entertainment System, which is being used to monitor, track the vehicle, and to offer local entertainment system. The development system makes used of two embedded devices to split the entertainment system from the security system to ensure isolation and security. The security system is equipped with camera, distress signal switch and GPS/GPRS module to track, report a problem, and monitor the vehicle by sending data to a centralized database server where vehicle owner can access and retrieve these data to guarantee the safety of the passengers and the vehicle too. The second system is the entertainment system, where this system uses a powerful Intel atom embedded device and local network to allow users to connect and offer entertaining services. These services include, E-Book library and multimedia streaming. The main concept of research to develop a low cost system to secure and entertain passengers on vehicles like buses, train and even cars. The development is cost effective and as well as can be modified to add extra modules or to develop extra entertainment services. If the vehicle is stolen the system is able to send a distress signal to the owner or company. They can help the passengers by monitoring through the vehicle camera. In this research we have successfully developed and tested the system.

Performance Analysis of Mail Clients on Low Cost Computer With ELGamal and RSA Using SNORT

2018 ◽  
pp. 332-353
Author(s):  
Sreerama Murthy Kattamuri ◽  
Vijayalakshmi Kakulapati ◽  
Pallam Setty S.
Keyword(s):  
Intrusion Detection ◽  
Low Power ◽  
Intrusion Detection System ◽  
Detection System ◽  
Low Cost ◽  
Raspberry Pi ◽  
Ip Address ◽  
Intrusion Prevention ◽  
Plain Text ◽  
Intrusion Prevention System

An intrusion detection system (IDS) focuses on determining malicious tasks by verifying network traffic and informing the network administrator for restricting the user or source or source IP address from accessing the network. SNORT is an open source intrusion detection system (IDS) and SNORT also acts as an intrusion prevention system (IPS) for monitoring and prevention of security attacks on networks. The authors applied encryption for text files by using cryptographic algorithms like Elgamal and RSA. This chapter tested the performance of mail clients in low cost, low power computer Raspberry Pi, and verified that SNORT is efficient for both algorithms. Within low cost, low power computer, they observed that as the size of the file increases, the run time is constant for compressed data; whereas in plain text, it changed significantly.

scholarly journals Low-Cost Image Search System on Off-Line Situation

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 153 ◽  
Author(s):  
Mery Diana ◽  
Juntaro Chikama ◽  
Motoki Amagasaki ◽  
Masahiro Iida
Keyword(s):  
Low Cost ◽  
Model Performance ◽  
Cosine Similarity ◽  
Raspberry Pi ◽  
Image Search ◽  
Search Tasks ◽  
Cost System ◽  
Network Properties ◽  
General Average ◽  
Fully Connected

Implementation of deep learning in low-cost hardware, such as an edge device, is challenging. Reducing the complexity of the network is one of the solutions to reduce resource usage in the system, which is needed by low-cost system implementation. In this study, we use the general average pooling layer to replace the fully connected layers on the convolutional neural network (CNN) model, used in the previous study, to reduce the number of network properties without decreasing the model performance in developing image classification for image search tasks. We apply the cosine similarity to measure the characteristic similarity between the feature vector of image input and extracting feature vectors from testing images in the database. The result of the cosine similarity calculation will show the image as the result of the searching image task. In the implementation, we use Raspberry Pi 3 as a low-cost hardware and CIFAR-10 dataset for training and testing images. Base on the development and implementation, the accuracy of the model is 68%, and the system generates the result of the image search base on the characteristic similarity of the images.

scholarly journals Inexpensive Piezoelectric Elements for Nozzle Contact Detection and Build Platform Leveling in FFF 3D Printers

2018 ◽  
Author(s):  
Michael Simpson ◽  
Simon Khoury
Keyword(s):  
Output Voltage ◽  
Contact Detection ◽  
Test Duration ◽  
Electronic Circuits ◽  
Fused Filament Fabrication ◽  
Nozzle Height ◽  
A Value ◽  
Piezoelectric Elements ◽  
3D Printers ◽  
Contact Sensor

Inexpensive piezoelectric diaphragms can be used as sensors to facilitate both nozzle height setting and build platform leveling in FFF (Fused Filament Fabrication) 3D printers. Tests simulating nozzle contact are conducted to establish the available output and an output of greater than 8 Volts found at 20 ºC, a value which is readily detectable by simple electronic circuits. Tests are also conducted at a temperature of 80 ºC and, despite a reduction of greater than 80% in output voltage, this is still detectable. The reliability of piezoelectric diaphragms is investigated by mechanically stressing samples over 100,000 cycles at both 20 ºC and 80 ºC and little loss of output over the test duration is found. The development of a nozzle contact sensor using a single piezoelectric diaphragm is described.

Using ICT and Energy Technologies for Improving Global Engineering Education

2021 ◽  
Author(s):  
Pritpal Singh
Keyword(s):  
Engineering Education ◽  
Educational Software ◽  
Low Cost ◽  
Raspberry Pi ◽  
Solar Panels ◽  
Information Communication ◽  
Energy Technologies ◽  
Global Engineering ◽  
3D Printers ◽  
The Cost

Information, communication, and energy technologies have the potential to improve engineering education worldwide. With the availability of low cost, open-source microcontrollers/microcomputers, such as the Arduino and Raspberry Pi platforms, and a wide variety of sensors and communication tools, a range of engineering applications and innovations may be developed at a low price. Furthermore, the cost of solar panels and LED lamps have also dropped dramatically in recent years and these also allow for improved energy support in regions that lack energy access or require autonomous monitoring/processing. Also, low-cost 3D printers are now widely available for making simple prototypes of hardware. Finally, low-cost educational software tools have also become available. Combining these technologies enables engineering education to be brought into traditionally inaccessible communities in the world. In this book chapter, examples of how ICT and energy technologies are being used to teach students engineering technologies in underserved communities will be described. Application areas to be described will include environmental monitoring, clean water systems, and remote learning.

Sign in / Sign up

Export Citation Format

Share Document