scholarly journals Android App Controlled Bluetooth Robotic Vehicle

2017 ◽  
Author(s):  
Sa’adah Saleem Al-Jabri ◽  
Fatma Saif Al-Habsi ◽  
A. Jamaludeen A. Jamaludeen
Keyword(s):  
Embedded System ◽  
Low Cost ◽  
Processing Unit ◽  
Entire System ◽  
Industrial Environment ◽  
Android App ◽  
Java Platform ◽  
Robotic Vehicle ◽  
Kinetics Of ◽  
Cost Components

The objective of the present work is to design and develop an android app based user interface to control a robotic vehicle using wireless bluetooth technology. The entire system consists of carefully selected replaceable low-cost components to meet the rugged industrial environment. The proposed single-board in-vehicle embedded system is equipped with the HC-05 bluetooth model to interact with microcontroller and android app, dc gear motor and L293D motor driver to control the kinetics of a robotic vehicle, and ATmega328P microcontroller as core processing unit fixed on self-designed chassis. The back-hand design for the android app is developed using open source called ‘App Inventor’ developed by MIT and suitable to develop app without Java platform. The in-vehicle electronics hardware is developed around the ATmega328P microcontroller and bluetooth module is interfaced with microcontroller through the UART protocol to exchange the data with android app. By pressing remote button developed in the android app the direction of the robotic vehicle can be decided. The major advantages of this proposed design is, minimum version of in-built bluetooth smartphone is used to install the developed app and wireless bluetooth technology offers zero communication cost. Moreover, this robotic vehicle can also be utilized other application such as, exploring the toxic area, detection of explosive landmines, multipurpose surveillance vehicle.

Hardware Realization of Antifogging System

2017 ◽  
pp. 153-172
Author(s):  
Amruta Laxman Deshmukh ◽  
Satbir Singh ◽  
Balwinder Singh
Keyword(s):  
Embedded System ◽  
Low Power ◽  
Computer Model ◽  
Surveillance System ◽  
Low Cost ◽  
Model System ◽  
Raspberry Pi ◽  
Processing Unit ◽  
Matlab Code ◽  
Condensed Water

There are many reasons for invisibility of objects on road in daylight, majority of them are Fog (condensed water droplets in atmosphere), smog (soot particles in air). This reduced visibility is one of the prime factors responsible for accident of vehicles and disadvantage in surveillance system. This chapter takes account of a method that comprises of a complete embedded system for the process of restoring the captured foggy images. Use of a novel ‘Mean Channel Prior' algorithm for defogging is presented. Further detailed step by step explanation is given for hardware implementation of MATLAB code. Hardware consists of raspberry pi which is an ARM7 Quad Core processor based mini computer model. System serves as portable, low cost and low power processing unit with provision of interfacing a camera and a display screen.

scholarly journals Adapting the 3D-printed Openflexure microscope enables computational super-resolution imaging

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 2003
Author(s):  
Stephen D. Grant ◽  
Gemma S. Cairns ◽  
Jordan Wistuba ◽  
Brian R. Patton
Keyword(s):  
Fluorescence Imaging ◽  
Low Cost ◽  
Super Resolution ◽  
Diffraction Limit ◽  
Entire System ◽  
3D Printed ◽  
Resolution Imaging ◽  
Cost Components ◽  
Better Than

We report on a 3D printed microscope, based on a design by the Openflexure project, that uses low cost components to perform fluorescence imaging. The system is sufficiently sensitive and mechanically stable to allow the use of the Super Resolution Radial Fluctuations algorithm to obtain images with resolution better than the diffraction limit. Due to the low-cost components, the entire system can be built for approximately $1200.

Study of the Cu(II) removal from aqueous solutions by adsorption on titania

2013 ◽  
Vol 12 (3) ◽  
pp. 239-247
Keyword(s):  
Heavy Metals ◽  
Ionic Strength ◽  
Toxic Metals ◽  
Low Cost ◽  
Lateral Interaction ◽  
Tio2 Surface ◽  
High Toxicity ◽  
Removal Of Heavy Metals ◽  
Solution Parameters ◽  
Kinetics Of

The removal of heavy metals from wastewaters is a matter of paramount importance due to the fact that their high toxicity causes major environmental pollution problems. One of the most efficient, applicable and low cost methods for the removal of toxic metals from aqueous solutions is that of their adsorption on an inorganic adsorbent. In order to achieve high efficiency, it is important to understand the influence of the solution parameters on the extent of the adsorption, as well as the kinetics of the adsorption. In the present work, the adsorption of Cu(II) species onto TiO2 surface was studied. It was found that the adsorption is a rapid process and it is not affected by the value of ionic strength. In addition, it was found that by increasing the pH, the adsorbed amount of Cu2+ ions and the value of the adsorption constant increase, whereas the value of the lateral interaction energy decreases.

scholarly journals Low-Cost Embedded System Using Convolutional Neural Networks-Based Spatiotemporal Feature Map for Real-Time Human Action Recognition

2021 ◽  
Vol 11 (11) ◽  
pp. 4940
Author(s):  
Jinsoo Kim ◽  
Jeongho Cho
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Action Recognition ◽  
Processing Speed ◽  
Recognition Accuracy ◽  
Low Cost ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Data ◽  
Feature Maps

The field of research related to video data has difficulty in extracting not only spatial but also temporal features and human action recognition (HAR) is a representative field of research that applies convolutional neural network (CNN) to video data. The performance for action recognition has improved, but owing to the complexity of the model, some still limitations to operation in real-time persist. Therefore, a lightweight CNN-based single-stream HAR model that can operate in real-time is proposed. The proposed model extracts spatial feature maps by applying CNN to the images that develop the video and uses the frame change rate of sequential images as time information. Spatial feature maps are weighted-averaged by frame change, transformed into spatiotemporal features, and input into multilayer perceptrons, which have a relatively lower complexity than other HAR models; thus, our method has high utility in a single embedded system connected to CCTV. The results of evaluating action recognition accuracy and data processing speed through challenging action recognition benchmark UCF-101 showed higher action recognition accuracy than the HAR model using long short-term memory with a small amount of video frames and confirmed the real-time operational possibility through fast data processing speed. In addition, the performance of the proposed weighted mean-based HAR model was verified by testing it in Jetson NANO to confirm the possibility of using it in low-cost GPU-based embedded systems.

scholarly journals Recurrent Neural Network for Human Activity Recognition in Embedded Systems Using PPG and Accelerometer Data

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1715
Author(s):  
Michele Alessandrini ◽  
Giorgio Biagetti ◽  
Paolo Crippa ◽  
Laura Falaschetti ◽  
Claudio Turchetti
Keyword(s):  
Neural Network ◽  
Embedded System ◽  
Activity Recognition ◽  
Human Activity ◽  
Recurrent Neural Network ◽  
Low Cost ◽  
Low Complexity ◽  
Human Activity Recognition ◽  
Motion Artifacts ◽  
Accelerometer Data

Photoplethysmography (PPG) is a common and practical technique to detect human activity and other physiological parameters and is commonly implemented in wearable devices. However, the PPG signal is often severely corrupted by motion artifacts. The aim of this paper is to address the human activity recognition (HAR) task directly on the device, implementing a recurrent neural network (RNN) in a low cost, low power microcontroller, ensuring the required performance in terms of accuracy and low complexity. To reach this goal, (i) we first develop an RNN, which integrates PPG and tri-axial accelerometer data, where these data can be used to compensate motion artifacts in PPG in order to accurately detect human activity; (ii) then, we port the RNN to an embedded device, Cloud-JAM L4, based on an STM32 microcontroller, optimizing it to maintain an accuracy of over 95% while requiring modest computational power and memory resources. The experimental results show that such a system can be effectively implemented on a constrained-resource system, allowing the design of a fully autonomous wearable embedded system for human activity recognition and logging.

The Development of Embedded System for Energy Saving in Electro-Hydraulic System

2013 ◽  
Vol 418 ◽  
pp. 63-69
Author(s):  
Sema Patchim ◽  
Watcharin Po-Ngaen
Keyword(s):  
Embedded System ◽  
Low Power ◽  
Hydraulic System ◽  
Fuzzy Controller ◽  
Low Cost ◽  
Operational Performance ◽  
Functional Design ◽  
Power Utility ◽  
Load Sensing ◽  
Oil Flow

In last decade, energy efficiency of hydraulic actuators systems has been especially important in industrial machinery applications [1-. And an advanced electronics world most of the applications are developed by microcontroller based embedded system. Energy processor based variable oil flow of hydraulic controller was presented to improve the efficiency of the motor by maintaining with the load sensing. These PIC processor combined with fuzzy controller were help to design efficient optimal power hydraulic machine controller. A functional design of processor and in this system was completed by using load sensing signal to control oil flow. The advantage of the proposed system was optimized operational performance and low power utility. Without having the architectural concept of any motor we can control it by using this method. This is a low cost low power controller and easy to use. The experiment results verified its validity.

scholarly journals Semi-Active Magnetic Levitation System for Education

2021 ◽  
Vol 11 (12) ◽  
pp. 5330
Author(s):  
Gisela Pujol-Vázquez ◽  
Alessandro N. Vargas ◽  
Saleh Mobayen ◽  
Leonardo Acho
Keyword(s):  
Pid Control ◽  
Magnetic Levitation ◽  
Low Cost ◽  
Control Scheme ◽  
Hands On ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
And Control ◽  
Active Control Strategy ◽  
Cost Components

This paper describes how to construct a low-cost magnetic levitation system (MagLev). The MagLev has been intensively used in engineering education, allowing instructors and students to learn through hands-on experiences of essential concepts, such as electronics, electromagnetism, and control systems. Built from scratch, the MagLev depends only on simple, low-cost components readily available on the market. In addition to showing how to construct the MagLev, this paper presents a semi-active control strategy that seems novel when applied to the MagLev. Experiments performed in the laboratory provide comparisons of the proposed control scheme with the classical PID control. The corresponding real-time experiments illustrate both the effectiveness of the approach and the potential of the MagLev for education.

Statistical Modeling, Optimization and Kinetics of Mn2+ Adsorption in Aqueous Solution Using a Biosorbent

2019 ◽  
Vol 233 (8) ◽  
pp. 1201-1214 ◽  
Author(s):  
Elaheh Tajari ◽  
Narges Samadani Langeroodi ◽  
Mahnaz Khalafi
Keyword(s):  
Wheat Bran ◽  
Low Cost ◽  
Weight Ratio ◽  
P Value ◽  
Core Shell ◽  
Optimal Conditions ◽  
Solution Ph ◽  
Shell Weight ◽  
Removal Ratio ◽  
Kinetics Of

Abstract This paper describes the adsorption of Mn2+ ions from water with a mixture of wheat bran and Japanese medlar core shell (weight ratio of 30–70 wheat bran to Japanese medlar core shell) as low-cost adsorbent. Scanning Electron Microscope was used to characterize the adsorbent. The response surface methodology (RSM) that is usually approximated by a second-order regression model was employed to evaluate the effects of solution pH, initial Mn2+ concentration, adsorbent weight and contact time on the removal ratio of the Mn2+ ions. In this regard, the significant variables initial Mn2+ ions concentration, pH, adsorbent weight and square pH were found based on the small P-value for the model coefficients. The predicted optimal conditions were also performed. In the process optimization, maximal value of the removal ratio of Mn2+ was achieved as 96.91%. Additionally, this paper discusses the kinetic of adsorption in optimal conditions.

scholarly journals Improvement of Hydrogen Desorption Characteristics of MgH2 With Core-shell Ni@C Composites

Molecules ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3113 ◽  
Author(s):  
Cuihua An ◽  
Qibo Deng
Keyword(s):  
Low Cost ◽  
Hydrogen Desorption ◽  
Core Shell ◽  
Desorption Kinetics ◽  
Hydrogen Storage Materials ◽  
High Hydrogen ◽  
Dehydrogenation Kinetics ◽  
Materials Research ◽  
High Theoretical Capacity ◽  
Kinetics Of

Magnesium hydride (MgH2) has become popular to study in hydrogen storage materials research due to its high theoretical capacity and low cost. However, the high hydrogen desorption temperature and enthalpy as well as the depressed kinetics, have severely blocked its actual utilizations. Hence, our work introduced Ni@C materials with a core-shell structure to synthesize MgH2-x wt.% Ni@C composites for improving the hydrogen desorption characteristics. The influences of the Ni@C addition on the hydrogen desorption performances and micro-structure of MgH2 have been well investigated. The addition of Ni@C can effectively improve the dehydrogenation kinetics. It is interesting found that: i) the hydrogen desorption kinetics of MgH2 were enhanced with the increased Ni@C additive amount; and ii) the dehydrogenation amount decreased with a rather larger Ni@C additive amount. The additive amount of 4 wt.% Ni@C has been chosen in this study for a balance of kinetics and amount. The MgH2-4 wt.% Ni@C composites release 5.9 wt.% of hydrogen in 5 min and 6.6 wt.% of hydrogen in 20 min. It reflects that the enhanced hydrogen desorption is much faster than the pure MgH2 materials (0.3 wt.% hydrogen in 20 min). More significantly, the activation energy (EA) of the MgH2-4 wt.% Ni@C composites is 112 kJ mol−1, implying excellent dehydrogenation kinetics.

Sign in / Sign up

Export Citation Format

Share Document