Portable Device and Mobile Application for the Detection of Ultraviolet Radiation in Real Time with a Low Cost Sensor in Arduino

2020 ◽  
pp. 301-312
Author(s):  
Joe Llerena-Izquierdo ◽  
Nebel Viera-Sanchez ◽  
Bladimir Rodriguez-Moreira
Keyword(s):  
Ultraviolet Radiation ◽  
Real Time ◽  
Mobile Application ◽  
Low Cost ◽  
Portable Device

scholarly journals TOWARDS A LOW-COST, REAL-TIME PHOTOGRAMMETRIC LANDSLIDE MONITORING SYSTEM UTILISING MOBILE AND CLOUD COMPUTING TECHNOLOGY

2016 ◽  
Vol XLI-B5 ◽  
pp. 791-797 ◽  
Author(s):  
P. Chidburee ◽  
J. P. Mills ◽  
P. E. Miller ◽  
K. D. Fieber
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Monitoring System ◽  
Mobile Application ◽  
Low Cost ◽  
Landslide Hazard ◽  
Initial Assessment ◽  
Landslide Monitoring ◽  
Computing Technology ◽  
Photogrammetric Measurement

Close-range photogrammetric techniques offer a potentially low-cost approach in terms of implementation and operation for initial assessment and monitoring of landslide processes over small areas. In particular, the Structure-from-Motion (SfM) pipeline is now extensively used to help overcome many constraints of traditional digital photogrammetry, offering increased user-friendliness to nonexperts, as well as lower costs. However, a landslide monitoring approach based on the SfM technique also presents some potential drawbacks due to the difficulty in managing and processing a large volume of data in real-time. This research addresses the aforementioned issues by attempting to combine a mobile device with cloud computing technology to develop a photogrammetric measurement solution as part of a monitoring system for landslide hazard analysis. The research presented here focusses on (i) the development of an Android mobile application; (ii) the implementation of SfM-based open-source software in the Amazon cloud computing web service, and (iii) performance assessment through a simulated environment using data collected at a recognized landslide test site in North Yorkshire, UK. Whilst the landslide monitoring mobile application is under development, this paper describes experiments carried out to ensure effective performance of the system in the future. Investigations presented here describe the initial assessment of a cloud-implemented approach, which is developed around the well-known VisualSFM algorithm. Results are compared to point clouds obtained from alternative SfM 3D reconstruction approaches considering a commercial software solution (Agisoft PhotoScan) and a web-based system (Autodesk 123D Catch). Investigations demonstrate that the cloud-based photogrammetric measurement system is capable of providing results of centimeter-level accuracy, evidencing its potential to provide an effective approach for quantifying and analyzing landslide hazard at a local-scale.

scholarly journals TOWARDS A LOW-COST, REAL-TIME PHOTOGRAMMETRIC LANDSLIDE MONITORING SYSTEM UTILISING MOBILE AND CLOUD COMPUTING TECHNOLOGY

2016 ◽  
Vol XLI-B5 ◽  
pp. 791-797
Author(s):  
P. Chidburee ◽  
J. P. Mills ◽  
P. E. Miller ◽  
K. D. Fieber
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Monitoring System ◽  
Mobile Application ◽  
Low Cost ◽  
Landslide Hazard ◽  
Initial Assessment ◽  
Landslide Monitoring ◽  
Computing Technology ◽  
Photogrammetric Measurement

Close-range photogrammetric techniques offer a potentially low-cost approach in terms of implementation and operation for initial assessment and monitoring of landslide processes over small areas. In particular, the Structure-from-Motion (SfM) pipeline is now extensively used to help overcome many constraints of traditional digital photogrammetry, offering increased user-friendliness to nonexperts, as well as lower costs. However, a landslide monitoring approach based on the SfM technique also presents some potential drawbacks due to the difficulty in managing and processing a large volume of data in real-time. This research addresses the aforementioned issues by attempting to combine a mobile device with cloud computing technology to develop a photogrammetric measurement solution as part of a monitoring system for landslide hazard analysis. The research presented here focusses on (i) the development of an Android mobile application; (ii) the implementation of SfM-based open-source software in the Amazon cloud computing web service, and (iii) performance assessment through a simulated environment using data collected at a recognized landslide test site in North Yorkshire, UK. Whilst the landslide monitoring mobile application is under development, this paper describes experiments carried out to ensure effective performance of the system in the future. Investigations presented here describe the initial assessment of a cloud-implemented approach, which is developed around the well-known VisualSFM algorithm. Results are compared to point clouds obtained from alternative SfM 3D reconstruction approaches considering a commercial software solution (Agisoft PhotoScan) and a web-based system (Autodesk 123D Catch). Investigations demonstrate that the cloud-based photogrammetric measurement system is capable of providing results of centimeter-level accuracy, evidencing its potential to provide an effective approach for quantifying and analyzing landslide hazard at a local-scale.

scholarly journals A Low-Cost Platform for Modeling and Controlling the Yaw Dynamics of an Agricultural Tractor to Gain Autonomy

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1826
Author(s):  
Sergio Sandoval Pérez ◽  
Juan Miguel González López ◽  
Ramón O. Jimenez Betancourt ◽  
Efraín Villalvazo Laureano ◽  
Jesús Ezequiel Molinar Solís ◽  
...  
Keyword(s):  
Real Time ◽  
Mobile Application ◽  
State Feedback ◽  
Low Cost ◽  
Basic Knowledge ◽  
Control Algorithms ◽  
Local Reference System ◽  
Local Reference ◽  
Dynamic Variables ◽  
Agricultural Tractor

In this study, a low-cost proposed platform for training dynamics (PPTD) is proposed based on operational amplifiers to understand the dynamics and variables of the agricultural tractor John Deere tractor model 4430 to gain autonomy and analyze the behavior of control algorithms proposed in real time by state feedback. The proposed platform uses commercial sensors and interacts with the Arduino Uno and/or Daq-6009 board from National Instruments. A mobile application (APP) was also developed for real-time monitoring of autonomous control signals, the local reference system, and physical and dynamic variables in the tractor; this platform can be used as a mobile alternative applied to a tractor in physically installed form. In the presented case, the PPTD was mounted on a John Deere tractor to test its behavior; moreover, it may be used on other tractor models similarly as established here. The established results of this platform were compared with models established in MATLAB, validating the proposal. All simulations and developments are shared through a web-link as open-source files so that anyone with basic knowledge of electronics and modeling of vehicles can reproduce the proposed platform.

scholarly journals Low-cost wireless sensor network applied to real-time monitoring and control of water consumption in residences

2019 ◽  
Vol 14 (6) ◽  
pp. 1
Author(s):  
Arnon Jadir Rodrigues Alves ◽  
Leandro Tiago Manera ◽  
Marcel Veloso Campos
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Water Consumption ◽  
Mobile Application ◽  
Low Cost ◽  
Wireless Sensor ◽  
Monitoring And Control ◽  
Real Time Monitoring ◽  
And Control

The objective of this work is to explore the implementation of a low-cost real-time monitoring and control of water consumption together with a user feedback interface. Water usage information will be available in a cloud storage and can be accessed through a mobile application. The collected data allows access and supervision of both client- and water concessionaire. Project feasibility is analyzed in terms of hardware and software, as well as each element required for the design. The simulations were carried out with the purpose of verifying system operation, considering the following metrics: transmission rate, signal strength and transmission quality. After the simulations, the hardware and software were integrated, and the final result was presented through a mobile application. This work presents and applies a design and development methodology of Wireless Sensor Network (WSN) using Internet of Things (IoT) technologies and Smart City in water-distribution systems.

EXPERIMENTATION OF A LOW COST ELECTRONIC SYSTEM FOR MEASUREMENT OF THE ULTRAVIOLET RADIATION INDEX TO THE CITY OF CAMPINA GRANDE, BRAZIL

2019 ◽  
Author(s):  
Emerson da Trindade Marcelino ◽  
Júlio Mannuel Tavares Diniz ◽  
ALVARO ROCHA ◽  
Eisenhawer de Moura Fernandes ◽  
Raimundo Duarte ◽  
...  
Keyword(s):  
Ultraviolet Radiation ◽  
Low Cost ◽  
Electronic System ◽  
The City

LOW COST REAL TIME ROCKET TELEMETRY SYSTEM DESIGN

2019 ◽  
Author(s):  
Gabriel de Almeida Souza ◽  
Larissa Barbosa ◽  
Glênio Ramalho ◽  
Alexandre Zuquete Guarato
Keyword(s):  
System Design ◽  
Real Time ◽  
Low Cost ◽  
Telemetry System

Low-Cost High-Speed Techniques for Real-Time Simulation of Power Electronic Systems

2007 ◽  
Author(s):  
R. E. Crosbie ◽  
J. J. Zenor ◽  
R. Bednar ◽  
D. Word ◽  
N. G. Hingorani
Keyword(s):  
Real Time ◽  
High Speed ◽  
Low Cost ◽  
Electronic Systems ◽  
Power Electronic ◽  
Real Time Simulation ◽  
Time Simulation

scholarly journals Application of Deep Learning in Integrated Pest Management: A Real-Time System for Detection and Diagnosis of Oilseed Rape Pests

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yong He ◽  
Hong Zeng ◽  
Yangyang Fan ◽  
Shuaisheng Ji ◽  
Jianjian Wu
Keyword(s):  
Deep Learning ◽  
Integrated Pest Management ◽  
Pest Management ◽  
Real Time ◽  
Oilseed Rape ◽  
Data Augmentation ◽  
Low Cost ◽  
Response Speed ◽  
Original Model ◽  
Real Time System

In this paper, we proposed an approach to detect oilseed rape pests based on deep learning, which improves the mean average precision (mAP) to 77.14%; the result increased by 9.7% with the original model. We adopt this model to mobile platform to let every farmer able to use this program, which will diagnose pests in real time and provide suggestions on pest controlling. We designed an oilseed rape pest imaging database with 12 typical oilseed rape pests and compared the performance of five models, SSD w/Inception is chosen as the optimal model. Moreover, for the purpose of the high mAP, we have used data augmentation (DA) and added a dropout layer. The experiments are performed on the Android application we developed, and the result shows that our approach surpasses the original model obviously and is helpful for integrated pest management. This application has improved environmental adaptability, response speed, and accuracy by contrast with the past works and has the advantage of low cost and simple operation, which are suitable for the pest monitoring mission of drones and Internet of Things (IoT).

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