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.

A CNC Equipment Distributed Monitoring System Based on Cloud Computing Technology

2014 ◽  
Vol 1022 ◽  
pp. 392-395 ◽  
Author(s):  
Rang Yong Zhang ◽  
Geng Ma ◽  
Guang He Cheng
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Wireless Network ◽  
Monitoring System ◽  
Communication Technology ◽  
Wide Area ◽  
Distributed Monitoring ◽  
Real Time Monitoring ◽  
Computing Technology ◽  
Remote Diagnostics

CNC equipment distributed monitoring system based on cloud computing technology provides a sable and reliable remote real time monitoring system to monitoring a mount of CNC equipment distributed in a large wide area by wireless network and GPRS communication technology which can be used to remote diagnostics and improve service respond speed.

LZER0: GNSS cost-effective real-time positioning applied to landslide monitoring

2020 ◽  
Author(s):  
Lavinia Tunini ◽  
David Zuliani ◽  
Paolo Fabris ◽  
Marco Severin
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Cost Effective ◽  
Single Frequency ◽  
Landslide Monitoring ◽  
Natural Risk ◽  
Near Surface ◽  
Landslide Event ◽  
Wide Range

<p>The Global Navigation Satellite Systems (GNSS) provide a globally extended dataset of primordial importance for a wide range of applications, such as crustal deformation, topographic measurements, or near surface processes studies. However, the high costs of GNSS receivers and the supporting software can represent a strong limitation for the applicability to landslide monitoring. Low-cost tools and techniques are strongly required to face the plausible risk of losing the equipment during a landslide event.</p><p>Centro di Ricerche Sismologiche (CRS) of Istituto Nazionale di Oceanografia e di Geofisica Sperimentale OGS in collaboration with SoluTOP, in the last years, has developed a cost-effective GNSS device, called LZER0, both for post-processing and real-time applications. The aim is to satisfy the needs of both scientific and professional communities which require low-cost equipment to increase and improve the measurements on structures at risk, such as landslides or buildings, without losing precision.</p><p>The landslide monitoring system implements single-frequency GNSS devices and open source software packages for GNSS positioning, dialoguing through Linux shell scripts. Furthermore a front-end web page has been developed to show real-time tracks. The system allows measuring real-time surface displacements with a centimetre precision and with a cost ten times minor than a standard RTK GPS operational system.</p><p>This monitoring system has been tested and now applied to two landslides in NE- Italy: one near Tolmezzo municipality and one near Brugnera village. Part of the device development has been included inside the project CLARA 'CLoud plAtform and smart underground imaging for natural Risk Assessment' funded by the Italian Ministry of Education, University and Research (MIUR).</p>

scholarly journals Flood Detection and Water Monitoring System Using IOT

2020 ◽  
Vol 9 (07) ◽  
pp. 25113-25115
Author(s):  
Minakshi Roy ◽  
Prakar Pradhan ◽  
Jesson George ◽  
Nikhil Pradhan
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Mobile Application ◽  
Water Monitoring ◽  
The Internet ◽  
Computing Technology ◽  
Time Data ◽  
Smart Water ◽  
Flood Detection ◽  
Time Changes

Since we are now currently present in an era of Computing Technology, it is essential for everyone and everything to be connected to the internet. IOT is a technology that brings us more and more close to this goal. Our project comprises of a smart water monitoring system which is a small prototype for flood detection and avoidance system. This paper explains the working and the workflow of all the components present inside our project. The sensors sense the environment and sends real-time data to the cloud (firebase cloud) and users can view and access this data via their mobile platform. The model gives a warning after the water level rises to a particular height. Since it is a small scaled prototype for flood detection and avoidance system, the working of this model is good. The data are uploaded and changed in the cloud in precision to the sensor and real-time changes in the mobile application is achieved. This model can be used to greatly reduce the casualties in a devastating event of flood.

Smart and Low Cost Real Time Water Quality Monitoring System Using IoT

2019 ◽  
Author(s):  
Jeba Anandh S ◽  
Anandharaj M ◽  
Aswinrajan J ◽  
Karankumar G ◽  
Karthik P
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Water Quality Monitoring ◽  
Quality Monitoring

scholarly journals Design of Early Warning System Based on Wireless Sensor Network

2018 ◽  
Vol 14 (01) ◽  
pp. 66
Author(s):  
Gan Bo ◽  
Jin Shan
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Monitoring System ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Sensor Data ◽  
Landslide Monitoring ◽  
Remote Transmission ◽  
Sensor Data Acquisition

In order to solve the shortcomings of the landslide monitoring technology method, a set of landslides monitoring and early warning system is designed. It can achieve real-time sensor data acquisition, remote transmission and query display. In addition, aiming at the harsh environment of landslide monitoring and the performance requirements of the monitoring system, an improved minimum hop routing protocol is proposed. It can reduce network energy consumption, enhance network robustness, and improve node layout and networking flexibility. In order to realize the remote transmission of data, GPRS wireless communication is used to transmit monitoring data. Combined with remote monitoring center, real-time data display, query, preservation and landslide warning and prediction are realized. The results show that the sensor data acquisition system is accurate, the system is stable, and the node network is flexible. Therefore, the monitoring system has a good use value.

scholarly journals A study on the development of a light scattering particulate matter sensor and monitoring system

2020 ◽  
Vol 17 (3) ◽  
pp. 867-890
Author(s):  
Jun-Hee Choi ◽  
Hyun-Sug Cho
Keyword(s):  
Big Data ◽  
Particulate Matter ◽  
Light Scattering ◽  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Gravimetric Method ◽  
Correction Method ◽  
Measurement Methods ◽  
Linear Correction

The gravimetric method, which is mainly used among particulate matter (PM) measurement methods, includes the disadvantages that it cannot measure PM in real time and it requires expensive equipment. To overcome these disadvantages, we have developed a light scattering type PM sensor that can be manufactured at low cost and can measure PM in real time. We have built a big data system that can systematically store and analyze the data collected through the developed sensor, as well as an environment where PM states can be monitored mobile in real time using such data. In addition, additional studies were conducted to analyze and correct the collected big data to overcome the problem of low accuracy, which is a disadvantage of the light scattering type PM sensor. We used a linear correction method and proceeded to adopt the most suitable value based on error and accuracy.

scholarly journals An IoT based Low-cost Weather Monitoring System for Smart Farming

2021 ◽  
Author(s):  
L.P.S.S.K. Dayananda ◽  
A. Narmilan ◽  
P. Pirapuraj
Keyword(s):  
Liquid Crystal ◽  
Mobile Phone ◽  
Real Time ◽  
Monitoring System ◽  
Liquid Crystal Display ◽  
Low Cost ◽  
Weather Conditions ◽  
Weather Data ◽  
The Internet ◽  
Arduino Uno

Background: Weather monitoring is an important aspect of crop cultivation for reducing economic loss while increasing productivity. Weather is the combination of current meteorological components, such as temperature, wind direction and speed, amount and kind of precipitation, sunshine hours and so on. The weather defines a time span ranging from a few hours to several days. The periodic or continuous surveillance or the analysis of the status of the atmosphere and the climate, including parameters such as temperature, moisture, wind velocity and barometric pressure, is known as weather monitoring. Because of the increased usage of the internet, weather monitoring has been upgraded to smart weather monitoring. The Internet of Things (IoT) is one of the new technology that can help with many precision farming operations. Smart weather monitoring is one of the precision agriculture technologies that use sensors to monitor correct weather. The main objective of the research is to design a smart weather monitoring and real-time alert system to overcome the issue of monitoring weather conditions in agricultural farms in order for farmers to make better decisions. Methods: Different sensors were used in this study to detect temperature and humidity, pressure, rain, light intensity, CO2 level, wind speed and direction in an agricultural farm and real time clock sensor was used to measured real time weather data. The major component of this system was an Arduino Uno microcontroller and the system ran according to a program written in the Arduino Uno software. Result: This is a low-cost smart weather monitoring system. This system’s output unit were a liquid crystal display and a GSM900A module. The weather data was displayed on a liquid crystal display and the GSM900A module was used to send the data to a mobile phone. This smart weather station was used to monitor real-time weather conditions while sending weather information to the farmer’s mobile phone, allowing him to make better decisions to increase yield.

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