scholarly journals The AIDSS Module for Data Acquisition in Crisis Situations and Environmental Protection

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1267
Author(s):  
Andrija Krtalić ◽  
Milan Bajić ◽  
Tamara Ivelja ◽  
Ivan Racetin
Keyword(s):  
Data Acquisition ◽  
Near Infrared ◽  
Measurement Unit ◽  
Digital Cameras ◽  
Infrared Sensors ◽  
Multiple Sensors ◽  
Hazardous Area ◽  
Remotely Piloted Aircraft ◽  
Antipersonnel Mines ◽  
Line Scanner

The Toolbox implementation for removal of antipersonnel mines, submunitions and unexploded ordnance (TIRAMISU) Advanced Intelligence Decision Support System is an operational system proposed to Mine Action Centres worldwide for conducting non-technical surveys in humanitarian demining. The system consists of three modules, one of which is the module for data acquisition introduced and described in this study. The module has been designed, produced, improved, used and operationally tested and validated on several platforms (helicopters, remotely piloted aircraft systems (RPAS) and a blimp), with various sensors and acquisition units (Global Positioning System (GPS) and inertial measurement unit) in a variety of combinations for additional data acquisition from deep inside a suspected hazardous area. For the purposes of aerial data acquisition over a suspected hazardous area, the use of multiple sensors such as visible digital cameras and multi-spectral visible, near infrared (VNIR), hyperspectral VNIR and thermal infrared sensors are of benefit, because they display the scene in different ways. Off-the-shelf equipment and software were mostly used, but some specific equipment, such as sensor pods, was developed and also some software solutions for data acquisition and pre-processing (transforming hyperspectral line scanner data into hyperspectral images, and producing hyperspectral cubes). The technical stability and robustness of the module were confirmed by operationally testing and evaluating the systems on the aforementioned platforms and missions in several actual suspected hazardous areas in Croatia and Bosnia and Herzegovina, between 2001 and 2015.

scholarly journals Using Ordinary Digital Cameras in Place of Near-Infrared Sensors to Derive Vegetation Indices for Phenology Studies of High Arctic Vegetation

2016 ◽  
Vol 8 (10) ◽  
pp. 847 ◽  
Author(s):  
Helen Anderson ◽  
Lennart Nilsen ◽  
Hans Tømmervik ◽  
Stein Karlsen ◽  
Shin Nagai ◽  
...  
Keyword(s):  
Near Infrared ◽  
Vegetation Indices ◽  
High Arctic ◽  
Digital Cameras ◽  
Infrared Sensors ◽  
Arctic Vegetation

scholarly journals The Evaluation of Real Time Milk Analyse Result Reliability in the Czech Republic

2016 ◽  
Vol 64 (4) ◽  
pp. 1155-1166 ◽  
Author(s):  
Oto Hanuš ◽  
Luděk Stádník ◽  
Marcela Klimešová ◽  
Martin Tomáška ◽  
Lucie Hasoňová ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Real Time ◽  
Near Infrared ◽  
Explanatory Power ◽  
Dairy Herd ◽  
Advanced Technology ◽  
Cell Counting ◽  
Measurement Unit ◽  
Real Time System ◽  
Herd Management

The good result reliability of regular analyzes of milk composition could improve the health monitoring of dairy cows and herd management. The aim of this study was the analysis of measurement of abilities and properties of RT (Real Time) system (AfiLab = AfiMilk (NIR measurement unit (near infrared spectroscopy) and electrical conductivity (C) of milk by conductometry) + AfiFarm (calibration and interpretation software)) for the analysis of individual milk samples (IMSs). There were 2 × 30 IMSs in the experiment. The reference values (RVs) of milk components and properties (fat (F), proteins (P), lactose (L), C and the somatic cell count (SCC)) were determined by conventional (direct and indirect: conductometry (C); infrared spectroscopy 1) with the filter technology and 2) with the Fourier transformations (F, P, L); fluoro-opto-electronic cell counting (SCC) in the film on the rotation disc (1) and by flow cytometry (2)) methods. AfiLab method (alternative) showed less close relationships as compared to the RVs as relationships between reference methods. This was expected. However, these relationships (r) were mostly significant: F from .597 to .738 (P ≤ 0.01 and ≤ 0.001); P from .284 to .787 (P > 0.05 and P ≤ 0.001); C .773 (P ≤ 0.001). Correlations (r) were not significant (P > 0.05): L from −.013 to .194; SCC from −.148 to −.133. Variability of the RVs explained the following percentages of variability in AfiLab results: F to 54.4 %; P to 61.9 %; L only 3.8 %; C to 59.7 %. Explanatory power (reliability) of AfiLab results to the animal is increasing with the regularity of their measurements (principle of real time application). Correlation values r (x minus 1.64 × sd for confidence interval (one-sided) at a level of 95 %) can be used for an alternative method in assessing the calibration quality. These limits are F 0.564, P 0.784 and C 0.715 and can be essential with the further implementation of this advanced technology of dairy herd management.

Development of a New Measurement Unit (MilkSpec-1) for Rapid Determination of Fat, Lactose, and Protein in Raw Milk Using Near-Infrared Transmittance Spectroscopy

2002 ◽  
Vol 56 (5) ◽  
pp. 599-604 ◽  
Author(s):  
Young-Ah Woo ◽  
Yoko Terazawa ◽  
Jie Yu Chen ◽  
Chie Iyo ◽  
Fuminori Terada ◽  
...  
Keyword(s):  
Near Infrared ◽  
Rapid Determination ◽  
Scatter Correction ◽  
Raw Milk ◽  
Milk Composition ◽  
Measurement Unit ◽  
Calibration Model ◽  
Transmittance Spectra ◽  
Infrared Transmittance

A new measurement unit, the MilkSpec-1, has been developed to determine rapidly and nondestructively the content of fat, lactose, and protein in raw milk using near-infrared transmittance spectroscopy. The spectral range over 700 to 1100 nm was used. This unit was designed for general glass test tubes, 12 mm in diameter and 10 mL in volume. Al2O3 with a thickness of 2.5 mm was found to be optimum as a reference for acquiring the milk spectrum for this measurement. The NIR transmittance spectra of milk were acquired from raw milk samples without homogenization. The calibration model was developed and predicted by using a partial least-squares (PLS) algorithm. In order to reduce the scattering effect due to fat globules and casein micelles in NIR transmittance spectra, multiplicative scatter correction (MSC) and/or second derivative treatment were performed. MSC treatment proved to be useful for the development of calibration models for fat and protein. This study resulted in low standard errors of prediction (SEP), with 0.06, 0.10, and 0.10% for fat, lactose, and protein, respectively. It is shown that accurate, rapid, and nondestructive determination of milk composition could be successfully performed by using the MilkSpec-1, presenting the potential use of this method for real-time on-line monitoring in a milking process.

scholarly journals Application of near infrared sensors to preconcentration of hydrothermally-formed copper ore

2016 ◽  
Vol 85 ◽  
pp. 148-167 ◽  
Author(s):  
Shekwonyadu Iyakwari ◽  
Hylke J. Glass ◽  
Gavyn K. Rollinson ◽  
Przemyslaw B. Kowalczuk
Keyword(s):  
Near Infrared ◽  
Infrared Sensors ◽  
Copper Ore

Performance Analysis in Object Diameter Estimation based on Single and Multiple Non-Destructive and Discrete Infrared Sensors

2014 ◽  
Vol 67 (1) ◽  
Author(s):  
Norashikin M. Thamrin ◽  
Norhashim Mohd. Arshad ◽  
Ramli Adnan ◽  
Rosidah Sam ◽  
Noorfazdli Abd. Razak ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
Pass Rate ◽  
Small Scale ◽  
Infrared Sensors ◽  
Scanning Method ◽  
Average Percentage ◽  
Multiple Sensors ◽  
Localization And Mapping ◽  
Aerial Vehicle

In Simultaneous Localization and Mapping (SLAM) technique, recognizing and marking the landmarks in the environment is very important. Therefore, in a commercial farm, rows of trees, borderline of rows as well as the trees and other features are mostly used by the researchers in realizing the automation process in this field. In this paper, the detection of the tree based on its diameter is focused. There are few techniques available in determining the size of the tree trunk inclusive of the laser scanning method as well as image-based measurements. However, those techniques require heavy computations and equipments which become constraints in a lightweight unmanned aerial vehicle implementation. Therefore, in this paper, the detection of an object by using a single and multiple infrared sensors on a non-stationary automated vehicle platform is discussed. The experiments were executed on different size of objects in order to investigate the effectiveness of this proposed method. This work is initially tested on the ground, based in the lab environment by using an omni directional vehicle which later will be adapted on a small-scale unmanned aerial vehicle implementation for tree diameter estimation in the agriculture farm.  In the current study, comparing multiple sensors with single sensor orientation showed that the average percentage of the pass rate in the pole recognition for the former is relatively more accurate than the latter with 93.2 percent and 74.2 percent, respectively. 

Sign in / Sign up

Export Citation Format

Share Document