<title>Subsurface radiowave tomography imaging in environmental monitoring applications</title>

To combine various sensors to get a system for specific use became popular within the last 10 years. Metric mid format cameras meanwhile reach the 100 MPix and entered the mapping market to compete with the big format sensors. Beside that also other sensors as SLR Cameras provide high resolution and enter the aerial surveying market for orthophoto production or monitoring applications. Flexibility, purchase-costs, size and weight are common aspects to design multi-sensor systems. Some sensors are useful for mapping while others are part of environmental monitoring systems. Beside classical surveying aircrafts also UL Airplanes, Para/Trikes or UAVs make use of multi sensor systems. Many of them are customer specific while other already are frequently used in the market. This paper aims to show some setup, their application, what are the results and what are the pros and cons of them are.

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Environmental Monitoring of Methane with Quartz-Enhanced Photoacoustic Spectroscopy Exploiting an Electronic Hygrometer to Compensate the H2O Influence on the Sensor Signal

Sensors ◽

10.3390/s20102935 ◽

2020 ◽

Vol 20 (10) ◽

pp. 2935 ◽

Cited By ~ 3

Author(s):

Arianna Elefante ◽

Giansergio Menduni ◽

Hubert Rossmadl ◽

Verena Mackowiak ◽

Marilena Giglio ◽

...

Keyword(s):

Water Vapor ◽

Environmental Monitoring ◽

Photoacoustic Spectroscopy ◽

Simultaneous Detection ◽

Vapor Concentration ◽

Interband Cascade Laser ◽

Qepas Signal ◽

Monitoring Applications ◽

Ch4 Concentration ◽

Qepas Sensor

A dual-gas sensor based on the combination of a quartz-enhanced photoacoustic spectroscopy (QEPAS) sensor and an electronic hygrometer was realized for the simultaneous detection of methane (CH4) and water vapor (H2O) in air. The QEPAS sensor employed an interband cascade laser operating at 3.34 μm capable of targeting a CH4 absorption line at 2988.8 cm−1 and a water line at 2988.6 cm−1. Water vapor was measured with both the electronic hygrometer and the QEPAS sensor for comparison. The measurement accuracy provided by the hygrometer enabled the adjustment of methane QEPAS signal with respect to the water vapor concentration to retrieve the actual CH4 concentration. The sensor was tested by performing prolonged measurements of CH4 and H2O over 60 h to demonstrate the effectiveness of this approach for environmental monitoring applications.

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FCM clustering and FLS based CH selection to enhance sustainability of wireless sensor networks for environmental monitoring applications

Journal of Ambient Intelligence and Humanized Computing ◽

10.1007/s12652-020-02159-9 ◽

2020 ◽

Author(s):

Anagha Rajput ◽

Vinoth Babu Kumaravelu

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Environmental Monitoring ◽

Wireless Sensor ◽

Monitoring Applications ◽

Fcm Clustering ◽

Ch Selection

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Environmental Monitoring Based on the Wireless Sensor Networking Technology

International Journal of Agricultural and Environmental Information Systems ◽

10.4018/ijaeis.2014100101 ◽

2014 ◽

Vol 5 (4) ◽

pp. 1-39 ◽

Cited By ~ 4

Author(s):

Eirini Karapistoli ◽

Ioanna Mampentzidou ◽

Anastasios A. Economides

Keyword(s):

Environmental Monitoring ◽

Real Life ◽

Pollution Monitoring ◽

Wireless Sensor ◽

General View ◽

Monitoring Applications ◽

Sensor Networking ◽

Wireless Sensor Networking ◽

Networking Technology ◽

Critical Overview

This paper investigates real-life environmental monitoring applications based on Wireless Sensor Networks (WSNs). Wireless sensor networking is an emerging technology, which through the research in the labs and the real deployments has proved to be a significant and valuable tool for scientists in their effort to explore various environmental phenomena. During the last decades, this wireless networking technology has been adopted by many scientific fields in order to accurately and effectively monitor climate phenomena such as air pollution, destruction phenomena (i.e., landslides), etc. It has also been widely used in agriculture as well as in horticulture for field monitoring. This paper provides a critical overview of the basic components existing WSN deployments use. It also categorizes these deployments, 111 in total, into five different field categories, namely agricultural monitoring, environmental monitoring, air-water pollution monitoring, monitoring of destruction phenomena, as well as monitoring of livestock, and wild animal, in order to provide a general view of the technologies used, the conditions under which the deployments were conducted, and much more. Then, five easy-to-use guides are provided discussing basic considerations for deploying WSNs in each of these fields. These guides cover various issues, such as sensor node platforms, operating systems (OSs), topologies, installation and maintenance issues, and much more. In order to showcase the usefulness of consulting the resulted guides, this work considers representative application scenarios for each of these field deployments.

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Theoretical Modeling of Viscosity Monitoring with Vibrating Resonance Energy Transfer for Point-of-Care and Environmental Monitoring Applications

Micromachines ◽

10.3390/mi10010003 ◽

2018 ◽

Vol 10 (1) ◽

pp. 3 ◽

Cited By ~ 4

Author(s):

Gorkem Memisoglu ◽

Burhan Gulbahar ◽

Joseba Zubia ◽

Joel Villatoro

Keyword(s):

Energy Transfer ◽

Environmental Monitoring ◽

System Design ◽

Point Of Care ◽

Resonance Energy Transfer ◽

Microfluidic Channel ◽

Resonance Energy ◽

Polluted Water ◽

Hardware Complexity ◽

Monitoring Applications

Förster resonance energy transfer (FRET) between two molecules in nanoscale distances is utilized in significant number of applications including biological and chemical applications, monitoring cellular activities, sensors, wireless communications and recently in nanoscale microfluidic radar design denoted by the vibrating FRET (VFRET) exploiting hybrid resonating graphene membrane and FRET design. In this article, a low hardware complexity and novel microfluidic viscosity monitoring system architecture is presented by exploiting VFRET in a novel microfluidic system design. The donor molecules in a microfluidic channel are acoustically vibrated resulting in VFRET in the case of nearby acceptor molecules detected with their periodic optical emission signals. VFRET does not require complicated hardware by directly utilizing molecular interactions detected with the conventional photodetectors. The proposed viscosity measurement system design is theoretically modeled and numerically simulated while the experimental challenges are discussed. It promises point-of-care and environmental monitoring applications including viscosity characterization of blood or polluted water.

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Adaptive WSN Scheduling for Lifetime Extension in Environmental Monitoring Applications

International Journal of Distributed Sensor Networks ◽

10.1155/2012/286981 ◽

2011 ◽

Vol 8 (1) ◽

pp. 286981 ◽

Cited By ~ 4

Author(s):

Jong Chern Lim ◽

Chris Bleakley

Keyword(s):

Environmental Monitoring ◽

Network Lifetime ◽

Data Gathering ◽

Temporal Correlation ◽

Research Problem ◽

Monitoring Applications ◽

Efficient Sampling ◽

Real World Datasets ◽

Application Specific ◽

Sampling Schedule

Wireless sensor networks (WSNs) are often used for environmental monitoring applications in which nodes periodically measure environmental conditions and immediately send the measurements back to the sink for processing. Since WSN nodes are typically battery powered, network lifetime is a major concern. A key research problem is how to determine the data gathering schedule that will maximize network lifetime while meeting the user's application-specific accuracy requirements. In this work, a novel algorithm for determining efficient sampling schedules for data gathering WSNs is proposed. The algorithm differs from previous work in that it dynamically adapts the sampling schedule based on the observed internode data correlation as well as the temporal correlation. The performance of the algorithm has been assessed using real-world datasets. For two-tier networks, the proposed algorithm outperforms a highly cited previously published algorithm by up to 512% in terms of lifetime and by up to 30% in terms of prediction accuracy. For multihop networks, the proposed algorithm improves on the previously published algorithm by up to 553% and 38% in terms of lifetime and accuracy, respectively.

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