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| submission-date = 2018-10-09
 
| submission-date = 2018-10-09
 
| type = Report
 
| type = Report
| url = https://mediawiki.envri.eu/images/0/05/D1.1._Roadmap_for_the_emergence_of_European_industry_providers_and_market_landscape_analysis.pdf
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| pdf =
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| zenodo =
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| url = http://www.envriplus.eu/wp-content/uploads/2018/10/D1.1-Emerging-technologies-emerging-markets-fostering-the-innovation-potential-of-research-infrastructures.pdf
 
}}
 
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The aim of WP1-task 1.1, is to identify and analyse emerging environmental observations technologies (sensors and platforms) that could be useful to, and benefit from, Research infrastructures (RIs) to realize and achieve their market potential. The task also aims to explore technical challenges, market barriers and ongoing initiatives related to these technologies. The deliverable D1.1 is tailored to be a source of inspiration for Small and Medium Enterprises (SMEs), while investigating new business opportunities, as well as for the EU bodies, pointing them the specific areas requiring additional attention and financing.
 
The aim of WP1-task 1.1, is to identify and analyse emerging environmental observations technologies (sensors and platforms) that could be useful to, and benefit from, Research infrastructures (RIs) to realize and achieve their market potential. The task also aims to explore technical challenges, market barriers and ongoing initiatives related to these technologies. The deliverable D1.1 is tailored to be a source of inspiration for Small and Medium Enterprises (SMEs), while investigating new business opportunities, as well as for the EU bodies, pointing them the specific areas requiring additional attention and financing.
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Monitoring environmental parameters and climate change is a complex task which answers grand challenges. It is of crucial importance (Bell and Joseph 2018) for all countries and societies. Development of technologies for such monitoring is in huge demand and driven by numerous factors (fig.1). Among them are demand for the high quality of measurements and development of new types of measurements, reduction of measurements costs, necessity to control the pollution and avoiding the legislative responsibility for the contamination of the environment. Besides, there is a large societal demand based on the ongoing decrease of air, soil and water quality. Environmental monitoring is a complicated activity, because technical requirements for the innovative measurement platforms, systems and sensors can vary significantly across regions and domains. Such variations certainly create unwanted difficulties for the technology producers, especially small and medium enterprises (SMEs), due to their generally limited resources. European businesses are limited in their development in this field due to the inability to overcome the technological differences, to overview the possible paths for development of corresponding markets and to establish the contacts in-between research communities, technology producers and other supporting businesses. This deliverable of ENVRIplus<ref>https://www.envriplus.eu/</ref> project serves to overpass mentioned difficulties of environmental measurements in Europe. It is aimed to help SMEs, scientific communities and other interested partners to establish fruitful, beneficial collaborations and to understand the possible vectors of development of European environmental measurements and monitoring.  
 
Monitoring environmental parameters and climate change is a complex task which answers grand challenges. It is of crucial importance (Bell and Joseph 2018) for all countries and societies. Development of technologies for such monitoring is in huge demand and driven by numerous factors (fig.1). Among them are demand for the high quality of measurements and development of new types of measurements, reduction of measurements costs, necessity to control the pollution and avoiding the legislative responsibility for the contamination of the environment. Besides, there is a large societal demand based on the ongoing decrease of air, soil and water quality. Environmental monitoring is a complicated activity, because technical requirements for the innovative measurement platforms, systems and sensors can vary significantly across regions and domains. Such variations certainly create unwanted difficulties for the technology producers, especially small and medium enterprises (SMEs), due to their generally limited resources. European businesses are limited in their development in this field due to the inability to overcome the technological differences, to overview the possible paths for development of corresponding markets and to establish the contacts in-between research communities, technology producers and other supporting businesses. This deliverable of ENVRIplus<ref>https://www.envriplus.eu/</ref> project serves to overpass mentioned difficulties of environmental measurements in Europe. It is aimed to help SMEs, scientific communities and other interested partners to establish fruitful, beneficial collaborations and to understand the possible vectors of development of European environmental measurements and monitoring.  
  
<div class="figure" id="figure1">[[File:ENVRIplus D1.1-Fig. 1-Factors influencing the development of technology.png|center|frame|Figure 1: Factors influencing the development of technology]]</div>
+
FIGURE 1 FACTORS INFLUENCING THE DEVELOPMENT OF TECHNOLOGY
  
 
==1.3 Approach of this work: methodology==
 
==1.3 Approach of this work: methodology==
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This technique is employed to measure exchanges between the surface (i.e.: ecosystem, including vegetation and soil) and the atmosphere.
 
This technique is employed to measure exchanges between the surface (i.e.: ecosystem, including vegetation and soil) and the atmosphere.
  
<div class="figure" id="figure2">[[File:ENVRIplus D1.1-Fig. 2-Eddy covariance technique on-site.png|center|frame|Figure 2: Eddy co-variance technique on-site]]</div>
+
FIGURE 2 EDDY-COVARIANCE TECHNIQUE ON-SITE
  
 
It can be used, for example, to measure how much a given surface is either a sink or a source for a greenhouse gas such as CO2 or any other species that can be sampled with a sufficiently fast time response. The technique is based on fast (10 Hz or more) measurements of both three dimensional wind velocity (atmospheric turbulence, usually done through an ultrasonic anemometer) and atmospheric concentration of the chemical species of interests (generally CO2, CH4 and N2O in addition to energy). These two measurements can be related together following a specific mathematical approach to yield a flux with a high temporal resolution and integrated at ecosystem scale (1 km2).  
 
It can be used, for example, to measure how much a given surface is either a sink or a source for a greenhouse gas such as CO2 or any other species that can be sampled with a sufficiently fast time response. The technique is based on fast (10 Hz or more) measurements of both three dimensional wind velocity (atmospheric turbulence, usually done through an ultrasonic anemometer) and atmospheric concentration of the chemical species of interests (generally CO2, CH4 and N2O in addition to energy). These two measurements can be related together following a specific mathematical approach to yield a flux with a high temporal resolution and integrated at ecosystem scale (1 km2).  
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Optical sensors operate based on the principle of fluorescence quenching (Tengberg et al. 2006). Nowadays, the Aanderaa optodes 3835 & 4330 are the most used sensors implemented in ARGO floats, gliders and on moorings. Oxygen optodes are based on the oxygen luminescence quenching of a platinum porphyrin complex (fluorescent indicator) that is immobilized in a sensing foil. Optodes show a nonlinear decrease in luminescence decay time with increasing oxygen concentration. The signal can be linearized by means of the Stern–Volmer equation: [O2] = (τ0/τ – 1)/Ksv, where [O2] is oxygen concentration in μmol/L, τ is luminescence decay time, τ0 is the decay time in the absence of [O2], and Ksv is the Stern– Volmer constant (Demas et al. 1999). The advantages of the optical sensors are their excellent long-term stability and high precision. They also appear to be accurate provided they have sufficient time to come into equilibrium with the surrounding temperature and oxygen concentration and provided that their temperature response has been carefully calibrated (possibly by individual sensor factory-calibration plus in-situ calibration check/correction based on concomitant Winkler profile).
 
Optical sensors operate based on the principle of fluorescence quenching (Tengberg et al. 2006). Nowadays, the Aanderaa optodes 3835 & 4330 are the most used sensors implemented in ARGO floats, gliders and on moorings. Oxygen optodes are based on the oxygen luminescence quenching of a platinum porphyrin complex (fluorescent indicator) that is immobilized in a sensing foil. Optodes show a nonlinear decrease in luminescence decay time with increasing oxygen concentration. The signal can be linearized by means of the Stern–Volmer equation: [O2] = (τ0/τ – 1)/Ksv, where [O2] is oxygen concentration in μmol/L, τ is luminescence decay time, τ0 is the decay time in the absence of [O2], and Ksv is the Stern– Volmer constant (Demas et al. 1999). The advantages of the optical sensors are their excellent long-term stability and high precision. They also appear to be accurate provided they have sufficient time to come into equilibrium with the surrounding temperature and oxygen concentration and provided that their temperature response has been carefully calibrated (possibly by individual sensor factory-calibration plus in-situ calibration check/correction based on concomitant Winkler profile).
  
=====4.2.3.2.1 The Aanderaa optode sensors 3830-3835=====
+
=====4.2.3.2.1 TheAanderaaoptodesensors3830-3835=====
  
 
This sensors have a measuring range of 0-500 μM, a resolution of 1 μM and an accuracy of 5 μM as well as an operating depth of up to 6000 m. Due to their small size and power requirements, the first generation of optode sensors (3830/3835) have been also tested on profiling floats (Kortzinger et al. 2005). The first results obtained in 2004 demonstrated that high quality long-term oxygen measurements from ARGO floats are feasible.
 
This sensors have a measuring range of 0-500 μM, a resolution of 1 μM and an accuracy of 5 μM as well as an operating depth of up to 6000 m. Due to their small size and power requirements, the first generation of optode sensors (3830/3835) have been also tested on profiling floats (Kortzinger et al. 2005). The first results obtained in 2004 demonstrated that high quality long-term oxygen measurements from ARGO floats are feasible.
  
<div class="figure" id="figure3">[[File:ENVRIplus D1.1-Fig. 3-The Aanderaa optode sensor on a provor float.png|center|frame|Figure 3: The Aanderaa optode sensor on a provor float]]</div>
+
FIGURE 3 THE AANDERAA OPTODE SENSOR ON A PROVOR FLOAT
  
 
=====4.2.3.2.2 The SBE 63 sensor=====
 
=====4.2.3.2.2 The SBE 63 sensor=====
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Several companies sell in situ fluorometer systems that come with biofouling protection. There are also FRRF systems that can be fitted to observatories and autonomous systems. In the past five years there have been many long term deployments of fluorimeter systems that have provided useful and sensible data despite potential biofouling or other calibration issues. Like for the most other sensors, pre- and post- deployment in situ calibration measurements is the best way to correct the drift. Moreover, if the intent is to convert the fluorescence values to chlorophyll-A or other specific values, it is advised to collect size fractionated algal pigment samples for calibration purposes. Wet Labs ECO Triplet, or TriOS microFlu, nanoFlu, matrixFlu VIS; TurnerDesigns Cyclops and Chelsea AquaTracka III are examples of widely used systems.  
 
Several companies sell in situ fluorometer systems that come with biofouling protection. There are also FRRF systems that can be fitted to observatories and autonomous systems. In the past five years there have been many long term deployments of fluorimeter systems that have provided useful and sensible data despite potential biofouling or other calibration issues. Like for the most other sensors, pre- and post- deployment in situ calibration measurements is the best way to correct the drift. Moreover, if the intent is to convert the fluorescence values to chlorophyll-A or other specific values, it is advised to collect size fractionated algal pigment samples for calibration purposes. Wet Labs ECO Triplet, or TriOS microFlu, nanoFlu, matrixFlu VIS; TurnerDesigns Cyclops and Chelsea AquaTracka III are examples of widely used systems.  
  
<div class="figure" id="figure4">[[File:ENVRIplus D1.1-Fig. 4-TRIOS fluorometers equipped with Ifremer antifouling devices.png|center|frame|TRIOS fluorometers equipped with Ifremer antifouling devices]]</div>
+
FIGURE 4 TRIOS FLUOROMETERS EQUIPPED WITH IFREMER ANTIFOULING DEVICES
 
 
<div class="tablecaption" id="table53">TABLE 53 CORE SPECIFICATIONS FOR MEASURING FLUORESCENCE</div>
 
{| class="wikitable"
 
|+ FLUORESCENCE / Chlorophyll-Α
 
|-
 
! scope="row" | Measurement Range
 
| 0 - 125
 
| μg/l
 
|-
 
! scope="row" | Sensitivity
 
| 0,02
 
| μg/l
 
|}
 
  
 +
TABLE 53 CORE SPECIFICATIONS FOR MEASURING FLUORESCENCE
 +
 
===4.2.9 Underwater sound===
 
===4.2.9 Underwater sound===
  
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Devices called hydrophones are widely used to track the underwater sounds. Hydrophones convert sound in water into electrical signals that can be amplified, recorded, played back over loudspeakers, and used to measure the characteristics of the sound. Most hydrophones are made from a piezoelectric material. Under the pressure of a sound wave, the piezoelectric element flexes and produces electrical signals. Some hydrophones, called omnidirectional hydrophones, record sounds from all directions with equal sensitivity. Other hydrophones, called directional hydrophones, have a higher sensitivity to signals from a particular direction. Directional receivers are most often constructed using a number of omnidirectional hydrophones combined in an array. Directional hydrophones are typically used in systems constructed for locating and tracking objects. Hydrophones are specially designed for underwater use. They are normally encased in rubber or polyurethane to provide protection from seawater. They can be mounted in several different ways, such as attached to a boat, towed, or placed in a fixed position underwater.
 
Devices called hydrophones are widely used to track the underwater sounds. Hydrophones convert sound in water into electrical signals that can be amplified, recorded, played back over loudspeakers, and used to measure the characteristics of the sound. Most hydrophones are made from a piezoelectric material. Under the pressure of a sound wave, the piezoelectric element flexes and produces electrical signals. Some hydrophones, called omnidirectional hydrophones, record sounds from all directions with equal sensitivity. Other hydrophones, called directional hydrophones, have a higher sensitivity to signals from a particular direction. Directional receivers are most often constructed using a number of omnidirectional hydrophones combined in an array. Directional hydrophones are typically used in systems constructed for locating and tracking objects. Hydrophones are specially designed for underwater use. They are normally encased in rubber or polyurethane to provide protection from seawater. They can be mounted in several different ways, such as attached to a boat, towed, or placed in a fixed position underwater.
  
<div class="tablecaption" id="table54">TABLE 54 CORE SPECIFICATIONS FOR MEASURING PASSIVE ACOUSTICS (GEOLOGY SPECIFIC)</div>
+
TABLE 54 CORE SPECIFICATIONS FOR MEASURING PASSIVE ACOUSTICS (GEOLOGY SPECIFIC)
{| class="wikitable"
 
|+ PASSIVE ACOUSTICS (Geology specific)
 
|-
 
! scope="row" | Measurement Range
 
| 0,1 – 100
 
| Hz
 
|-
 
! scope="row" | Accuracy
 
| 1
 
| V/μPa
 
|-
 
! scope="row" | Sensitivity
 
| -190
 
| dB (re 1V/μPa)
 
|}
 
  
 
+
TABLE 55 CORE SPECIFICATIONS FOR MEASURING PASSIVE ACOUSTICS (OCEAN CIRCULATION
<div class="tablecaption" id="table55">TABLE 55 CORE SPECIFICATIONS FOR MEASURING PASSIVE ACOUSTICS (OCEAN CIRCULATION SPECIFIC)</div>
 
{| class="wikitable"
 
|+ PASSIVE ACOUSTICS (Ocean circulation specific)
 
|-
 
! scope="row" | Measurement Range
 
| 20 – 200.000
 
| Hz
 
|-
 
! scope="row" | Accuracy
 
| 1
 
| V/μPa
 
|-
 
! scope="row" | Sensitivity
 
| -190
 
| dB (re 1V/μPa)
 
|}
 
  
 
====4.2.10 Imagery of microorganisms and habitat====
 
====4.2.10 Imagery of microorganisms and habitat====
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The analysis of underwater imagery imposes a series of unique challenges, which need to be tackled by the IT community in collaboration with biologists and ocean scientists. Among the challenges are image enhancement, scene understanding, classification, detection, segmentation; detection and monitoring of marine life, form tracking, automatic video annotation and summarization, context-aware machine learning and image understanding, image compression.
 
The analysis of underwater imagery imposes a series of unique challenges, which need to be tackled by the IT community in collaboration with biologists and ocean scientists. Among the challenges are image enhancement, scene understanding, classification, detection, segmentation; detection and monitoring of marine life, form tracking, automatic video annotation and summarization, context-aware machine learning and image understanding, image compression.
 
+
 
<div class="tablecaption" id="table56">TABLE 56 CORE SPECIFICATIONS OF EMSO FOR RECORDING HD VIDEO AND STILL IMAGES</div>
+
TABLE 56 CORE SPECIFICATIONS OF EMSO FOR RECORDING HD VIDEO AND STILL IMAGES
{| class="wikitable"
+
 
|+ High Definition video and Still imaging Specifications
+
====4.2.10.1 The Imaging FlowCytoBot (IFCB) (McLane Research Laboratories)====
|-
 
! scope="row" | Resolution
 
| 4240×2824
 
| pixels
 
|-
 
! scope="row" | Minimum video capture speed
 
| 7
 
| Frames per second
 
|-
 
! scope="row" | Sensitivity
 
| Minimum 46%
 
| QE
 
|-
 
! scope="row" | Sensor type
 
| CCD + CMOS
 
|
 
|-
 
! scope="row" | Sensor size
 
| 1
 
| inches
 
|-
 
! scope="row" | Output protocol
 
| TCP/IP, USB3
 
|
 
|-
 
! scope="row" | Sensitivity to IR light
 
| 850 -900
 
| Nano metres
 
|}
 
 
 
====4.2.10.1 The Imaging FlowCytoBot (IFCB) (McLane Research Laboratories)====
 
  
 
IFCB is an in-situ automated submersible imaging flow cytometer that generates high resolution (1380x1034 pixels) images of suspended particles in-flow, in the size range <10 to 150 μm (such as diatoms and dinoflagellates). The instrument continuously samples at a rate of 15 ml seawater per hour, and, depending on the target population, can generate up to 30,000 high resolution images per hour. IFCB uses a combination of flow cytometry and video technology. Laser-induced fluorescence and light scattering from individual particles are measured and used to trigger targeted image acquisition. The optical and image data is then transmitted to the computer in real time, through an Ethernet link. Collected images are continuously monitored and processed externally by the specific automated image classification software. For each imaged particle, approximately 200 different parameters are extracted. Images can be automatically classified to the genus or even species level with demonstrated accuracy comparable to that of human experts (Olson and Sosik 2007).
 
IFCB is an in-situ automated submersible imaging flow cytometer that generates high resolution (1380x1034 pixels) images of suspended particles in-flow, in the size range <10 to 150 μm (such as diatoms and dinoflagellates). The instrument continuously samples at a rate of 15 ml seawater per hour, and, depending on the target population, can generate up to 30,000 high resolution images per hour. IFCB uses a combination of flow cytometry and video technology. Laser-induced fluorescence and light scattering from individual particles are measured and used to trigger targeted image acquisition. The optical and image data is then transmitted to the computer in real time, through an Ethernet link. Collected images are continuously monitored and processed externally by the specific automated image classification software. For each imaged particle, approximately 200 different parameters are extracted. Images can be automatically classified to the genus or even species level with demonstrated accuracy comparable to that of human experts (Olson and Sosik 2007).
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====4.2.10.3 The FastCAM prototype (IFREMER - LDCM)====
 
====4.2.10.3 The FastCAM prototype (IFREMER - LDCM)====
  
This system is based on a high resolution (2 Megapixels) and high speed camera allowing the acquisition of 340 frames per second. It digitizes 10 mL of sample with a 10 times magnification within only 15 min (which is not possible with the first generation of FlowCAM devices). Comparison of grayscale images with those obtained with the first generation of FlowCAM showed that this new system analyses samples much faster and provides high image quality. A LED, driven by a control box emits light pulses of 5 μs duration. Light is injected into a large core diameter (1 mm) optical fiber to homogenize the beam. Upon the exit from the optical fiber, light illuminates the flow cell. A 10X magnification microscope objective associated with a tube lens images the organisms that circulate in the flow cell. The frame grabbing is synchronized with the LED light emission. A pixel of the image corresponds to 0.5 μm. The images are saved on the PC in real time thanks to a fast hard drive. For the image acquisition, a specific software is developed in Visual Basic 12. A second software developed in C language is used for image processing. Thanks to the «Matrox MIL 10» library, nearly 50 parameters are computed based on each image. These parameters then are used to classify images by applying existing classification tools, like «Plankton Identifier» (Delphi and Tanagra environments) or «ZooImage» (R environment)
+
This system is based on a high resolution (2 Megapixels) and high speed camera allowing the acquisition of 340 frames per second. It digitizes 10 mL of sample with a 10 times magnification within only 15 min (which is not possible with the first generation of FlowCAM devices). Comparison of grayscale images with those obtained with the first generation of FlowCAM showed that this new system analyses samples much faster and provides high image quality. A LED, driven by a control box emits light pulses of 5 μs duration. Light is injected into a large core diameter (1 mm) optical fiber to homogenize the beam. Upon the exit from the optical fiber, light illuminates the flow cell. A 10X magnification microscope objective associated with a tube lens images the organisms that circulate in the flow cell. The frame grabbing is synchronized with the LED light emission. A pixel of the image corresponds to 0.5 μm. The images are saved on the PC in real time thanks to a fast hard drive. For the image acquisition, a specific software is developed in Visual Basic 12. A second software developed in C language is used for image processing. Thanks to the «Matrox MIL 10» library, nearly 50 parameters are computed based on each image. These parameters then are used to classify images by applying existing classification tools, like «Plankton Identifier» (Delphi and Tanagra environments) or «ZooImage» (R environment)
  
 
====4.2.10.4 Underwater Vision Profiler UVP5 (Hydroptic)====
 
====4.2.10.4 Underwater Vision Profiler UVP5 (Hydroptic)====
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Oceans environmental monitoring and seafloor exploitation needs in situ sensors and optical devices (cameras, lights) in various locations and on various carriers in order to initiate and to calibrate environmental models or to perform the supervision of underwater industrial processes. To be economically operational, these systems must be equipped with a biofouling protection of sensors and optical devices used in situ. Indeed, biofouling can modify the transducing interfaces of the sensors and cause unacceptable bias on the measurements performed by the in situ monitoring system in less than 15 days. In the same way biofouling can decrease the optical properties of windows and thus alter the lighting and the quality of the images recorded by the cameras.
 
Oceans environmental monitoring and seafloor exploitation needs in situ sensors and optical devices (cameras, lights) in various locations and on various carriers in order to initiate and to calibrate environmental models or to perform the supervision of underwater industrial processes. To be economically operational, these systems must be equipped with a biofouling protection of sensors and optical devices used in situ. Indeed, biofouling can modify the transducing interfaces of the sensors and cause unacceptable bias on the measurements performed by the in situ monitoring system in less than 15 days. In the same way biofouling can decrease the optical properties of windows and thus alter the lighting and the quality of the images recorded by the cameras.
  
<div class="figure" id="figure5">[[File:ENVRIplus D1.1-Fig. 5-Fouling on the sensors is the main constrains for in situ ocean autonomous measurements.png|center|frame|Figure 5: Fouling on the sensors is the main constraint for in situ ocean autonomous measurements]]</div>
+
FIGURE 5 FOULING ON THE SENSORS IS THE MAIN CONSTRAINT FOR IN SITU OCEAN AUTONOMOUS MEASUREMENTS
  
 
It is acknowledged that a coastal monitoring system must be able to run without maintenance for 3 months in order for the system to be economically acceptable. For deep-sea observatories, actual maintenance interval for the Canadian Venus system is 6 months. ESONET, the European network of excellence for deep-sea observatories defines maintenance interval recommendation from 12 up to 36 months.
 
It is acknowledged that a coastal monitoring system must be able to run without maintenance for 3 months in order for the system to be economically acceptable. For deep-sea observatories, actual maintenance interval for the Canadian Venus system is 6 months. ESONET, the European network of excellence for deep-sea observatories defines maintenance interval recommendation from 12 up to 36 months.
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Platform innovation is one of the drivers of increasing capabilities of marine systems. It is a structuring point for the constitution of several RIs (EUROARGO - profiling floats, GROOM - gliders, EMSO - sea floor + water column fixed point observatories, EuroFLEETS - oceanographic vessels). Each RI needs to mobilize the providers to cope with its own specifications and at the same time to benefit from inter RI cooperation. In this respect, manufacturers of sensors have to adapt to niche markets with high commercial/manufacturing cost ratio. That is why there is a market tendency for the instruments to include several sensors (multiprobe instruments since the 90s, EMSO Generic Instrumentation Module in 2017 EGIM).
 
Platform innovation is one of the drivers of increasing capabilities of marine systems. It is a structuring point for the constitution of several RIs (EUROARGO - profiling floats, GROOM - gliders, EMSO - sea floor + water column fixed point observatories, EuroFLEETS - oceanographic vessels). Each RI needs to mobilize the providers to cope with its own specifications and at the same time to benefit from inter RI cooperation. In this respect, manufacturers of sensors have to adapt to niche markets with high commercial/manufacturing cost ratio. That is why there is a market tendency for the instruments to include several sensors (multiprobe instruments since the 90s, EMSO Generic Instrumentation Module in 2017 EGIM).
  
<div class="figure" id="figure6">[[File:ENVRIplus D1.1-Fig. 6-Multiparameter system for sea measurements.png|center|frame|Multiparameter system for sea measurements]]</div>
+
FIGURE 6 MULTIPARAMETER SYSTEM FOR SEA MEASUREMENTS
  
 
AUVs and Gliders (marine drones) use the aircraft concept of “pay load” to offer an interface to any sensor of the client. Research Infrastructures need a careful metrology approach (WP2 ENVRIPLUS) and an easy plug and play sensor interface policy (see WP1 Task 4 in ENVRIPLUS) to deal with this industrial structuration.
 
AUVs and Gliders (marine drones) use the aircraft concept of “pay load” to offer an interface to any sensor of the client. Research Infrastructures need a careful metrology approach (WP2 ENVRIPLUS) and an easy plug and play sensor interface policy (see WP1 Task 4 in ENVRIPLUS) to deal with this industrial structuration.
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The energy constraint and the volume of data are limitations for long time monitoring. These limitations are addressed by implementing duty cycles, data compression and tentative in-situ data treatment. The Research Infrastructures such as JERICO, GROOM and EMSO are leading actors in implementing new generations of hydrophones and hydrophone interfaces to monitor both noise and marine mammal sounds.
 
The energy constraint and the volume of data are limitations for long time monitoring. These limitations are addressed by implementing duty cycles, data compression and tentative in-situ data treatment. The Research Infrastructures such as JERICO, GROOM and EMSO are leading actors in implementing new generations of hydrophones and hydrophone interfaces to monitor both noise and marine mammal sounds.
  
<div class="tablecaption" id="table57">TABLE 57 PROPOSED HYDROPHONE REQUIREMENTS FOR NOISE AND BIOACOUSTICS IN THE OPEN-OCEAN – FOR FIXO3/EMSO – ERIC DELORY – PLOCAN</div>
+
TABLE 57 PROPOSED HYDROPHONE REQUIREMENTS FOR NOISE AND BIOACOUSTICS IN THE OPEN-OCEAN – FOR FIXO3/EMSO – ERIC DELORY – PLOCAN
{| class="wikitable"
 
! scope="col" | Resolution
 
! scope="col" | Dynamic Range (DR)
 
! scope="col" | Directivity
 
! scope="col" | Accuracy
 
! scope="col" | Sampling frequency
 
! scope="col" | Special requirements
 
! scope="col" | Other1
 
! scope="col" | Other2
 
|-
 
| 16 to 24 bits, with different gains to fit DR
 
| <SS0; 50 to 180dB re 1μPa
 
| Omni-Directional
 
| +/-3dB
 
| 100kSps
 
|  Embedded noise and bioacoustics statistics
 
| Store on detection, Solidstate storage
 
| Low power for standalone systems<br />*ESONET Label
 
|}
 
  
 
====4.4.2.2 Active acoustics====
 
====4.4.2.2 Active acoustics====
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UAVs play an important role in gas sensing, especially in the remote areas or areas with limited accessibility. For example, drones are widely used to perform measurements of volcanic gases. Thus, McGonigle et al. (2008) carried out measurements of volcanic gases at la Fossa volcano crater in Italy. They used the UAV helicopter capable of 12 minutes flight time and equipped with the ultraviolet and infrared spectrometers for SO2 and CO2 measurements. Khan et al. 2012 developed a greenhouse gas analyser for the installation on the helicopter UAV, using a vertical cavity surface emitting laser (VCSEL) for these purposes. Watai et al. (2005) mounted NDIR sensing system on UAV to monitor atmospheric CO2. Authors designed economic and accurate gas sensor and performed several flight tests with the payload of 3.5 kg and operation time of no longer than 1 hour. While WSNs are usually equipped with MOX sensors as was discussed above, UAV mostly apply optical sensing devices. Malaver, Motta et al. (2015) performed analysis of applications of both MOX and optical devices to integrate both sensing technologies at both platforms and reduce the costs. The table presented in this study is shown below.
 
UAVs play an important role in gas sensing, especially in the remote areas or areas with limited accessibility. For example, drones are widely used to perform measurements of volcanic gases. Thus, McGonigle et al. (2008) carried out measurements of volcanic gases at la Fossa volcano crater in Italy. They used the UAV helicopter capable of 12 minutes flight time and equipped with the ultraviolet and infrared spectrometers for SO2 and CO2 measurements. Khan et al. 2012 developed a greenhouse gas analyser for the installation on the helicopter UAV, using a vertical cavity surface emitting laser (VCSEL) for these purposes. Watai et al. (2005) mounted NDIR sensing system on UAV to monitor atmospheric CO2. Authors designed economic and accurate gas sensor and performed several flight tests with the payload of 3.5 kg and operation time of no longer than 1 hour. While WSNs are usually equipped with MOX sensors as was discussed above, UAV mostly apply optical sensing devices. Malaver, Motta et al. (2015) performed analysis of applications of both MOX and optical devices to integrate both sensing technologies at both platforms and reduce the costs. The table presented in this study is shown below.
  
<div class="tablecaption" id="table58">TABLE 58 ADVANTAGES AND DISADVANTAGES OF MOX AND OPTICAL SENSORS FOR GHG MEASUREMENTS ACCORDING TO MALAVER, MOTTA ET AL. (2015)</div>
+
TABLE 58 ADVANTAGES AND DISADVANTAGES OF MOX AND OPTICAL SENSORS FOR GHG MEASUREMENTS ACCORDING TO MALAVER, MOTTA ET AL. (2015)
{| class="wikitable"
 
! rowspan="2" scope="col" | Category
 
! colspan="2" scope="col" | MOX sensors
 
! colspan="2" scope="col" | Optical Sensing Techniques
 
|-
 
| ''Advantages''
 
| ''Disadvantages''
 
| ''Advantages''
 
| ''Disadvantages''
 
|-
 
! scope="row" | Aerial missions
 
| Low energy consumption and light weight
 
| Slow sensor response hinder aerial applications
 
| Tested and proved
 
| Energy consumption and weight may limit flight endurance
 
|-
 
! scope="row" | Ground missions
 
| Tested and proved
 
| Cross reference to different gases and sensitive to humidity
 
| High sampling frequency, high specificity to target gas
 
| No data/sensor is too expensive to be left unattended
 
|-
 
! scope="row" | Continuous release mission
 
| Low energy consumption and light weight, covers wide range of gasses
 
| No data
 
|  High sampling frequency, high specificity to target gas
 
| Energy consumption and weight may limit flight endurance
 
|-
 
! scope="row" | Instantaneous release
 
| Low energy consumption and light weight, covers wide range of gasses
 
| Low sensor response time
 
| High sampling frequency, high specificity to target gas
 
| Energy consumption and weight may limit flight endurance
 
|-
 
! scope="row" | Computational resources
 
| Few output variables. Some variables remain over large range of gases
 
| No data
 
|  No data
 
|  The number of output variables to measure depends on the optical technique and target gas
 
|-
 
! scope="row" | Resolution
 
| Regular resistive sensors achieve ppm gases
 
| Few sensors achieve ppb resolution
 
| Several techniques achieve ppm and ppb resolution
 
|  No data
 
|-
 
! scope="row" | Cost position in market cost
 
| Low
 
| None
 
| Low for NDIR modules
 
| Medium too high for complex systems
 
|}
 
  
 
UAVs or drones are relatively new measurement platforms that have been used in most of the countries with strong climate research programs. Their great advantage is that they can be used in the conditions where presence of human is not desirable or not possible. These platforms are represented by the machines of diverse constructions and capabilities. Based on the ability to perform the measurements, UAV can be divided into following groups:
 
UAVs or drones are relatively new measurement platforms that have been used in most of the countries with strong climate research programs. Their great advantage is that they can be used in the conditions where presence of human is not desirable or not possible. These platforms are represented by the machines of diverse constructions and capabilities. Based on the ability to perform the measurements, UAV can be divided into following groups:
Line 1,686: Line 1,544:
 
The weight of drones can vary from 500 g to nearly 15 tons, while the time of autonomous activity varies from several minutes to several days. The price of drones may vary from several hundred euro (dollars) to several millions in case large autonomous machines are utilized. Integration of instrumentation on this platform also appears as non-trivial task, because the instruments shall be light and well balanced on the platform. They also shall have the possibility for wireless communication (GPS, IRIDIUM, GLONASS) and data transfer. Environmental parameters that can be measured by means of UAVs include temperature, pressure, humidity and wind parameters. Drones can also be equipped with visible and IR cameras, laser altimetry and multispectral imagery. In the future, various gas and aerosol analysers will be developed for the installation on this platform. The potential of drones includes measurements in remote locations, routine long-term measurements, measurement campaigns and validation of information obtained from satellites.  
 
The weight of drones can vary from 500 g to nearly 15 tons, while the time of autonomous activity varies from several minutes to several days. The price of drones may vary from several hundred euro (dollars) to several millions in case large autonomous machines are utilized. Integration of instrumentation on this platform also appears as non-trivial task, because the instruments shall be light and well balanced on the platform. They also shall have the possibility for wireless communication (GPS, IRIDIUM, GLONASS) and data transfer. Environmental parameters that can be measured by means of UAVs include temperature, pressure, humidity and wind parameters. Drones can also be equipped with visible and IR cameras, laser altimetry and multispectral imagery. In the future, various gas and aerosol analysers will be developed for the installation on this platform. The potential of drones includes measurements in remote locations, routine long-term measurements, measurement campaigns and validation of information obtained from satellites.  
 
Most of UAV systems find their application in the projects of the economically developed countries. However, these countries are not responsible for global pollution in the same extent as many developing countries, where people lack to take care of the environment due to the constant fight for their wellbeing. In these countries, the health of population is often under strike due to decreasing quality of water and air resources. Cost-effective drones can be used in these countries to sample and monitor water quality, composition of atmosphere and climate patterns.
 
Most of UAV systems find their application in the projects of the economically developed countries. However, these countries are not responsible for global pollution in the same extent as many developing countries, where people lack to take care of the environment due to the constant fight for their wellbeing. In these countries, the health of population is often under strike due to decreasing quality of water and air resources. Cost-effective drones can be used in these countries to sample and monitor water quality, composition of atmosphere and climate patterns.
 
+
 
<div class="tablecaption" id="table59">TABLE 59 STRENGTHS AND LIMITATIONS OF UAVS</div>
+
TABLE 59 STRENGTHS AND LIMITATIONS OF UAVS
{| class="wikitable"
+
 
! scope="row" | Strengths
+
==6.3 Systems for biosphere measurements==
! scope="row" | Limitations
 
|-
 
! scope="row" | Eco-friendly if battery powered
 
| Special person required for navigation
 
|-
 
! scope="row" | Silent, not disturbing nature
 
| Special person required for the interpretation of the results
 
|-
 
! scope="row" | Cheap versions available
 
| Agreed air path is required
 
|-
 
! scope="row" | Can fly in remote areas
 
| Unmanned technology is taken as a threat
 
|-
 
! scope="row" | Can collect results on routine basis for a long time
 
| Can be hacked
 
|}
 
 
 
==6.3 Systems for biosphere measurements==
 
  
 
Most of the drones employed in biosphere sciences are similar to the UAVs used in atmospheric applications. Generally rotary drones (e.g.: hexacopters, octocopters, etcetera) are used, since they have a high stability and are able to stay fixed at certain positions and altitudes in order to perform measurements. Payloads that are used in biosphere drone measurements are generally related to the assessment of vegetation status (i.e.: stresses and in homogeneities) or the amount of total biomass. For the first assessment a combination of thermal, RGB and hyperspectral cameras are used; while for the latter techniques such as Light Detection and Ranging (LIDAR) are used.’
 
Most of the drones employed in biosphere sciences are similar to the UAVs used in atmospheric applications. Generally rotary drones (e.g.: hexacopters, octocopters, etcetera) are used, since they have a high stability and are able to stay fixed at certain positions and altitudes in order to perform measurements. Payloads that are used in biosphere drone measurements are generally related to the assessment of vegetation status (i.e.: stresses and in homogeneities) or the amount of total biomass. For the first assessment a combination of thermal, RGB and hyperspectral cameras are used; while for the latter techniques such as Light Detection and Ranging (LIDAR) are used.’
Line 1,718: Line 1,557:
 
Underwater Unmanned Autonomous Vehicles (gliders and other UAVs) are commonly used by oceanographers for research and monitoring of the physical and biogeochemical characteristics of the first 1000m of the ocean. The recently created GOOS program called “OceanGliders” (current web domain is http://www.ego-network.org) is gathering the major part of the worldwide gliders fleet and focuses its activity on the sustainable measurements of five Essential Ocean Variables (EOVs): temperature, salinity, chlorophyll a, oxygen and Coloured Dissolved Organic Matter (CDOM). Unless only these parameters are part of the network, many other sensors have been developed, integrated, tested and operationally deployed on AUVs such as passive acoustics, ADCP (current sensor), turbulence, hydrocarbonic sensor, nutrients, pH etc. Currently these sensors are not integrated in the network mainly for harmonized data management reasons but also because the technology is sporadically used by the community. The increasing capacities of gliders (depth, endurance and payload) and the relatively low cost of the technology, make it a very interesting tool for marine and maritime industries. Ocean gliders naturally complement existing elements of the GOOS with their utility on the continental slopes, ability to complete repeat surveys and resolve mesoscale oceanographic features such as fronts.
 
Underwater Unmanned Autonomous Vehicles (gliders and other UAVs) are commonly used by oceanographers for research and monitoring of the physical and biogeochemical characteristics of the first 1000m of the ocean. The recently created GOOS program called “OceanGliders” (current web domain is http://www.ego-network.org) is gathering the major part of the worldwide gliders fleet and focuses its activity on the sustainable measurements of five Essential Ocean Variables (EOVs): temperature, salinity, chlorophyll a, oxygen and Coloured Dissolved Organic Matter (CDOM). Unless only these parameters are part of the network, many other sensors have been developed, integrated, tested and operationally deployed on AUVs such as passive acoustics, ADCP (current sensor), turbulence, hydrocarbonic sensor, nutrients, pH etc. Currently these sensors are not integrated in the network mainly for harmonized data management reasons but also because the technology is sporadically used by the community. The increasing capacities of gliders (depth, endurance and payload) and the relatively low cost of the technology, make it a very interesting tool for marine and maritime industries. Ocean gliders naturally complement existing elements of the GOOS with their utility on the continental slopes, ability to complete repeat surveys and resolve mesoscale oceanographic features such as fronts.
  
<div class="figure" id="figure7"><gallery>
+
FIGURE 7 DRONES FOR UNDERWATER MEASUREMENTS: (A) SEA EXPLORER, (B) SEAGLIDER
File:ENVRIplus D1.1-Fig. 7A-Drones for underwater measurements, (A) Sea explorer, (B) Seaglider.png|(A) Sea explorer
 
File:ENVRIplus D1.1-Fig. 7B-Drones for underwater measurements, (A) Sea explorer, (B) Seaglider.png|(B) Seaglider]]
 
</gallery>
 
 
 
Figure 7: Drones for underwater measurements</div>
 
  
 
The European Glider Network is composed of about 100 platforms that are deployed in the Atlantic, Mediterranean Sea and Baltic Sea. It is important to precise that some of the European gliders are also deployed in non-European region for specific research purposes. The European Glider Network will certainly keep growing as many “new” laboratories are currently purchasing platforms (Ireland and Sweden for example).
 
The European Glider Network is composed of about 100 platforms that are deployed in the Atlantic, Mediterranean Sea and Baltic Sea. It is important to precise that some of the European gliders are also deployed in non-European region for specific research purposes. The European Glider Network will certainly keep growing as many “new” laboratories are currently purchasing platforms (Ireland and Sweden for example).
Line 1,760: Line 1,594:
 
As known from the ENVRIplus community, technologies for the energy supply are represented by solar cells (63%), wind and hydroturbines (4% each) and other solutions (29%). Thus, solar panels is by far the most used technology, used to provide energy for isolated sites. Figure 8 shows the diagram of usage of various power supply solutions for isolated scientific stations within ENVRIplus network.  
 
As known from the ENVRIplus community, technologies for the energy supply are represented by solar cells (63%), wind and hydroturbines (4% each) and other solutions (29%). Thus, solar panels is by far the most used technology, used to provide energy for isolated sites. Figure 8 shows the diagram of usage of various power supply solutions for isolated scientific stations within ENVRIplus network.  
  
<div class="figure" id="figure8">[[File:ENVRIplus D1.1-Fig. 8-Power supply systems. ENVRIplus WP 3.1 'Energy report', 2017.png|center|frame|Figure 8: Power supply systems. ENVRIplus WP 3.1 "Energy report" (2017)]]</div>
+
FIGURE 8 POWER SUPPLY SYSTEMS. ENVRIPLUS WP 3.1 "ENERGY REPORT", 2017
  
 
===7.2.1 Solar panels===
 
===7.2.1 Solar panels===
Line 1,787: Line 1,621:
 
Lead acid batteries, VRLA (Valve Regulated Lead Acid), with gel or AGM are, by far, the most used ones through the ENVRI RI community. They are especially widely used for terrestrial measurements. Figure 9 shows the distribution (%) among battery technologies used for the measurements at 27 scientific stations within ENVRI network. As can be seen, 69% are taken by the lead batteries and 23% by lithium batteries, while alkaline and other technologies represent 4% each.  
 
Lead acid batteries, VRLA (Valve Regulated Lead Acid), with gel or AGM are, by far, the most used ones through the ENVRI RI community. They are especially widely used for terrestrial measurements. Figure 9 shows the distribution (%) among battery technologies used for the measurements at 27 scientific stations within ENVRI network. As can be seen, 69% are taken by the lead batteries and 23% by lithium batteries, while alkaline and other technologies represent 4% each.  
  
<div class="figure" id="figure9">[[File:ENVRIplus D1.1-Fig. 9-Power storage systems. ENVRIplus WP 3.1 'Energy report', 2017.png|center|frame|Figure 9: Power storage systems. ENVRIplus WP 3.1 "Energy report" (2017)]]</div>
+
FIGURE 9 POWER STORAGE SYSTEMS. ENVRI+ WP3.1 "ENERGY REPORT", 2017
  
 
The biggest challenges of the batteries are that they need to face and run under very low temperatures, down to -20°C, and sometimes down to -40° to 50°C and be as light as possible. The weight of batteries is especially important when one considers their installation on drones. Light weight of the batteries allows larger amount of scientific equipment to be installed and, thus, is more desirable. Lithium batteries are currently the ones with the highest energy-to-weight ratio. That is why they are widely used for the environmental measurements within oceanic domain, and for the installation on drones. In the table 60 we summarize the companies providing technologies for the power supply and specify the type/ model of technology.  
 
The biggest challenges of the batteries are that they need to face and run under very low temperatures, down to -20°C, and sometimes down to -40° to 50°C and be as light as possible. The weight of batteries is especially important when one considers their installation on drones. Light weight of the batteries allows larger amount of scientific equipment to be installed and, thus, is more desirable. Lithium batteries are currently the ones with the highest energy-to-weight ratio. That is why they are widely used for the environmental measurements within oceanic domain, and for the installation on drones. In the table 60 we summarize the companies providing technologies for the power supply and specify the type/ model of technology.  
  
<div class="tablecaption" id="table60">TABLE 60 COMPANIES PRODUCING TECHNOLOGICAL SOLUTIONS</div>
+
TABLE 60 COMPANIES PRODUCING TECHNOLOGICAL SOLUTIONS
{| class="wikitable"
 
! scope="col" | Technology
 
! scope="col" | Manufacturer
 
! scope="col" | Specification/model
 
! scope="col" | Comments
 
|-
 
! scope="row" | Solar panels
 
| Kyocera
 
| Any, Mono or poly crystalline from 10 to 100 W (typically)
 
| rowspan="4" | The market of solar panels is a new and very dynamic market, where new companies appear and disappear every day.
 
|-
 
!
 
| Victron
 
| Any, Mono or poly crystalline from 10 to 100 W (typically)
 
|-
 
! PhotoWatt (not exist anymore)
 
| Any, Mono or poly crystalline from 10 to 100 W (typically)
 
|-
 
! SolarWorld (not exist anymore)
 
| Any, Mono or poly crystalline from 10 to 100 W (typically)
 
|-
 
! scope="row" | Wind turbines
 
| Primus
 
| Primus AIR 30
 
|
 
|-
 
!
 
|
 
| Primus AIR 40
 
|
 
|-
 
!
 
| FORGEN
 
| Forgen Ventus 70
 
|
 
|-
 
!
 
|
 
| Forgen Antarctic
 
|
 
|-
 
!
 
| Wind-Kinetic
 
| Polar
 
|
 
|-
 
! scope="row" | Fuel Cell
 
| EFOY
 
| EFOY Pro 600
 
|
 
|-
 
! scope="row" | Batteries
 
| Sonnenschein
 
| Gel Dryfit, cycling, 30 to 100 Ah.
 
|
 
|-
 
!
 
| YUASA
 
| AGM cycling, 30 to 100 Ah.
 
|
 
|-
 
!
 
| Victron
 
| Gel or AGM cycling, 30 to 100 Ah.
 
|
 
|-
 
!
 
| Enersys
 
| Cyclon
 
|
 
|-
 
!
 
| Shaft
 
| Lithium Sulfuryl Chloride
 
| Non rechargeable. Mainly used for the measurements in the oceanic domain.
 
|-
 
!
 
| Victron
 
| Lithium FePO<sub>4</sub>
 
| Rechargeable battery.
 
|}
 
  
 
=8 Place of Research Infrastructures on the technological market=
 
=8 Place of Research Infrastructures on the technological market=
Line 1,880: Line 1,633:
 
The core of the scientific business dedicated to environmental measurements and climate change observations can be seen in interactions of producing companies with the consumers of their products. Such interactions are developed, facilitated, and actively promoted. However, these interactions are not always beneficial or successful due to the different views and capabilities of producers and consumers communities. Thus, producers do not always have the possibility to understand the needs of consumers due to the lack of communication or inability to dedicate the funds for the market research. This results in the production of low-functional, expensive devices and, consequently, decrease of companies revenues and incomes. At the same time, the end-users do not have the chance to explain the producers their needs and cannot afford purchasing expensive devices directly from them. Research infrastructures are the bodies that act as intermediates between producers of the technologies, their end-users and third parties, such as grant holders, providing benefits for all market players as shown below at figure 10.
 
The core of the scientific business dedicated to environmental measurements and climate change observations can be seen in interactions of producing companies with the consumers of their products. Such interactions are developed, facilitated, and actively promoted. However, these interactions are not always beneficial or successful due to the different views and capabilities of producers and consumers communities. Thus, producers do not always have the possibility to understand the needs of consumers due to the lack of communication or inability to dedicate the funds for the market research. This results in the production of low-functional, expensive devices and, consequently, decrease of companies revenues and incomes. At the same time, the end-users do not have the chance to explain the producers their needs and cannot afford purchasing expensive devices directly from them. Research infrastructures are the bodies that act as intermediates between producers of the technologies, their end-users and third parties, such as grant holders, providing benefits for all market players as shown below at figure 10.
  
<div class="figure" id="figure10">[[File:ENVRIplus D1.1-Fig. 10-Interactions of RIs with other participants in the market.png|center|frame|Interactions of RIs with other participants in the market]]</div>
+
FIGURE 10 INTERACTIONS OF RIS WITH OTHER PARTICIPANTS IN THE MARKET.
  
The arrows between the RI body and the companies represent:
+
The arrows between the RI body and the companies represent:
# Services that can be provided by RIs to the companies
+
# Services that can be provided by RIs to the companies
#* Representing large groups of the end-users, RIs are capable of purchasing products of high cost, which can be shared among the multiple end-users.
+
* Representing large groups of the end-users, RIs are capable of purchasing products of high cost, which can be shared among the multiple end-users.
#* As large entities, connecting numerous research institutes and governmental structures, RIs can collect the demands for the standardization and metrology and pass them to the companies for the future implementation.
+
* As large entities, connecting numerous research institutes and governmental structures, RIs can collect the demands for the standardization and metrology and pass them to the companies for the future implementation.
#* RIs can predict natural disasters affecting business and human well-being. This is a valuable capability for business management and crisis prevention.
+
* RIs can predict natural disasters affecting business and human well-being. This is a valuable capability for business management and crisis prevention.
#* Co-designing innovation. RIs can promote the development of new products and services as well as to adapt them to the market needs and rules.
+
* Co-designing innovation. RIs can promote the development of new products and services as well as to adapt them to the market needs and rules.
#* RIs can provide the facilities, necessary for testing of new technologies
+
* RIs can provide the facilities, necessary for testing of new technologies
#* RIs can perform data collection and management, to support companies and generate income.
+
* RIs can perform data collection and management, to support companies and generate income.
# Services that companies can provide to RIs
+
# Services that companies can provide to RIs
#* Companies can sell their innovative devices to RIs. In case the devices are of high cost, RIs will be able to purchase them in contrast to the single users/scientists.
+
* Companies can sell their innovative devices to RIs. In case the devices are of high cost, RIs will be able to purchase them in contrast to the single users/scientists.
#* Companies can provide new services to the RI, in larger extent than to the single users.
+
* Companies can provide new services to the RI, in larger extent than to the single users.
#* Data collection and transmission. While using the facilities of RIs, companies can collect data at low cost. This data can be shared with the members of RIs to make their work more efficient.
+
* Data collection and transmission. While using the facilities of RIs, companies can collect data at low cost. This data can be shared with the members of RIs to make their work more efficient.
# Services that RIs can provide to customers (end-users)
+
# Services that RIs can provide to customers (end-users)
#* RIs can assure that all the customers (end-users) have equal possibilities to access the facilities for the environmental measurements and climate change investigations, as well as to the data provided by each and every RI.
+
* RIs can assure that all the customers (end-users) have equal possibilities to access the facilities for the environmental measurements and climate change investigations, as well as to the data provided by each and every RI.
#* RIs provide transferable and reusable data and knowledge.
+
* RIs provide transferable and reusable data and knowledge.
# RIs become an attractive receiver of grants and funding
+
# RIs become an attractive receiver of grants and funding
#* Given the same amount of financial support, RIs can provide the access to the research facilities to larger amount of scientists or other interested communities.
+
* Given the same amount of financial support, RIs can provide the access to the research facilities to larger amount of scientists or other interested communities.
# Direct interactions between the end-users and producing companies
+
# Direct interactions between the end-users and producing companies
#* Direct interactions are possible, but are never as beneficial as interactions through the RIs due to the reasons mentioned in points1-4.
+
* Direct interactions are possible, but are never as beneficial as interactions through the RIs due to the reasons mentioned in points1-4.
 
+
 
==8.2 RIs as innovative business partners==
+
==8.2 RIs as innovative business partners==
 
+
 
From the types of interactions described above, it can be seen that RIs can catalyse the development of technologies by being their direct users and acting as innovation partners:
+
From the types of interactions described above, it can be seen that RIs can catalyse the development of technologies by being their direct users and acting as innovation partners:
 +
 
 +
RIs as contributors to new products and services – RIs can work as competitive infrastructures for businesses. Start-up companies with limited possibilities of purchasing of high-tech devices can become more beneficial by using shared devices within RIs. Such access to the systems through the RIs will reduce the cost of system operation, ensure the full time-load of devices and, thus, increase the effectiveness of work.
  
RIs as contributors to new products and services – RIs can work as competitive infrastructures for businesses. Start-up companies with limited possibilities of purchasing of high-tech devices can become more beneficial by using shared devices within RIs. Such access to the systems through the RIs will reduce the cost of system operation, ensure the full time-load of devices and, thus, increase the effectiveness of work.
 
  
 
RIs as users of innovative techniques – Upon their development and growth, RIs will demand new technological solutions with better measurement characteristics and thus promote research, development and manufacturing of new technological devices for environmental measurements and climate change investigations.
 
RIs as users of innovative techniques – Upon their development and growth, RIs will demand new technological solutions with better measurement characteristics and thus promote research, development and manufacturing of new technological devices for environmental measurements and climate change investigations.
Line 1,913: Line 1,667:
 
It is important to note, that companies, interested in the collaboration with RIs can be represented by Small and Medium sized companies (SMEs) as well as by large consortiums and conglomerates. Both SMEs and larger companies will have their own benefits from collaboration with RIs, however the interactions of the entities in such cases might differ. Table 61 compares the interactions of single researchers with SMEs and RIs with SMEs.
 
It is important to note, that companies, interested in the collaboration with RIs can be represented by Small and Medium sized companies (SMEs) as well as by large consortiums and conglomerates. Both SMEs and larger companies will have their own benefits from collaboration with RIs, however the interactions of the entities in such cases might differ. Table 61 compares the interactions of single researchers with SMEs and RIs with SMEs.
  
<div class="tablecaption" id="table61">TABLE 61 INTERACTION OF RESEARCHERS AND RIS WITH SMES</div>
+
TABLE 61 INTERACTION OF RESEARCHERS AND RIS WITH SMES
{| class="wikitable"
 
! scope="col" | Researcher to SMEs
 
! scope="col" | RIs to SMEs
 
|-
 
| Purchases at the small scale
 
| Purchases at the large scale
 
|-
 
| Precisely specifies the requirements for the instrument
 
| Provides specifications for the instrument
 
|-
 
| Vision of small scientific niche
 
| Vision of the worldwide market for research and applications
 
|-
 
| Share experience in their own scientific community
 
| Promotes exchange of experiences between communities
 
|}
 
Table 62 compares interactions of scientists with the large industrial agglomerates and such interactions of RIs.
 
  
<div class="tablecaption" id="table62">TABLE 62 INTERACTION OF RESEARCHERS AND RIS WITH LARGE COMPANIES</div>
+
TABLE 62 INTERACTION OF RESEARCHERS AND RIS WITH LARGE COMPANIES
{| class="wikitable"
 
! scope="col" | Researcher to large companies
 
! scope="col" | RIs to large companies
 
|-
 
| Provides knowledge in very specific field of expertise
 
| Provides all spectra of knowledge in the field
 
|-
 
| Interested to use the infrastructure of large company
 
| Provides infrastructure for business
 
|-
 
| Improves image of innovative industrial company
 
| Broadcast the image of innovative industrial company
 
|}
 
  
 
==8.3 Addressed technologies==
 
==8.3 Addressed technologies==
Line 1,951: Line 1,675:
 
On the way of development, technologies pass several stages. These stages are represented by the Technology Readiness Level (TRL) ranging from 1 to 9, where 1 refers to the least developed technology and 9 to the most developed one. Usually it is assumed, that technologies with the TRL from 1 to 5 are immature technologies, developed and worked on by individual scientists. Contrary, technologies with the TRL from 8 to 9 are mature technologies, ready to become commercial products. As can be noticed, technologies with the TRL 6-7 are in the intermediate state. In this stage they cannot be further developed with the capacities of scientists, as such development would require significant allocation of funds. At this intermediate stage, they are also unlikely to attract funds from the commercial sector, as the companies are not ready to invest in the technologies that will not bring the profit in the short-term perspective. TRL scale is illustrated in figure 11.
 
On the way of development, technologies pass several stages. These stages are represented by the Technology Readiness Level (TRL) ranging from 1 to 9, where 1 refers to the least developed technology and 9 to the most developed one. Usually it is assumed, that technologies with the TRL from 1 to 5 are immature technologies, developed and worked on by individual scientists. Contrary, technologies with the TRL from 8 to 9 are mature technologies, ready to become commercial products. As can be noticed, technologies with the TRL 6-7 are in the intermediate state. In this stage they cannot be further developed with the capacities of scientists, as such development would require significant allocation of funds. At this intermediate stage, they are also unlikely to attract funds from the commercial sector, as the companies are not ready to invest in the technologies that will not bring the profit in the short-term perspective. TRL scale is illustrated in figure 11.
  
<div class="figure" id="figure11">[[File:ENVRIplus D1.1-Fig. 11-Technology readiness level Axis (1-9) and stages of the technological product.png|center|frame|Technology readiness level Axis (1-9) and stages of the technological product]]</div>
+
FIGURE 11 TECHNOLOGY READINESS LEVEL AXIS (1-9) AND STAGED OF THE TECHNOLOGICAL PRODUCT.
  
 
RIs thus refer to the emerging technologies with the TRL from 6 to 7, to ensure that they will overpass the financial barrier and become the commercially successful technologies with the great potential of further development and improvement. Also RIs will target improvement of technologies, such as their miniaturization and bettering of precision, as these parameters can also be referred as innovation.
 
RIs thus refer to the emerging technologies with the TRL from 6 to 7, to ensure that they will overpass the financial barrier and become the commercially successful technologies with the great potential of further development and improvement. Also RIs will target improvement of technologies, such as their miniaturization and bettering of precision, as these parameters can also be referred as innovation.
Line 2,025: Line 1,749:
 
Application of sensors in various fields of human activity - it is a common mistake to think that existing and novel sensors can find their applications only in the scientific research. Common application areas also include private and public healthcare, education and increasing general information and awareness. Increase of number of spheres where the sensors will be applied is another well-seen trend.
 
Application of sensors in various fields of human activity - it is a common mistake to think that existing and novel sensors can find their applications only in the scientific research. Common application areas also include private and public healthcare, education and increasing general information and awareness. Increase of number of spheres where the sensors will be applied is another well-seen trend.
  
<div class="tablecaption" id="table63">TABLE 63 APPLICATIONS OF SENSORS FOR AIR AND WATER QUALITY MONITORING</div>
+
TABLE 63 APPLICATIONS OF SENSORS FOR AIR AND WATER QUALITY MONITORING
{| class="wikitable"
 
! scope="col" | Application
 
! scope="col" | Description
 
! scope="col" | Example
 
|-
 
! scope="row" | Research
 
| Scientific studies and experiments to track air or water pollution
 
| Network of sensors aimed to measure atmospheric and water quality/state in urban or natural areas
 
|-
 
! scope="row" | Personal exposure monitoring
 
| Monitoring air and water quality, that a single individual is exposed to in normal, everyday conditions
 
| Monitoring air and water quality in the private location of (for air) in the car
 
|-
 
! scope="row" | Control of health
 
| Monitoring pollution levels that might promote patient sickness
 
| A person having a clinical condition wears a sensor to identify the sudden change in ambient pollution of air or water, potentially affecting his/her health
 
|-
 
! scope="row" | Supplementing Existing Monitoring Data
 
| Sensors are placed within local monitoring area to fill the coverage
 
| Increasing the density of sensor network to improve the understanding of pollution gradient
 
|-
 
! scope="row" | Identification of source of pollution
 
| Identification of pollution source by deploying a network of sensors in the vicinity of suspected source
 
| A network of sensors can be installed near to the industrial facility to monitor the pollution gradient as a function of time
 
|-
 
! scope="row" | Education activities
 
| Using various sensors to educate students about the source of pollutions and means of its measurement
 
| Sensors are provided to students to understand the principles of measurements and importance of climate change tracking
 
|-
 
! scope="row" | General information and awareness
 
| Using sensors in public places to increase the awareness of people about pollution
 
| Install the sensors in the zones of public access to illustrate the current state of pollution of air and water
 
|}
 
  
 
As a result of this work, authors present the table, summarizing the technologies mentioned in the current document, in relation to the RIs, they are applied in and in relation to the domains, where they are used. The table can be found in a separate annex 1.
 
As a result of this work, authors present the table, summarizing the technologies mentioned in the current document, in relation to the RIs, they are applied in and in relation to the domains, where they are used. The table can be found in a separate annex 1.
Line 2,340: Line 2,031:
  
 
{{DocumentMetadata
 
{{DocumentMetadata
| url = https://mediawiki.envri.eu/images/b/bc/D1.1-Emerging-technologies-emerging-markets-fostering-the-innovation-potential-of-research-infrastructures.pdf
+
| url = http://www.envriplus.eu/wp-content/uploads/2018/10/D1.1-Emerging-technologies-emerging-markets-fostering-the-innovation-potential-of-research-infrastructures.pdf
 +
| pdf =
 +
| zenodo =
  
 
| project = ENVRIplus
 
| project = ENVRIplus
Line 2,403: Line 2,096:
 
<!-- Document type -->
 
<!-- Document type -->
 
[[Category:Report]]
 
[[Category:Report]]
<!--Domains-->
+
<!-- Relevant domains -->
[[Category:All domains]]
+
[[Category:Atmosphere]]
 +
[[Category:Ecosystem]]
 +
[[Category:Marine]]
 +
[[Category:Solid Earth]]
 
<!-- Keywords -->
 
<!-- Keywords -->
 
[[Category:Innovation]]
 
[[Category:Innovation]]

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