Der Kraken erwacht | Kraken Robotics Inc. (TSXV:PNG)(FRA:2KQ) (Seite 65)
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ISIN: CA50077N1024 · WKN: A2DYP6 · Symbol: PNG
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Letzter Kurs 30.05.24 TSX Venture
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| 157,61 | +256,99 | |
| 1,7450 | +14,80 | |
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| 142,70 | -10,67 | |
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Antwort auf Beitrag Nr.: 57.100.551 von gretel3 am 23.02.18 12:00:33Sehr spannende Sache, dein Fundstück!!!
Wenn ich sehe wo Kraken noch überall seine Tentakel hat.
Schau mal hier:
http://www.stockhouse.com/companies/bullboard?symbol=v.png&p…
Die sind mit ihrer Technik schon gut dabei. Aber sie sind immer noch unter der Oberfläche, was die Investoren angeht. Oder ändert sich das gerade?
Placement Closed
I tried to participate but they have already raised the 1,5MM, good news it closed so quickly, I expect they will announce mid to late next week
Read more at http://www.stockhouse.com/companies/bullboard#WEk7XHBl7vTLiy…
schönes Wochenende
Wenn ich sehe wo Kraken noch überall seine Tentakel hat.
Schau mal hier:
http://www.stockhouse.com/companies/bullboard?symbol=v.png&p…
Die sind mit ihrer Technik schon gut dabei. Aber sie sind immer noch unter der Oberfläche, was die Investoren angeht. Oder ändert sich das gerade?
Placement Closed
I tried to participate but they have already raised the 1,5MM, good news it closed so quickly, I expect they will announce mid to late next week
Read more at http://www.stockhouse.com/companies/bullboard#WEk7XHBl7vTLiy…
schönes Wochenende
Avitas Systems: ein Partner von Kraken
interessanter Artikel
Digitally Transforming Inspection Services
Brad Tomer, Avitas Systems Thursday, February 1, 2018 - 6:00am
Inspectors can select exact POI on digital 3-D models of entire assets. (Source: Avitas Systems)
399 12
Industrial inspections are typically labor-intensive and conducted on a time-based schedule. The collection of data is generally manual, time-consuming and involves humans being exposed to high-risk environments. For example, ropes teams hang from high places, inspectors enter confined spaces and workers often are exposed to severe elements. These inspections result in suboptimal data collection based on a human’s ability to work in such environments.
Data collection is subjective, inconsistent and prone to human error. Inspections are conducted on a periodic basis, and sometimes the find rate of time-based inspections is less than 2%, making more than 98% of the inspections unnecessary. In other instances, the inspection interval is too long, and adverse incidents occur as a result. For example, to inspect some assets in the oil and gas industry, such as flare stacks, operators must take them out of service, causing lost revenue.
Once inspection data are collected, value must be extracted from it. This process also is manual and not integrated, leaving findings disorganized and subject to interpretation. These findings can vary from inspector to inspector or even from one day to the next. In the process of transferring and communicating inspection results for paper or PDF reports, data can be lost. Additionally, firms often delete much of the data after the report is finished, which limits the ability to learn from historical records. Overall, reporting can take six months or more after the inspection is completed.
Platform detects anomalies, generates alerts
To address these challenges, some companies are using unmanned aerial vehicles (UAVs) or AUVs. During a subsea inspection, for example, many companies require a support vessel and crew to command ROVs. This process is usually expensive and weather dependent. During aboveground inspections, UAVs can collect thousands of images, but inspectors need to manually examine these data to develop a report, which doesn’t save much time. The true benefits of robotic inspection derive from the ability to efficiently maximize the added data that are collected over time with a smaller logistical footprint.
Avitas Systems, a GE Venture, is taking a more systematic approach to inspections by collecting data autonomously and fusing those data into an advanced analytics platform, where artificial intelligence (AI), physics models and algorithms combine to automatically detect asset anomalies and generate alerts.
To develop these solutions, Avitas Systems brings together a team of subject matter experts across diverse technologies and businesses, including engineering, analytics, computer vision, flight operations and GE’s Global Research Center for the customization of these technologies.
Avitas Systems uses a variety of robotics, including UAVs, AUVs, surface robots such as crawlers and customized sensor technology, to make its services crossindustry, targeted and thorough. By incorporating robotics in data collection, the company can prevent inspectors from performing high-risk tasks and provide more consistent inspections to better detect asset defects earlier and faster, which means communities surrounding industrial assets are safer, too. All the while, minimal machine downtime is required, so companies don’t have costly turnaround time.
Advanced 3-D modeling, AI
What makes robotic data collection with Avitas Systems more efficient is the company’s advanced 3-D modeling and unique integration of AI to enable its analytics. The company’s data collection process improves the quality and consistency of inspection insights, which customers often can see livestreamed. Inspectors can select exact points of inspection (POI) on digital 3-D models of entire assets.
Users simply select POI on the model, change the perspective of the model to define the sensor angle and indicate the size of the resolvable defect by extending the POI, which translates into a robot’s standoff distance. This point-and-click method reduces the inspection planning time from hours to minutes, with a more targeted approach. Avitas Systems autonomously converts this 3-D modeling, integrated with existing customer requirements such as no-fly zones, into safe and precise paths that robots follow for data collection.
These paths can be repeated, which allows increased efficiency and the ability to detect changes in an asset over time. Change detection produces historical data in the form of images that sensors capture, including RGB, infrared and ultraviolet imaging, stored on the company’s digital, cloud-based platform. The platform centralizes the data, unlike many other companies, and allows archival searches of inspection records as the data grow.
Deep learning models are stored on the original Avitas Systems AI Workbench. (Source: Avitas Systems)
Predictive analytics
In addition to data warehousing, the platform notably includes predictive analytics so inspections can be planned according to risk, as opposed to time intervals. Risky assets receive increased attention, thus improving safety. Avitas Systems fuses manual and autonomous inspection data, existing asset performance data, external data sources (e.g., weather) and new inputs from subsequent inspections. Advanced algorithms then detect asset defects and anomalies automatically. Defects and anomalies vary across the industry, including flare stack damage or subsea gas bubbles.
Avitas Systems can quickly and more accurately determine the likelihood a defect will lead to failure in a few hours instead of several weeks and at a reduced cost. Automated defect recognition means inspectors no longer need to manually peruse disparate datasets across different teams. As more data are ingested from diverse sources, the deep learning models stored on Avitas Systems’ original AI Workbench retrain for smarter actionable insights.
The platform uses predictive analytics to recommend targeted inspection scheduling and planning, which significantly improves accuracy and enables earlier resolution of potential issues. The recommendations and networkwide risk maps for assets are displayed in the company’s customer-focused, web-based interface with accessible dashboards based on user type. The advanced reporting tools available in the interface integrate with existing management and reporting systems.
Partnerships
With the company’s hybrid of technologies, human perspective complements the dexterity of advanced robotic technology and analytics. Avitas Systems is making inspectors’ jobs easier and more efficient. This first inspectionas- a-service solution and the fundamental algorithms it involves can apply to multiple industries, including oil and gas, electric power and transportation. Avitas Systems is partnering with market leaders in robotics and AI to expand its platform globally. By partnering with Kraken Robotics, for example, Avitas Systems will be able to incorporate sensor technology for subsea inspection across the oil and gas, offshore renewable energy and shipping industries.
interessanter Artikel
Digitally Transforming Inspection Services
Brad Tomer, Avitas Systems Thursday, February 1, 2018 - 6:00am
Inspectors can select exact POI on digital 3-D models of entire assets. (Source: Avitas Systems)
399 12
Industrial inspections are typically labor-intensive and conducted on a time-based schedule. The collection of data is generally manual, time-consuming and involves humans being exposed to high-risk environments. For example, ropes teams hang from high places, inspectors enter confined spaces and workers often are exposed to severe elements. These inspections result in suboptimal data collection based on a human’s ability to work in such environments.
Data collection is subjective, inconsistent and prone to human error. Inspections are conducted on a periodic basis, and sometimes the find rate of time-based inspections is less than 2%, making more than 98% of the inspections unnecessary. In other instances, the inspection interval is too long, and adverse incidents occur as a result. For example, to inspect some assets in the oil and gas industry, such as flare stacks, operators must take them out of service, causing lost revenue.
Once inspection data are collected, value must be extracted from it. This process also is manual and not integrated, leaving findings disorganized and subject to interpretation. These findings can vary from inspector to inspector or even from one day to the next. In the process of transferring and communicating inspection results for paper or PDF reports, data can be lost. Additionally, firms often delete much of the data after the report is finished, which limits the ability to learn from historical records. Overall, reporting can take six months or more after the inspection is completed.
Platform detects anomalies, generates alerts
To address these challenges, some companies are using unmanned aerial vehicles (UAVs) or AUVs. During a subsea inspection, for example, many companies require a support vessel and crew to command ROVs. This process is usually expensive and weather dependent. During aboveground inspections, UAVs can collect thousands of images, but inspectors need to manually examine these data to develop a report, which doesn’t save much time. The true benefits of robotic inspection derive from the ability to efficiently maximize the added data that are collected over time with a smaller logistical footprint.
Avitas Systems, a GE Venture, is taking a more systematic approach to inspections by collecting data autonomously and fusing those data into an advanced analytics platform, where artificial intelligence (AI), physics models and algorithms combine to automatically detect asset anomalies and generate alerts.
To develop these solutions, Avitas Systems brings together a team of subject matter experts across diverse technologies and businesses, including engineering, analytics, computer vision, flight operations and GE’s Global Research Center for the customization of these technologies.
Avitas Systems uses a variety of robotics, including UAVs, AUVs, surface robots such as crawlers and customized sensor technology, to make its services crossindustry, targeted and thorough. By incorporating robotics in data collection, the company can prevent inspectors from performing high-risk tasks and provide more consistent inspections to better detect asset defects earlier and faster, which means communities surrounding industrial assets are safer, too. All the while, minimal machine downtime is required, so companies don’t have costly turnaround time.
Advanced 3-D modeling, AI
What makes robotic data collection with Avitas Systems more efficient is the company’s advanced 3-D modeling and unique integration of AI to enable its analytics. The company’s data collection process improves the quality and consistency of inspection insights, which customers often can see livestreamed. Inspectors can select exact points of inspection (POI) on digital 3-D models of entire assets.
Users simply select POI on the model, change the perspective of the model to define the sensor angle and indicate the size of the resolvable defect by extending the POI, which translates into a robot’s standoff distance. This point-and-click method reduces the inspection planning time from hours to minutes, with a more targeted approach. Avitas Systems autonomously converts this 3-D modeling, integrated with existing customer requirements such as no-fly zones, into safe and precise paths that robots follow for data collection.
These paths can be repeated, which allows increased efficiency and the ability to detect changes in an asset over time. Change detection produces historical data in the form of images that sensors capture, including RGB, infrared and ultraviolet imaging, stored on the company’s digital, cloud-based platform. The platform centralizes the data, unlike many other companies, and allows archival searches of inspection records as the data grow.
Deep learning models are stored on the original Avitas Systems AI Workbench. (Source: Avitas Systems)
Predictive analytics
In addition to data warehousing, the platform notably includes predictive analytics so inspections can be planned according to risk, as opposed to time intervals. Risky assets receive increased attention, thus improving safety. Avitas Systems fuses manual and autonomous inspection data, existing asset performance data, external data sources (e.g., weather) and new inputs from subsequent inspections. Advanced algorithms then detect asset defects and anomalies automatically. Defects and anomalies vary across the industry, including flare stack damage or subsea gas bubbles.
Avitas Systems can quickly and more accurately determine the likelihood a defect will lead to failure in a few hours instead of several weeks and at a reduced cost. Automated defect recognition means inspectors no longer need to manually peruse disparate datasets across different teams. As more data are ingested from diverse sources, the deep learning models stored on Avitas Systems’ original AI Workbench retrain for smarter actionable insights.
The platform uses predictive analytics to recommend targeted inspection scheduling and planning, which significantly improves accuracy and enables earlier resolution of potential issues. The recommendations and networkwide risk maps for assets are displayed in the company’s customer-focused, web-based interface with accessible dashboards based on user type. The advanced reporting tools available in the interface integrate with existing management and reporting systems.
Partnerships
With the company’s hybrid of technologies, human perspective complements the dexterity of advanced robotic technology and analytics. Avitas Systems is making inspectors’ jobs easier and more efficient. This first inspectionas- a-service solution and the fundamental algorithms it involves can apply to multiple industries, including oil and gas, electric power and transportation. Avitas Systems is partnering with market leaders in robotics and AI to expand its platform globally. By partnering with Kraken Robotics, for example, Avitas Systems will be able to incorporate sensor technology for subsea inspection across the oil and gas, offshore renewable energy and shipping industries.
zu blöde, dass ich zu früh gekauft hatte. Jetzt gäbe es günstigere Einstiegspreise
da die Aktien zur Finanzierung des laufenden Geschäftes dienen, bin ich ganz optimistisch, dass demnächst positiven Meldungen zum Geschäftsverlauf folgen werden. Der Grundstein ist mit dem Ocean Cluster schließlich bereits gelegt.
Trading Spotlight
Antwort auf Beitrag Nr.: 57.081.315 von gretel3 am 21.02.18 15:42:45so richtig abschmieren will der Kurs aber auch nicht 
und bei Stockhouse sehen manche die Meldung positiv
Viele Privatanleger werden nur den 14-Cent-Preis sehen und verrückt werden, aber alles in allem, wenn Sie die volle PR lesen, sind die Nachrichten gute Nachrichten.
1) Der RBC-Kredit ist in gutem Zustand und signalisiert Vertrauen in die Kraken-Bilanz
2) Die Eigenkapitalfinanzierung ist nicht vermittelte, dies ist auch ein Vertrauensvotum, dass wir keine bezahlten Pitchmen benötigen, um Geld zu sammeln, sagte der PR erwähnt die Möglichkeit der Vermittlung Gebühren
3) Es gibt starke Insider-Beteiligung
Read more at http://www.stockhouse.com/companies/bullboard#ReW5XcvF5lRzmp…
und bei Stockhouse sehen manche die Meldung positiv
Viele Privatanleger werden nur den 14-Cent-Preis sehen und verrückt werden, aber alles in allem, wenn Sie die volle PR lesen, sind die Nachrichten gute Nachrichten.
1) Der RBC-Kredit ist in gutem Zustand und signalisiert Vertrauen in die Kraken-Bilanz
2) Die Eigenkapitalfinanzierung ist nicht vermittelte, dies ist auch ein Vertrauensvotum, dass wir keine bezahlten Pitchmen benötigen, um Geld zu sammeln, sagte der PR erwähnt die Möglichkeit der Vermittlung Gebühren
3) Es gibt starke Insider-Beteiligung
Read more at http://www.stockhouse.com/companies/bullboard#ReW5XcvF5lRzmp…
na ja, das war zu erwarten, dass der Kurs in Kanada erst mal in Richtung Süden geht
man darf gespannt sein, wie der Kurs darauf reagiert, dass die shares zu einem sehr niedrigen Preis von 0,14 CDN$ ausgegeben wurden.
Pressemeldung vom 20.02.18
ST. JOHN’S, NEWFOUNDLAND – 20 FEBRUARY 2018 /Marketwired/ – Kraken Robotics Inc. (TSX-V: PNG) (OTCQB: KRKNF) (“Kraken” or the “Company”), is pleased to announce that it is undertaking a non-brokered private placement offering for aggregate gross proceeds of up to CDN$1.5 million (the “Offering”).
Pursuant to the Offering, the Company may issue an aggregate of up to 10,714,285 common shares (the “Shares”) at a price of CDN$0.14 per Share. There are no warrants being issued as part of this offering. All shares issued under the Offering will be subject to a four month hold period from the closing date under applicable Canadian securities laws, in addition to such other restrictions as may apply under applicable securities laws of jurisdictions outside Canada.
The closing of the Offering is expected to occur on or about February 26, 2018 and remains subject to receipt of all necessary regulatory approvals including acceptance for filing by the TSX Venture Exchange. The Company intends to use the net proceeds of the Offering to build inventory for customer trials and general corporate and working capital purposes. A finder’s fee may be paid by the Company through the issuance of finder shares in an amount equal to 6% of the Shares placed with subscribers introduced by any finder under the Offering.
ST. JOHN’S, NEWFOUNDLAND – 20 FEBRUARY 2018 /Marketwired/ – Kraken Robotics Inc. (TSX-V: PNG) (OTCQB: KRKNF) (“Kraken” or the “Company”), is pleased to announce that it is undertaking a non-brokered private placement offering for aggregate gross proceeds of up to CDN$1.5 million (the “Offering”).
Pursuant to the Offering, the Company may issue an aggregate of up to 10,714,285 common shares (the “Shares”) at a price of CDN$0.14 per Share. There are no warrants being issued as part of this offering. All shares issued under the Offering will be subject to a four month hold period from the closing date under applicable Canadian securities laws, in addition to such other restrictions as may apply under applicable securities laws of jurisdictions outside Canada.
The closing of the Offering is expected to occur on or about February 26, 2018 and remains subject to receipt of all necessary regulatory approvals including acceptance for filing by the TSX Venture Exchange. The Company intends to use the net proceeds of the Offering to build inventory for customer trials and general corporate and working capital purposes. A finder’s fee may be paid by the Company through the issuance of finder shares in an amount equal to 6% of the Shares placed with subscribers introduced by any finder under the Offering.
ich bin gespannt, wann der "Ocean Cluster" endlich zu einer Meldung führt, die den Kurs nach oben bringt. Gestern hat er ja schon mal in Richtung 0,19 Kanadische Dollar gezuckt.
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