The Well Monitoring system is primarily intended for detection and reporting of oil and gas leakages from abandoned Oil and gas wells lacking connected infrastructure.

Trollhetta has added new DynamicImager modules for Deep Learning applications for models trained with Tensorflow, Darknet or Coffe.

Ketil Boe gave a talk at the Integra yearly Conference in Oslo on April 10th. The topic was “Artificial intelligence – What is it and how will it influence our business?” . An article (Norwegian)  related to the talk can be found on: https://www.itbaktuelt.no/2019/04/30/egenskapene-med-kunstig-intelligens-og-dynamisk-modellering/

Dr. Georg Brustad is educated from Engineering Cybernetics, NTNU and has background from Camo and Dynamica AS. He has long experience from solving problems related to control systems, dynamic modelling and statistic analysis with customers from, among others, the oil and gas and process industry.   Bsc. Frode Haugen has a degree both from Trondheim

On April 10th Trollhetta received “Innovators Award 2018” in Boston for the Image processing development tool DynamicImager.

Trollhetta, together with NAAS in Trondheim and CDS in Romania, has been awarded a project with the tittle ” Intelligent Sensor and satellite Network” (ISSN) by the European Space Agency (ESA).

Trollhetta togeher with Norsk Automasjon, NTNU,  SINTEF and NCEI is running a workshop on “Next generation of intelligent sensor network” at NTNU.

In this weeks issue (06.02.12) of Teknisk Ukeblad you can read more about the current product development project SubSea Oil and Gas Leakage Detection using Video Analyzes (SLDVA). ” – Gas and oil leakage can be identified much easier and quicker using camera technology” -Says Ole Tom Furu, Business Development Manager at Weatherford Petroleum Consultants

The NOK 22M WINDSENSE project receives NOK 10M in funding from The Norwegian Research Council.  WINDSENSE will develop an Add-on instrumentation system for off shore wind turbine.The idea is to bring to the market a cost-efficient add-on instrumentation system that is able to collect technical condition and lifetime related parameters from components in a wind