World’s first device for real-time , continuous monitoring of gas at industrial sites.

Founded in 2014, Ambisense’s Ambilytics™ platform optimises the delivery of environmental risk assessment on some of the world’s largest infrastructure projects across industrial, Oil & Gas and Waste Management verticals, partnering with global multinationals such as CEMEX, SGS & Arcadis. Ambilytics™ encompasses both IoT and AI solutions, combining information from remotely deployed field devices with contextual data sources such as weather, satellite, geophysical and operational data to build machine learning models. These models identify the relationships, patterns, and drivers hidden within the data and allow customers to forecast and predict the behaviour of targeted environmental pollutants.

It is estimated that the costs of climate change will stand at $500bn annually by the end of the 21st century.  To meet the growing demand for cost-effective bespoke applications to mitigate this and other types of environmental risks, Ambisense has developed a toolkit to enable customers to build fully customisable, web-enabled instruments to acquire and analyse the data required quickly and cost-effectively.  Each element can be tailored to different needs whether a client wants to measure gas, air or water quality or anything in between.  Ultimately, it can help to:

  • Reduce monitoring costs by minimising time to site
  • Obtain live and continuous information from remote sites
  • Continuously monitor and troubleshoot problem locations
  • Understand and minimise environmental risk
  • Build useful datasets quickly and cost effectively to analyse problems
  • Build predictive models for environmental processes

Ambisense began life as an Irish EPA STRIVE funded project developed in the National Centre for Sensor Research (NCSR) in Dublin City University, one of the largest and most successful research institutions of its kind in the world with annual income of €100M and 250 multi-disciplinary researchers working on novel sensing techniques for a variety of applications.