Skip to main content

Vaisala forecasts the Xweather

Data ranges from road conditions and air quality to heat wave detection and lightning strikes
By Adam Hill October 3, 2022 Read time: 2 mins
Vaisala's XWeather suite provides weather and environmental data

Vaisala has launched Xweather, a forecast and observation suite of services providing real-time and hyperlocal weather and environmental data via sensors and machine learning.

Information ranges from road conditions and air quality to heat wave detection and lightning strikes, using what Vaisala calls "a combination of intelligent hardware and software, utilising the latest artificial intelligence and machine learning technologies".

The firm says Xweather brings a new level of accuracy to forecasting by combining massive amounts of weather and environmental data from several sources.

“Until now, the lack of real-time, local data has been a major source for error in weather and environment forecasting," says Samuli Hänninen, head of Xweather.

"With Xweather, businesses and developers can utilise data about the environment in real time from a hyperlocal location that is relevant for them."

Solutions include predicting the availability of renewable energy - such as wind and solar - to increased driving safety and air quality monitoring.

Xweather can also be used to predict lightning strikes at roadsides, which means infrastructure and rescue services can be mobilised quickly to manage a potential fire and thus protect homes and lives.

“Understanding is not enough: we need to take action," continues Hänninen. "We want to help organisations not only think and plan, but to act. The data and insight are available now, let’s together put that data to work."

Xweather data products can be delivered as API or enterprise package and include:

MapsGL – high-quality, vector-based weather data, imagery, and visualisations.

Automotive – Weather, road weather, and air quality information for infotainment, navigation, advanced driver assistance, and autonomous driving.

Lightning – Real-time lightning data, including classification of strikes and their damage potential.

Renewable energy – Historic data sets and forecasted wind and solar data.

Air quality – Air Quality Index and a hyperlocal Air Quality Forecast service connected to local sensors for street level AQ information and forecasts. 

Solutions for businesses with Xweather include Wx Beacon, Thunderstorm Manager, Wx Horizon and RoadAI.
 

For more information on companies in this article

Related Content

  • Jenoptik uses sensor fusion to avoid monitoring confusion
    January 26, 2018
    Jenoptik’s Uwe Urban looks at the advantages of ‘sensor fusion’ for the ITS sector. When considering the ideal sensing and monitoring system to enable the ITS sector to deliver improvements in mobility and road safety, for general policing security and border protection, we have to think beyond radar-base systems or laser scanners. What is needed today are solutions for detecting and tracking vehicles while recording evidence to deacide if any action is necessary. There is no sole sensor capable of
  • Data exploits parking potential
    March 11, 2015
    David Crawford parallel parks with innovations in two continents. Surveys of US cities indicate that drivers searching for parking can account for up to 37% of all urban traffic congestion. A 2011 study by IBM of 20 cities around the world found that nearly six out of ten drivers had abandoned their search for a parking space at least once; while motorists generally spent on average 20 minutes looking for a sought-after spot.
  • AppyWay launches Parking API
    June 9, 2020
    The underlying problem when parking is information about available spaces
  • ITS need not reinvent machine vision
    October 29, 2014
    Machine vision techniques hold the potential to solve a multitude of challenges facing the transportation sector Optical Character Recognition (OCR), the base technology for number plate recognition, has been in industrial use for more than three decades. It is a prime example of how, instead of having to start from scratch, the transportation sector can leverage and adapt the machine vision expertise already used in industry in order to provide robust solutions with new capabilities. “The real val