LISBON, Portugal, Nov. 06, 2019 (GLOBE NEWSWIRE) -- WebSummit -- Vaisala, a global leader in weather, environmental, and industrial measurement, and Renovo, a global automotive software company, today announced Vaisala will be providing data to the Renovo Platform for connected and autonomous vehicles (CAVs). Initially, Vaisala’s road surface state dataset will be made available through Renovo’s system.

Once implemented, automated vehicle fleet deployments using the Renovo Platform will be able to seamlessly access Vaisala’s enhanced road surface state data and environmental intelligence. This data, coupled with Vaisala’s algorithms and analytics systems, will provide critical observational intelligence to help CAVs operate safely in any weather condition.

“The Renovo platform offers a new approach for transport companies and OEM’s supporting autonomous driving to develop, test, and operate the most advanced fleets,” said Markus Melin, Vice President, Vaisala Digital. “Vaisala recently acquired Foreca’s professional business-to-business weather services business that focuses on road weather and is highly recognized in particular by automotive OEMs. We are delighted to offer our new road surface intelligence and observation capabilities via the Renovo Platform.”

Through the Vaisala integration, the Renovo Platform will deliver unprecedented access to environmental observation datasets.  CAVs will receive prevailing and predicted road weather conditions from multiple sources, including reference grade stationary sensors, mobile road weather stations (including Vaisala’s Mobile Detector MD30), and sources like visual road state via computer vision. Vaisala’s algorithms and analytics systems then combine all observation data, couple it with weather forecast and road information, and communicate a near real-time view and reliable dataset of upcoming road state to CAVs.

“Vaisala is a leading creator of weather and road surface state information technology making them an important addition to the Renovo ecosystem,” said Chris Heiser, CEO and co-founder of Renovo. “Not only does Vaisala provide more precise road grip information, their vast network of weather and road sensors offer a new depth of information for CAVs to help them operate safely in any weather condition.”

Renovo’s platform is already powering highly automated vehicle fleets on public and private roads including Voyage.auto. Vaisala joins the Renovo platform along with a growing list of leading companies in the automated mobility sector including Samsung, Verizon, Seagate, Velodyne LiDAR, NVIDIA, Intel, Parsons, INRIX, Argus Cyber Security, Carmera, Affectiva, Seoul Robotics,  Phantom Auto, EdgeConneX. Understand.ai, Metamoto, and Bestmile.

More information for media:
Vaisala
Amy Eggen, Vice President, Marketing & Communications, Weather and Environment, Vaisala
Tel. +1 720 3461975, amy.eggen@vaisala.com

Renovo
Mike West
+1 415 689 8574
renovo@codewordagency.com

Vaisala is a global leader in weather, environmental, and industrial measurement. Building on over 80 years of experience, Vaisala provides observations for a better world. We are a reliable partner for customers around the world, offering a comprehensive range of innovative observation and measurement products and services. Headquartered in Finland, Vaisala employs approximately 1,850 professionals worldwide and is listed on the Nasdaq Helsinki stock exchange.
www.vaisala.com
twitter.com/VaisalaGroup

About Renovo
Renovo is an automotive software company focused on enabling the global commercialization of autonomous vehicle fleets. Renovo’s scalable platform merges software, data management, and automotive-grade safety systems into a unified solution for autonomous vehicle fleet deployments. Renovo combines Silicon Valley agility with proven automotive capabilities in a singular commitment to bring autonomous vehicles to the greatest scale, highest safety and lowest cost imaginable.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/8d7a6f9b-c493-41eb-821e-02049f68ad88.