ClimaCell Leverages IoT to Generate Precise Weather Forecasts

IOT News

ClimaCell-Leverages-IoT-to-Generate-Precise-Weather-Forecasts ClimaCell Leverages IoT to Generate Precise Weather ForecastsWeather forecasting demands a detailed and precise data set — not just to train the weather forecasting models but also to look at weather conditions at a granular level. Typically, weather forecasting has remained the domain of government agencies, all thanks to their all-access pass to nation’s huge data sets and abundant compute power to run these extremely sophisticated forecast models.

But ClimaCell, a Boston, Massachusetts-based weather technology company is proving to stand-out in this government occupied territory, thanks to its indigenous, unique, and innovative ways to get climate data from a variety of relatively non-traditional sensors that can depict a clear picture about more precise local weather predictions.

Even though, there are other players like Dark Sky, ClimaCell’s approach is very different, and unique, and has attracted many clients like the Delta, JetBlue, and United airlines, sports teams like the New England Patriots, and agtechs like Netafim.

According to ClimaCell  CEO Shimon Elkabetz, “The biggest problem is that to predict the weather, you need to have observations and you need to have models”. Adding further Shimon said, “The entire industry is basically repackaging the data and models of the government [agencies]. And the governments don’t create the relevant infrastructure everywhere in the world. Even in the U.S., there’s room for improvement.”

This is where ClimaCell stands out from other players in the industry. The Boston-based startup, instead of relying on government sensors, employs the Internet of Things (IoT) to gather climate data from far more remote places. The sensing technology that ClimaCell incorporates is apt at turning millions of existing connected hardware devices — like cell phones, street cameras, connected vehicles, airplanes, and drones — into virtual weather stations.