OpenSignal Nets $4M To Build Out Its Crowdsourced Mobile Sensor Data Maps

Crowdsourced mobile signal mapper OpenSignal has closed a $4 million Series A funding round, led by chipmaker Qualcomm via its investment arm, Qualcomm Ventures. Prior investors O’Reilly AlphaTech Ventures and Passion Capital also participated in the round.

The UK startup previously raised a $1.3million seed round led by O’Reilly AlphaTech Ventures, back in 2012.

OpenSignal’s premise focuses on offering independent/unbiased — and likely more accurate — signal maps (vs carriers self reporting their coverage) by encouraging smartphone users to download and run its signal-checking software on their devices.

CEO Brendan Gill tells TechCrunch it’s now had more than nine million people download its app globally. “This boils down to over 35 billion data points on the coverage and performance of wireless networks.  We have data on every single mobile operator in every country out there.  We’ve also mapped over 250 million WiFi hotspots as well,” he says.

Gill says the OpenSignal maps are now comprehensive enough to enable it to determine the best carrier in “pretty much any metropolitan area in the world outside of some parts of the Middle East & Africa (although both of those areas are growing very fast for us)”.

“In the larger metropolitan areas e.g. New York, London, we can drill down to neighborhood level. However, there is still much to be gained by increasing our user-base as we’ll be able to drill down to ever increasing levels of granularity,” he adds.

OpenSignal’s business model involves providing intel on the consumer experience on mobile and wireless networks to a range of paying customers — including carriers, web companies, consultancy firms, hedge funds and telecoms regulators.

“In the year since we started commercial operations we’ve signed up over 20 paying customers around the world (spanning all five continents) including Telefonica, China Mobile and Deloitte,” says Gill.

OpenSignal says it will be using the new funding for building out its team — with a focus on hiring data specialists in a range of areas — from individuals with expertise in data mining and locating hidden correlations, to people who can tell stories using data visualization, to data engineers who can build scalable pipelines for handling large volumes of data.

The future for OpenSignal is evidently going to be about expanding the type of crowdsourced data it captures — fueled by the increasing numbers of sensors being embedded into mobile devices (or linked to mobile devices via Bluetooth connectivity).

It has already started this expansion, launching a meteorology app called WeatherSignal in May last year — which it dubbed a “side project” at the time.

The network drew on mobile sensor data from the likes of light meters and barometers, but also expanded the amount of data feeding its meteorology mapping after stumbling on a correlation between battery temperature and the ambient temperature around a particular device. So basically turning something that wasn’t intended to be a weather sensor into a weather-related data-set by applying an algorithm that could unpick the correlation between battery temperature and outdoor climate.

Since WeatherSignal launched, the quantity of connected sensors in and around mobile devices has continued to proliferate — meaning there is huge potential for expanding the types of maps that can be created in the future using a crowdsourced OpenSignal-esque approach.

“We are only scratching the surface of the insight that can be drawn from wireless sensors, with OpenSignal, and from weather related sensors, with our sister project WeatherSignal and we won’t be reducing the focus on either of those in the near future,” says Gill.

Two areas of particular interest to OpenSignal are Bluetooth Low Energy beacons, and air quality sensors, according to Gill.

“There’s no doubt that there will be an explosion in the rise of BLE beacons (including iBeacons) in the coming years and we have an opportunity to crowdsource a reference database of these,” he says, pointing out that the level of location granularity supported by mapping BLE beacons offers huge potential to map dynamic context.

“BLE beacons could know your context right down to something as specific as ‘in isle 6 of the supermarket looking at the vegetarian dishes’.  So we consider crowdsourcing a reference database of BLE sensors as equivalent to crowdsourcing a reference database of context for the world, which is a very powerful opportunity,” he adds.

On the air quality sensor front, Gill says that’s interesting to OpenSignal because mobile makers are working on embedding these sensors into devices. The size of the data-set that could be built using OpenSignal’s crowdsourced approach could yield applications for civic planning scenarios.

“As we’ve seen with other companies like Waze there is a huge opportunity to tap into the sensors that people are carrying around in their pockets to understand the flow and conditions of the cities we live in.  We believe that tapping into these crowdsourced sensor networks will be instrumental in building the smart cities of the future,” he adds.