Modern smartphones, often containing more than two dozen sensors, have turned into mobile measuring stations. Found in virtually every part of the globe, these devices have the potential to provide incredibly valuable troves of data. But there needs to be a rewards system to encourage people to provide this information – and ensure data protection remains intact.

An estimated four to five billion smartphones are in use worldwide in 2018. And each one of them has approximately 25 sensors inside. These record the ambient light, fingerprints, direction, acceleration, rotation and temperature – even the current air pressure. These sensors often go unnoticed as they help users surf the web, play games and navigate their surroundings. But they could also contribute to the greater good: They are capable of making earthquake warnings, sending traffic alerts, recording weather data digitally and measuring urban noise levels.

How does it all work? Special apps read the sensor data and send it to be analyzed by a cloud-based platform. This can link every single smartphone to the Internet of Things (IoT). It’s having a critical mass that’s important: Just like with a regular survey, a certain amount of collective information can provide new insights. And the more IoT data there is, more representative the result becomes.

Weather forecasts and earthquake warnings on your smartphone

The London-based start-up OpenSignal, for example, built an app that combines the data from a smartphone’s light, magnetometer and barometer sensors to make weather calculations using Big Data analysis. And researchers from the US university UC Berkeley have been working since 2016 together with the Telekom Innovation Laboratories in Silicon Valley on an earthquake early warning system based on measurements from smartphones. The app MyShake aims to turn Android smartphones into a seismic sensor network that can warn users seconds before an earthquake hits notoriously unstable California.

The researchers make use of the accelerometer sensor found in smartphones. This is normally used, for example, to control games with an algorithm measuring movement of the device. But when the data matches the vibration profile of an earthquake, the app sends the time, location and strength of the shaking to the university’s seismological department. The scientists then compare the data using analytics software with that of their seismographs. The collected figures then provide them with new insights into when future earthquakes might occur using Big Data technologies. Some 300,000 around the world have already downloaded the app. It still doesn’t send alerts to smartphone users: The developers admit they need “more global data to improve the algorithms and more testing to ensure accuracy,” before they can start providing public earthquake warnings.

Rewarding the swarm’s participation

But the true power of swarm intelligence can only be harnessed when smartphone users are compensated for downloading an app and providing their data. While MyShake users will soon benefit from having a personalized earthquake early warning system in their pockets, the weather app WeatherSignal provides participants with additional features. It can direct users to the next strong WiFi signal with a compass, has a map of WiFi hotspots in the area and measures the speed of their wireless networks.

Data protection becomes crucial

Along with developing a rewards system, it’s important to address questions of data protection. More users have grown reluctant to part with their personal information in the wake of recent data scandals. The MyShake app, for example, only transmits sensor data anonymized to cloud servers before it’s encrypted and stored in the university’s data archive. Providers should pay attention to both data anonymization and data minimization – that is, collect only information truly relevant to their intended aims. They must transparently show users which data is being processed for each purpose. Only then can there be a win-win situation for both businesses and consumers.