Smartphones' GPS reveals how transport is used in cities and improves route planning Researchers have created an algorithm to determine what mode of transport a person is using The algorithm uses accelerometers and other sensors built into phones It identifies patterns created by walking, trains, buses, trams and cars It could be used to plan transport routes and track the spread of diseases Smartphones can already track everywhere you go and now researchers have created a way of using the device to determine what mode of transport you are using to get there. Scientists from the Helsinki Institute for Information Technology used accelerometers and other sensors built into smartphones to develop a "transportation algorithm." It identifies certain patterns in the phone's movement and can tell whether the user is stationary, walking, riding the bus and even the difference between a train and a tram. Scientists from the Helsinki Institute for Information Technology used accelerometers built into smartphones to develop a 'transportation algorithm.' It identifies certain patterns, pictured, in the phone's movement and can tell whether the user is stationary, walking, riding the bus and even the difference between a train and a tram The accelerometer in a smartphone can be activated by movement. For example, when using the directions tool on the iPhone 5S, Apple Maps can tell the difference between driving and walking movements. If the phone is stationary but moving in a set direction, Apple Maps will give driving directions. Once the phone is picked up and used in a person's hands, Apple Maps will switch to walking directions. The Finnish researchers created their algorithm using a similar method. They analysed the frequency and velocity of the number of stops and starts for each mode of transport. The team were able to develop an algorithm that automatically identifies a mode of transport. By identifying how people within a city move around, the algorithm could be used to develop new transport routes. The researchers also claim the data could be used to track the spread of disease and other potential dangers, and give the emergency services information about the fastest routes. For example, when using the directions tool on the iPhone 5S, Apple Maps will assess the location and position of a smartphone - for example on a car seat, in a pocket or in a person's hand. Once the phone is picked up and used in a person's hands, determined by slight movements of the phone, Apple Maps switches to walking directions. The Finnish researchers created the patterns for their algorithm using a similar method. They then recreated the patterns based on the phone's location, for example, in a hand, bag or on a seat, to see how they differed. From these two tests, the team were able to develop an algorithm that automatically identifies a mode of transport. When this is used alongside location data, collected using a phone's in-built GPS and Wi-Fi sensors, the team were able to accurately track a person's movements around a city. Accelerometers in smartphones are activated by movement. For example, when using the iPhone 5S, Apple Maps can tell the difference between driving and walking. If the phone is stationary but moving, Apple Maps gives driving directions. Once the phone is picked up, pictured, Apple Maps switches to walking directions The researchers included Samuli Hemminki, Petteri Nurmi and Sasu Tarkoma from the Helsinki Insitute for Information Technology. They said: "The capability to capture transportation behaviour accurately on smartphones would have a positive impact on many research fields. For example, human mobility tracking would directly benefit from an ability to automatically monitor the transportation behaviour of individuals. This in turn would enable improving urban planning, monitoring and addressing the spread of diseases and other potential hazards, as well as providing emergency responders information of the fastest route to aid the lost or injured. Their research could additionally be used with apps, for example, to track a person's driving habits for insurance quotes. Alternatively, police forces could use this data to reconstruct accidents or find accident black spots.