Automatic retrieval of data for industrial machines with handheld devices : Positioning in indoor environments using iBeacons

Sammanfattning: Positioning of mobile phones or other handheld devices in indoor environments is hard because it’s often not possible to retrieve a GPS-signal. Therefore, other techniques need to be used for this. Despite the difficulties with indoor positioning, the Swedish mining company LKAB want to do exactly this in their processing plants. LKAB has developed an Apple iPhone mobile application to maintain real-time process data and documents for their machines. To retrieve the information an OCR code need to be manually scanned with the application. Instead of manually scanning these codes, LKAB want to develop an Indoor Positioning System that can automatically locate handheld devices in their production plants. This thesis aimed to create a proof of concept Apple iOS application that can position devices without GPS-signals. In the system developed Bluetooth Low Energy iBeacons is used to transmit data to the application. From this data Received Signal Strength Indication values is collected and sent off to a server that transform the values into positioning fingerprints. These fingerprints are used together with the classification algorithms K-Nearest Neighbour to determine in which, on pre-hand created, group the user is located. In these created groups there is a defined set of machines that is being presented back to the user. Test results conducted with the proof of concept application shows that the implemented system works and gives a positioning accuracy of up to 75%.