Device Localization and Tracking based on WiFi Access Points in Amazon Traditional Fulfilment Centers

This Thesis presents and describes the study of a simple, effective and modular solution to a recurring problem in all Amazon fulfillment centers around the world. The problem analyzed is peculiar to traditional (non-robotic) Amazon sites, that is, the sites that do not exploit the aid of automated robots for the storage and recovery process of objects inside the warehouse. This problem consists in a recurring lack of mobile devices due to an involuntary abandonment by the warehouse workers in hidden areas inside the warehouse, or inside pallets of articles destined for transfer to other sorting centers. In this way it becomes very difficult to find them or recover them from the outside, often resulting in real losses. The mobile devices used by the warehouse workers are mainly scanners and tablets. Most of them have a high cost to the company since they are very advanced in terms of technology and they are specific for each type of task performed. In a large fulfilment center thousands of them can be moved and used in a single day. The proposed solution is the development of a web application that can detect the position of a particular device relying on WiFi access points which are installed on the entire surface of the warehouse. The mobile devices can periodically perform signal scans to identify nearby WiFi access points, obtaining also some details such as the signal strength of each access point detected. Specifically, this last information can be exploited to get the distance between the WiFi access point and the device which has to be localized. Since the position of each access point is fixed and known inside the warehouse, it is possible to extend the concept of position trilateration to find the point where the device is located. In this way it is possible to find a device in case of loss or to check if it has left the warehouse. The experiments carried out had positive results and show how the analyzed method is simple, effective and easy to implement. Due to its modulability it can also be easily applied to environments other than the Amazon warehouse.