Bluetooth Low Energy based proximity detection and localization in smart communities

Internet of things will bring connected devices to a new level of pervasiveness, where any tangible thing of our daily life may embed some electronics. From a sophisticated smartwatch that embeds complex sensing and communication technologies, to the use of a basic electronic component to implement a digital signature, such as RFIDs. All these smart things worn or distributed around us enables multiple functionalities, when they can interact with each other. In this thesis, I describe the design, characterization and validation of a monitoring system based on Internet of Things technologies, for managing groups moving together in a city. Communication and energy efficiency aspects are firstly explored, to identify Bluetooth Low Energy as a promising protocol enabling scalable and energy efficient networks of things. In the thesis, the protocol has been stressed to demonstrate trade-offs between throughput, energy efficiency, scalability and the possibility to perform multi-hop communication. The potential of the protocol has been exploited within the framework of the CLIMB project. Here, the application requirements and constraints fostered the use of Bluetooth for localization and proximity detection, leading to the investigation of novel strategies to improve accuracy without affecting power consumption and ease of use