In smartcard-based travel payment systems, passengers have to place the smartcard near the journey registration devices once each for check-in and check-out to authenticate their travel. This is an annoying process when if the journey involves multiple stops. In this paper, we describe a working system of secure energy-efficient automatic ticketing (SEAT) for public transport, which transforms traditional check-in/check-out system into Be-in/Be-out system. In SEAT, a Bluetooth low energy (BLE) enabled smartphone communicates with registration devices to track the journey for pricing without any human intervention. SEAT is vigilant toward the energy consumption of the BLE device under various conditions, and security and privacy threats to the overall ecosystem. We develop models for energy consumption and latency for BLE devices under the influence of mutual interference based on experiments with 32 BLE devices. We utilize these models to develop an energy-efficient protocol for SEAT that is secure and privacy preserving. Our experiments show that a BLE module consumes only 18.3 J daily under the proposed system model, which is less than 0.1% of the total capacity of a typical smartphone battery.

Bluetooth is a widely used technology for short range communications. Limited device density and frequency hopping based communication usually eliminates the chances of mutual interference among independent Bluetooth Pico nets. However, with the advent of Internet of Things, there is a sharp increase in Bluetooth-equipped devices, especially in wearable devices. This gives raise to multiple collocated Pico nets, thus increasing the mutual interference leading to performance degradation of Bluetooth communication. In this work, we study the latency and energy consumption by Bluetooth low energy (BLE) devices under the influence of mutual interference, which has not been studied in the literature. Based on the experimental results involving 32 BLE devices, we investigate the influence of mutual interference and develop models for energy consumption and latency. These models can be utilized in future BLE enabled devices.