Oppotunistic crowdsensing framework for Internet of things using Bluetooth low energy
Researchers have leveraged modern day sensor rich smartphones to collect crowdsourced data and analyse it for different phenomenon of interests. Crowdsensing applications must bear with the limited energy, sensing, and computational resources available on the phone. To relief some burden from the smartphones, the authors envision a new crowdsourcing architecture where low-cost, low-energy sensors embedded in objects around us, i.e. walls, traffic lights, and billboards, providing a variety of sensors depending on their context, e.g. AirQuality, temperature. These devices would carry on the sensing, processing, and broadcasting of sensor data using wireless interfaces. Smartphones on the other hand, would opportunistically discover and collect data from these devices to provide a much better, richer, and energy-efficient sensing infrastructure. They discuss the usage of Bluetooth low energy (BLE) as a new energy-efficient sensing resource for crowdsensing. They focus on defining a unified BLE sensing framework, which provides a number of smart sensing schemes to ease the development of energy efficient and context aware crowdsensing applications. They also provide an open-source library that allows developers to utilise this framework and acts as a layer to support opportunistic crowdsensing out of the box.