Abstract
The tracking of frequently visited places, also known as stay points, is a critical feature in location-aware mobile applications as a way to adapt the information and services provided to smartphones users according to their moving patterns. Location based applications usually employ the GPS receiver along with Wi-Fi hot-spots and cellular cell tower mechanisms for estimating user location. Typically, fine-grained GPS location data are collected by the smartphone and transferred to dedicated servers for trajectory analysis and stay points detection. Such Mobile Cloud Computing approach has been successfully employed for extending smartphone’s battery lifetime by exchanging computation costs, assuming that on-device stay points detection is prohibitive. In this article, we propose and validate the feasibility of having an alternative event-driven mechanism for stay points detection that is executed fully on-device, and that provides higher energy savings by avoiding communication costs. Our solution is encapsulated in a sensing middleware for Android smartphones, where a stream of GPS location updates is collected in the background, supporting duty cycling schemes, and incrementally analyzed following an event-driven paradigm for stay points detection. To evaluate the performance of the proposed middleware, real world experiments were conducted under different stress levels, validating its power efficiency when compared against a Mobile Cloud Computing oriented solution.
Highlights
Technological advances in the computation, sensing and communication dimensions of smartphone devices have contributed to their acceptance by users all around the world [1]
We analyzed the energy savings produced by its event-driven design when compared against an Mobile Cloud Computing (MCC) approach that transmits location data for offloading the detection of stay points
As part of fair experimental conditions, the smartphones were only employed for running the experimentation, discarding any other uses, no additional mobile apps were installed on them, and only the mobile app corresponding to the experiments was kept in foreground, using the GPS as the unique location provider
Summary
Technological advances in the computation, sensing and communication dimensions of smartphone devices have contributed to their acceptance by users all around the world [1]. The smartphone’s sensing dimension is supported by a diversity of sensors that enables the unobtrusive acquisition of context information (e.g., location, user activity, ambient context variables, etc.) from raw sensory data [2]. Long-term context-aware applications must query sensors on a continuous basis, which could significantly impact on energy resources of smartphones [3] This is because the battery capacity remains as the main challenge of mobile platforms, growing only 5% to 10% per year [4,5], or roughly doubling each 10 years [6].
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