Advertising Strategy for Maximizing Profit Using CrowdSensing Trajectory Data.

Out-door billboard advertising is a traditional method to attract potential customers for making commercial profits, which represent the income from attracted customers’ consumption minus the cost of billboards. Existing billboard selection strategies usually prefer to select the billboards with a large flow of customers without considering many factors, such as customers’ preferences and detour distance. In this paper, a billboard selection optimization problem is formulated to find the appropriate billboards so that advertisers could obtain best commercial profits. First, we adopt the semi-markov model to predict customers’ mobility by using crowdsensing trajectory data. Then, with the consideration of customers’ preferences and detour distance, two advertising strategies are proposed to address the billboard selection problem for two situations. In the end, we conduct extensive simulations based on the widely-used real-world trajectory: epfl. The results of simulations demonstrate that our advertising strategies could achieve the superior commercial profits compared with the state-of-the-art strategies, which could match the analysis of theory .