Wireless acoustic sensor networks (WASNs) are known for their potential applications in multiple areas, such as audio-based surveillance, binaural hearing aids or advanced acoustic monitoring. The knowledge of the spatial position of a source of interest is usually a requirement for many of these applications. Therefore, source localization is an important problem to be addressed in WASNs. Unfortunately, most localization algorithms need costly signal processing stages that prevent them from being implemented in low-cost sensor networks, requiring additional modules for signal acquisition and processing. This paper presents a low-complexity method for acoustic event detection and localization considering a change detection statistical framework. Two possible implementation approaches based on the efficient cumulative sum (CUSUM) algorithm are presented and discussed. Results from simulations and a real deployment show that the proposed techniques can be easily implemented in low-cost sensor networks, providing good localization accuracy and making good use of the available node resources.

There has been a variety of rate adaptation solutions proposed for both indoor and mobile scenarios. However, dynamic channel changing conditions (e.g., temporal channel variation due to unpredictable traffic pattern) make it virtually impossible to guarantee the same evaluation environment for all these schemes. Moreover, developing these schemes exhaustively on actual hardware can be gruesomely long. In this work, we propose an integrated framework which utilizes empirical data gathered from the vehicular testbed to objectively compare different rate adaptation schemes for Vehicular Ad-hoc Networks (VANETs). Using this framework, we implemented some well-known adaptation schemes and evaluated their performance. The main contribution of this paper is a methodology to compare rate adaptation schemes in an environment which is both realistic and repeatable. In addition, our results shed new light on impact of various different environment and channel factors on the performance of different schemes.